{"gname":"Yale University","grp_id":"53","rels":[{"rel_title":"Differentiating nonfluent\/agrammatic and logopenic primary progressive aphasia in Catalan-Spanish bilinguals by applying multilingual multimodal machine learning to connected speech","rel_doi":"10.64898\/2026.09.18.26363435","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363435","rel_abs":"Background The nonfluent\/agrammatic (nfv) and logopenic (lv) variants of primary progressive aphasia (PPA) disrupt fluency through distinct underlying neurocognitive mechanisms. Differential diagnosis currently requires hours of cognitive-linguistic testing, with additional barriers for bilingual patients due to a shortage of bilingual service providers and a lack of well-established assessment methods. In English speakers, a promising automated approach for differentiating nfvPPA and lvPPA is to derive speech-timing measures and linguistic features from connected speech as input to machine learning (ML) classification algorithms. To our knowledge, this approach has not been evaluated in the context of bilingualism. Methods Thirty four Catalan Spanish simultaneous bilingual patients (lv = 24, nfv = 10) were asked to describe a picture (Western Aphasia Battery Picnic Scene) in both their dominant and non-dominant language. From the participant's recorded response, we derived four feature sets: speech-timing measures, derived with PRAAT; word-level parameters, derived from corpora; linguistic features, derived with the natural language processing tools SpaCy and CLAN; image-text congruence scores, derived with the vision-language encoder Multilingual-CLIP. Each feature set was fed into classification algorithms for differentiating nfv from lv in participants' non-dominant and dominant samples. Then, we combined each feature set's classifier into an ensemble model. We used the McNemar test to determine the statistical significance of differences in classification performance between responses in the non-dominant and dominant language. Results The best-performing classifier achieved F1 macro scores of 93% (word-level parameters) and 92% (ensemble) in the non-dominant and dominant language, respectively. For all feature sets and ensemble models, classification performance did not significantly differ between the non-dominant and dominant language. Ensemble modeling did not significantly improve classification performance in either language. Conclusions Taking advantage of recent advances in multilingual multimodal machine learning, we accurately differentiate Catalan-Spanish bilingual individuals with nfvPPA and lvPPA using a largely automated, time-efficient (1-2 minutes), and ecologically valid connected-speech-based approach. Future directions include evaluating this approach on larger datasets balanced by PPA subtype, using automated transcriptions of connected speech. Our study represents a step towards addressing current inequities in PPA differential diagnosis for non-English-speaking bilingual speakers. Trial registration Data from the clinical trial NCT05741853 was retrospectively analyzed","rel_num_authors":21,"rel_authors":[{"author_name":"Lokesha Srinivas Pugalenthi","author_inst":"Rice University"},{"author_name":"Andrew Parker Collins","author_inst":"University of Connecticut"},{"author_name":"N\u00faria Montagut Colomer","author_inst":"Hospital Cl\u00ednic de Barcelona"},{"author_name":"Sonia-Karin Marqu\u00e9s-Kiderle","author_inst":"Hospital Cl\u00ednic de Barcelona"},{"author_name":"Camille Wagner Rodriguez","author_inst":"The University of Texas at Austin"},{"author_name":"Jan Christian Holst Chaires","author_inst":"The University of Texas at Austin"},{"author_name":"Whendy Avila Motta","author_inst":"The University of Texas at Austin"},{"author_name":"Julia Filella-Merc\u00e8","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Junyi Jessy Li","author_inst":"The University of Texas at Austin"},{"author_name":"Fernando Llanos","author_inst":"The University of Texas at Austin"},{"author_name":"Nuole Zhu","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Sara Rubio-Guerra","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Ignacio Illan-Gala","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Sergi Borrego-\u00c9cija","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Albert Llad\u00f3","author_inst":"Hospital Cl\u00ednic de Barcelona"},{"author_name":"Juan Fortea","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Alberto Lle\u00f3","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Raquel S\u00e1nchez-Valle","author_inst":"Hospital Cl\u00ednic de Barcelona"},{"author_name":"Maya L. Henry","author_inst":"The University of Texas at Austin"},{"author_name":"Miguel \u00c1ngel Santos Santos","author_inst":"Hospital de la Santa Creu i Sant Pau"},{"author_name":"Stephanie M. Grasso","author_inst":"The University of Texas at Austin"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Privacy-Aware Distillation of Large Language Models for Enhanced Multimorbidity Scoring","rel_doi":"10.64898\/2026.09.19.26363476","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.19.26363476","rel_abs":"The trustworthy use of large language models (LLMs) is a growing challenge in safeguarding sensitive patient data from leakage. We introduce and evaluate a privacy-preserving knowledge distillation framework for LLM-based clinical modeling, using multimorbidity scoring as a healthcare task. Although LLMs can encode rich clinical knowledge and improve upon traditional rule-based comorbidity scoring, their direct evaluation on large-scale biobank data remains constrained by patient privacy. In our framework, multimorbidity reasoning is distilled from state-of-the-art LLM teacher models into compact student models (CoLLMs) using synthetic cohorts that preserve UK Biobank distributions without exposing real patient data. This approach achieves high-fidelity knowledge transfer (Spearman rho = 0.75-0.89). Independent LLM-as-a-Judge evaluation confirms the clinical significance of the distilled knowledge and reveals substantial variability among teacher models. When applied to real UK Biobank data, CoLLM-derived multimorbidity scores improve survival prediction (C-index up to 0.91) and exhibit higher SNP heritability (h^2 approximately 0.05). Our work establishes a trustworthy, privacy-compliant pathway for large-scale healthcare applications of LLMs.","rel_num_authors":4,"rel_authors":[{"author_name":"Raghav Awasthi","author_inst":"Case Western Reserve University"},{"author_name":"Yihe Yang","author_inst":"Case Western Reserve University"},{"author_name":"Mengxuan Li","author_inst":"Case Western Reserve University"},{"author_name":"Xiaofeng Zhu","author_inst":"Case Western Reserve university"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Weighing the Odds: Body Mass Index and Recurrence-Free Survival in Early-Onset Colorectal Cancer","rel_doi":"10.64898\/2026.09.19.26363465","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.19.26363465","rel_abs":"Background: Early-Onset Colorectal Cancer (EOCRC, < 50 years) is rising sharply in many parts of the world. The \"obesity paradox\", where overweight correlates with better outcome despite obesity being a risk factor, is established in colorectal cancer (CRC) overall but remains ambiguous in EOCRC. Aim: To investigate the association of Body Mass Index (BMI) at diagnosis and recurrence-free survival (RFS) in EOCRC and compare it to average-onset colorectal cancer (AOCRC, older than or equal to 50 years). Methods: A retrospective cohort study at Sahlgrenska University Hospital included 1,459 patients with curative-intent colorectal adenocarcinoma surgery comprising EOCRC (n=159) and AOCRC (n=1,300) cohorts. Cox proportional hazards models assessed the relation of BMI to RFS, adjusted for tumour stage, location, and differentiation. Restricted cubic splines were used to model BMI as a continuous variable, and model fit was assessed with likelihood-ratio tests (LRT). Results: In EOCRC, continuous BMI was significantly associated with RFS (LRT p=0.02), displaying a U-shaped association with the lowest hazard at BMI 27 and highest at BMI <20 and >30. In AOCRC continuous BMI was not associated with RFS (LRT p=0.15) and the spline curve was flat. An interaction analysis showed a significant difference between the cohorts (LRT p=0.046). Conclusion: Continuous BMI was significantly associated with RFS in EOCRC but not in AOCRC suggesting the \"obesity paradox\" may be specific to EOCRC. This may reflect differences in body composition, tumour biology and systemic metabolism between EOCRC and AOCRC or may be due to methodological biases. Future research should incorporate biomarkers, as well as refined measures of body composition.","rel_num_authors":4,"rel_authors":[{"author_name":"Erik Delryd","author_inst":"Institute of Clinical Science, Sahlgrenska Academy"},{"author_name":"Andy Tran","author_inst":"University of Iowa"},{"author_name":"Elinor Bexe Lindskog","author_inst":"Institute of Clinical Sciences, Sahlgrenska Academy"},{"author_name":"David Ljungman","author_inst":"Institute of Clinical Sciences, Sahlgrenska Academy"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Decision Support in Publicly Available Patient Information Policies at U.S. Osteopathic Medical Schools: A Vignette-Based Document Analysis","rel_doi":"10.64898\/2026.09.18.26363437","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363437","rel_abs":"Research Objectives: To evaluate whether publicly available institutional guidance supports patient-information decisions across scenarios and schools, and characterize document synthesis and evaluation consistency. Methods: We conducted an exploratory, vignette-based document analysis of a geographically diverse nonprobability sample of 20 U.S. osteopathic medical schools. Eight educational vignettes yielded 160 school-vignette pairs. Each pair underwent three separate AI-assisted retrieval-and-evaluation runs, classifying decision support as Explicitly Supported, Inferable, Ambiguous, or Not Addressed. Response selection prioritized greater support for discordant pairs, followed by fewer contributing documents and run order. One investigator verified or revised selected discordant classifications against cited evidence. Explicitly Supported and Inferable were grouped post hoc as sufficient decision support. Analyses were descriptive and included an exploratory two-school model-investigator comparison. Results: At least one eligible source was retrieved for 159 of 160 pairs (99.4%). Final classifications were Explicitly Supported for 18 pairs (11.3%), Inferable for 3 (1.9%), Ambiguous for 132 (82.5%), and Not Addressed for 7 (4.4%). Sufficient support occurred in 21 pairs (13.1%), most frequently for generative AI-assisted reflective writing (7\/20 schools, 35%), and in none for personal cloud notes or official clinical logs. Ten schools had no sufficiently supported vignette; the maximum was four of eight. Multiple documents contributed to 111 evaluations (69.4%). Three-run ratings were unanimous for 113 pairs (70.6%), with 80.2% pairwise exact agreement. Investigator review retained 44 of 47 selected discordant ratings and revised three upward. In the two-school comparison, the investigator more frequently judged evidence sufficient when models judged it insufficient than the reverse. Conclusions: Relevant public guidance was frequently retrieved, but few school-vignette pairs were classified as providing sufficient scenario-specific decision support. These findings highlight a gap between identifying relevant guidance and determining an appropriate course of action within this evaluation framework. They support institutional review of how student-facing materials explain information use, storage, sharing, and approval requirements. Vignette-based review identifies questions requiring clarification. Evaluation with learners and assessment of internal and clinical-site guidance would help determine how these findings translate to students' decisions.","rel_num_authors":2,"rel_authors":[{"author_name":"Na Dai","author_inst":"Independent Researcher"},{"author_name":"Kirsten L Waarala","author_inst":"College of Osteopathic Medicine, Michigan State University, East Lansing, MI, USA"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Compound climate extremes, socioeconomic conditions and human mobility influence dengue dynamics heterogeneously across Vietnam","rel_doi":"10.64898\/2026.09.19.26363468","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.19.26363468","rel_abs":"Dengue presents a major public health challenge in Vietnam, driven by biological, behavioural, and environmental factors. Compound climate extremes, such as sequential hydrometeorological events, can influence dengue risk yet remain understudied. We evaluated the effects of compound climate extremes, socioeconomic conditions, and human mobility on dengue relative risk across 670 districts in Vietnam over 20 years, stratifying by eight subregions spanning emerging to endemic transmission. Dengue risk was greatest following dry-then-wet conditions in seven subregions. Higher temperatures increased risk across North and Central Vietnam, but had limited effect in the South. Mobility associations followed an urban-rural gradient, with increased risk in highly rural districts where residents travelled more frequently to fewer destinations, and in urban districts with more visitors and dispersed outgoing mobility. Stratifying climatic and socioeconomic effects by subregion improved predictive skill at lead times of 1 to 6 months over unstratified and baseline models, with substantial spatial variation. Accounting for compound extremes across distinct spatial contexts could strengthen disease early warning systems in Vietnam and beyond.","rel_num_authors":15,"rel_authors":[{"author_name":"Chloe Fletcher","author_inst":"Barcelona Supercomputing Center"},{"author_name":"Sophie Belman","author_inst":"Yale School of Public Health"},{"author_name":"Kien Quoc Do","author_inst":"Pasteur Institute in Ho Chi Minh City"},{"author_name":"Quang Duy Pham","author_inst":"Pasteur Institute in Ho Chi Minh City"},{"author_name":"Thi Thanh Thao Nguyen","author_inst":"Pasteur Institute in Ho Chi Minh City"},{"author_name":"Rory Gibb","author_inst":"University College London"},{"author_name":"Phan Trong Lan","author_inst":"National Institute of Hygiene and Epidemiology"},{"author_name":"Tran Cong Tu","author_inst":"National Institute of Hygiene and Epidemiology"},{"author_name":"Nguyen Hai Tuan","author_inst":"National Institute of Hygiene and Epidemiology"},{"author_name":"Daniela L\u00fchrsen","author_inst":"Barcelona Supercomputing Center"},{"author_name":"Gina Tsarouchi","author_inst":"HR Wallingford"},{"author_name":"Quillon Harpham","author_inst":"HR Wallingford"},{"author_name":"Felipe J Col\u00f3n-Gonz\u00e1lez","author_inst":"Wellcome Trust"},{"author_name":"John Rossman Bertholf Palmer","author_inst":"Universitat Pompeu Fabra"},{"author_name":"Rachel Lowe","author_inst":"Barcelona Supercomputing Center"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Multi-component chlorination intervention to reduce neonatal infections in healthcare facilities in western Kenya (CLEAN Trial): study protocol for a cluster randomized controlled trial","rel_doi":"10.64898\/2026.09.18.26363445","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363445","rel_abs":"Background: The proportion of births occurring at healthcare facilities is rising globally, yet the birthing environment in healthcare facilities in low-income settings is often contaminated with bacterial pathogens, including antibiotic-resistant pathogens, that can lead to serious infections for newborns and their mothers. There is a need for effective strategies to reduce environmental contamination in healthcare facilities to reduce infection risks among facility-born neonates and their mothers. Methods: We designed the CLEAN (ChLorine to reduce Enteric and Antibiotic resistant infections in Neonates) cluster randomized controlled trial in western Kenya to evaluate the impact of a multi-component chlorination intervention on environmental contamination and maternal and neonatal infection risks. Thirty-six medium-sized public health facilities will be randomized in a 1:1 allocation ratio to receive a passive chlorination technology for water supply treatment paired with a reliable supply of chlorine-based disinfectant or status quo. Up to 22,500 mothers-neonate dyads will be enrolled and followed from birth through 28 days to collect symptoms of infection and mortality, with a subset of mother-neonate dyads selected for rectal swab collection to measure rectal colonization with sepsis-associated bacterial species. Environmental samples will be collected to measure bacterial pathogens on staff hands, high-touch surfaces, and in water supply. The primary objectives of the study are to evaluate the impact of the intervention on the following outcomes: (1) rectal carriage of bacterial pathogens one week post-birth among facility-born neonates and their mothers, (2) cumulative incidence in the first 7 days post-birth of possible serious bacterial infection among facility-born neonates, and (3) cumulative incidence in the first 7 days post-birth of symptoms of possible maternal sepsis. Discussion: This study will generate evidence on the effectiveness of a novel chlorination intervention to reduce healthcare associated infections, including antibiotic resistant infections, and improve maternal and neonatal survival. Trial registration: Clinical Trials NCT06824350. Registered 7 February 2025, https:\/\/clinicaltrials.gov\/study\/NCT06824350","rel_num_authors":13,"rel_authors":[{"author_name":"Yoshika Crider","author_inst":"University of Minnesota"},{"author_name":"Mwale Chiyenge","author_inst":"University of California, Berkeley"},{"author_name":"Erick Odoyo","author_inst":"Walter Reed Army Institute of Research-Africa, Kenya"},{"author_name":"Joyce Kisiangani","author_inst":"University of California, Berkeley"},{"author_name":"Jeremy Lowe","author_inst":"University of California, Berkeley"},{"author_name":"Josline Wangia","author_inst":"Kenya Medical Research Institute"},{"author_name":"Blastus Bwire","author_inst":"Remit Kenya"},{"author_name":"Mwanzia Kioko","author_inst":"CARE"},{"author_name":"Kelly Alexander","author_inst":"CARE"},{"author_name":"Carol Nekesa","author_inst":"Remit Kenya"},{"author_name":"Lillian Musila","author_inst":"Kenya Medical Research Institute"},{"author_name":"Phelgona Otieno","author_inst":"Kenya Medical Research Institute"},{"author_name":"Amy Pickering","author_inst":"University of California, Berkeley"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration","rel_doi":"10.64898\/2026.09.18.26363439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363439","rel_abs":"Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.","rel_num_authors":51,"rel_authors":[{"author_name":"Emily W Paolillo","author_inst":"University of California, San Francisco"},{"author_name":"Sreya Dhanam","author_inst":"University of California, San Francisco"},{"author_name":"Jack Carson Taylor","author_inst":"University of California, San Francisco"},{"author_name":"Mark Sanderson-Cimino","author_inst":"University of California, San Francisco"},{"author_name":"Ray Fregly","author_inst":"University of California, San Francisco"},{"author_name":"Rowan Saloner","author_inst":"University of California, San Francisco"},{"author_name":"Kaitlin B Casaletto","author_inst":"University of California, San Francisco"},{"author_name":"Joel H Kramer","author_inst":"University of California, San Francisco"},{"author_name":"Bruce L Miller","author_inst":"University of California, San Francisco"},{"author_name":"William W Seeley","author_inst":"University of California, San Francisco"},{"author_name":"Maria Luisa Gorno-Tempini","author_inst":"University of California, San Francisco"},{"author_name":"Peter A Ljubenkov","author_inst":"University of California, San Francisco"},{"author_name":"Julio C Rojas","author_inst":"University of California, San Francisco"},{"author_name":"Suzee Lee","author_inst":"University of California, San Francisco"},{"author_name":"Virginia Sturm","author_inst":"University of California, San Francisco"},{"author_name":"Brian Appleby","author_inst":"Case Western Reserve University"},{"author_name":"Ece Bayram","author_inst":"University of Colorado Anschutz"},{"author_name":"David Clark","author_inst":"Indiana University"},{"author_name":"Ciaran M Considine","author_inst":"Vanderbilt University"},{"author_name":"Richard R Darby","author_inst":"Vanderbilt University"},{"author_name":"Gregory S Day","author_inst":"Mayo Clinic, Jacksonville"},{"author_name":"Alyssa De Vito","author_inst":"Brown University"},{"author_name":"Mark Eldaief","author_inst":"Massachusetts General Hospital & Harvard Medical School"},{"author_name":"Julie A Fields","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Nupur Ghoshal","author_inst":"Washington University"},{"author_name":"Edward D Huey","author_inst":"Brown University"},{"author_name":"David J Irwin","author_inst":"University of Pennsylvania"},{"author_name":"Kejal Kantarci","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Justin Y Kwan","author_inst":"National Institutes of Health"},{"author_name":"Ian R Mackenzie","author_inst":"University of British Columbia"},{"author_name":"Joseph C Masdeu","author_inst":"Houston Methodist"},{"author_name":"Chiadi U Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Alexander Pantelyat","author_inst":"Johns Hopkins University"},{"author_name":"Belen Pascual","author_inst":"Houston Methodist"},{"author_name":"Tanav Popli","author_inst":"University of Michigan"},{"author_name":"Katya Rascovsky","author_inst":"University of Pennsylvania"},{"author_name":"Neguine Rezaii","author_inst":"Massachusetts General Hospital"},{"author_name":"Sonja W Scholz","author_inst":"National Institutes of Health"},{"author_name":"Allison Snyder","author_inst":"National Institutes of Health"},{"author_name":"M. Carmela Tartaglia","author_inst":"University of Toronto"},{"author_name":"Bryan J Traynor","author_inst":"National Institutes of Health"},{"author_name":"Bonnie Wong","author_inst":"MGH"},{"author_name":"John Kornak","author_inst":"University of California, San Francisco"},{"author_name":"Walter K Kremers","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Leah K Forsberg","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Hilary W Heuer","author_inst":"University of California, San Francisco"},{"author_name":"Bradley F Boeve","author_inst":"Mayo Clinic, Rochester"},{"author_name":"Howard J Rosen","author_inst":"University of California, San Francisco"},{"author_name":"Adam L Boxer","author_inst":"University of California, San Francisco"},{"author_name":"Adam M Staffaroni","author_inst":"University of California, San Francisco"},{"author_name":"- ALLFTD Consortium","author_inst":""}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Testing the Feasibility of a Smartphone Application for Collecting Data on Occupational Violence Exposure Among Nurses and Midwives","rel_doi":"10.64898\/2026.09.14.26363061","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.14.26363061","rel_abs":"Background: Nurses are disproportionately affected by occupational violence, yet conventional incident reporting and retrospective surveys underestimate its extent and miss its context. Ecological momentary assessment (EMA) offers a way to capture violence in near-real time. Aim: To evaluate the feasibility of a smartphone EMA application for capturing the incidence, characteristics, and reporting of occupational violence among hospital nurses and midwives. Methods: In a prospective, single-site feasibility study at a large public hospital, nurses and midwives used a commercially available EMA application (MetricWire) to report occupational violence in two-hourly blocks across their shifts over a three-week period. Incidence, incident characteristics, reporting, and usability were analysed descriptively. Findings: Of 108 enrolled participants, 69 contributed 607 momentary assessments, recording 111 incidents. Violence was reported in 18.6% of assessments, and 62% of participants reported at least one incident. Most incidents were verbal (69%) and patient-perpetrated (86%); 59% involved witnessing violence against a colleague. Although 57% of incidents were reported to someone, only 6% reached the formal incident management system. Respondents (n = 16) found the application easy to use and acceptable. Conclusion: Smartphone-based EMA feasibly and acceptably captures contextually rich, near-real-time data on occupational violence, including the witnessed exposure and under-reporting that conventional systems miss.","rel_num_authors":5,"rel_authors":[{"author_name":"Jed Duff","author_inst":"Queensland University of Technology"},{"author_name":"Michael Chataway","author_inst":"Queebsland University of Technology"},{"author_name":"Grace Xu","author_inst":"Queensland University of Technology"},{"author_name":"Amand Fox","author_inst":"Queensland University of Technology"},{"author_name":"Sandra Johnston","author_inst":"Queensland University of Technology"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"A Causal Multi-modal AI Model Stratifies Residual Risk and Identifies Candidates for Treatment Escalation in Node-Positive HR+\/HER2- Early Breast Cancer","rel_doi":"10.64898\/2026.09.15.26362492","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.15.26362492","rel_abs":"PURPOSE Prognostic biomarkers that estimate residual recurrence risk after standard adjuvant therapy to guide further treatment escalation are an unmet clinical need. This study used Ataraxis Breast CTX, a causal multi-modal AI model integrating clinical variables and histopathology, to stratify residual risk in clinically defined high-risk patients. We aimed to identify patients who have excellent outcomes on standard-of-care chemoendocrine therapy and patients who may benefit from additional therapies such as everolimus or CDK4\/6 inhibitors. METHODS CTX combines clinical variables with image features from H&E images to produce estimates of recurrence risk (CTX-prognostic) and chemotherapy benefit (CTX-benefit). Prospective-retrospective validation was performed in the phase III UNIRAD trial to assess CTX-prognostic's performance in the subset of patients who had not received neoadjuvant chemotherapy, who had received adjuvant chemotherapy, and who had H&E slides available (n = 556). The primary endpoint in this study was disease-free survival (DFS). As an exploratory analysis, we evaluated CTX-benefit's ability to predict benefit from adjuvant everolimus. RESULTS CTX-prognostic effectively stratified patients into high- and low-risk groups. Across all patients, 5-year DFS was significantly higher in the low-risk group (93%) than in the high-risk group (80%). Additionally, treatment benefit from everolimus differed significantly by CTX-benefit score in an exploratory multivariable analysis adjusting for age, tumor size, nodal status, grade, and menopausal status (interaction p = 0.01). CONCLUSION CTX identified patients with good outcomes under chemoendocrine therapy alone and patients with residual risk who may benefit from treatment escalation. Additionally, CTX was found to be predictive of everolimus benefit. These results suggest that CTX may effectively stratify clinically high-risk HR+\/HER2- patients by residual risk and may inform selection of adjuvant escalation strategies.","rel_num_authors":14,"rel_authors":[{"author_name":"Thomas Bachelot","author_inst":"Medical Oncology Department, Centre Leon Berard, Lyon, France"},{"author_name":"Sylvie Chabaud","author_inst":"Department of Clinical Research and Innovation, Centre Leon Berard, Lyon, France"},{"author_name":"Jerome Lemonnier","author_inst":"Research and Development Unicancer, Paris, France"},{"author_name":"Paul H. Cottu","author_inst":"Medical Oncology, Institut Curie, Universite, Paris, France"},{"author_name":"Florence Dalenc","author_inst":"Institut Claudius Regaud, IUCT-Oncopole, Toulouse, France"},{"author_name":"Frederick M. Howard","author_inst":"University of Chicago, Chicago, IL"},{"author_name":"Lajos Pusztai","author_inst":"Yale Cancer Center, New Haven, CT"},{"author_name":"Cerise Tang","author_inst":"Ataraxis AI"},{"author_name":"Dhruva Biswas","author_inst":"Ataraxis AI"},{"author_name":"Ken Zeng","author_inst":"Ataraxis AI"},{"author_name":"Jan Witowski","author_inst":"Ataraxis AI"},{"author_name":"Krzysztof J. Geras","author_inst":"Ataraxis AI"},{"author_name":"Fabrice Andre","author_inst":"Gustave Roussy and Paris-Saclay University, Villejuif, France"},{"author_name":"Frederique Madeleine Penault-Llorca","author_inst":"Centre Jean Perrin, Universite Clermont Auvergne, INSERM, U1240 Imagerie Moleculaire et Strategies Theranostiques, Clermont-Ferrand, France"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"A Causal Multi-modal AI Model Stratifies Residual Risk and Identifies Candidates for Treatment Escalation in Node-Positive HR+\/HER2- Early Breast Cancer","rel_doi":"10.64898\/2026.09.15.26362492","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.15.26362492","rel_abs":"PURPOSE Prognostic biomarkers that estimate residual recurrence risk after standard adjuvant therapy to guide further treatment escalation are an unmet clinical need. This study used Ataraxis Breast CTX, a causal multi-modal AI model integrating clinical variables and histopathology, to stratify residual risk in clinically defined high-risk patients. We aimed to identify patients who have excellent outcomes on standard-of-care chemoendocrine therapy and patients who may benefit from additional therapies such as everolimus or CDK4\/6 inhibitors. METHODS CTX combines clinical variables with image features from H&E images to produce estimates of recurrence risk (CTX-prognostic) and chemotherapy benefit (CTX-benefit). Prospective-retrospective validation was performed in the phase III UNIRAD trial to assess CTX-prognostic's performance in the subset of patients who had not received neoadjuvant chemotherapy, who had received adjuvant chemotherapy, and who had H&E slides available (n = 556). The primary endpoint in this study was disease-free survival (DFS). As an exploratory analysis, we evaluated CTX-benefit's ability to predict benefit from adjuvant everolimus. RESULTS CTX-prognostic effectively stratified patients into high- and low-risk groups. Across all patients, 5-year DFS was significantly higher in the low-risk group (93%) than in the high-risk group (80%). Additionally, treatment benefit from everolimus differed significantly by CTX-benefit score in an exploratory multivariable analysis adjusting for age, tumor size, nodal status, grade, and menopausal status (interaction p = 0.01). CONCLUSION CTX identified patients with good outcomes under chemoendocrine therapy alone and patients with residual risk who may benefit from treatment escalation. Additionally, CTX was found to be predictive of everolimus benefit. These results suggest that CTX may effectively stratify clinically high-risk HR+\/HER2- patients by residual risk and may inform selection of adjuvant escalation strategies.","rel_num_authors":14,"rel_authors":[{"author_name":"Thomas Bachelot","author_inst":"Medical Oncology Department, Centre Leon Berard, Lyon, France"},{"author_name":"Sylvie Chabaud","author_inst":"Department of Clinical Research and Innovation, Centre Leon Berard, Lyon, France"},{"author_name":"Jerome Lemonnier","author_inst":"Research and Development Unicancer, Paris, France"},{"author_name":"Paul H. Cottu","author_inst":"Medical Oncology, Institut Curie, Universite, Paris, France"},{"author_name":"Florence Dalenc","author_inst":"Institut Claudius Regaud, IUCT-Oncopole, Toulouse, France"},{"author_name":"Frederick M. Howard","author_inst":"University of Chicago, Chicago, IL"},{"author_name":"Lajos Pusztai","author_inst":"Yale Cancer Center, New Haven, CT"},{"author_name":"Cerise Tang","author_inst":"Ataraxis AI"},{"author_name":"Dhruva Biswas","author_inst":"Ataraxis AI"},{"author_name":"Ken Zeng","author_inst":"Ataraxis AI"},{"author_name":"Jan Witowski","author_inst":"Ataraxis AI"},{"author_name":"Krzysztof J. Geras","author_inst":"Ataraxis AI"},{"author_name":"Fabrice Andre","author_inst":"Gustave Roussy and Paris-Saclay University, Villejuif, France"},{"author_name":"Frederique Madeleine Penault-Llorca","author_inst":"Centre Jean Perrin, Universite Clermont Auvergne, INSERM, U1240 Imagerie Moleculaire et Strategies Theranostiques, Clermont-Ferrand, France"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Promising prognostic factors in Cutaneous Leishmaniasis in regions of Leishmaniavirus 1 circulation","rel_doi":"10.64898\/2026.09.18.26363400","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363400","rel_abs":"ABSTRACT Background Cutaneous leishmaniasis (CL) caused by Leishmania (Viannia) may involve parasite dissemination from the primary skin lesion to clinically healthy mucosal sites, a process potentially relevant to the development of mucosal leishmaniasis. Parasite burden and Leishmania RNA Virus 1 (LRV1) have been proposed as factors influencing parasite persistence, dissemination, and treatment response. We investigated whether parasite load and LRV1 detection in skin lesions were associated with Leishmania in clinically healthy nasal mucosa and, in a subset of patients, with therapeutic outcome. We also assessed the relationship between LRV1 and parasite load. Methodology\/Principal findings  We conducted a prospective observational cohort study. Parasite load and LRV1 were assessed by qPCR in skin lesions and clinically healthy nasal mucosa from patients with localized cutaneous leishmaniasis in Rondonia, Brazilian Amazon. Samples were evaluated before treatment (D0), at the end of treatment (D20), and during follow-up (D90-180). Among 178 patients screened, CL was confirmed in 113. LRV1 was detected in skin lesions in 34.51% of patients and in nasal mucosa in 24.13%. Leishmania DNA was detected in clinically healthy nasal mucosa in 12.38% of patients. LRV1 detection in the skin lesion was associated with detection of Leishmania in the nasal mucosa. Higher parasite loads were observed in more recent lesions. Among patients evaluated for therapeutic outcome, higher parasite load before treatment was associated with treatment failure and was the factor most strongly associated with an unfavorable response in multivariate analysis. Conclusions\/Significance LRV1 detection in cutaneous lesions was associated with Leishmania in clinically healthy nasal mucosa, although the significance of this association and its relationship with parasite dissemination require further investigation. In contrast, parasite burden was associated with therapeutic outcome, with higher pre-treatment loads observed in patients who experienced treatment failure. The absence of an association between LRV1 and parasite load suggests that these two parameters may provide distinct information regarding parasite detection at mucosal sites and therapeutic response.","rel_num_authors":8,"rel_authors":[{"author_name":"Cipriano Ferreira da Silva-J\u00fanior","author_inst":"Instituto Oswaldo Cruz"},{"author_name":"Sayonara dos Reis","author_inst":"Funda\u00e7\u00e3o Oswaldo Cruz Noroeste: Fiocruz Rondonia"},{"author_name":"Renata  Bispo Santos","author_inst":"Funda\u00e7\u00e3o Oswaldo Cruz Noroeste: Fiocruz Rondonia"},{"author_name":"Moreno  Magalh\u00e3es de Souza Rodrigues","author_inst":"Johns Hopkins School of Medicine: The Johns Hopkins University School of Medicine"},{"author_name":"Juan  Miguel Villalobos Salcedo","author_inst":"Funda\u00e7\u00e3o Oswaldo Cruz Noroeste: Fiocruz Rondonia"},{"author_name":"Gabriel  Eduardo Melim Ferreira","author_inst":"Funda\u00e7\u00e3o Oswaldo Cruz Noroeste: Fiocruz Rondonia"},{"author_name":"Lilian  Motta Cantanh\u00eade","author_inst":"Instituto Oswaldo Cruz"},{"author_name":"Elisa Cupolillo","author_inst":"Fundacao Oswaldo Cruz"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Spatiotemporal dynamics, factors associated with neonatal mortality and health interventions in Mali: a modeling study","rel_doi":"10.64898\/2026.09.17.26363290","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363290","rel_abs":"Background Neonatal mortality in Sub-Saharan Africa remains high, accounting for approximately 46% of all neonatal deaths worldwide. In Mali, neonatal mortality stands at 29 deaths per 1,000 live births, with marked subnational disparities. This study aimed to assess the spatiotemporal dynamics of neonatal mortality in Mali from 2012 to 2023 and to project potential reductions in neonatal mortality by 2035 under different scenarios of scaling up three high-impact interventions. Methods We analyzed data from the 2012-2013, 2018, and 2023-2024 Demographic and Health Surveys to assess spatiotemporal patterns in neonatal mortality across Mali. Multilevel mixed-effects logistic regression identified factors associated with neonatal mortality. Global Moran's I and Local Indicators of Spatial Association assessed spatial dependence and identified high-high clusters. The Lives Saved Tool estimated potential reductions in neonatal deaths under alternative intervention scale-up scenarios through 2035. Results National neonatal mortality declined from 34 deaths per 1,000 live births (95% CI: 31-38) in 2012 to 29 (95% CI: 26-32) in 2023. Significant spatial clustering persisted across all survey rounds (Global Moran's I, all p<0.001), with recurrent high-high clusters in Sikasso, Mopti, Segou and Tombouctou. Male neonates had higher odds of death (AOR, 1.66; 95% CI, 1.26-2.19), whereas birth intervals of at least 2 years (AOR range, 0.42-0.48), postnatal care (AOR, 0.42; 95% CI, 0.19-0.94), and improved sanitation (AOR, 0.42; 95% CI, 0.27-0.67) were associated with lower odds. LiST projections indicated that scaling up thermal care, neonatal resuscitation, and clean cord care could avert more than half of preventable neonatal deaths by 2035. Conclusions Persistent clusters of high neonatal mortality were identified in Sikasso, Segou, Mopti, and Tombouctou, highlighting the need for geographically targeted strategies. Scaling up high-impact neonatal interventions could substantially reduce preventable neonatal deaths in Mali.","rel_num_authors":15,"rel_authors":[{"author_name":"Fatoumata  Bintou TRAORE","author_inst":"National Institute for Public Health, Bamako (Mali)"},{"author_name":"Cheick  Sidya Sidib\u00e9","author_inst":"National Training Institute in Health Sciences"},{"author_name":"Youssouf Keita","author_inst":"World Bank"},{"author_name":"Fatoumata Sidib\u00e9","author_inst":"National Public Health Institute"},{"author_name":"Ibrahim Terera","author_inst":"National Public Health Institute"},{"author_name":"Mariam Traor\u00e9","author_inst":"National Public Health Institute"},{"author_name":"Mamadou Berth\u00e9","author_inst":"National Public Health Institute"},{"author_name":"Haoua Dembel\u00e9","author_inst":"National Public Health Institute"},{"author_name":"Boureyma Belem","author_inst":"National Public Health Institute"},{"author_name":"Kassoum Kon\u00e9","author_inst":"National Public Health Institute"},{"author_name":"Aissata Tour\u00e9","author_inst":"National Public Health Institute"},{"author_name":"Abdoulaye Dabo","author_inst":"National Public Health Institute"},{"author_name":"Fatou Diawara","author_inst":"National Public Health Institute"},{"author_name":"Ibrehima Guindo","author_inst":"National Public Health Institute"},{"author_name":"Abdoulaye Maiga","author_inst":"Johns Hopkins University Bloomberg School of Public Health"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Artificial Intelligence-Enhanced Electrocardiography for Detection and Prediction of Hypertrophic Cardiomyopathy across Monogenic and Polygenic Susceptibility","rel_doi":"10.64898\/2026.09.12.26362902","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.12.26362902","rel_abs":"Background: Cascade screening increasingly identifies carriers of pathogenic or likely pathogenic sarcomere variants at risk for hypertrophic cardiomyopathy (HCM) in whom penetrance is incomplete, and surveillance relies on resource-intensive serial imaging. We evaluated whether a validated artificial intelligence-enhanced electrocardiography (AI-ECG) model identifies the HCM phenotype at first clinical assessment, predicts development of HCM during follow-up, and complements polygenic risk. Methods: We assembled 1,095 genotype-positive (G+) individuals with pathogenic or likely pathogenic sarcomere variants from Yale-New Haven Hospital (n=119), Erasmus MC (n=858), and Motol University Hospital (n=118). At baseline (first clinical assessment), individuals were classified as phenotype-positive (P+) or phenotype-negative (P-). A previously validated AI-ECG model applied to 12-lead ECG images generated an HCM score. The primary outcome was detection of phenotypic positivity at baseline; secondary analyses included manifest HCM (at baseline or during follow-up) and identifying risk of developing future HCM among G+\/P- individuals. In 57,007 UK Biobank participants, we assessed whether AI-ECG adds to an established polygenic risk score (PRS). Results: Among 1,095 G+ individuals (median age 46 years [IQR 34- 56]; 52.1% female), 808 (73.8%) were P+ at baseline, 56 (5.1%) developed HCM during follow-up, and 231 (21.1%) remained P-. AI-ECG achieved an AUROC of 0.91 (95% CI 0.89-0.93) for P+ at baseline and 0.92 (95% CI 0.90-0.94) for manifest HCM. At a threshold of 0.15, sensitivity was 0.78, specificity 0.89, PPV 0.95, and NPV 0.59. Among G+\/P- individuals, higher AI-ECG scores predicted development of HCM (HR 1.55 per 1-SD; 95% CI 1.28- 1.88; p< 0.001; adjusted HR 1.38; 95% CI 1.11- 1.71; p=0.004). In the UK Biobank, individuals with both high AI-ECG and high PRS had 60-fold higher odds of HCM (adjusted OR 60.2; 95% CI 26.5- 137.2), versus 15.0 for high AI-ECG alone and 4.1 for high PRS alone. Conclusions: AI-ECG detects the HCM phenotype at baseline in sarcomere variant carriers, predicts development of HCM in G+\/P- individuals, and complements PRS in the general population, supporting AI-ECG as a scalable tool to detect HCM and guide surveillance in individuals with monogenic or polygenic susceptibility.","rel_num_authors":14,"rel_authors":[{"author_name":"Philip M. Croon","author_inst":"Yale School of Medicine"},{"author_name":"Ryan B. Choi","author_inst":"Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT, USA"},{"author_name":"Evangelos K. Oikonomou","author_inst":"Section of Cardiovascular Medicine, Dept. of Internal Medicine, Yale School of Medicine, New Haven, CT, USA"},{"author_name":"Sumukh V. Shankar","author_inst":"Section of Cardiovascular Medicine, Dept. of Internal Medicine, Yale School of Medicine, New Haven, CT, USA"},{"author_name":"Lovedeep S. Dhingra","author_inst":"Section of Cardiovascular Medicine, Dept. of Internal Medicine, Yale School of Medicine, New Haven, CT, USA"},{"author_name":"Nico Bruining","author_inst":"Thoraxcenter, Cardiovascular Institute, Erasmus Medical Center, Rotterdam, The Netherlands"},{"author_name":"Peter-Paul Zwetsloot","author_inst":"Thoraxcenter, Cardiovascular Institute, Erasmus Medical Center, Rotterdam, The Netherlands"},{"author_name":"Michelle Michels","author_inst":"Thoraxcenter, Cardiovascular Institute, Erasmus Medical Center, Rotterdam, The Netherlands"},{"author_name":"Rudolf A. de Boer","author_inst":"Thoraxcenter, Cardiovascular Institute, Erasmus Medical Center, Rotterdam, The Netherlands"},{"author_name":"Veronika Puchnerov\u00e1","author_inst":"Department of Cardiology, Motol University Hospital, Prague, Czech Republic"},{"author_name":"Ji\u0159\u00ed Bonaventura","author_inst":"Department of Cardiology, Motol University Hospital, Prague, Czech Republic"},{"author_name":"Robert M.A. van der Boon","author_inst":"Thoraxcenter, Cardiovascular Institute, Erasmus Medical Center, Rotterdam, The Netherlands"},{"author_name":"Sounok Sen","author_inst":"Section of Cardiovascular Medicine, Dept. of Internal Medicine, Yale School of Medicine, New Haven, CT, USA"},{"author_name":"Rohan Khera","author_inst":"Section of Cardiovascular Medicine, Dept. of Internal Medicine, Yale School of Medicine, New Haven, CT, USA"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Differential Associations of Postoperative Plasma and Cerebrospinal Fluid Albumin Changes with Delirium Following Non-Cardiac Surgery","rel_doi":"10.64898\/2026.09.18.26363418","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363418","rel_abs":"BACKGROUND: Postoperative increases in cerebrospinal fluid (CSF) to plasma albumin ratio (CPAR), a blood-brain barrier dysfunction marker, have been associated with postoperative delirium (POD) and prolonged hospital stay. However, the contributions of plasma versus CSF albumin changes remain unclear. AIM: To determine whether 24-hour postoperative changes in plasma and CSF albumin are independently associated with POD and hospital length of stay. METHODS: Plasma and CSF albumin concentrations were measured before and 24-hours postoperatively in older non-cardiac surgery patients. Multivariable logistic and negative binomial regression models evaluated associations between albumin changes and POD or hospital length of stay, adjusting for age, baseline cognition, surgery type, and fluid administration. RESULTS: Of 240 patients, 31 (13.3%) developed POD. From before to 24-hours after surgery, both plasma albumin (median 3.95 to 3.43 g\/dL, p<0.001) and CSF albumin decreased (median 22.68 to 20.43 mg\/dL, p<0.001). Greater plasma albumin decreases (per 0.43 g\/dL) were independently associated with POD (OR 2.14, 95% CI 1.28-3.58; p=0.004) and longer hospital stay (mean ratio 1.44, 95% CI 1.26-1.64; p<0.001). In contrast, CSF albumin changes (per 5.8 mg\/dL higher) were not associated with POD (OR 0.97, 95% CI 0.60-1.58; p=0.91) but were modestly associated with longer hospital stay (mean ratio 1.17, 95% CI 1.04-1.32; p=0.01). CONCLUSIONS: Plasma and CSF albumin decreased postoperatively, but only plasma decreases were associated with POD. These results suggest that associations between CPAR increases and POD may be due to postoperative plasma albumin decreases and highlight limitations of CPAR as a standalone marker of postoperative BBB dysfunction.","rel_num_authors":21,"rel_authors":[{"author_name":"Refaat Hassan","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Ligia Sant'Ana Dumont","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Mary Cooter Wright","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Jeffry Takla","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Kristen Monten","author_inst":"School of Medicine, Duke University"},{"author_name":"Samuel Teshome","author_inst":"School of Medicine, Duke University"},{"author_name":"Edward R. Marcantonio","author_inst":"Divisions of General Medicine and Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School"},{"author_name":"Niccolo Terrando","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Jeffrey N. Browndyke","author_inst":"Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine"},{"author_name":"Heather E. Whitson","author_inst":"Duke Center for the Study of Aging and Human Development, Duke University Medical Center"},{"author_name":"Harvey J. Cohen","author_inst":"Duke Center for the Study of Aging and Human Development, Duke University Medical Center"},{"author_name":"Andrea G. Nackley","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Megan K. Wong","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Marguerita E. Klein","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Piper C. Boykin","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Noah J. Timko","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Michael Muehlbauer","author_inst":"Duke Molecular Physiology Institute, Duke University School of Medicine"},{"author_name":"E. Wesley Ely","author_inst":"Critical Illness, Brain Dysfunction, and Survivorship Center, Vanderbilt University Medical Center"},{"author_name":"Joseph P. Mathew","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Miles Berger","author_inst":"Department of Anesthesiology, Duke University School of Medicine"},{"author_name":"Michael Devinney","author_inst":"Department of Anesthesiology, Duke University School of Medicine"}],"rel_date":"2026-09-21","rel_site":"medrxiv"},{"rel_title":"Municipal Wastewater in Ottawa, Canada contains a reservoir of bacteriophages with clinically relevant Escherichia coli and Klebsiella pneumoniae Hosts","rel_doi":"10.64898\/2026.09.20.752992","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.20.752992","rel_abs":"The recent rise of antimicrobial resistant bacteria in health care and environmental settings has been detrimental to the feasibility of antibiotic treatments for patients and agricultural applications. Along with this escalating issue, a resurgence of bacteriophage research has occurred, and phage therapy is proving to be a powerful case-specific alternative. However, a centralized source of phages that are accessible, abundant, and characterized as candidates for potential use in therapeutic applications remains to be fully established. This study aims to identify the range of bacteriophages available in municipal wastewater from Ottawa, Ontario that can infect and lyse Escherichia coli O1:K1:H7 and Klebsiella pneumoniae K3 hosts. Building-level sewer shed, influent, and primary sludge samples were screened for the presence of these phages which were then isolated through several rounds of plaque purification, sequenced by Nanopore technology, and annotated. Ten phages belonging to the genus Kayfunavirus, Vectrevirus, Kuravirus, or Sugarlandvirus were identified and bio-banked from different types of wastewater at several time points. These phages are 96-99% identical to phages isolated in Germany, Switzerland, and Spain, but contain divergent structural and metabolic genes. This work contributes to the ever-growing database of sequenced phages, provided with a physical archive of the organisms, and helps uncover the extent of phage biodiversity at different levels of wastewater treatment facilities that are readily available for screening in phage therapy applications.","rel_num_authors":6,"rel_authors":[{"author_name":"Sean E.K. Stephenson","author_inst":"Children's Hospital of Eastern Ontario, Research Institute"},{"author_name":"Walaa Eid","author_inst":"Children's Hospital of Eastern Ontario, Research Institute"},{"author_name":"Elisabeth Mercier","author_inst":"University of Ottawa, Department of Civil Engineering"},{"author_name":"Robert Delatolla","author_inst":"University of Ottawa, Department of Civil Engineering"},{"author_name":"Adam D Rudner","author_inst":"University of Ottawa"},{"author_name":"Tyson E. Graber","author_inst":"Children's Hospital of Eastern Ontario, Research Institute"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Municipal Wastewater in Ottawa, Canada contains a reservoir of bacteriophages with clinically relevant Escherichia coli and Klebsiella pneumoniae Hosts","rel_doi":"10.64898\/2026.09.20.752992","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.20.752992","rel_abs":"The recent rise of antimicrobial resistant bacteria in health care and environmental settings has been detrimental to the feasibility of antibiotic treatments for patients and agricultural applications. Along with this escalating issue, a resurgence of bacteriophage research has occurred, and phage therapy is proving to be a powerful case-specific alternative. However, a centralized source of phages that are accessible, abundant, and characterized as candidates for potential use in therapeutic applications remains to be fully established. This study aims to identify the range of bacteriophages available in municipal wastewater from Ottawa, Ontario that can infect and lyse Escherichia coli O1:K1:H7 and Klebsiella pneumoniae K3 hosts. Building-level sewer shed, influent, and primary sludge samples were screened for the presence of these phages which were then isolated through several rounds of plaque purification, sequenced by Nanopore technology, and annotated. Ten phages belonging to the genus Kayfunavirus, Vectrevirus, Kuravirus, or Sugarlandvirus were identified and bio-banked from different types of wastewater at several time points. These phages are 96-99% identical to phages isolated in Germany, Switzerland, and Spain, but contain divergent structural and metabolic genes. This work contributes to the ever-growing database of sequenced phages, provided with a physical archive of the organisms, and helps uncover the extent of phage biodiversity at different levels of wastewater treatment facilities that are readily available for screening in phage therapy applications.","rel_num_authors":6,"rel_authors":[{"author_name":"Sean E.K. Stephenson","author_inst":"Children's Hospital of Eastern Ontario, Research Institute"},{"author_name":"Walaa Eid","author_inst":"Children's Hospital of Eastern Ontario, Research Institute"},{"author_name":"Elisabeth Mercier","author_inst":"University of Ottawa, Department of Civil Engineering"},{"author_name":"Robert Delatolla","author_inst":"University of Ottawa, Department of Civil Engineering"},{"author_name":"Adam D Rudner","author_inst":"University of Ottawa"},{"author_name":"Tyson E. Graber","author_inst":"Children's Hospital of Eastern Ontario, Research Institute"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A glyoxal sensing Pseudomonas aeruginosa transcription factor enables lung infection","rel_doi":"10.64898\/2026.09.20.752901","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.20.752901","rel_abs":"Aldehydes are a class of normally unwanted toxic electrophilic compounds that mainly arise from oxidation of glucose, lipids or DNA. However, it has recently come to light that they can also be weaponized by professional phagocytes to kill engulfed bacteria. How microbes subvert these assaults remains largely enigmatic. Here we describe the function, atomic structure and mechanism of the first bacterial transcription factor able to directly sense the dicarbonyl glyoxal (GO), which we aptly named the Glyoxal Regulator (GloR, from Pseudomonas aeruginosa PAO1), We show that GloR directly senses GO through a reversible cysteine modification that results in its binding to a conserved DNA regulatory motif (a glo box), which then triggers a transcriptional activation of a defined set of genes to help counter GO toxicity and enable acute lung infection. Despite substantial evolutionary divergence, when unmodified gloR and a glo box-regulated reporter were transferred into E. coli, a strikingly tight GO-specific regulation was maintained, suggesting this system could be readily transferred between unrelated microbial species. As homologs of GloR were identified in diverse bacterial species we anticipate its use to be widespread in both pathogens and environmental bacteria. Taken together, we present the first bona fide bacterial aldehyde regulator which senses host GO to enable survival during infection.","rel_num_authors":10,"rel_authors":[{"author_name":"Christopher J. Corcoran","author_inst":"Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA."},{"author_name":"David G. Glanville","author_inst":"Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA."},{"author_name":"Bonnie J. Cuthbert","author_inst":"Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, California, USA."},{"author_name":"Rodger de Miranda","author_inst":"Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, California, USA."},{"author_name":"Jocelin Martinez","author_inst":"Department of Molecular Biology and Biochemistry, University of California, Irvine,     Irvine, California, USA."},{"author_name":"Johnathan D. Keith","author_inst":"Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham, Alabama, USA."},{"author_name":"Peter Prevelige","author_inst":"Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, USA"},{"author_name":"Susan E. Birket","author_inst":"Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA."},{"author_name":"Celia W. Goulding","author_inst":"Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, California, USA."},{"author_name":"Andrew T. Ulijasz","author_inst":"Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA."}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Nutrient and prey-sensing signaling pathways converge on the sphingolipid methyltransferase SMT1 to regulate trap formation in a predatory fungus","rel_doi":"10.64898\/2026.09.18.752630","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.18.752630","rel_abs":"The nematode trapping fungus Arthrobotrys oligospora transitions from saprophytic growth to a predatory lifestyle by forming adhesive traps in response to nutrient limitation and nematode derived cues. How nutrient availability integrates with prey sensing to control trap formation remains unclear. The presence of glucose can suppress trap formation and we found that Cre1, a conserved transcription factor that regulates the carbon catabolite repression pathway in fungi is essential for trap formation. Comparative transcriptomics and functional studies identified SMT1, which encodes a sphingolipid C9 methyltransferase, as a Cre1-dependent target that is sufficient to restore trap formation defect in the cre1 mutant. Smt1 contributes to the formation of sterol-enriched membrane domain at the tip of a growing trap hyphae and thus affects trap morphogenesis. We further discovered that the expression of SMT1 depends on both Cre1 and another transcription factor Ste12 that acts downstream of the pheromone response MAPK pathway critical for prey-sensing. These findings reveal functional crosstalk between Cre1 and Ste12 where both transcription factors are required for the expression of SMT1 and demonstrate that a predatory fungus integrates nutrient and prey-derived signals to regulate predatory lifestyle switching.","rel_num_authors":7,"rel_authors":[{"author_name":"Tsung-Yu Huang","author_inst":"Academia Sinica"},{"author_name":"Ching-Ting Yang","author_inst":"Max Planck Institute for Biology T\u00fcbingen: Max-Planck-Institut fur Biologie Tubingen"},{"author_name":"Chih-Yen Kuo","author_inst":"Max Planck Institute for Biology T\u00fcbingen: Max-Planck-Institut fur Biologie Tubingen"},{"author_name":"A. Pedro Gon\u00e7alves","author_inst":"Academia Sinica"},{"author_name":"Guillermo Vidal-Diez de Ulzurrun","author_inst":"Max Planck Institute for Biology T\u00fcbingen: Max-Planck-Institut fur Biologie Tubingen"},{"author_name":"Hillel Schwartz","author_inst":"Max Planck Institute for Biology T\u00fcbingen: Max-Planck-Institut fur Biologie Tubingen"},{"author_name":"Yen-Ping Hsueh","author_inst":"Max Planck Institute for Biology T\u00fcbingen: Max-Planck-Institut fur Biologie Tubingen"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Localized SARS-CoV-2 Infection Triggers a Tissue-Wide Antiviral Response and Functional Impairment of Olfactory Sensory Neurons","rel_doi":"10.64898\/2026.09.19.752823","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.19.752823","rel_abs":"Olfactory dysfunction is a hallmark of COVID-19, yet the mechanisms by which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes widespread sensory impairment remain incompletely understood. We compared the olfactory epithelial tropism of multiple SARS-CoV-2 variants in a mouse model and observed that Alpha and Beta variants exhibited the greatest infectivity for the olfactory epithelium (OE), whereas Omicron rarely infected this tissue despite comparable pulmonary viral titers. We further defined the effects of SARS-CoV-2 on olfactory sensory neurons (OSNs) using immunohistochemistry, single-cell RNA sequencing, spatial gene expression characterization, and functional odor stimulation. The localized infection of sustentacular cells triggered a tissue-wide interferon-stimulated antiviral response that extended beyond infected regions for Alpha and Beta but was largely absent following Omicron infection. Mature OSNs transiently adopted an interferon-responsive state before exhibiting persistent downregulation of odorant signal transduction, mitochondrial, and activity-dependent gene pathways. Consistent with these transcriptional changes, odor stimulation failed to elicit normal activity-dependent gene expression during SARS-CoV-2 infection, indicating impaired neuronal function without widespread neuronal loss. Progressive accumulation of macrophages further indicated sustained inflammatory remodeling of the OE. Together, these findings demonstrate that SARS-CoV-2 infection initiates tissue-wide antiviral signaling in the OE that persistently disrupts OSN function, providing a mechanistic framework for COVID-19-associated anosmia.","rel_num_authors":11,"rel_authors":[{"author_name":"Jiaying Liu","author_inst":"University of California, Davis"},{"author_name":"Muhammad Shoaib Akhtar","author_inst":"University of California, Davis"},{"author_name":"Hongwei Liu","author_inst":"University of California, Davis"},{"author_name":"Yaejin Kim","author_inst":"University of California, Davis"},{"author_name":"Brianna M. Ramirez","author_inst":"University of California, Davis"},{"author_name":"Anthony L Weidner","author_inst":"University of California, Davis"},{"author_name":"Austin Chan","author_inst":"University of California, Davis"},{"author_name":"Maxwell Collins","author_inst":"University of California, Davis"},{"author_name":"Stefan Rothenburg","author_inst":"University of California, Davis"},{"author_name":"Lark L Coffey","author_inst":"University of California, Davis"},{"author_name":"Qizhi Gong","author_inst":"University of California, Davis"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Focused Ultrasound Neuromodulation of the Central Lateral Thalamus in a Non-Human Primate Model of Disorders of Consciousness","rel_doi":"10.64898\/2026.09.15.751608","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751608","rel_abs":"Objectives: Disorders of consciousness (DOC) affect an estimated 200,000 patients in the United States. Effective treatment options have remained elusive. Focused ultrasound neuromodulation (FUS) of brain regions controlling consciousness, such as the central lateral thalamus (CLT), has emerged as a promising non-invasive treatment. However, prior studies have been limited by broad effective stimulation volumes, missing control conditions, and limited target validation. This study investigated the effects of FUS of the CLT in a non-human primate model of DOC with robust control conditions and more robust targeting than previous experiments. Materials and Methods: Two male rhesus macaques underwent 1-hour propofol anesthesia sessions as a model of DOC. Bilateral CLT targets were sonicated using a stereotactically mounted 256-element phased-array focused ultrasound system. Focused and unfocused (random phases) paradigms were tested in both animals, and a spotlighting (sonicating multiple targets) paradigm was tested in one animal. Arousal was monitored via EEG beta power, pulse oximetry, breathing rate, and movement, and compared between sonication and control sessions for each paradigm. Results: Paired Wilcoxon signed-rank tests showed no significant differences for any of the four measures across the three paradigms (all pFDR [&ge;] 0.30). The largest observed effect was increased body movement under the unfocused paradigm (rrb = +0.58), though this did not reach statistical significance. Animals remained physiologically stable throughout sessions and recovery periods, with no clinically significant changes in heart rate, breathing rate, blood oxygen saturation, or other safety concerns. Conclusions: Under the tested parameters, FUS of the CLT did not produce measurable changes in arousal. The absence of adverse physiological effects supports the safety of this FUS paradigm. The largest effect occurring under spatially distributed sonication, consistent with prior evidence that broader stimulation volumes produce stronger arousal responses, suggests that distributed network stimulation may warrant investigation as an alternative to focal targeting. Future studies should investigate this possibility and should include robust control conditions to properly quantify effects.","rel_num_authors":6,"rel_authors":[{"author_name":"Carter Lybbert","author_inst":"University of Utah"},{"author_name":"Caroline Garrett","author_inst":"University of Utah"},{"author_name":"Taylor D Webb","author_inst":"University of Utah"},{"author_name":"Keisuke Tsunoda","author_inst":"Washington University"},{"author_name":"Ruksana Begum","author_inst":"University of Utah"},{"author_name":"Jan Kubanek","author_inst":"University of Utah"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Dorsal ocelli set the luminance-dependent operating state of the bumblebee visual system","rel_doi":"10.64898\/2026.09.15.751776","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751776","rel_abs":"Despite long-standing hypotheses that insect dorsal ocelli modulate compound-eye processing to support flight stabilization, dim-light navigation, and locomotor speed, the neurophysiological basis of these functions remains unclear. Combining behavioural assays with multi-site local field potential recordings in bumblebees, we tested how ocellar input affects compound-eye processing. Ocellar occlusion impaired orientation precision at dusk, supporting a role for ocelli in dim-light navigation. Under bright daytime skies, occlusion did not affect orientation but reduced flight speed, consistent with a role in locomotor control under high illumination. Neurophysiologically, ocellar occlusion disrupted luminance-dependent scaling across the visual system, most prominently in the medulla. In intact bees, broadband neural power scaled inversely with luminance, decreasing under bright and increasing under dim conditions. When ocellar input was blocked, this relationship reversed, leaving visual-system activity in a high-power, dark-like state even under bright illumination. Ocellar modulation was particularly evident in the green-sensitive pathway, implicated in optic-flow processing and flight-speed regulation, providing a neural correlate of the behavioural speed reduction while UV-sensitive responses remained largely invariant following ocellar occlusion. These findings reconcile disparate views of ocellar function and identify ocelli as regulators of the neural dynamic range supporting orientation in low light and movement control in bright conditions.","rel_num_authors":5,"rel_authors":[{"author_name":"C. Ernesto Restrepo","author_inst":"Stockholm University"},{"author_name":"Priscila Araujo","author_inst":"Stockholm University"},{"author_name":"Sanja Mikulovic","author_inst":"Leibniz Institute for Neurobiology, Magdeburg"},{"author_name":"Pavol Bauer","author_inst":"Dynatrace, Vienna"},{"author_name":"Emily Baird","author_inst":"Stockholm University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"G\u03b2\u03b3 dually regulates the M current via increased channel surface expression and PIP2 sensitivity","rel_doi":"10.64898\/2026.09.15.751787","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751787","rel_abs":"The M-current, generated by voltage gated KV7.2\/7.3 channels, sets the threshold for neuronal action potential and acts as a key brake on repetitive firing. The M-current is tightly regulated by signaling molecules, such as calmodulin and phosphatidylinositol-4,5-bisphosphate (PIP2). Here, we show that coexpression of the ubiquitous subunit dimer of heterotrimeric G-proteins, G{beta}{gamma}, with KV7.2\/7.3 in Xenopus laevis oocytes doubles maximal M-current. This regulation requires free, prenylated, membrane-associated G{beta}{gamma} and operates via two distinct mechanisms: 1) increasing plasma membrane (PM) channel density and 2) stabilizing KV7.2\/7.3-PIP2 coupling. Conversely, G{beta}{gamma} scavengers reduce basal KV7.2\/7.3 current and weaken PIP2 coupling. Proximity ligation assays confirm colocalization of G{beta}{gamma} and KV7.2\/7.3 in the PM. Peptide array and AlphaFold modeling identify putative interaction sites on the channel cytoplasmic domain. Finally, the disease-causing G{beta}1 variant I80N abolished G{beta}{gamma}-induced M-current potentiation. Together, these findings establish G{beta}{gamma} as a significant physiological regulator and potential site of vulnerability in neuronal M-current function.","rel_num_authors":14,"rel_authors":[{"author_name":"Boris Shalomov","author_inst":"Tel Aviv University"},{"author_name":"Iiulia Papa-Dmitrieva","author_inst":"Tel Aviv University"},{"author_name":"Tal Keren Raifman","author_inst":"Tel Aviv University"},{"author_name":"Sharon Weiss","author_inst":"Tel Aviv University"},{"author_name":"Flavia De Martino","author_inst":"University of Naples Federico II"},{"author_name":"Adi Gali-Sayag","author_inst":"Tel Aviv University"},{"author_name":"Joel A Hirsch","author_inst":"Tel Aviv University"},{"author_name":"Maurizio Taglialatela","author_inst":"University of Naples Federico II"},{"author_name":"Vincenzo Barrese","author_inst":"University of Naples Federico II"},{"author_name":"Kerstin Zuehlke","author_inst":"Max-Delbruck-Center for Molecular Medicine in the Helmholtz Association (MDC)"},{"author_name":"Enno Klussmann","author_inst":"Max-Delbruck-Center for Molecular Medicine in the Helmholtz Association (MDC)"},{"author_name":"Iain Greenwood","author_inst":"City St George's University of London"},{"author_name":"Ilana Lotan","author_inst":"Tel Aviv University"},{"author_name":"Nathan Dascal","author_inst":"Tel Aviv University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Number, order and time influence how the brain integrates distinct experiences","rel_doi":"10.64898\/2026.09.15.751783","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751783","rel_abs":"How does the brain integrate experiences that are separated in time? The present study addressed this question using sensory preconditioning protocols in rats. In these protocols, rats integrate an A-B association (e.g., tone-light) formed in stage 1 with a B-shock association (e.g., light-shock) formed in stage 2 to generate fear responses (freezing) when tested with A alone in stage 3. Here we show that the mechanism of integration depends on the number, order and timing of events across the two stages of training. When the events are novel (low number of exposures) and the interval between stages 1 and 2 is short (24 hours), the A-B and B-shock associations are integrated through formation of a mediated A-shock association during stage 2. By contrast, when the events are more familiar (greater number of exposures), ordered in a particular way, and the interval between stages 1 and 2 is long (14-days), the A-B and B-shock associations are integrated through their chaining at the time of testing with A alone. Thus, number, order and time determine how distinct experiences are integrated in the brain. These findings are discussed with respect to theories of integration and information processing in the medial temporal lobe.","rel_num_authors":5,"rel_authors":[{"author_name":"Alina B Thomas","author_inst":"University of New South Wales"},{"author_name":"Francesca S Wong","author_inst":"UNSW Sydney"},{"author_name":"Simon Killcross","author_inst":"University of New South Wales"},{"author_name":"R Fred Westbrook","author_inst":"University of New South Wales"},{"author_name":"Nathan Holmes","author_inst":"UNSW Sydney"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Serum metabolomics reveals signatures associated with physical resilience trajectories from middle to older age","rel_doi":"10.64898\/2026.09.14.751497","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751497","rel_abs":"Lifecourse physical resilience is defined by the ability to maintain abilities across multiple domains of physical performance. While the importance of physical resilience in functional independence and mobility disability is clear, studies investigating metabolomic signatures of physical resilience are lacking. Here, we performed untargeted metabolomics on serum samples from a community-based cohort of 237 individuals followed over 28 years, and applied spectral data mining tools to map identified metabolites to health phenotypes from public repositories. We identified metabolites across multiple chemical classes, including acylcarnitines, glutamine conjugates, and phosphocholines, that were differentially associated with physical resilience status. Notably, medium-chain acylcarnitines negatively associated with physical resilience were more frequently observed in disease phenotypes than in healthy individuals. Kynurenine, a tryptophan metabolite linked to age-related functional decline, increased more steeply with age in individuals with low physical resilience. We also found that metabolites of the antihypertensive drug verapamil were associated with physical resilience in a metabolism-dependent manner, differing between oxidative and glucuronidated forms. Together, these metabolic signatures offer a resource for identifying biochemical pathways and biomarkers relevant to physical resilience for healthy aging.","rel_num_authors":10,"rel_authors":[{"author_name":"Jeong In Seo","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA"},{"author_name":"Toon A.W. Scheurink","author_inst":"Center for Clinical Neuroscience and Cognition, University Medical Centre Groningen (UMCG), University of Groningen (RUG), Groningen, the Netherlands, 9713 GZ"},{"author_name":"Crystal X. Wang","author_inst":"Department of Psychiatry, University of California San Diego, La Jolla, CA, USA"},{"author_name":"Kine Eide Kvitne","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA"},{"author_name":"Wilhan D. Goncalves Nunes","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA"},{"author_name":"Jasmine Zemlin","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA"},{"author_name":"Jaclyn Bergstrom","author_inst":"Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, California, USA"},{"author_name":"Pieter C. Dorrestein","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA"},{"author_name":"Ipsita Mohanty","author_inst":"Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, United States \/ Department of Nutritional Sciences, Th"},{"author_name":"Anthony J.A. Molina","author_inst":"Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, California, USA"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"The DNA Legacy of Thomas Jefferson","rel_doi":"10.64898\/2026.09.18.752809","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.18.752809","rel_abs":"Allegations that Thomas Jefferson fathered the children of the enslaved Sally Hemings emerged in the context of U.S. presidential politics in the late 1700s and early 1800s and entailed strongly contested denials and affirmations by family members, biographers, and historians ever since. Previous analysis of Y chromosome markers in contemporary members of the Jefferson and Hemings patrilines was consistent with the paternity hypothesis but rejected by those who pointed out that, absent Jefferson DNA and its direct comparison to the DNA of possible descendants, other Jefferson males could have fathered Sally Hemings children. In this study, we developed an innovative technique to recover DNA from multiple rootless hair samples in a museum collection whose provenance, mitochondrial genomes, Y chromosome markers, and identity to each other indicate that these hairs and the DNA from them are from Thomas Jefferson. Using these DNA data, we find clear evidence of Thomas Jefferson ancestry in descendants of both his wife Martha Wayles Jefferson and Sally Hemings. We measured the amount of identical-by-descent DNA shared between Thomas Jefferson and his known and putative descendants. We find that the amount of shared Jefferson DNA is more likely under the model of direct Thomas Jefferson paternity than other proposed scenarios.","rel_num_authors":14,"rel_authors":[{"author_name":"Richard E. Green","author_inst":"University of California, Santa Cruz"},{"author_name":"Samuel H. Vohr","author_inst":"University of California, Santa Cruz"},{"author_name":"Joshua D Kapp","author_inst":"University of California, Santa Cruz"},{"author_name":"Jane E. Ailes","author_inst":"Independent scholar"},{"author_name":"Samuel Sacco","author_inst":"University of California, Santa Cruz"},{"author_name":"Remy Nguyen","author_inst":"University of California, Santa Cruz"},{"author_name":"James Cahill","author_inst":"University of Florida"},{"author_name":"Peter D. Heintzman","author_inst":"Centre for Palaeogenetics and Department of Geological Sciences, Stockholm University"},{"author_name":"Joanne Flores","author_inst":"Smithsonian Institution"},{"author_name":"Logan Kistler","author_inst":"Smithsonian Institution, National Museum of Natural History"},{"author_name":"Courtney A. Hofman","author_inst":"University of Oklahoma"},{"author_name":"Robert C. Fleischer","author_inst":"Center for Conservation Genomics, Smithsonian National Zoo and Conservation Biology Institute"},{"author_name":"Beth Shapiro","author_inst":"University of California Santa Cruz"},{"author_name":"Richard Kurin","author_inst":"Smithsonian Institution"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Region-dependent regulatioin of Tau phosphorylation in a mouse model of tauopathy","rel_doi":"10.64898\/2026.09.14.751492","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751492","rel_abs":"Hyperphosphorylation of Tau promotes its aggregation and neurofibrillary tangle (NFT) formation, contributing to neuronal dysfunction and neurodegeneration in diseases such as Alzheimer's Disease (AD) and AD-related dementias (ADRDs). However, the mechanisms underlying dysregulated Tau phosphorylation under pathological contexts remain unclear. Glycerophosphodiester phosphodiesterase 2 (GDE2) is a six-transmembrane enzyme that acts at the cell surface to cleave the glycosylphosphatidylinositol (GPI)-anchor that tethers a subclass of proteins to the membrane. Here, we show that in the PS19 tauopathy mouse model, GDE2 disruption modulates Tau phosphorylation, decreasing Tau's propensity for aggregation by regulating local kinase environments in a region-specific manner. In the cortex, GDE2 ablation in PS19 mice (PS19;Gde2KO) transiently delays Tau phosphorylation at pro-aggregation sites (Serine (S)202\/Threonine (T)205, T212, and S396) and accelerates phosphorylation at the anti-aggregation site S262, with a marked reduction in S202\/T205 and T212 phosphorylation at 6 months. While Tau phosphorylation at S202\/T205 is similarly delayed in the hippocampus, PS19;Gde2KO animals show increased phosphorylation at S262 at 6 months. Consistent with these changes, AKT and Glycogen Synthase Kinase-3  \/ {beta} (GSK3  \/ {beta}) activities are decreased in the cortex, while AKT activity is increased in the hippocampus, with no changes in protein phosphatase 1 (PP1) and protein phosphatase 2A (PP2A) activity. Primary cortical neurons from PS19;Gde2KO animals showed reduced Tau phosphorylation at S202\/T205, implying cell-autonomous roles for neuronal GDE2 in this process. GDE2 overexpression in heterologous SH-SY5Y cells increased Tau phosphorylation at S202\/T205, while a catalytically inactive form of GDE2 did not, suggesting that GDE2 regulation of target GPI-anchored protein surface activity is required to modulate Tau phosphorylation. Taken together, our study identifies GDE2 as a component of the complex regulatory network that controls Tau phosphorylation in the context of tauopathy and provides insight into putative pathways relevant to Tau pathologies observed in disease.","rel_num_authors":2,"rel_authors":[{"author_name":"Consuelo Jimenez-Ornelas","author_inst":"Johns Hopkins University"},{"author_name":"Shanthini Sockanathan","author_inst":"Johns Hopkins University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A Test for Confounding in Coupling of Multimodal Neuroimaging Data","rel_doi":"10.64898\/2026.09.14.750774","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.750774","rel_abs":"Multimodal neuroimaging studies often involve comparisons between brain maps. Recently, statistical methods have been proposed to quantify and assess spatial correspondence between two modalities. The simple permutation-based inter-modal correspondence (SPICE) test evaluates whether within-subject correspondence exceeds chance, where the null distribution is constructed by permuting subject labels for one modality. Despite its easy implementation and minimal spatial assumptions, the critical assumption underlying permutation analysis, that subjects are exchangeable under the null, may be violated when covariates such as age, sex, or disease status systematically alter brain map distributions. This violation can produce results analogous to Simpson's paradox, where apparent population-level correspondence reflects between-group differences rather than genuine within-subject coupling. We propose a formal U-statistic-based test for such covariate effects, enabling both diagnostic evaluation of assumption violations and scientific discovery. Using synthetic and semi-synthetic neuroimaging data, we demonstrate well-controlled Type I error and high statistical power. We apply our method to test for confounding effects due to age and sex using real data from two pairs of imaging modalities in the Philadelphia Neurodevelopmental Cohort. Our framework increases the rigor and interpretability of intermodal coupling analyses, with broad implications for neuroimaging studies in heterogeneous populations, especially in developmental, aging, and disease-focused research.","rel_num_authors":6,"rel_authors":[{"author_name":"Yiyan Hao","author_inst":"University of Pennsylvania"},{"author_name":"Simon Vandekar","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Aaron Alexander-Bloch","author_inst":"University of Pennsylvania"},{"author_name":"Theodore Satterthwaite","author_inst":"University of Pennsylvania"},{"author_name":"Brian White","author_inst":"Children's Hospital of Philadelphia"},{"author_name":"Russell Shinohara","author_inst":"University of Pennsylvania"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Zero-shot evaluations expose structured generalization limits in predictive models of the brain","rel_doi":"10.64898\/2026.09.15.751562","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751562","rel_abs":"Artificial neural networks (ANNs) can predict neural responses to natural images with remarkable accuracy, making them promising models of human vision. However, prediction scores alone reveal little about what computations these models have captured or how well they generalize beyond the images on which they are trained. Here, we introduce a principled zero-shot model evaluation framework in which ANN-based encoding models are frozen before being tested on not just held out images but entirely new datasets. Our strongest tests repurpose decades of cognitive neuroscience experiments as diagnostic benchmarks for identifying which computations current models capture and where they fail. To implement this framework we built encoding models of human category-selective regions (FFA, PPA, and EBA) using several pretrained ANNs and evaluated these fixed models across 7 independent fMRI datasets and 31 cognitive experiments from 10 published studies. This framework revealed three broad patterns. First, zero-shot evaluations exposed systematic limits to model predictivity that were largely hidden by standard within-dataset cross-validation. These limits were structured varying across brain regions and model classes and depending strongly on the similarity between the images used to build and test the models. Second, current models reproduced some, but not all, classical findings from cognitive neuroscience, providing a diagnosis of the computations that current models have yet to capture. Finally, models that performed well on prediction tests also tended to succeed at reproducing cognitive neuroscience findings, suggesting that prediction and explanation are closely linked. Unlike prediction scores however, cognitive tests help diagnose where and why models fail. Together, the zero-shot evaluation framework provides a scalable and unified approach for evaluating brain models across prediction and cognitive neuroscience tests, which can help us better understand what current models capture and what still remains to be explained.","rel_num_authors":14,"rel_authors":[{"author_name":"Ruolin Wang","author_inst":"Georgia Institute of Technology"},{"author_name":"Mayukh Deb","author_inst":"Georgia Institute of Technology"},{"author_name":"Alex Abate","author_inst":"Harvard Medical School"},{"author_name":"Alish Dipani","author_inst":"Georgia Institute of Technology"},{"author_name":"Kushal R Dudipala","author_inst":"Georgia Institute of Technology"},{"author_name":"Sanjana Chillarege","author_inst":"Georgia Institute of Technology"},{"author_name":"Kruthik Ravikanti","author_inst":"Georgia Institute of Technology"},{"author_name":"Yuxuan Li","author_inst":"Georgia Institute of Technology"},{"author_name":"Haider Al-Tahan","author_inst":"Georgia Institute of Technology"},{"author_name":"Ranjani Koushik","author_inst":"Georgia Institute of Technology"},{"author_name":"Elizabeth Mieczkowski","author_inst":"Princeton University"},{"author_name":"Herrick Fung","author_inst":"Georgia Institute of Technology"},{"author_name":"Nancy Kanwisher","author_inst":"Massachusetts Institute of Technology"},{"author_name":"N. Apurva Ratan Murty","author_inst":"Georgia Institute of Technology"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A transformer-based model reveals sparse, stimulus-dependent orientation readout from macaque V1 population activity","rel_doi":"10.64898\/2026.09.15.751671","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751671","rel_abs":"Orientation information in primary visual cortex (V1) is represented by large populations of neurons with overlapping tuning preferences, yet how this information is selectively read out remains unclear. Here we proposed a transformer-based model to reconstruct oriented Gabor stimuli from two-photon calcium responses of more than 1000 simultaneously recorded macaque V1 neurons. The model reconstructed stimulus orientation with high precision and revealed, through its self-attention maps, a sparse and stimulus-dependent readout structure. For each stimulus orientation, reconstruction was dominated by a small number of highly weighted readout neurons that were tuned near the presented orientation and showed enhanced effective orientation signals after self-attention modulation. After removal of these neurons and retraining, reconstruction recovered through recruitment of substitute neurons with similar response properties, indicating that sparse readout can be flexibly supported by redundant population encoding. Decoder comparisons showed that a simple linear decoder and a multilayer perceptron recovered orientation less precisely than the transformer, suggesting that the model's advantage was not explained simply by generic nonlinear decoding capacity. Together, these findings suggest a population-level principle in which redundant orientation encoding supports sparse, stimulus-dependent, and flexible readout.","rel_num_authors":3,"rel_authors":[{"author_name":"Xin Wang","author_inst":"Peking University"},{"author_name":"Shiming Tang","author_inst":"Peking University"},{"author_name":"Cong Yu","author_inst":"Zhejiang University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Quantifying the Effect of Trunk Postural Control on Reaching with Progressive Shoulder Abduction Loading in Hemiparetic Stroke","rel_doi":"10.64898\/2026.09.14.750678","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.750678","rel_abs":"Background: Adults post hemiparetic stroke exhibit motor deficits in both the trunk and arm that impact function. In the paretic arm, involuntary coupling of torques in the fingers, wrist, and elbow during shoulder abduction, known as the flexion synergy, reduces reaching function. While there have been deficits shown to exist at the trunk such as weakness and altered coordination, it remains unclear if active trunk control compounds reaching deficits. This study examined if active trunk control with progressive shoulder abduction loading impacts reaching function in stroke and control participants. Methods: Thirteen adults, 9 post hemiparetic stroke (64.11 {+\/-} 6.57 years) and 4 age matched controls (66.25 {+\/-} 0.96 years), completed seated reaching tasks with the trunk restrained and unrestrained while reaching with their arm coupled to the ACT-3D robotic device on a frictionless table, lifting against 25% MVT, and 50% MVT. A linear mixed effects model was used with limb as a random factor, and group, trunk restraint, and shoulder abduction load as fixed factors for quantifying changes in reaching distance expressed percent limb length (% LL). Findings: Across limbs (paretic, non-paretic, control), when the trunk was un-restrained, reaching distance was reduced (p<.05). Further reduction in reaching distance was observed in the paretic compared to the non-paretic and control (p< .05) limbs. Reaching velocity was fastest for controls (3.26 {+\/-} 1.52 m\/s) compared to non-paretic (3.24 {+\/-} 1.19 m\/s) and paretic (1.59 {+\/-} 1.32 m\/s) limbs in stroke. Shoulder abduction loading had an effect on reaching distance in the paretic limb (p<.05) Table: .83 {+\/-} .13 % LL, 25% MVT: .77 {+\/-} .14 % LL, 50% MVT: .76 {+\/-} .15 %LL). Greater shoulder excursion occurred during non-paretic limb reaching compared to the paretic limb with an increase of 14.80 mm (p<.05). Conclusion: Active trunk control impacted reaching function and further reduced reaching distance in chronic hemiparetic stroke participants. However, the primary driver of reduced reaching distance was the flexion synergy. While reaching speed increased the demand at the trunk, excursions were comparable during paretic and non-paretic limb reaching, suggesting that overall trunk function was intact during this paradigm.","rel_num_authors":3,"rel_authors":[{"author_name":"Kathleen Carolyn Suvada","author_inst":"University of Illinois at Chicago"},{"author_name":"Julius P.A. Dewald","author_inst":"Northwestern University"},{"author_name":"Ana Maria Acosta","author_inst":"Northwestern University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A Physiologically Detailed Biomechanical Model of the Mouse Distal Forelimb for Simulation of Fine Motor Control","rel_doi":"10.64898\/2026.09.14.751232","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751232","rel_abs":"This study presents a physiologically detailed biomechanical model of the mouse distal forelimb that incorporates intrinsic musculature, tendon routing, and digit-level skeletal anatomy, features simplified or omitted in existing musculoskeletal models. Using high-resolution anatomical reconstruction and computational modeling, we created a physiological representation of the wrist and digits capable of simulating complex forelimb movements. The model enables simulation of coordinated distal forelimb movement and digit-level muscle behavior during grasping-related tasks. Simulations were performed for multiple tasks, including grasping, grasping with supination, wrist flexion, and digit I flexion, with analysis focused on the grasping task due to its integration of both intrinsic and extrinsic musculature. Model performance was evaluated through comparisons of marker trajectories between torque-driven reference motion and muscle-driven simulations, temporal shuffle control, and comparisons between experimentally recorded electromyography (EMG) activity and model-predicted muscle excitation profiles. The model successfully reproduced coordinated distal forelimb kinematics, demonstrated strong agreement between torque-driven and muscle-driven simulation approaches, and generated physiologically plausible muscle excitation patterns consistent with experimentally observed EMG activity during grasping-related movement. These findings establish the model as a framework for studying fine motor control, neuromuscular coordination, and movement-related impairments in mice while providing a foundation for future investigation of neurological disorders and their underlying biomechanical mechanisms.","rel_num_authors":5,"rel_authors":[{"author_name":"Nicolas Lindo Sandoval","author_inst":"University of Colorado Denver | Anschutz Medical Campus"},{"author_name":"Jesse I Gilmer","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Angie Geraldin Cuenu Velasco","author_inst":"University of Geneva"},{"author_name":"Daniel Huber","author_inst":"University of Geneva"},{"author_name":"Mazen Al Borno","author_inst":"Queens College of the City University of New York"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A bipolar disorder-associated ultra-rare AKAP11 protein-truncating variant attenuates stimulus-dependent PKA activation and induces anxiety- and depression-related behaviors in mice","rel_doi":"10.64898\/2026.09.19.752887","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.19.752887","rel_abs":"Rare genetic variants associated with psychiatric disorders are thought to have larger individual effect sizes and direct biological roles, offering a unique opportunity for understanding causal relationships between genetic architecture and disease phenotypes. A recent whole-exome sequencing meta-analysis identified an increased burden of ultra-rare protein-truncating variants (PTVs) in AKAP11 in patients with bipolar disorder and schizophrenia. AKAP11 encodes an A-kinase anchoring protein that mediates the association of protein kinase A (PKA) and its substrates. How ultra-rare AKAP11 variants contribute to psychiatric disorder pathogenesis remains unknown. Here, using CRISPR-Cas9 genome editing, we introduced into the mouse Akap11 locus an ultra-rare PTV identified in a human patient with bipolar disorder. This ultra-rare PTV reduced Akap11 mRNA and protein levels without producing stable novel mRNA isoforms, leading to Akap11 haploinsufficiency. Male heterozygous mice exhibited behavioral abnormalities consistent with anxiety- and depression-like phenotypes. Transcriptomic and proteomic profiling of the neocortex revealed molecular changes involving synaptic organization, synaptic signaling, and neurite morphogenesis. Notably, the heterozygous mutant showed selective elevation in type I, but not type II, PKA regulatory subunits, as well as PKA catalytic subunits, in the neocortex. Functionally, these changes were accompanied by reduced phosphorylation of PKA substrates, attenuated stimulus-dependent PKA activity in cortical excitatory neurons, and impaired nascent dendritic development in cortical neurons. Together, our study presents a clinically relevant and genetically precise mouse model that provides mechanistic insight into how ultra-rare PTVs may contribute to psychiatric disorder pathogenesis, and a platform for testing rational therapeutics.","rel_num_authors":11,"rel_authors":[{"author_name":"Anna Xiao Luo","author_inst":"Department of Psychiatry and Behavioral Sciences, Division of Neurobiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"author_name":"Leon Deng","author_inst":"Department of Psychiatry and Behavioral Sciences, Division of Neurobiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"author_name":"Yannan Li","author_inst":"Psychoimmune Biology Program, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"author_name":"Xiaodi Zhang","author_inst":"Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, U"},{"author_name":"Junnan Li","author_inst":"Department of Psychiatry and Behavioral Sciences, Division of Neurobiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"author_name":"Xiaolei Zhu","author_inst":"Psychoimmune Biology Program, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"author_name":"Xiaobo Mao","author_inst":"Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, U"},{"author_name":"Yijing Su","author_inst":"Department of Oral Medicine, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA"},{"author_name":"Bin Wu","author_inst":"Department of Biophysics and Biophysical Chemistry, Johns Hopkins University, Baltimore, MD, USA"},{"author_name":"Christopher A. Ross","author_inst":"Department of Psychiatry and Behavioral Sciences, Division of Neurobiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"author_name":"Pan P. Li","author_inst":"Department of Psychiatry and Behavioral Sciences, Division of Neurobiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Analysis of Rare Coding Variation Identifies New Genetic Contributors to Schizophrenia","rel_doi":"10.64898\/2026.09.18.752670","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.18.752670","rel_abs":"In this study, we present the largest rare coding variant association study of schizophrenia to date, with 87,959 schizophrenia cases and 150,587 controls. We identify 16 genes at exome-wide significance: SETD1A, ZMYM2, HERC1, RB1CC1, SCAF1, XPO7, SP4, FYN, PPP3CA, CUL1, HDAC9, JARID2, ATP9A, PTK2, STAG1, and SCN2A, and an additional 24 at a 5% false discovery rate. Cases carrying ultra-rare, damaging variants, primarily protein-truncating and deleterious missense mutations, show strong enrichment in constrained genes with consistent effects across ancestries. Half of the 40 identified genes overlap with those implicated in developmental delay, autism, or bipolar disorder, underscoring shared neurodevelopmental risk. All 40 genes identified are highly expressed in excitatory and inhibitory neurons, and their expression patterns span diverse developmental stages. Functionally, the identified genes implicate chromatin regulation, protein degradation, and synaptic function. Overall, our results advance understanding of the genetic architecture of schizophrenia, provide a foundation for modeling risk genes in cellular and animal systems, and offer a framework for future work toward biologically informed patient stratification.","rel_num_authors":109,"rel_authors":[{"author_name":"Julia M. Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Connor Dowd","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"F. Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Chiara Auwerx","author_inst":"Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Center for Genomic Medicine, Department of M"},{"author_name":"Soyeon Kim","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Medicine, Kyung Hee University Co"},{"author_name":"Cong Huai","author_inst":"Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shangh"},{"author_name":"Lin He","author_inst":"Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shangh"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia."},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya."},{"author_name":"Rehema M. Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya."},{"author_name":"Charles R.J.C. Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya."},{"author_name":"Nastassja Koen","author_inst":"Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa."},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa."},{"author_name":"Joseph Kyebuzibwa","author_inst":"Makerere University, Kampala, Uganda."},{"author_name":"Anne Stevenson","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Epidemiology, Harvard T. H. Chan "},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Kai Wang","author_inst":"Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA."},{"author_name":"Makoto Arai","author_inst":"Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan."},{"author_name":"Yasue Horiuchi","author_inst":"Shizuoka Graduate University of Public Health, Shizuoka, Japan."},{"author_name":"Masanari Itokawa","author_inst":"Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan."},{"author_name":"Nora Ayola Serrano","author_inst":"Clnica Psiquitrica CEMIC, Cartagena, Bolvar, Colombia"},{"author_name":"Carrie E. Bearden","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Sintia I. Belangero","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; Graduate Program of Functional and Structural Bi"},{"author_name":"Saulo G. Castor Albuquerque","author_inst":"Hospital de Saoede Mental Professor Frota Pinto, Fortaleza, Cear, Brazil."},{"author_name":"Nicolas Crossley","author_inst":"Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medelln Antioquia, Colombia."},{"author_name":"Andre L. de Souza Rodrigues","author_inst":"Genetics and Molecular Biology Graduate Program, Federal University of Par, BelZm, Par, Brazil.; Department of Specialized Health, State University of Par, BelZ"},{"author_name":"Ana M. Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Mateus M. Diniz","author_inst":"Pax Clnica Instituto de Psiquiatria, Aparecida de Goinia, Gois, Brazil."},{"author_name":"Thiago H. Freitas","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; School of Medicine, Universidade de Fortaleza (U"},{"author_name":"Ary Gadelha","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; Interdisciplinary Laboratory of Clinical Neurosc"},{"author_name":"Juliana Gomez-Makhinson","author_inst":"Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA."},{"author_name":"Nayana Holanda","author_inst":"Neuropsychopharmacology Laboratory, Drug Research and Development Center, Department of Physiology and Pharmacology, Federal University of Cear, Fortaleza, Cear"},{"author_name":"Alex Kopelowicz","author_inst":"Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA."},{"author_name":"Pedro G. Lorencetti","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; Interdisciplinary Laboratory of Clinical Neurosc"},{"author_name":"Lucas C. Quarantini","author_inst":"Department of Neurology and Psychiatry, Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil."},{"author_name":"Ana M. Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I. Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA.; Laboratory of Ne"},{"author_name":"Marcos L. Santoro","author_inst":"Interdisciplinary Laboratory of Clinical Neurosciences (LINC), Department of Psychiatry, Paulista School of Medicine, Federal University of So Paulo, So Paulo, "},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carolina Ziebold","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil."},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatra Ramn de la Fuente Muiz, Mexico City, Mexico."},{"author_name":"Marco Antonio Sanabrais-JimZnez","author_inst":"Instituto Nacional de Psiquiatra Ramn de la Fuente Muiz, Mexico City, Mexico."},{"author_name":"Eric Hahn","author_inst":"Department of Psychiatry and Psychotherapy, CharitZ - UniversitStsmedizin Berlin, Berlin, Germany.; Hanoi Medical University, Hanoi, Vietnam."},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Hanoi, Vietnam.; CharitZ - UniversitStsmedizin Berlin, Berlin, Germany."},{"author_name":"Penelope A. Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia."},{"author_name":"Jennifer Forsyth","author_inst":"Department of Psychology, University of Washington, Seattle, Washington, USA."},{"author_name":"Adeniran Okewole","author_inst":"Department of Psychiatry, University of Cambridge, Cambridge, UK."},{"author_name":"Rodney C.P. Go","author_inst":"University of Alabama at Birmingham, Birmingham, Alabama, USA."},{"author_name":"Raquel Gur","author_inst":"University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA."},{"author_name":"Ruben Gur","author_inst":"University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA."},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK."},{"author_name":"Aarno Palotie","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Eija HSmSlSinen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland."},{"author_name":"Olli PietilSinen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland."},{"author_name":"Stephen J. Glatt","author_inst":"Upstate Medical University, Syracuse, New York, USA."},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden."},{"author_name":"Celso Arango Lpez","author_inst":"Hospital Universitario La Paz, IdiPAZ, Madrid, Spain.; School of Medicine, Universidad Autonoma de Madrid, CIBERSAM, Madrid, Spain."},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK."},{"author_name":"Nick Bass","author_inst":"Division of Psychiatry, University College London, London, UK."},{"author_name":"Ann E. Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA."},{"author_name":"David St. Clair","author_inst":"University of Aberdeen, Aberdeen, UK."},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA."},{"author_name":"Douglas H. Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK."},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK."},{"author_name":"Tnu Esko","author_inst":"University of Tartu, Tartu, Estonia."},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA."},{"author_name":"Aiden P. Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland."},{"author_name":"Derek W. Morris","author_inst":"University of Galway, Galway, Ireland."},{"author_name":"Dara Manoach","author_inst":"Mass General Research Institute, Harvard Medical School, Boston, Massachusetts, USA."},{"author_name":"Mikael Landen","author_inst":"Section of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.; Department of Medical Epidemi"},{"author_name":"- Consortium","author_inst":"SCHEMA Consortium"},{"author_name":"Michael Boehnke","author_inst":"University of Michigan School of Public Health, Ann Arbor, Michigan, USA."},{"author_name":"Anders D. Brglum","author_inst":"Department of Biomedicine, Aarhus University, Aarhus, Denmark.; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark"},{"author_name":"Claire Churchhouse","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK."},{"author_name":"Michael C. O'Donovan","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Michael J. Owen","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Elliott Rees","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Patrick F. Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden.; University of North Carolina, Chapel Hill, North Carolina, USA."},{"author_name":"Marquis P. Vawter","author_inst":"University of California, Irvine, Irvine, California, USA."},{"author_name":"James T.R. Walters","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Laura Scott","author_inst":"University of Michigan School of Public Health, Ann Arbor, Michigan, USA."},{"author_name":"Sarah E. Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia."},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University, Hanoi, Vietnam."},{"author_name":"Thi Minh Tam Ta","author_inst":"Hanoi Medical University, Hanoi, Vietnam.; CharitA a UniversitAtsmedizin Berlin, Berlin, Germany."},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatra Ramn de la Fuente Muiz, Mexico City, Mexico."},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medelln, Antioquia, Colombia.; Department of Psychiatry, S"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Roel A. Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Akira Sawa","author_inst":"Johns Hopkins Schizophrenia Center and Johns Hopkins iMIND, Department of Psychiatry, Neuroscience, Biomedical Engineering, Pharmacology, Genetic Medicine, and "},{"author_name":"Carlos N. Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA.; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA."},{"author_name":"Michele T. Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA.; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA."},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK."},{"author_name":"James A. Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA."},{"author_name":"Rocky Stroud II","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Epidemiology, Harvard T. H. Chan "},{"author_name":"Lukoye Atwoli","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya.; Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya."},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda."},{"author_name":"Symon M. Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya."},{"author_name":"Karestan C. Koenen","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Epidemiology, Harvard T. H. Chan "},{"author_name":"Dan J. Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of C"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia."},{"author_name":"Shengying Qin","author_inst":"Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shangh"},{"author_name":"Mark J. Daly","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Benjamin M. Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Analysis of Rare Coding Variation Identifies New Genetic Contributors to Schizophrenia","rel_doi":"10.64898\/2026.09.18.752670","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.18.752670","rel_abs":"In this study, we present the largest rare coding variant association study of schizophrenia to date, with 87,959 schizophrenia cases and 150,587 controls. We identify 16 genes at exome-wide significance: SETD1A, ZMYM2, HERC1, RB1CC1, SCAF1, XPO7, SP4, FYN, PPP3CA, CUL1, HDAC9, JARID2, ATP9A, PTK2, STAG1, and SCN2A, and an additional 24 at a 5% false discovery rate. Cases carrying ultra-rare, damaging variants, primarily protein-truncating and deleterious missense mutations, show strong enrichment in constrained genes with consistent effects across ancestries. Half of the 40 identified genes overlap with those implicated in developmental delay, autism, or bipolar disorder, underscoring shared neurodevelopmental risk. All 40 genes identified are highly expressed in excitatory and inhibitory neurons, and their expression patterns span diverse developmental stages. Functionally, the identified genes implicate chromatin regulation, protein degradation, and synaptic function. Overall, our results advance understanding of the genetic architecture of schizophrenia, provide a foundation for modeling risk genes in cellular and animal systems, and offer a framework for future work toward biologically informed patient stratification.","rel_num_authors":109,"rel_authors":[{"author_name":"Julia M. Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Connor Dowd","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"F. Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Chiara Auwerx","author_inst":"Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Center for Genomic Medicine, Department of M"},{"author_name":"Soyeon Kim","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Medicine, Kyung Hee University Co"},{"author_name":"Cong Huai","author_inst":"Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shangh"},{"author_name":"Lin He","author_inst":"Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shangh"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia."},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya."},{"author_name":"Rehema M. Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya."},{"author_name":"Charles R.J.C. Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya."},{"author_name":"Nastassja Koen","author_inst":"Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa."},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa."},{"author_name":"Joseph Kyebuzibwa","author_inst":"Makerere University, Kampala, Uganda."},{"author_name":"Anne Stevenson","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Epidemiology, Harvard T. H. Chan "},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Kai Wang","author_inst":"Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA."},{"author_name":"Makoto Arai","author_inst":"Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan."},{"author_name":"Yasue Horiuchi","author_inst":"Shizuoka Graduate University of Public Health, Shizuoka, Japan."},{"author_name":"Masanari Itokawa","author_inst":"Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan."},{"author_name":"Nora Ayola Serrano","author_inst":"Clnica Psiquitrica CEMIC, Cartagena, Bolvar, Colombia"},{"author_name":"Carrie E. Bearden","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Sintia I. Belangero","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; Graduate Program of Functional and Structural Bi"},{"author_name":"Saulo G. Castor Albuquerque","author_inst":"Hospital de Saoede Mental Professor Frota Pinto, Fortaleza, Cear, Brazil."},{"author_name":"Nicolas Crossley","author_inst":"Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medelln Antioquia, Colombia."},{"author_name":"Andre L. de Souza Rodrigues","author_inst":"Genetics and Molecular Biology Graduate Program, Federal University of Par, BelZm, Par, Brazil.; Department of Specialized Health, State University of Par, BelZ"},{"author_name":"Ana M. Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Mateus M. Diniz","author_inst":"Pax Clnica Instituto de Psiquiatria, Aparecida de Goinia, Gois, Brazil."},{"author_name":"Thiago H. Freitas","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; School of Medicine, Universidade de Fortaleza (U"},{"author_name":"Ary Gadelha","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; Interdisciplinary Laboratory of Clinical Neurosc"},{"author_name":"Juliana Gomez-Makhinson","author_inst":"Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA."},{"author_name":"Nayana Holanda","author_inst":"Neuropsychopharmacology Laboratory, Drug Research and Development Center, Department of Physiology and Pharmacology, Federal University of Cear, Fortaleza, Cear"},{"author_name":"Alex Kopelowicz","author_inst":"Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA."},{"author_name":"Pedro G. Lorencetti","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil.; Interdisciplinary Laboratory of Clinical Neurosc"},{"author_name":"Lucas C. Quarantini","author_inst":"Department of Neurology and Psychiatry, Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil."},{"author_name":"Ana M. Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I. Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA.; Laboratory of Ne"},{"author_name":"Marcos L. Santoro","author_inst":"Interdisciplinary Laboratory of Clinical Neurosciences (LINC), Department of Psychiatry, Paulista School of Medicine, Federal University of So Paulo, So Paulo, "},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carolina Ziebold","author_inst":"Department of Psychiatry, Escola Paulista de Medicina, Universidade Federal de So Paulo, So Paulo, SP, Brazil."},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatra Ramn de la Fuente Muiz, Mexico City, Mexico."},{"author_name":"Marco Antonio Sanabrais-JimZnez","author_inst":"Instituto Nacional de Psiquiatra Ramn de la Fuente Muiz, Mexico City, Mexico."},{"author_name":"Eric Hahn","author_inst":"Department of Psychiatry and Psychotherapy, CharitZ - UniversitStsmedizin Berlin, Berlin, Germany.; Hanoi Medical University, Hanoi, Vietnam."},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Hanoi, Vietnam.; CharitZ - UniversitStsmedizin Berlin, Berlin, Germany."},{"author_name":"Penelope A. Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia."},{"author_name":"Jennifer Forsyth","author_inst":"Department of Psychology, University of Washington, Seattle, Washington, USA."},{"author_name":"Adeniran Okewole","author_inst":"Department of Psychiatry, University of Cambridge, Cambridge, UK."},{"author_name":"Rodney C.P. Go","author_inst":"University of Alabama at Birmingham, Birmingham, Alabama, USA."},{"author_name":"Raquel Gur","author_inst":"University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA."},{"author_name":"Ruben Gur","author_inst":"University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA."},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK."},{"author_name":"Aarno Palotie","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Eija HSmSlSinen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland."},{"author_name":"Olli PietilSinen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland."},{"author_name":"Stephen J. Glatt","author_inst":"Upstate Medical University, Syracuse, New York, USA."},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden."},{"author_name":"Celso Arango Lpez","author_inst":"Hospital Universitario La Paz, IdiPAZ, Madrid, Spain.; School of Medicine, Universidad Autonoma de Madrid, CIBERSAM, Madrid, Spain."},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK."},{"author_name":"Nick Bass","author_inst":"Division of Psychiatry, University College London, London, UK."},{"author_name":"Ann E. Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA."},{"author_name":"David St. Clair","author_inst":"University of Aberdeen, Aberdeen, UK."},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA."},{"author_name":"Douglas H. Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK."},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK."},{"author_name":"Tnu Esko","author_inst":"University of Tartu, Tartu, Estonia."},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA."},{"author_name":"Aiden P. Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland."},{"author_name":"Derek W. Morris","author_inst":"University of Galway, Galway, Ireland."},{"author_name":"Dara Manoach","author_inst":"Mass General Research Institute, Harvard Medical School, Boston, Massachusetts, USA."},{"author_name":"Mikael Landen","author_inst":"Section of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.; Department of Medical Epidemi"},{"author_name":"- Consortium","author_inst":"SCHEMA Consortium"},{"author_name":"Michael Boehnke","author_inst":"University of Michigan School of Public Health, Ann Arbor, Michigan, USA."},{"author_name":"Anders D. Brglum","author_inst":"Department of Biomedicine, Aarhus University, Aarhus, Denmark.; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark"},{"author_name":"Claire Churchhouse","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK."},{"author_name":"Michael C. O'Donovan","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Michael J. Owen","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Elliott Rees","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Patrick F. Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden.; University of North Carolina, Chapel Hill, North Carolina, USA."},{"author_name":"Marquis P. Vawter","author_inst":"University of California, Irvine, Irvine, California, USA."},{"author_name":"James T.R. Walters","author_inst":"MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, Wales, UK."},{"author_name":"Laura Scott","author_inst":"University of Michigan School of Public Health, Ann Arbor, Michigan, USA."},{"author_name":"Sarah E. Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia."},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University, Hanoi, Vietnam."},{"author_name":"Thi Minh Tam Ta","author_inst":"Hanoi Medical University, Hanoi, Vietnam.; CharitA a UniversitAtsmedizin Berlin, Berlin, Germany."},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatra Ramn de la Fuente Muiz, Mexico City, Mexico."},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medelln, Antioquia, Colombia.; Department of Psychiatry, S"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Roel A. Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Akira Sawa","author_inst":"Johns Hopkins Schizophrenia Center and Johns Hopkins iMIND, Department of Psychiatry, Neuroscience, Biomedical Engineering, Pharmacology, Genetic Medicine, and "},{"author_name":"Carlos N. Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA.; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA."},{"author_name":"Michele T. Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA.; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA."},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK."},{"author_name":"James A. Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA."},{"author_name":"Rocky Stroud II","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Epidemiology, Harvard T. H. Chan "},{"author_name":"Lukoye Atwoli","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya.; Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya."},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda."},{"author_name":"Symon M. Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya."},{"author_name":"Karestan C. Koenen","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Department of Epidemiology, Harvard T. H. Chan "},{"author_name":"Dan J. Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of C"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia."},{"author_name":"Shengying Qin","author_inst":"Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shangh"},{"author_name":"Mark J. Daly","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"},{"author_name":"Benjamin M. Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.; Stanley Center for Psychiatric Re"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"SEX-DEPENDENT MODULATION OF WHOLE BRAIN cFOS EXPRESSION BY LIGHT AND MELANOPSIN IN THE MOUSE","rel_doi":"10.64898\/2026.09.14.751302","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751302","rel_abs":"Light is a fundamental feature of the environment, signaling time of day, weather changes, approaching predators, and other survival cues. The extensive projections from the retina to the brain provide an anatomical substrate for light to adaptively tune circuit function based on changing environmental light. Yet we understand little about the scope and functional impact of light outside of visual and circadian circuits. To address this, we created a whole-brain atlas of light-induced cFos expression in the mouse brain. This approach yielded a strikingly broad pattern of light-driven cFos activation throughout the brain that extended beyond canonical visual circuits, with unexpectedly strong modulation of neuromodulatory centers. These patterns differed starkly in males and females, and were dependent primarily on melanopsin-expressing, intrinsically photosensitive retinal ganglion cells. These findings uncover surprising brainwide patterns of light modulation and are shared as an interactive resource so that they can inspire new, future studies.","rel_num_authors":6,"rel_authors":[{"author_name":"Jacob D Bhoi","author_inst":"Northwestern University"},{"author_name":"Maya R Sheth","author_inst":"Northwestern University"},{"author_name":"Lisseth Gonzalez","author_inst":"Northwestern University"},{"author_name":"Andrew Kang","author_inst":"Northwestern University"},{"author_name":"Anna C Wcislak","author_inst":"Northwestern University"},{"author_name":"Tiffany M Schmidt","author_inst":"Northwestern University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A lactate-HIF1-VDR positive feedback loop drives protective SPP1+ macrophage differentiation to inhibit schistosomiasis induced liver fibrosis","rel_doi":"10.64898\/2026.09.15.751751","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751751","rel_abs":"Hepatic fibrosis remains a major cause of morbidity and mortality in patients with schistosomiasis without effective therapy. Here we show that vitamin D receptor (VDR) signaling in macrophages is essential for limiting fibrosis, acting through a previously unrecognized metabolic epigenetic circuit. Hepatic macrophages exhibit the highest VDR expression among liver resident cells, and pharmacological VDR activation with paricalcitol selectively expands a protective SPP1+ macrophage subset derived from circulating monocytes. Myeloid specific VDR knockout exacerbates fibrosis and abrogates paricalcitol's hepatoprotective effects, whereas SPP1+ macrophage depletion worsens disease. Mechanistically, VDR activation synergizes with hypoxia and lactate to drive SPP1 expression via glycolytic reprogramming. Moreover, lactate and HIF1alpha cooperatively induce VDR transcription by binding to the Vdr promoter and enhancing histone lactylation, forming a positive feedback loop that amplifies the antifibrotic response. Our findings establish the lactate-HIF1alpha-VDR-SPP1 axis as an endogenous defense mechanism and identify macrophage VDR as a promising therapeutic target for fibrotic liver diseases.","rel_num_authors":9,"rel_authors":[{"author_name":"Zhou Xing","author_inst":"Naval Medical University"},{"author_name":"Pingping Yang","author_inst":"Naval Medical University"},{"author_name":"Huiyu Xia","author_inst":"Naval Medical University"},{"author_name":"Rui Yin","author_inst":"Naval Medical University"},{"author_name":"Bin Le","author_inst":"Naval Medical University"},{"author_name":"Fangbin Zhou","author_inst":"Naval Medical University"},{"author_name":"Xiaoying Guo","author_inst":"China Medical University"},{"author_name":"Xiaobin Fan","author_inst":"Naval Medical University"},{"author_name":"Xing He","author_inst":"Naval Medical University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"CD55-CD319-CX3CR1 flow cytometry gating strategy recapitulates scRNA-seq-defined memory CD8 T cell subpopulations","rel_doi":"10.64898\/2026.09.15.751807","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751807","rel_abs":"Human CD8 T cells have traditionally been classified into naive, central memory, effector memory, and terminal effector subsets using CCR7 and CD45RA expression, a framework that has guided immunological research and clinical immune monitoring for nearly three decades. However, recent single-cell studies have revealed transcriptionally distinct CD8 T cell populations, including GZMK-, GZMB-, and central memory-like states, raising important questions regarding their relationship to canonical flow cytometric subsets. Here, we systematically integrated transcriptomic, epigenetic, and phenotypic analyses to evaluate the correspondence between these classification schemes. We demonstrate that conventional CCR7-CD45RA gating generates heterogeneous populations containing extensive mixtures of transcriptionally and epigenetically distinct CD8 T cell states, resulting in poor resolution of biologically meaningful subsets. To address this limitation, we developed a surface-marker framework based on CD55, CD319, and CX3CR1 that accurately identifies transcriptionally defined human CD8 T cell populations using standard flow cytometry. This strategy enables direct isolation of viable cells, including GZMK-expressing cells increasingly implicated in aging, chronic inflammation, autoimmunity, and cancer, which previously could only be identified using intracellular staining or single-cell sequencing. Functional characterization of purified subsets revealed marked differences in proliferative capacity, cytokine production, and cytotoxic activity, demonstrating that transcriptionally defined states possess distinct immune functions. Together, these findings establish a biologically grounded framework for CD8 T cell classification and provide a practical platform for mechanistic studies, biomarker discovery, and cellular immunotherapy applications.","rel_num_authors":12,"rel_authors":[{"author_name":"Pavla Bohacova","author_inst":"Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA"},{"author_name":"Marina Terekova","author_inst":"Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA"},{"author_name":"Oleg Shpynov","author_inst":"JetBrains Research, Munich, Germany"},{"author_name":"Thomas Francis","author_inst":"Centre for Human and Applied Physiological Sciences, School of Basic and Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London"},{"author_name":"Kamila Husarcikova","author_inst":"Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA"},{"author_name":"Petr Tsurinov","author_inst":"JetBrains Research, Paphos, Cyprus"},{"author_name":"Jan Kossl","author_inst":"Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA"},{"author_name":"Maksim Kleverov","author_inst":"Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA"},{"author_name":"Molly Keppel","author_inst":"Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA"},{"author_name":"Stephen D.R. Harridge","author_inst":"Centre for Human and Applied Physiological Sciences, School of Basic and Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London"},{"author_name":"Nathan Singh","author_inst":"Center for Gene and Cellular Immunotherapy; Division of Oncology, Section of Cellular Therapies, Washington University School of Medicine."},{"author_name":"Maxim N. Artyomov","author_inst":"Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool","rel_doi":"10.64898\/2026.09.15.751735","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751735","rel_abs":"Motivation Single-cell RNA sequencing (scRNA-seq) cluster annotation is a critical step in data analysis. Current methods are time-consuming, difficult to reproduce, or limited in tissue or species coverage. Results We developed celltypeEnrich, a cluster-level annotation tool that uses a hypergeometric test to identify enrichment of cell-type-specific genes from input gene lists. Enrichment results from up to 26 reference datasets are used to determine a consensus annotation. Benchmarking using scRNA-seq datasets from three tissues spanning two species showed 62-72% annotation accuracy for celltypeEnrich, generally outperforming other tools, which had either lower accuracy, incomplete tissue coverage, or the need for parameter optimization. The performance of celltypeEnrich remained stable when input gene lists were down-sampled to 25% of their original size. Availability and Implementation celltypeEnrich is freely available at (https:\/\/celltypeenrich.gdcb.iastate.edu) as an R Shiny web application under the MIT license for non-profit academic use.","rel_num_authors":2,"rel_authors":[{"author_name":"Sabrena Rutledge","author_inst":"Iowa State University"},{"author_name":"Geetu Tuteja","author_inst":"Iowa State University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"GAPDH is tethered to axonal transport vesicles by S-acylation","rel_doi":"10.64898\/2026.09.17.752404","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.752404","rel_abs":"Vesicle movement along axonal microtubules in neurons requires the ATP-dependent molecular motors dynein and kinesin. Fast axonal transport is fueled by ATP, provided by vesicle-associated glycolytic enzymes, but how these predicted soluble enzymes attach to vesicles in unclear. One potential mechanism is the protein lipid modification S-acylation, which involves the addition of long chain fatty acids to protein cysteine residues mediated by the ZDHHC (Asp-His-His-Cys) family of protein S-acyltransferases. Among the many effects this lipid modification imparts is an increase in protein localization to membranes. We found that eight of the ten glycolytic enzymes are S-acylated in the brain. Of the 10 glycolytic enzymes, we focused on glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as it is the first enzyme of the payoff phase of glycolysis. GAPDH is S-acylated on cysteine 247 by ZDHHC5 and ZDHHC17. Importantly, C247 point mutation impairs GAPDH association with vesicles in hippocampal neurons. Investigating the role of S-acylation in glycolytic enzyme localization will lead to novel insights into neuronal transport mechanisms and may also shed light on neurodegenerative disease pathology and potential drug targets.","rel_num_authors":9,"rel_authors":[{"author_name":"Nisandi N Herath","author_inst":"University of Guelph"},{"author_name":"Jordan A Kogut","author_inst":"University of Guelph"},{"author_name":"Andrey A Petropavlovskiy","author_inst":"University of Guelph"},{"author_name":"Amelia H Doerksen","author_inst":"University of Guelph"},{"author_name":"Charlotte A Townsend Bennie","author_inst":"University of Guelph"},{"author_name":"Anthony Dang","author_inst":"University of Waterloo"},{"author_name":"Gareth M Thomas","author_inst":"Lewis Katz School of Medicine at Temple University"},{"author_name":"Dale DO Martin","author_inst":"University of Waterloo"},{"author_name":"Shaun S Sanders","author_inst":"University of Guelph"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"A non-retinoid triazolopyrimidine RBP4 antagonist for the treatment of Stargardt disease","rel_doi":"10.64898\/2026.09.14.751502","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751502","rel_abs":"Stargardt disease is a juvenile-onset retinal dystrophy characterized by the buildup of cytotoxic lipofuscin deposits in the retinal pigment epithelium (RPE), leading to photoreceptor degeneration and eventual blindness. Currently, there are no FDA-approved treatments for Stargardt disease. Bisretinoids, byproducts of the visual cycle, are the major cytotoxic components of the lipofuscin deposits, and bisretinoid synthesis relies on the traffic of retinol from the bloodstream to the retina. Selective targeting of the key retinol transporter, Retinol-Binding Protein 4 (RBP4), offers an appealing strategy for halting the buildup of lipofuscin in the RPE and arresting the progression of Stargardt disease. Retinol delivery depends on RBP4 interaction with another serum protein, Transthyretin (TTR). We previously reported several libraries of RBP4 antagonists that effectively blocked the association of the TTR-RBP4-retinol tertiary complex, thereby lowering the overall retinol load in the retina; however, some chemotypes displayed off-target activity that warranted further optimization. Here, we report the pharmacological characterization of AKR-XI-85 and its analogs as promising non-retinoid small-molecule RBP4 antagonists. AKR-XI-85 displayed excellent in vitro and in vivo efficacy and desirable pharmacokinetic properties without any limiting off-target activity. In Abca4-\/- mice, chronic dosing of the compound induced a prolonged reduction in serum RBP4 levels and achieved a dramatic, 70 % reduction in the accumulation of A2E, a critical component of toxic lipofuscin. As such, AKR-XI-85 may be an attractive drug candidate for the treatment of Stargardt disease and other lipofuscin-dependent retinopathies.","rel_num_authors":9,"rel_authors":[{"author_name":"K. Alison Rinderspacher","author_inst":"Columbia University Irving Medical Center"},{"author_name":"Andras Varadi","author_inst":"Columbia University Irving Medical Center"},{"author_name":"Boglarka Racz","author_inst":"Columbia University Irving Medical Center"},{"author_name":"Andrew S. Wasmuth","author_inst":"Columbia University Irving Medical Center"},{"author_name":"Shi-Xian Deng","author_inst":"Columbia University Irving Medical Center"},{"author_name":"Patricia Weber","author_inst":"Harrington Discovery Institute Therapeutics Development Center"},{"author_name":"Donald W. Landry","author_inst":"Columbia University Irving Medical Center"},{"author_name":"Peter R. Bernstein","author_inst":"Harrington Discovery Institute Therapeutics Development Center"},{"author_name":"Konstantin Petrukhin","author_inst":"Columbia University Irving Medical Center"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"The functional diversification of somatosensory neuron repertoires across Mammalia","rel_doi":"10.64898\/2026.09.19.752904","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.19.752904","rel_abs":"The striking diversity of mammalian body forms and surfaces, lifestyles, and habitats prompts the question of how each species' somatosensory neuron repertoire accommodates such diversity. The visual and olfactory systems diversify by gaining and losing sensor\/receptor genes and corresponding sensory cell types. Using multiomic single-cell analysis of dorsal root ganglia neurons from thirteen different mammalian species and cross-species functional studies enabled by cell-type-specific enhancer viruses, we show that mammals instead assemble species-specific, functionally distinct somatosensory neuron repertoires from a conserved set of neuron types (orthotypes). Repertoire diversification takes multiple forms: orthotype abundance scales with variable bodily traits like hair follicle density, facilitating relevant behaviors; sensor\/receptor expression is shuffled across species, such that orthotypes can detect different stimuli in different species; and orthotypes split into functionally distinct, species-specific subtypes (paratypes). Thus, unlike other sensory systems, the mammalian somatosensory system diversifies through multifarious changes to conserved orthotypes, enabling adaptation to diverse habitats, lifestyles, and body forms.","rel_num_authors":18,"rel_authors":[{"author_name":"S. Andrew Shuster","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Jia Yin Xiao","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Bruno Gegenhuber","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Shamsuddin A. Bhuiyan","author_inst":"Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA"},{"author_name":"Min Dai","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Yongting Chen","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Michelle M. DeLisle","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Preston Sheng","author_inst":"Department of Biological Sciences, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA"},{"author_name":"Elizabeth Howell","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Michael Brecht","author_inst":"Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universitat zu Berlin, Berlin, Germany"},{"author_name":"Elena O. Gracheva","author_inst":"Department of Cellular and Molecular Physiology, Department of Neuroscience, Center for Neuroethology and Physiological Plasticity, Yale University School of Me"},{"author_name":"Cynthia F. Moss","author_inst":"Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA"},{"author_name":"David L. Paul","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Ishmail Abdus-Saboor","author_inst":"Department of Biological Sciences, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA"},{"author_name":"Gord Fishell","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"William Renthal","author_inst":"Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA"},{"author_name":"Michael E. Greenberg","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"David D. Ginty","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"The functional diversification of somatosensory neuron repertoires across Mammalia","rel_doi":"10.64898\/2026.09.19.752904","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.19.752904","rel_abs":"The striking diversity of mammalian body forms and surfaces, lifestyles, and habitats prompts the question of how each species' somatosensory neuron repertoire accommodates such diversity. The visual and olfactory systems diversify by gaining and losing sensor\/receptor genes and corresponding sensory cell types. Using multiomic single-cell analysis of dorsal root ganglia neurons from thirteen different mammalian species and cross-species functional studies enabled by cell-type-specific enhancer viruses, we show that mammals instead assemble species-specific, functionally distinct somatosensory neuron repertoires from a conserved set of neuron types (orthotypes). Repertoire diversification takes multiple forms: orthotype abundance scales with variable bodily traits like hair follicle density, facilitating relevant behaviors; sensor\/receptor expression is shuffled across species, such that orthotypes can detect different stimuli in different species; and orthotypes split into functionally distinct, species-specific subtypes (paratypes). Thus, unlike other sensory systems, the mammalian somatosensory system diversifies through multifarious changes to conserved orthotypes, enabling adaptation to diverse habitats, lifestyles, and body forms.","rel_num_authors":18,"rel_authors":[{"author_name":"S. Andrew Shuster","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Jia Yin Xiao","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Bruno Gegenhuber","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Shamsuddin A. Bhuiyan","author_inst":"Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA"},{"author_name":"Min Dai","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Yongting Chen","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Michelle M. DeLisle","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Preston Sheng","author_inst":"Department of Biological Sciences, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA"},{"author_name":"Elizabeth Howell","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Michael Brecht","author_inst":"Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universitat zu Berlin, Berlin, Germany"},{"author_name":"Elena O. Gracheva","author_inst":"Department of Cellular and Molecular Physiology, Department of Neuroscience, Center for Neuroethology and Physiological Plasticity, Yale University School of Me"},{"author_name":"Cynthia F. Moss","author_inst":"Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA"},{"author_name":"David L. Paul","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Ishmail Abdus-Saboor","author_inst":"Department of Biological Sciences, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA"},{"author_name":"Gord Fishell","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"William Renthal","author_inst":"Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA"},{"author_name":"Michael E. Greenberg","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"David D. Ginty","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"The functional diversification of somatosensory neuron repertoires across Mammalia","rel_doi":"10.64898\/2026.09.19.752904","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.19.752904","rel_abs":"The striking diversity of mammalian body forms and surfaces, lifestyles, and habitats prompts the question of how each species' somatosensory neuron repertoire accommodates such diversity. The visual and olfactory systems diversify by gaining and losing sensor\/receptor genes and corresponding sensory cell types. Using multiomic single-cell analysis of dorsal root ganglia neurons from thirteen different mammalian species and cross-species functional studies enabled by cell-type-specific enhancer viruses, we show that mammals instead assemble species-specific, functionally distinct somatosensory neuron repertoires from a conserved set of neuron types (orthotypes). Repertoire diversification takes multiple forms: orthotype abundance scales with variable bodily traits like hair follicle density, facilitating relevant behaviors; sensor\/receptor expression is shuffled across species, such that orthotypes can detect different stimuli in different species; and orthotypes split into functionally distinct, species-specific subtypes (paratypes). Thus, unlike other sensory systems, the mammalian somatosensory system diversifies through multifarious changes to conserved orthotypes, enabling adaptation to diverse habitats, lifestyles, and body forms.","rel_num_authors":18,"rel_authors":[{"author_name":"S. Andrew Shuster","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Jia Yin Xiao","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Bruno Gegenhuber","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Shamsuddin A. Bhuiyan","author_inst":"Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA"},{"author_name":"Min Dai","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Yongting Chen","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Michelle M. DeLisle","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Preston Sheng","author_inst":"Department of Biological Sciences, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA"},{"author_name":"Elizabeth Howell","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"},{"author_name":"Michael Brecht","author_inst":"Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universitat zu Berlin, Berlin, Germany"},{"author_name":"Elena O. Gracheva","author_inst":"Department of Cellular and Molecular Physiology, Department of Neuroscience, Center for Neuroethology and Physiological Plasticity, Yale University School of Me"},{"author_name":"Cynthia F. Moss","author_inst":"Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA"},{"author_name":"David L. Paul","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"Ishmail Abdus-Saboor","author_inst":"Department of Biological Sciences, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA"},{"author_name":"Gord Fishell","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"William Renthal","author_inst":"Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA"},{"author_name":"Michael E. Greenberg","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA"},{"author_name":"David D. Ginty","author_inst":"Department of Neurobiology, Harvard Medical School, Boston, MA, USA | Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Rapid volumetric reconstruction and tracking for Fourier light-field microscopy enables real-time calcium imaging in freely behaving Hydra.","rel_doi":"10.64898\/2026.09.17.752193","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.752193","rel_abs":"Fourier light field microscopy (FLFM) enables high-speed volumetric imaging by encoding multiple angular perspectives of a three-dimensional sample onto a single image. For this reason, FLFM is well-suited to sparse and rapidly evolving biological systems. To aid in the adoption of FLFM, we present OpenFLR, an open-source software framework for real-time volumetric reconstruction, three-dimensional particle tracking, and calcium image processing using FLFM. OpenFLR reconstruction is distributed as four interchangeable interfaces: a Python library, a command-line script, an interactive web application, and an ImageJ\/micromanager plugin, so that the pipeline is accessible to both developers and bench biologists. Building on established Richardson-Lucy deconvolution, we use a hybrid experimental-computational PSF calibration strategy and a triangulation approach to tracking to extract particle positions in 3D directly from raw light field frames, bypassing reconstruction. We validate the complete pipeline on GCaMP6s recordings of freely behaving Hydra vulgaris, tracking sparse populations of neurons as they undergo large three-dimensional displacements.","rel_num_authors":5,"rel_authors":[{"author_name":"Raymond Adkins","author_inst":"Yale University"},{"author_name":"Ryan Hausen","author_inst":"Johns Hopkins University"},{"author_name":"Jamie Noss","author_inst":"Johns Hopkins University"},{"author_name":"Gerard Lemson","author_inst":"Johns Hopkins University"},{"author_name":"Jonathon Howard","author_inst":"Yale University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Rapid volumetric reconstruction and tracking for Fourier light-field microscopy enables real-time calcium imaging in freely behaving Hydra.","rel_doi":"10.64898\/2026.09.17.752193","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.752193","rel_abs":"Fourier light field microscopy (FLFM) enables high-speed volumetric imaging by encoding multiple angular perspectives of a three-dimensional sample onto a single image. For this reason, FLFM is well-suited to sparse and rapidly evolving biological systems. To aid in the adoption of FLFM, we present OpenFLR, an open-source software framework for real-time volumetric reconstruction, three-dimensional particle tracking, and calcium image processing using FLFM. OpenFLR reconstruction is distributed as four interchangeable interfaces: a Python library, a command-line script, an interactive web application, and an ImageJ\/micromanager plugin, so that the pipeline is accessible to both developers and bench biologists. Building on established Richardson-Lucy deconvolution, we use a hybrid experimental-computational PSF calibration strategy and a triangulation approach to tracking to extract particle positions in 3D directly from raw light field frames, bypassing reconstruction. We validate the complete pipeline on GCaMP6s recordings of freely behaving Hydra vulgaris, tracking sparse populations of neurons as they undergo large three-dimensional displacements.","rel_num_authors":5,"rel_authors":[{"author_name":"Raymond Adkins","author_inst":"Yale University"},{"author_name":"Ryan Hausen","author_inst":"Johns Hopkins University"},{"author_name":"Jamie Noss","author_inst":"Johns Hopkins University"},{"author_name":"Gerard Lemson","author_inst":"Johns Hopkins University"},{"author_name":"Jonathon Howard","author_inst":"Yale University"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Sustained 10% Oxygen Promotes Atrial Rather Than Ventricular Specification During Human iPSC-Cardiomyocyte Differentiation","rel_doi":"10.64898\/2026.09.16.750048","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.16.750048","rel_abs":"Background: Induced pluripotent stem cell-derived ventricular cardiomyocytes (iPSC-vCMs) hold great promise for replacing ventricular cardiomyocytes lost after myocardial infarction. However, their immature phenotype limits successful engraftment by increasing the risk of post-transplant arrhythmias. In contrast to the atmospheric O2 used during most iPSC-vCM differentiations, O2 levels inside the developing heart remain low, but very little is known on the effect on O2 on iPSC-vCM differentiation. Methods: We used a GMP compliant Quad Physoxia glovebox platform providing continuous stable specified O2 tensions during all processes to simulate the in vivo O2 conditions more closely with the aim of improving iPSC-vCM maturation. Results: We demonstrate by single cell RNA sequencing, and data integration with datasets for human cardiomyocytes from the different heart chambers as well as cell morphology-, ploidy-, and functional studies, that sustained 10% O2 throughout iPSC-CM differentiation promotes atrial- instead of ventricular iPSC-CM subtype specification. Conclusions: While this rejects our original hypothesis and forces some concerns to iPSC-vCM manufacturing by sphere technology, these unexpected data may serve as an attractive and easy approach to refine atrial iPSC-CM specification to benefit their exponentially growing diagnostic-, cytotoxic-, and regenerative use.","rel_num_authors":10,"rel_authors":[{"author_name":"Sabrina Bech Mathiesen","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark and Clinical Institute, University of Southern Denmark, Oden"},{"author_name":"Frederik Adam Bjerre","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark and Clinical Institute, University of Southern Denmark, Oden"},{"author_name":"Anne Kathrine S\u00f8gaard Terp","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark and Clinical Institute, University of Southern Denmark, Oden"},{"author_name":"Ditte Gry Ellman","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark and Clinical Institute, University of Southern Denmark, Oden"},{"author_name":"Jannik Hjortsh\u00f8j Larsen","author_inst":"Department of Molecular Medicine, Unit of Cardiovascular and Renal Research, University of Southern Denmark, Odense, Denmark"},{"author_name":"Peer Bendix Horn","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark"},{"author_name":"Per Svenningsen","author_inst":"Department of Molecular Medicine, Unit of Cardiovascular and Renal Research, University of Southern Denmark, Odense, Denmark"},{"author_name":"Ellen Ngar-Yun Poon","author_inst":"The School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China and Hong Kong Hub of Paediatric Excellence (HK HOPE), The C"},{"author_name":"Charlotte Harken Jensen","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark and Clinical Institute, University of Southern Denmark, Oden"},{"author_name":"Ditte Caroline Andersen","author_inst":"Andersen Group, Dep. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark and Clinical Institute, University of Southern Denmark, Oden"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"VCP is a critical component for TDP-43 disaggregase activity in skeletal muscle","rel_doi":"10.64898\/2026.09.14.751559","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751559","rel_abs":"TDP-43 aggregates are a unifying pathological feature between several neurodegenerative diseases and myopathies. Mutations in the AAA ATPase protein VCP have been linked to TDP-43 proteinopathies in both brain and skeletal muscle including frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and inclusion body myopathy (IBM). In the case of multisystem proteinopathy (MSP), patients with VCP mutations may present with combinations of these phenotypes. Of these MSP phenotypes IBM is the most common, affecting around 90% of patients. However, it is not well understood how mutations in VCP contribute to the accumulation of insoluble TDP-43 aggregates in the context of skeletal muscle. To study this further, we used in vitro and in vivo models of TDP-43 aggregation in skeletal muscle in the presence of VCP mutation or inhibition to study its effects on the ability to clear TDP-43 aggregates. Across multiple model systems we found that VCP disease mutations or inhibition causes a reduced capacity to clear insoluble TDP-43, suggesting a VCP loss of function in patients with VCP-related MSP.","rel_num_authors":4,"rel_authors":[{"author_name":"Eileen M Lynch","author_inst":"Washington University in St Louis"},{"author_name":"Sara K Pittman","author_inst":"Washington University in St Louis"},{"author_name":"Jil Daw","author_inst":"Washington University in St Louis"},{"author_name":"Conrad C Weihl","author_inst":"Washington University School of Medicine"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Visualizing micro- nanoplastics in the human brain: Early evidence for roles in microvascular pathology","rel_doi":"10.64898\/2026.09.14.751595","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751595","rel_abs":"Our environment has become progressively contaminated with non-biological materials, especially synthetic carbon polymers, plastics. Unsurprisingly some of these make it into the human body as detected by chemical analyses, yet it is unknown whether they cause harm or are innocent bystanders. Building on our observations of glossy deposits and unusual non-biological fluorescent particles in blood vessels, we aimed to determine whether these objects represented plastics. To do this we prepared plastics-enriched pellets from brain and subjected them to pyrolysis gas-chromatography\/mass spectroscopy (py-GC\/MS), electron microscopy and confocal laser scanning microscopy. Py-GC\/MS confirmed the presence of 10 different plastics. Contents of pellets were examined by thin-section EM. We then used laser scanning confocal microscopy to acquire hyperspectral profiles of each type of plastic in suspensions. We found fluorescent particles in all pellets from brains. All 12 plastics in the calibration standard fluoresced. We obtained hyperspectral profiles of single species plastics from industry: Polyethylene, polypropylene and polystyrene. Controls included chemical analysis of brain storage buffer, which had no detectable plastics; and imaging water only and areas on slides lacking tissue. Abundant particles with emission profiles similar to polyethylene and polypropylene decorated the walls of both arterioles and venules. These particles were coincident with glossy deposits we first observed in white matter, suggesting that both features represent plastics. In summary our results demonstrate that synthetic polymers exhibit detectable fluorescence, and particles with similar spectral properties are visible in histologic sections. This opens the door to investigating correlations between plastics and pathology.","rel_num_authors":7,"rel_authors":[{"author_name":"Elaine L Bearer","author_inst":"University of New Mexico"},{"author_name":"Marcus Garcia","author_inst":"University of New Mexico"},{"author_name":"Laurissa Barela","author_inst":"University of New Mexico"},{"author_name":"Andres Collazo","author_inst":"California Institute of Technology"},{"author_name":"Cathleen F Martinez","author_inst":"University of New Mexico"},{"author_name":"Taylor W Uselman","author_inst":"University of New Mexico School of Medicine"},{"author_name":"Gary Rosenberg","author_inst":"University of New Mexico"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Older Adults Forage Broadly for Information Despite Cost","rel_doi":"10.64898\/2026.09.14.751536","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751536","rel_abs":"Healthy aging has long been associated with impairments in learning from rewards. However, typical paradigms do not adequately distinguish between being motivated by information to learn about the world and being motivated by rewarding outcomes from our decisions. The present study describes how these distinct motivations guide learning about the environment across the lifespan. Participants (N=169; ages 18-71 [M=39, SD=15.4]) completed a task based on the board game Battleship, making sequential choices about which tile to uncover on a grid with the goal of finding and learning hidden shapes. While older adults performed worse on the task in terms of overall score, their search behavior stabilized earlier. Older adults also preferred to seek information over reward, spreading their choices more widely, making more choices per trial, and acquiring more information per trial. Additionally, older adults showed a persistent reliance on information gained from the outcomes of their choices. These findings suggest that, as individuals age, they prefer to seek information, which earns them fewer points and slows learning but incurs no cost to long-run projected performance. Despite the conventional view linking age with diminished learning, in a complex environment that disentangled information and reward, older adults remained engaged with no projected learning deficits. Our findings challenge assumptions about cognitive decline in aging and reframe information seeking in older adults as a persistent motivational preference that need not serve learning, raising the question of why the drive to seek information intensifies with age even when it confers no advantage.","rel_num_authors":3,"rel_authors":[{"author_name":"Abigail Hedden","author_inst":"University of Chicago"},{"author_name":"David L Barack","author_inst":"Carnegie Mellon University"},{"author_name":"Akram Bakkour","author_inst":"University of Chicago"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"High-order enhancer hubs buffer allelic regulatory variation through kinetic compensation","rel_doi":"10.64898\/2026.09.14.750771","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.750771","rel_abs":"Diploid genomes carry millions of heterozygous variants in cis-regulatory DNA, yet most genes produce similar RNA output from two parental alleles. How this balance is maintained is unclear. We developed Nanopore-HiChIP, a long-read method that maps high-order enhancer hubs on each haplotype. Over half of these enhancer hubs differ in chromatin architecture and transcription-factor occupancy between homologous chromosomes, but their target genes show substantially lower rates of allele-specific expression than genes lacking hub regulation. Single-cell kinetic modeling shows that burst frequency and burst size change in opposite directions, thereby preserving balanced transcriptional output. This hub-mediated kinetic buffering is enriched at haploinsufficient genes and coincides with smaller effects of expression quantitative trait loci. Enhancer hubs therefore absorb allelic regulatory variation through kinetic compensation, protecting dosage-sensitive transcription.","rel_num_authors":11,"rel_authors":[{"author_name":"Jiang Tan","author_inst":"Washington University in St. Louis"},{"author_name":"Monica Sentmanat","author_inst":"Washington University in St. Louis"},{"author_name":"Yukiv Wu","author_inst":"Washington University in St. Louis"},{"author_name":"Cody Peng","author_inst":"Johns Hopkins University"},{"author_name":"Catrina Fronick","author_inst":"Washington University in St. Louis"},{"author_name":"Christopher Markovic","author_inst":"Washington University in St. Louis"},{"author_name":"Xiaoxia Cui","author_inst":"Washington University in St. Louis"},{"author_name":"Robert Fulton","author_inst":"Washington University in St. Louis"},{"author_name":"Richard Head","author_inst":"Washington University in St. Louis"},{"author_name":"Ting Wang","author_inst":"Washington University in St. Louis"},{"author_name":"Yidan Sun","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"High-order enhancer hubs buffer allelic regulatory variation through kinetic compensation","rel_doi":"10.64898\/2026.09.14.750771","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.750771","rel_abs":"Diploid genomes carry millions of heterozygous variants in cis-regulatory DNA, yet most genes produce similar RNA output from two parental alleles. How this balance is maintained is unclear. We developed Nanopore-HiChIP, a long-read method that maps high-order enhancer hubs on each haplotype. Over half of these enhancer hubs differ in chromatin architecture and transcription-factor occupancy between homologous chromosomes, but their target genes show substantially lower rates of allele-specific expression than genes lacking hub regulation. Single-cell kinetic modeling shows that burst frequency and burst size change in opposite directions, thereby preserving balanced transcriptional output. This hub-mediated kinetic buffering is enriched at haploinsufficient genes and coincides with smaller effects of expression quantitative trait loci. Enhancer hubs therefore absorb allelic regulatory variation through kinetic compensation, protecting dosage-sensitive transcription.","rel_num_authors":11,"rel_authors":[{"author_name":"Jiang Tan","author_inst":"Washington University in St. Louis"},{"author_name":"Monica Sentmanat","author_inst":"Washington University in St. Louis"},{"author_name":"Yukiv Wu","author_inst":"Washington University in St. Louis"},{"author_name":"Cody Peng","author_inst":"Johns Hopkins University"},{"author_name":"Catrina Fronick","author_inst":"Washington University in St. Louis"},{"author_name":"Christopher Markovic","author_inst":"Washington University in St. Louis"},{"author_name":"Xiaoxia Cui","author_inst":"Washington University in St. Louis"},{"author_name":"Robert Fulton","author_inst":"Washington University in St. Louis"},{"author_name":"Richard Head","author_inst":"Washington University in St. Louis"},{"author_name":"Ting Wang","author_inst":"Washington University in St. Louis"},{"author_name":"Yidan Sun","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-09-21","rel_site":"biorxiv"},{"rel_title":"Time-to-Statin Prescription for Primary Atherosclerotic Cardiovascular Disease Prevention in a Lung Cancer Screening Program in Missouri: A Retrospective Cohort Study","rel_doi":"10.64898\/2026.09.16.26363270","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.16.26363270","rel_abs":"Background: Individuals undergoing lung cancer screening (LCS) represent a population at high risk for atherosclerotic cardiovascular disease (ASCVD), yet opportunities for cardiovascular prevention during screening encounters may be underutilized. While prior studies have examined whether statins are prescribed in eligible patients, little is known about the timing of statin initiation following LCS, particularly among statin-naive individuals. Methods: We conducted a retrospective cohort study using electronic health record data from a large academic health system in Missouri. Adults aged 50-80 who underwent LCS between January 1, 2015, and December 31, 2023, were statin-naive, and met 2019 ACC\/AHA criteria for primary prevention were included. The primary outcome was time-to-statin initiation following LCS. Kaplan-Meier methods and Cox proportional hazards models were used to evaluate timing and predictors of statin initiation across demographic, clinical, and socioeconomic subgroups. Results: Among 3,100 statin-eligible, statin-naive individuals who had undergone LCS, only 27.3% were prescribed a statin within one year of LCS. Uptake accrued gradually (10.5% by 90 days; 17.8% by 180 days; 23.2% by 270 days; 27.1% by 360 days). In adjusted models, earlier statin initiation was independently associated with a higher ASCVD risk category, a cardiology visit in the year preceding LCS, and former (versus current) smoking; older age and male sex were associated with slower initiation. Race, insurance type, and area deprivation were not independently associated with time-to-statin initiation. Conclusions: Despite high ASCVD risk, most statin-eligible patients undergoing LCS did not receive timely statin therapy. Earlier initiation tracked calculated ASCVD risk and specialty (cardiology) contact rather than race, sex, insurance, or area deprivation. Because most patients at high calculated risk still went untreated, integrating cardiovascular risk assessment and preventive decision support into LCS workflows may help reduce missed opportunities for ASCVD prevention.","rel_num_authors":6,"rel_authors":[{"author_name":"Isaac Che Ngang","author_inst":"Missouri Baptist Medical Center"},{"author_name":"Eyerusalem Kebede Zewde","author_inst":"Washington University in St Louis Department of Surgery"},{"author_name":"Sridharan Gopalsamy Ramaswamy","author_inst":"Washington University in St Louis Department of Surgery"},{"author_name":"Akila Anandarajah","author_inst":"Washington University in St Louis Department of Surgery"},{"author_name":"Benjamin Bowe","author_inst":"Washington University in St Louis Department of Surgery"},{"author_name":"Beryne Odeny","author_inst":"Washington University in St Louis Department of Surgery"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Methylation-Based ctDNA for Post-Treatment Surveillance of Non-Viral Head and Neck Cancer","rel_doi":"10.64898\/2026.09.17.26363361","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363361","rel_abs":"Importance: Recurrence rates in head and neck squamous cell carcinoma (HNSCC) remain high, yet current post-treatment surveillance relies primarily on clinical examination and imaging with known limitations. Circulating tumor DNA (ctDNA) has shown promise for recurrence detection in HPV-positive HNSCC, but less is known about its role in non-virally associated disease. Objective: To evaluate the diagnostic performance of a methylation-based ctDNA assay for detecting recurrence during post-treatment surveillance of non-virally associated HNSCC and to assess its prognostic association with survival outcomes. Design, Setting, and Participants: This retrospective single-institution cohort study included patients with non-metastatic non-virally associated HNSCC who underwent definitive therapy and had at least one Guardant360 ctDNA test during post-treatment surveillance between January 2024 and October 2025. Guardant360 identifies tumor-specific DNA methylation patterns via next-generation sequencing of plasma cell-free DNA. A positive result was defined by a methylation signal of 0.05% or greater. Main Outcomes and Measures: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC). Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Results: Fifty patients were included; most had larynx (38%) or oral cavity (36%) primaries, AJCC stage IVA-IVB disease (72%), T3-T4 tumors (69%), and N2-N3 nodal classification (48%). Treatment was chemoradiation (54%) or surgery (46%). At a median follow-up of 18.0 months, 13 patients recurred, and 12 had positive ctDNA results. Sensitivity, specificity, PPV, and NPV were 76.9%, 94.6%, 83.3%, and 92.1%, respectively (AUC, .858; 95% CI, .733-.982). Positive ctDNA was associated with worse PFS (1-year: 25.0% vs 96.4%; P < .001) and OS (1-year: 75.0% vs 100%; P < .001). Among 10 patients with recurrence and positive ctDNA, ctDNA preceded clinical detection in 6 (60%) by a median of 131 days. An exploratory analysis identified TP53, SETD2, and ROBO2 mutations as associated with recurrence. Conclusions and Relevance: A methylation-based ctDNA assay demonstrated high sensitivity and specificity for detecting disease recurrence in non-virally associated HNSCC. Positive post-treatment ctDNA was associated with inferior survival and preceded clinical detection in most cases, supporting ctDNA integration into surveillance strategies, though prospective validation is warranted.","rel_num_authors":13,"rel_authors":[{"author_name":"Danielle Tomer","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Patrik Brodin","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Nikhil Malik","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Sadiya Mayat","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Christian Velten","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Byung-Han Rhieu","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Enrico Castellucci","author_inst":"Department of Medical Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Bradley Schiff","author_inst":"Department of Otorhinolaryngology - Head & Neck Surgery, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Vikas Mehta","author_inst":"Department of Otorhinolaryngology - Head & Neck Surgery, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Richard Smith","author_inst":"Department of Otorhinolaryngology - Head & Neck Surgery, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Shalom Kalnicki","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Madhur Garg","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"},{"author_name":"Rafi Kabarriti","author_inst":"Department of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Cardiometabolic and Psychobehavioral Phenotypes Define Cardiovascular Risk Heterogeneity in Rheumatoid Arthritis","rel_doi":"10.64898\/2026.09.17.26363297","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363297","rel_abs":"Abstract Cardiovascular disease (CVD) is a major cause of morbidity and premature mortality in people with rheumatoid arthritis (RA). Whether multidimensional cardiometabolic, inflammatory, renal, behavioral, and psychosocial factors define distinct cardiovascular risk phenotypes in RA remains unclear. This study aimed to identify data-driven phenotypes and evaluate their associations with prevalent CVD. We analyzed 3,252 adults aged over 20 years with self-reported RA from the 2005-2018 National Health and Nutrition Examination Survey (NHANES). Unsupervised partitioning around medoids (PAM) clustering using Gower distance identified distinct data-driven cardiovascular-risk profiles. Cluster validity was assessed using silhouette analysis and internal train test validation. Survey-weighted binary logistic regression evaluated associations between phenotype membership and prevalent CVD. Six clinically interpretable data-driven phenotypes were identified with varying CVD prevalence: Severe Metabolic Diabetic (40.3%), Aging Diabetic Hypertensive (34.9%), Non-Diabetic Intermediate (20.2%), Mild Metabolic (14.8%), Cardiometabolic (10.4%), and Smoking-Predominant (19.4%). Compared with the Cardiometabolic phenotype, the Severe Metabolic Diabetic phenotype exhibited the highest odds of prevalent CVD (aOR 4.11, 95%CI:2.56-6.59), followed by the Aging Diabetic-Hypertensive phenotype (aOR 3.38, 95%CI:2.22-5.15). Higher odds of prevalent CVD were also observed in the Smoking-Predominant (aOR 1.99, 95% CI: 1.26-3.13) and Non-Diabetic Intermediate (aOR 1.77, 95% CI: 1.10-2.84) phenotypes. The six-cluster solution demonstrated moderate separation and strong internal correspondence across training and testing sets, while the phenotype-informed model showed moderate discrimination for prevalent CVD (AUC = 0.72). Among adults with rheumatoid arthritis (RA), distinct data-driven phenotypes were identified based on combined patterns of metabolic, inflammatory, renal, behavioral, and psychosocial factors, with differing burdens of prevalent cardiovascular disease (CVD). Phenotype-based approaches may provide a comprehensive framework for characterizing multidimensional cardiovascular risk in RA.","rel_num_authors":7,"rel_authors":[{"author_name":"Shah Tanzen Jahan","author_inst":"Department of Statistics, University of Rajshahi, Bangladesh"},{"author_name":"Anicha Akter","author_inst":"Department of Statistics, University of Rajshahi, Bangladesh"},{"author_name":"Sojib Hossain","author_inst":"Department of Statistics, University of Rajshahi, Bangladesh"},{"author_name":"Md Selim Reza","author_inst":"Tulane University, New Orleans, Louisiana, USA"},{"author_name":"Md. Mijanur Rahman","author_inst":"School of Clinical Medicine, University of New South Wales (UNSW), Sydney, Australia"},{"author_name":"Md. Mahmudul Alam","author_inst":"Department of Statistics, University of Rajshahi, Bangladesh"},{"author_name":"Md. Monimul Huq","author_inst":"Department of Statistics, University of Rajshahi, Bangladesh"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Large language model linguistic perplexity in childhood onset psychosis: unique features and developmental trends","rel_doi":"10.64898\/2026.09.17.26363314","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363314","rel_abs":"Objective: Child and early adolescent onset psychosis (COP) is associated with subtle changes in language linked to thought disorder, a key contributor to functional impairment. Large language models (LLM) can detect deviations from expected language patterns by jointly analyzing sentence structure and word choice. This integrated information is captured by measures such as (pseudo)-perplexity, which quantify how difficult it is for an LLM to predict individual words given the surrounding linguistic context. The objective was to determine if perplexity measures change with age and whether they are altered in COP. Method: This study tested for a difference in perplexity in COP cases (N = 23) mean age 12.78 years as compared to controls (N = 15) mean age 11.67 years. Extensive manually transcribed interviews were analyzed (controls: 3,829; cases: 6,579 mean words). Results: Perplexity derived from Large Language Model Meta AI (LLaMA) had a significant negative correlation with age in cases but not in controls. Pseudo-perplexity derived from Bidirectional Encoder Representations from Transformers (BERT) did not have a significant correlation with age in either group. Group differences were evaluated using generalized linear models with (pseudo)-perplexity as the dependent variable, case status as the predictor and age and number of words as covariates. The model predicting perplexity was significant and case status significantly predicted perplexity. In contrast, the model predicting pseudo-perplexity was not significant. Conclusion: These differences in perplexity are interpreted as reflecting an altered developmental trajectory in the real-time semantic and syntactic planning that directs the flow of language in individuals with COP.","rel_num_authors":19,"rel_authors":[{"author_name":"Anthony Deo","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Cynthia Lando","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Yuli Fradkin","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Ameerah Ali","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Thanharat Silamongkol","author_inst":"Rutgers"},{"author_name":"Emi Carpenter","author_inst":"Rutgers"},{"author_name":"Chloe Rosenkranz","author_inst":"Rutgers"},{"author_name":"Andrea Escoto","author_inst":"Rutgers"},{"author_name":"Caraline McDonnell","author_inst":"Rutgers"},{"author_name":"Rui He","author_inst":"Universitat Pompeu Fabra"},{"author_name":"Wolfram Hinzen","author_inst":"Department of Translation & Language Sciences, Universitat Pompeu Fabra"},{"author_name":"William W. GRaves","author_inst":"Rutgers"},{"author_name":"Johanne Solis","author_inst":"Rutgers"},{"author_name":"Walter Barr","author_inst":"Rutgers"},{"author_name":"Emma Deaso","author_inst":"Boston Children's Hospital"},{"author_name":"David Glahn","author_inst":"Boston Children's Hospital"},{"author_name":"Michele T Pato","author_inst":"Rutgers University"},{"author_name":"David Zald","author_inst":"Rutgers"},{"author_name":"Carlos Pato","author_inst":"Rutgers"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Impact of mass oral cholera vaccination in an endemic area of the Democratic Republic of the Congo: a surveillance-based counterfactual modeling analysis","rel_doi":"10.64898\/2026.09.17.26363298","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363298","rel_abs":"Abstract Background Oral cholera vaccines (OCVs) are a key component of cholera control recommended in cholera-endemic areas. Yet evidence of their population-level impact is limited, especially in Africa where most cholera deaths occur. Here, we estimate the impact of mass administration of OCVs in the cholera-endemic city of Uvira, Democratic Republic of the Congo. Methods We conducted enhanced cholera surveillance at the two official cholera treatment facilities in Uvira between Jan 2017 and Dec 2023, centered around a mass vaccination campaign that achieved 66% coverage with at least one dose of Euvichol Plus vaccine in 2020. We combined systematic rapid diagnostic case testing with repeated, representative population surveys capturing healthcare-seeking behavior, vaccination, population mobility, and antibody profiles to estimate seroincidence. We developed a Bayesian framework that integrates these data into an ensemble of mechanistic cholera transmission models that account for time-varying transmissibility, realistic immunity dynamics and loss of vaccination coverage to population turnover. OCV impact was assessed through ensemble counterfactual modeling of alternative vaccination scenarios. Findings We estimate that the 2020 mass vaccination averted 56% (95% Credible Interval: 34-81) of infections and deaths over the subsequent three years. This corresponds to 2,350 (median, 95% CrI: 890-8,960) averted facility-attended cases, and 44 (median, 95% CrI: 16-150) averted facility and community deaths. Vaccination of the entire eligible population of Uvira would have averted 64% (median, 95% CrI: 43-87) of cases and deaths, with a negative but limited influence of vaccine coverage loss because of population turnover (71% median, 95% CrI: 52-90 at half the population turnover). Interpretation Although mass vaccination averted a significant fraction of cholera cases that would have otherwise occurred in this endemic setting, imperfect coverage, population turnover, and high transmission rates contributed in offsetting the larger potential benefits of OCV. Successful cholera control in Uvira hinges on multisectorial approaches including provision of safe water and sanitation. Setting and communicating realistic expectations for mass vaccination programs in highly endemic areas is critical for maintaining confidence in the current generation of OCVs. Funding Gavi (M&E 9166 09 20 A16) and the Wellcome Trust (221688\/Z\/20\/Z).","rel_num_authors":24,"rel_authors":[{"author_name":"Javier Perez-Saez","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Espoir Bwenge Malembaka","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Judith A Bouman","author_inst":"Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland"},{"author_name":"Patrick Musole Bugeme","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Chloe Hutchins","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Jules Jackson","author_inst":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA"},{"author_name":"Esperance Tshiwedi-Tsilabia","author_inst":"Rodolphe Merieux Institut National de Recherche Biomedicale Goma, Goma, Democratic Republic of the Congo"},{"author_name":"Juan Dent Hulse","author_inst":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA"},{"author_name":"Jaime Mufitini Saidi","author_inst":"Zone de Sante d'Uvira, Ministere de la Sante Publique, Hygiene et Prevention, Uvira, Democratic Republic of the Congo"},{"author_name":"Baron Bashige Rumedeka","author_inst":"Oxfam International, Uvira, Democratic Republic of the Congo"},{"author_name":"Moise Itongwa","author_inst":"Oxfam International, Uvira, Democratic Republic of the Congo"},{"author_name":"Oliver Cumming","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Esther German","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Jean-Claude Kulondwa","author_inst":"Division Provinciale de la Sante du Sud-Kivu, Ministere de la Sante Publique, Hygiene et Prevention, Bukavu, Democratic Republic of the Congo"},{"author_name":"Amy B Dighe","author_inst":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA"},{"author_name":"Christy Clutter","author_inst":"Division of Infectious Diseases and Division of Microbiology and Immunology, University of Utah School of Medicine, Salt Lake City, Utah, USA"},{"author_name":"Justin Thomas Lessler","author_inst":"Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Daniel T Leung","author_inst":"Division of Infectious Diseases and Division of Microbiology and Immunology, University of Utah School of Medicine, Salt Lake City, Utah, USA"},{"author_name":"Karin Gallandat","author_inst":"Department of Sanitation, Water and Solid Waste for Development, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Duebendorf, Switzerland"},{"author_name":"Elizabeth C Lee","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Placide Welo Okitayemba","author_inst":"Programme National d'Elimination de Cholera et de lutte contre les autres Maladies Diarrheiques (PNECHOL-MD), Ministere de la Sante Publique, Hygiene et Prevent"},{"author_name":"Daniel Mukadi-Bamuleka","author_inst":"Rodolphe Merieux Institut National de Recherche Biomedicale Goma, Goma, Democratic Republic of the Congo"},{"author_name":"Jacqueline Knee","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Andrew S Azman","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Impact of mass oral cholera vaccination in an endemic area of the Democratic Republic of the Congo: a surveillance-based counterfactual modeling analysis","rel_doi":"10.64898\/2026.09.17.26363298","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363298","rel_abs":"Abstract Background Oral cholera vaccines (OCVs) are a key component of cholera control recommended in cholera-endemic areas. Yet evidence of their population-level impact is limited, especially in Africa where most cholera deaths occur. Here, we estimate the impact of mass administration of OCVs in the cholera-endemic city of Uvira, Democratic Republic of the Congo. Methods We conducted enhanced cholera surveillance at the two official cholera treatment facilities in Uvira between Jan 2017 and Dec 2023, centered around a mass vaccination campaign that achieved 66% coverage with at least one dose of Euvichol Plus vaccine in 2020. We combined systematic rapid diagnostic case testing with repeated, representative population surveys capturing healthcare-seeking behavior, vaccination, population mobility, and antibody profiles to estimate seroincidence. We developed a Bayesian framework that integrates these data into an ensemble of mechanistic cholera transmission models that account for time-varying transmissibility, realistic immunity dynamics and loss of vaccination coverage to population turnover. OCV impact was assessed through ensemble counterfactual modeling of alternative vaccination scenarios. Findings We estimate that the 2020 mass vaccination averted 56% (95% Credible Interval: 34-81) of infections and deaths over the subsequent three years. This corresponds to 2,350 (median, 95% CrI: 890-8,960) averted facility-attended cases, and 44 (median, 95% CrI: 16-150) averted facility and community deaths. Vaccination of the entire eligible population of Uvira would have averted 64% (median, 95% CrI: 43-87) of cases and deaths, with a negative but limited influence of vaccine coverage loss because of population turnover (71% median, 95% CrI: 52-90 at half the population turnover). Interpretation Although mass vaccination averted a significant fraction of cholera cases that would have otherwise occurred in this endemic setting, imperfect coverage, population turnover, and high transmission rates contributed in offsetting the larger potential benefits of OCV. Successful cholera control in Uvira hinges on multisectorial approaches including provision of safe water and sanitation. Setting and communicating realistic expectations for mass vaccination programs in highly endemic areas is critical for maintaining confidence in the current generation of OCVs. Funding Gavi (M&E 9166 09 20 A16) and the Wellcome Trust (221688\/Z\/20\/Z).","rel_num_authors":24,"rel_authors":[{"author_name":"Javier Perez-Saez","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Espoir Bwenge Malembaka","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Judith A Bouman","author_inst":"Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland"},{"author_name":"Patrick Musole Bugeme","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Chloe Hutchins","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Jules Jackson","author_inst":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA"},{"author_name":"Esperance Tshiwedi-Tsilabia","author_inst":"Rodolphe Merieux Institut National de Recherche Biomedicale Goma, Goma, Democratic Republic of the Congo"},{"author_name":"Juan Dent Hulse","author_inst":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA"},{"author_name":"Jaime Mufitini Saidi","author_inst":"Zone de Sante d'Uvira, Ministere de la Sante Publique, Hygiene et Prevention, Uvira, Democratic Republic of the Congo"},{"author_name":"Baron Bashige Rumedeka","author_inst":"Oxfam International, Uvira, Democratic Republic of the Congo"},{"author_name":"Moise Itongwa","author_inst":"Oxfam International, Uvira, Democratic Republic of the Congo"},{"author_name":"Oliver Cumming","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Esther German","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Jean-Claude Kulondwa","author_inst":"Division Provinciale de la Sante du Sud-Kivu, Ministere de la Sante Publique, Hygiene et Prevention, Bukavu, Democratic Republic of the Congo"},{"author_name":"Amy B Dighe","author_inst":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA"},{"author_name":"Christy Clutter","author_inst":"Division of Infectious Diseases and Division of Microbiology and Immunology, University of Utah School of Medicine, Salt Lake City, Utah, USA"},{"author_name":"Justin Thomas Lessler","author_inst":"Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Daniel T Leung","author_inst":"Division of Infectious Diseases and Division of Microbiology and Immunology, University of Utah School of Medicine, Salt Lake City, Utah, USA"},{"author_name":"Karin Gallandat","author_inst":"Department of Sanitation, Water and Solid Waste for Development, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Duebendorf, Switzerland"},{"author_name":"Elizabeth C Lee","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"},{"author_name":"Placide Welo Okitayemba","author_inst":"Programme National d'Elimination de Cholera et de lutte contre les autres Maladies Diarrheiques (PNECHOL-MD), Ministere de la Sante Publique, Hygiene et Prevent"},{"author_name":"Daniel Mukadi-Bamuleka","author_inst":"Rodolphe Merieux Institut National de Recherche Biomedicale Goma, Goma, Democratic Republic of the Congo"},{"author_name":"Jacqueline Knee","author_inst":"Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom"},{"author_name":"Andrew S Azman","author_inst":"Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Bidirectional relationship between Sleep Disturbance and Atrial Fibrillation: a SPRINT-based analysis","rel_doi":"10.64898\/2026.09.10.26362799","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.10.26362799","rel_abs":"Background: Sleep disturbance has been associated with atrial fibrillation (AF), but prior studies have largely relied on sleep assessed at a single time point or examined specific sleep disorders. Whether changes in sleep disturbance over time predict AF and, conversely, whether AF predicts subsequent sleep disturbance within the same population is not well established. Methods: We conducted a secondary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), which enrolled adults with hypertension and increased cardiovascular risk without diabetes. Two prospective analytic cohorts were constructed to examine each direction of the association: 7,232 participants without baseline AF for the analysis of sleep disturbance and incident AF, and 6,079 participants without clinically significant sleep disturbance at baseline for the reciprocal analysis. Sleep disturbance was assessed repeatedly using a 0-3 patient-reported symptom score, with clinically significant sleep disturbance defined as a score [&ge;]2. AF was ascertained from protocol 12-lead ECGs. Time-dependent Cox models evaluated time-updated sleep disturbance in relation to incident AF and time-updated AF in relation to incident clinically significant sleep disturbance, with adjustment for demographic, lifestyle, and cardiovascular risk factors. Results: During a median follow-up of 3.3 years, 189 incident AF events occurred. Time-updated clinically significant sleep disturbance was associated with a 78% higher adjusted risk of incident AF (HR, 1.78; 95% CI, 1.27-2.51). Each 1-point increase in the time-updated sleep score was associated with a 26% higher risk of AF (HR, 1.26; 95% CI, 1.09-1.46). Compared with a sleep score of 0, the adjusted HRs were 1.20 (95% CI, 0.85-1.70), 2.05 (95% CI, 1.33-3.15), and 1.72 (95% CI, 1.03-2.88) for scores of 1, 2, and 3, respectively. In the reciprocal analysis, 1,422 incident clinically significant sleep-disturbance events occurred during a median follow-up of 3.2 years. Time-updated AF was associated with a 59% higher adjusted risk of incident clinically significant sleep disturbance (HR, 1.59; 95% CI, 1.16-2.16). Associations in both directions were consistent across prespecified subgroups, with no significant effect modification. Conclusion: In adults with hypertension, sleep disturbance and AF were prospectively and reciprocally associated when evaluated longitudinally. These findings support a bidirectional relationship between sleep disturbance and AF and highlight the potential clinical relevance of assessing sleep health in patients with or at risk for AF.","rel_num_authors":8,"rel_authors":[{"author_name":"Moustafa Elnewishy","author_inst":"Wake Forest University School of Medicine"},{"author_name":"Asem M. Mohsen","author_inst":"Wake Forest University School of Medicine"},{"author_name":"Tarek Zaho","author_inst":"Wake Forest University School of Medicine"},{"author_name":"Richard Kazibwe","author_inst":"Wake Forest University School of Medicine"},{"author_name":"Takeki Suzuki","author_inst":"Wake Forest University"},{"author_name":"M. Benjamin Shoemaker","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Prashant D Bhave","author_inst":"Wake Forest University School of Medicine"},{"author_name":"Elsayed Z. Soliman","author_inst":"Wake Forest University School of Medicine"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Bronchoalveolar Lavage Metagenomic Sequencing in the Early Post-Lung Transplantation Period: A Pilot Comparison with Microbiologic Culture","rel_doi":"10.64898\/2026.09.17.26363318","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363318","rel_abs":"BACKGROUND: Conventional bronchoalveolar lavage (BAL) culture has limited sensitivity in lung transplant recipients due to universal antimicrobial prophylaxis and inability to detect non-culturable organisms. Metagenomic sequencing of BAL offers culture-independent pathogen identification, but concordance with conventional culture and clinical utility in the immediate post-transplant period have not been evaluated. METHODS: We prospectively enrolled 19 adult lung transplant recipients undergoing serial bronchoscopies during the immediate post-transplant period. BAL samples (n=33) were tested in parallel with conventional culture, microbial cell-free DNA (mcfDNA) sequencing (Karius Focus BAL; with quantitation determined by research analysis), and Oxford Nanopore sequencing using a unified three-tier organism classification framework. BAL host-response biomarkers were profiled concurrently. RESULTS: Karius reported Tier 1 pathogens in 19\/33 episodes (58%) versus 8\/33 by conventional culture (24%); organism-level concordance was low (Cohen's kappa 0.18). In 16 episodes where Karius reported a pathogen not recovered by culture, 8 across 3 participants represented predictive reports, defined as the same organism subsequently confirmed as causing invasive infection 2-46 days later, including fatal Pseudomonas pneumonia, Enterococcal surgical site infection, and Candidemia. Nanopore sequencing had low yield due to contaminating human DNA. Quantitative mcfDNA burden correlated positively with multiple alveolar inflammatory biomarkers including total protein, IL-6, and sST2. INTERPRETATION: BAL mcfDNA metagenomics identified clinically relevant pathogens not recovered by conventional culture, including predictive reports and non-culturable organisms. Quantitative mcfDNA signal correlated with alveolar inflammatory mediators, supporting the biological relevance of mcfDNA detection beyond conventional diagnostic classification and a role for metagenomic surveillance in the early post-transplant period.","rel_num_authors":16,"rel_authors":[{"author_name":"Georgios Kitsios","author_inst":"University of Pittsburgh"},{"author_name":"Michael A. Sy","author_inst":"University of Florida, Department of Epidemiology"},{"author_name":"Xiaohong Wang","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Andrew Craig","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Alicia Rizzo","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine; Center for Acute Lung Injury and Infection"},{"author_name":"John R. Francisco","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine; Center for Acute Lung Injury and Infection"},{"author_name":"Shulin Qin","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Matthew Hensley","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Kailey Hughes Kramer","author_inst":"University of Pittsburgh, Division of Infectious Diseases"},{"author_name":"Kentaro Noda","author_inst":"University of Chicago, Department of Surgery"},{"author_name":"Panayiotis Benos","author_inst":"University of Florida, Department of Epidemiology"},{"author_name":"Chadi Hage","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Pablo Sanchez","author_inst":"University of Chicago, Department of Surgery"},{"author_name":"Alison Morris","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Ghady Haidar","author_inst":"University of Pittsburgh, Division of Infectious Diseases"},{"author_name":"Mark E. Snyder","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine; Center for Acute Lung Injury and Infection"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Bronchoalveolar Lavage Metagenomic Sequencing in the Early Post-Lung Transplantation Period: A Pilot Comparison with Microbiologic Culture","rel_doi":"10.64898\/2026.09.17.26363318","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363318","rel_abs":"BACKGROUND: Conventional bronchoalveolar lavage (BAL) culture has limited sensitivity in lung transplant recipients due to universal antimicrobial prophylaxis and inability to detect non-culturable organisms. Metagenomic sequencing of BAL offers culture-independent pathogen identification, but concordance with conventional culture and clinical utility in the immediate post-transplant period have not been evaluated. METHODS: We prospectively enrolled 19 adult lung transplant recipients undergoing serial bronchoscopies during the immediate post-transplant period. BAL samples (n=33) were tested in parallel with conventional culture, microbial cell-free DNA (mcfDNA) sequencing (Karius Focus BAL; with quantitation determined by research analysis), and Oxford Nanopore sequencing using a unified three-tier organism classification framework. BAL host-response biomarkers were profiled concurrently. RESULTS: Karius reported Tier 1 pathogens in 19\/33 episodes (58%) versus 8\/33 by conventional culture (24%); organism-level concordance was low (Cohen's kappa 0.18). In 16 episodes where Karius reported a pathogen not recovered by culture, 8 across 3 participants represented predictive reports, defined as the same organism subsequently confirmed as causing invasive infection 2-46 days later, including fatal Pseudomonas pneumonia, Enterococcal surgical site infection, and Candidemia. Nanopore sequencing had low yield due to contaminating human DNA. Quantitative mcfDNA burden correlated positively with multiple alveolar inflammatory biomarkers including total protein, IL-6, and sST2. INTERPRETATION: BAL mcfDNA metagenomics identified clinically relevant pathogens not recovered by conventional culture, including predictive reports and non-culturable organisms. Quantitative mcfDNA signal correlated with alveolar inflammatory mediators, supporting the biological relevance of mcfDNA detection beyond conventional diagnostic classification and a role for metagenomic surveillance in the early post-transplant period.","rel_num_authors":16,"rel_authors":[{"author_name":"Georgios Kitsios","author_inst":"University of Pittsburgh"},{"author_name":"Michael A. Sy","author_inst":"University of Florida, Department of Epidemiology"},{"author_name":"Xiaohong Wang","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Andrew Craig","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Alicia Rizzo","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine; Center for Acute Lung Injury and Infection"},{"author_name":"John R. Francisco","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine; Center for Acute Lung Injury and Infection"},{"author_name":"Shulin Qin","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Matthew Hensley","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Kailey Hughes Kramer","author_inst":"University of Pittsburgh, Division of Infectious Diseases"},{"author_name":"Kentaro Noda","author_inst":"University of Chicago, Department of Surgery"},{"author_name":"Panayiotis Benos","author_inst":"University of Florida, Department of Epidemiology"},{"author_name":"Chadi Hage","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine"},{"author_name":"Pablo Sanchez","author_inst":"University of Chicago, Department of Surgery"},{"author_name":"Alison Morris","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Ghady Haidar","author_inst":"University of Pittsburgh, Division of Infectious Diseases"},{"author_name":"Mark E. Snyder","author_inst":"University of Pittsburgh, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine; Center for Acute Lung Injury and Infection"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Microbiome Profiling Reveals Prognostic Heterogeneity in Staphylococcus aureus Pneumonia","rel_doi":"10.64898\/2026.09.17.26363347","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363347","rel_abs":"Background: Staphylococcus aureus is a leading cause of severe pneumonia in mechanically ventilated patients. Clinical cultures identify pathogen presence but may not reflect lower respiratory tract microbial ecology. Whether culture-confirmed S. aureus pneumonia encompasses compositional heterogeneity with prognostic implications remains unknown. Methods: We performed 16S rRNA gene sequencing and shotgun nanopore metagenomics on endotracheal aspirate samples from mechanically ventilated patients with culture-confirmed S. aureus pneumonia in a prospective ICU registry. We quantified Staphylococcus abundance, assessed correlations with culture characteristics and host inflammatory biomarkers, and examined associations with 60-day mortality using Kaplan-Meier and Cox hazards analyses. Results: Among 109 patients, semi-quantitative culture growth and methicillin resistance showed no associations with outcomes. 16S sequencing (n=54) revealed marked heterogeneity in Staphylococcus relative abundance (range 0-96.7%), with only 33% demonstrating dominance (>50%). Dominance was associated with worse 60-day survival (50% vs. 80%,p=0.013) and remained independently predictive after adjusting for age, sex, and methicillin resistance (adjusted HR 3.24 [95%CI 1.12-9.36],p=0.030). Patients with dominance exhibited elevated pentraxin-3 (p=0.01) and reduced fractalkine (p=0.02). Nanopore metagenomics (n=28) validated these findings, with high absolute S. aureus read counts independently predicting mortality (adjusted HR 11.23 [95%CI 2.25-55.9],p=0.003). In an exploratory analysis of virulence genes (n=19), staphylokinase detection was associated with the hyperinflammatory phenotype (p=0.003) and mortality (p=0.046). Conclusions: Metagenomic profiling reveals clinically meaningful heterogeneity within culture-confirmed S. aureus pneumonia, masked by conventional diagnostics. Staphylococcus dominance identifies a high-risk phenotype with elevated bacterial burden, dysregulated host responses, and increased mortality, challenging the assumption that culture positivity represents a uniform clinical entity.","rel_num_authors":14,"rel_authors":[{"author_name":"Georgios Kitsios","author_inst":"University of Pittsburgh"},{"author_name":"Michael Aaron Sy","author_inst":"University of Florida"},{"author_name":"William G. Bain","author_inst":"University of Pittsburgh"},{"author_name":"Matthew Hensley","author_inst":"University of Pittsburgh"},{"author_name":"Shulin Qin","author_inst":"University of Pittsburgh"},{"author_name":"Xiaohong Wang","author_inst":"University of Pittsburgh"},{"author_name":"Kyle W. Inman","author_inst":"University of Pittsburgh"},{"author_name":"Charles Dela Cruz","author_inst":"University of Pittsburgh"},{"author_name":"Keven Robinson","author_inst":"University of Pittsburgh"},{"author_name":"Seyed Mehdi Nouraie","author_inst":"University of Pittsburgh"},{"author_name":"Faraaz A. Shah","author_inst":"University of Pittsburgh"},{"author_name":"Panayiotis Benos","author_inst":"University of Florida"},{"author_name":"Bryan J. McVerry","author_inst":"University of Pittsburgh"},{"author_name":"Alison Morris","author_inst":"Rutgers Robert Wood Johnson Medical School"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Association of polygenic risk scores with low-density lipoprotein cholesterol levels and control: findings from the Hispanic Community Health Study\/Study of Latinos (HCHS\/SOL)","rel_doi":"10.64898\/2026.09.16.26363269","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.16.26363269","rel_abs":"Background: Hypercholesterolemia is a prevalent cardiovascular (CVD) risk factor among Hispanics\/Latinos; however, rates of cholesterol awareness and treatment are low in this population. Using a polygenic risk score (PRS) associated with low-density lipoprotein cholesterol (LDL) levels may help identify those who would benefit most from statin therapy. Previous LDL-PRS have been developed but they have not been properly evaluated for use in a highly diverse Hispanic\/Latino population. Methods: The Hispanic Community Health Study\/Study of Latinos (HCHS\/SOL) is a prospective study that enrolled 16,415 Hispanic\/Latino adults aged 18-74 years from four U.S. communities in 2008-2011. We assessed the association of twenty PRS with baseline LDL levels and LDL control among 11,669 HCHS\/SOL participants with complete data and consent to conduct genetic research. Weighted PRS were calculated using effect estimates obtained from the PGS Catalog. Multivariable linear regression analysis was used to derive effect estimates (betas (&beta), 95% confidence intervals (CI)) for the association between each PRS, modeled continuously and by quintiles, with baseline LDL levels. Multivariable logistic regression was used to derive odds ratios and 95% CI for the association between each PRS and LDL control in statin users. Models were adjusted for predefined confounders and accounted for survey weights. Results: A PRS developed with PolyFun-pred, using European GWAS summary statistics, provided the largest incremental improvement for predicting LDL levels for the full sample (&Delta R2 0.114), Caribbean background (&Delta R2 0.096), majority African ancestry (&Delta R2 0.098), and majority Amerindian ancestry subgroups (&Delta R2 0.123). PRSCSx-EUR, using multiple ancestry GWAS and weights, improved PRS performance most for the Mainland background (&Delta R2 0.090) and majority European ancestry (&Delta R2 0.061) subgroups. For every one standard deviation increase across the 20 PRS asssesed, LDL increase varied between 3 and 14mg\/dL. Among 1,323 statin users, the odds of LDL control were greatly reduced with increasing PRS but differed between PRS and Hispanic\/Latino background groups and genetic ancestry groups. Conclusion: A polygenic risk score prioritizing functional annotations demonstrated superior performance for predicting LDL levels and LDL control across Hispanic\/Latino subgroups. These results emphasize that further development of PRS is needed for improved risk prediction before clinical application in diverse populations.","rel_num_authors":8,"rel_authors":[{"author_name":"Christina G Hutten","author_inst":"Rush University Medical Center"},{"author_name":"Tamar Sofer","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Brian W Spitzer","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Molly Scannell Bryan","author_inst":"University of Illinois at Chicago"},{"author_name":"Jiehuan Sun","author_inst":"University of Illinois at Chicago"},{"author_name":"Victoria Persky","author_inst":"University of Illinois at Chicago, School of Public Health"},{"author_name":"Martha L. Daviglus","author_inst":"Institute for Minority Health Research, University of Illinois-Chicago"},{"author_name":"Maria Argos","author_inst":"Boston University"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"AlphaGenome Atlas: in silico mutagenesis of the entire human genome improves prioritization and interpretation of non-coding variants","rel_doi":"10.64898\/2026.09.16.26363192","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.16.26363192","rel_abs":"A major challenge in genomics is deciphering the functional consequences of non-coding genetic variation. Here we present AlphaGenome Atlas, a comprehensive resource that enables the joint interpretation and prioritization of variant effects across the entire human genome. Using AlphaGenome, we predicted the regulatory effects across thousands of molecular phenotypes for every possible human single nucleotide variant and many observed indels. These predictions were then used to derive a unified and interpretable AlphaGenome Variant Impact (AVI) score and to map cis-regulatory motifs across the genome. AVI achieved state-of-the-art performance across diverse benchmarks with improved prioritization of deleterious non-coding variants. Application of the combined Atlas resource helped solve an epileptic encephalopathy rare disease case, increased the statistical power to detect rare non-coding variants driving population-level phenotypes, and enhanced the mechanistic interpretation of these variants. Thus, AlphaGenome Atlas improves the prioritization and molecular interpretation of non-coding variants with genetic and clinical significance.","rel_num_authors":43,"rel_authors":[{"author_name":"Jun Cheng","author_inst":"Google DeepMind"},{"author_name":"Kyle R. Taylor","author_inst":"Google DeepMind"},{"author_name":"Lauren Nicolaisen","author_inst":"Google DeepMind"},{"author_name":"Joshua Pan","author_inst":"Google DeepMind"},{"author_name":"Clare Bycroft","author_inst":"Google DeepMind"},{"author_name":"Matteo Perino","author_inst":"Google DeepMind"},{"author_name":"Tom Ward","author_inst":"Google DeepMind"},{"author_name":"Gareth Hawkes","author_inst":"University of Exeter Medical School"},{"author_name":"Laura E. Covill","author_inst":"Broad Institute of MIT and Harvard; Boston Children's Hospital"},{"author_name":"Melanie Weilert","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Raina W. Thomas","author_inst":"Google DeepMind"},{"author_name":"Natasha Latysheva","author_inst":"Google DeepMind"},{"author_name":"Maile J. Hirschmann","author_inst":"Broad Institute of MIT and Harvard; Harvard University"},{"author_name":"Xi Dawn Chen","author_inst":"Broad Institute of MIT and Harvard; Harvard University"},{"author_name":"Robin N Beaumont","author_inst":"University of Exeter Medical School"},{"author_name":"V. Kartik Chundru","author_inst":"University of Exeter Medical School"},{"author_name":"Michael N Weedon","author_inst":"University of Exeter Medical School"},{"author_name":"Simon Bourdareau","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Hoyin Chu","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Dhavanthi Hariharan","author_inst":"Google DeepMind"},{"author_name":"Thais Kagohara","author_inst":"Google DeepMind"},{"author_name":"Lucas Tenorio","author_inst":"Google DeepMind"},{"author_name":"Yosuke Ushigome","author_inst":"Google DeepMind"},{"author_name":"Courtney A. Shearer","author_inst":"Google DeepMind"},{"author_name":"Barbara Ikica","author_inst":"Google Research"},{"author_name":"Ada Fang","author_inst":"Google DeepMind"},{"author_name":"Mouad Naciri","author_inst":"Google DeepMind"},{"author_name":"Victoria Johnston","author_inst":"Google DeepMind"},{"author_name":"Richard Green","author_inst":"Google DeepMind"},{"author_name":"Lai Hong Wong","author_inst":"Google DeepMind"},{"author_name":"Vincent Dutordoir","author_inst":"Google DeepMind"},{"author_name":"Anne Mottram","author_inst":"Google DeepMind"},{"author_name":"Adam Gayoso","author_inst":"Google DeepMind"},{"author_name":"Eirini Arvaniti","author_inst":"Google DeepMind"},{"author_name":"Guido Novati","author_inst":"Google DeepMind"},{"author_name":"Heidi L. Rehm","author_inst":"Broad Institute of MIT and Harvard; Massachusetts General Hospital"},{"author_name":"Fei Chen","author_inst":"Broad Institute of MIT and Harvard; Harvard University"},{"author_name":"Caleb A. Lareau","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Caroline F Wright","author_inst":"University of Exeter Medical School"},{"author_name":"Anne O'Donnell-Luria","author_inst":"Broad Institute of MIT and Harvard; Massachusetts General Hospital; Boston Children's Hospital"},{"author_name":"Julia Zeitlinger","author_inst":"Stowers Institute for Medical Research; University of Kansas Medical Center"},{"author_name":"Pushmeet Kohli","author_inst":"Google DeepMind"},{"author_name":"Ziga Avsec","author_inst":"Google DeepMind"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"AlphaGenome Atlas: in silico mutagenesis of the entire human genome improves prioritization and interpretation of non-coding variants","rel_doi":"10.64898\/2026.09.16.26363192","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.16.26363192","rel_abs":"A major challenge in genomics is deciphering the functional consequences of non-coding genetic variation. Here we present AlphaGenome Atlas, a comprehensive resource that enables the joint interpretation and prioritization of variant effects across the entire human genome. Using AlphaGenome, we predicted the regulatory effects across thousands of molecular phenotypes for every possible human single nucleotide variant and many observed indels. These predictions were then used to derive a unified and interpretable AlphaGenome Variant Impact (AVI) score and to map cis-regulatory motifs across the genome. AVI achieved state-of-the-art performance across diverse benchmarks with improved prioritization of deleterious non-coding variants. Application of the combined Atlas resource helped solve an epileptic encephalopathy rare disease case, increased the statistical power to detect rare non-coding variants driving population-level phenotypes, and enhanced the mechanistic interpretation of these variants. Thus, AlphaGenome Atlas improves the prioritization and molecular interpretation of non-coding variants with genetic and clinical significance.","rel_num_authors":43,"rel_authors":[{"author_name":"Jun Cheng","author_inst":"Google DeepMind"},{"author_name":"Kyle R. Taylor","author_inst":"Google DeepMind"},{"author_name":"Lauren Nicolaisen","author_inst":"Google DeepMind"},{"author_name":"Joshua Pan","author_inst":"Google DeepMind"},{"author_name":"Clare Bycroft","author_inst":"Google DeepMind"},{"author_name":"Matteo Perino","author_inst":"Google DeepMind"},{"author_name":"Tom Ward","author_inst":"Google DeepMind"},{"author_name":"Gareth Hawkes","author_inst":"University of Exeter Medical School"},{"author_name":"Laura E. Covill","author_inst":"Broad Institute of MIT and Harvard; Boston Children's Hospital"},{"author_name":"Melanie Weilert","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Raina W. Thomas","author_inst":"Google DeepMind"},{"author_name":"Natasha Latysheva","author_inst":"Google DeepMind"},{"author_name":"Maile J. Hirschmann","author_inst":"Broad Institute of MIT and Harvard; Harvard University"},{"author_name":"Xi Dawn Chen","author_inst":"Broad Institute of MIT and Harvard; Harvard University"},{"author_name":"Robin N Beaumont","author_inst":"University of Exeter Medical School"},{"author_name":"V. Kartik Chundru","author_inst":"University of Exeter Medical School"},{"author_name":"Michael N Weedon","author_inst":"University of Exeter Medical School"},{"author_name":"Simon Bourdareau","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Hoyin Chu","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Dhavanthi Hariharan","author_inst":"Google DeepMind"},{"author_name":"Thais Kagohara","author_inst":"Google DeepMind"},{"author_name":"Lucas Tenorio","author_inst":"Google DeepMind"},{"author_name":"Yosuke Ushigome","author_inst":"Google DeepMind"},{"author_name":"Courtney A. Shearer","author_inst":"Google DeepMind"},{"author_name":"Barbara Ikica","author_inst":"Google Research"},{"author_name":"Ada Fang","author_inst":"Google DeepMind"},{"author_name":"Mouad Naciri","author_inst":"Google DeepMind"},{"author_name":"Victoria Johnston","author_inst":"Google DeepMind"},{"author_name":"Richard Green","author_inst":"Google DeepMind"},{"author_name":"Lai Hong Wong","author_inst":"Google DeepMind"},{"author_name":"Vincent Dutordoir","author_inst":"Google DeepMind"},{"author_name":"Anne Mottram","author_inst":"Google DeepMind"},{"author_name":"Adam Gayoso","author_inst":"Google DeepMind"},{"author_name":"Eirini Arvaniti","author_inst":"Google DeepMind"},{"author_name":"Guido Novati","author_inst":"Google DeepMind"},{"author_name":"Heidi L. Rehm","author_inst":"Broad Institute of MIT and Harvard; Massachusetts General Hospital"},{"author_name":"Fei Chen","author_inst":"Broad Institute of MIT and Harvard; Harvard University"},{"author_name":"Caleb A. Lareau","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Caroline F Wright","author_inst":"University of Exeter Medical School"},{"author_name":"Anne O'Donnell-Luria","author_inst":"Broad Institute of MIT and Harvard; Massachusetts General Hospital; Boston Children's Hospital"},{"author_name":"Julia Zeitlinger","author_inst":"Stowers Institute for Medical Research; University of Kansas Medical Center"},{"author_name":"Pushmeet Kohli","author_inst":"Google DeepMind"},{"author_name":"Ziga Avsec","author_inst":"Google DeepMind"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Impaired regulatory T cell mediated immune tolerance promotes neurodegeneration in glaucoma","rel_doi":"10.64898\/2026.09.17.26363354","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363354","rel_abs":"Neurodegenerative diseases are increasingly recognized to involve detrimental interactions between the immune and nervous systems, yet whether failure of peripheral immune tolerance actively drives neuronal loss frequently remains unclear. Here, using primary open-angle glaucoma as a model of chronic neurodegeneration, we demonstrate that dysregulated adaptive immunity is sufficient to promote retinal ganglion cell degeneration. Peripheral blood mononuclear cells from glaucoma patients, but not healthy donors, induced retinal ganglion cell loss following transfer into humanized immunodeficient mice without changes to the intraocular pressure, demonstrating a causal role for immune responses in the patient derived material. Comprehensive immune profiling further revealed selective changes in the regulatory T-cell compartment, indicating reduced activation, an impaired suppressive phenotype, and altered differentiation and trafficking states despite preserved overall regulatory T cell abundance. We further demonstrate that transient expansion of regulatory T cells preserves visual function, reduced optic nerve axonal degeneration, and limited retinal ganglion cell loss in an experimental glaucoma model. Together, these findings identify failure of regulatory T cell mediated immune tolerance as a mechanism that permits neurodegeneration in glaucoma and demonstrate that restoring immune regulation can ameliorate neuronal injury. Our data indicate that immune tolerance is a modifiable determinant of chronic neurodegeneration and suggest that immunoregulatory therapies may complement conventional pressure-lowering treatments to preserve vision in glaucoma.","rel_num_authors":11,"rel_authors":[{"author_name":"Huilan Zeng","author_inst":"University of South China"},{"author_name":"Merri-Grace Jones","author_inst":"University of Iowa"},{"author_name":"Zeb Zacharias","author_inst":"University of Iowa"},{"author_name":"Erin A Boese","author_inst":"University of Iowa"},{"author_name":"Wallace L.M. Alward","author_inst":"University of Iowa"},{"author_name":"Young H Kwon","author_inst":"University of Iowa"},{"author_name":"Jon C Houtman","author_inst":"University of Iowa"},{"author_name":"Edward Linton","author_inst":"University of Iowa"},{"author_name":"Randy H Kardon","author_inst":"University of Iowa"},{"author_name":"Oliver W Gramlich","author_inst":"University of Alabama-Birmingham"},{"author_name":"Markus Kuehn","author_inst":"University of Iowa"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Investigating 24-Hour Urine Expected Ranges of Non-Kidney Stone Formers: an EAU Endourology Research Group Systematic Review and Meta-Analysis","rel_doi":"10.64898\/2026.09.17.26363294","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363294","rel_abs":"Background and Objective: There is substantial variation in reference ranges for 24-hour urine collections, leading to diagnostic uncertainty. We aimed to curate robust evidence for expected ranges of 24-hour urine collections in the non-kidney stone forming population. Methods: We performed a systematic review (PROSPERO ID: CRD42024590784) of healthy adults without kidney stone disease undergoing 24-hour urine collections. Each component was meta-analysed in R, stratified by age, sex and ancestry, meta-regression and sensitivity analyses for study design, collection completeness and bias. An explicit eight-branch decision framework selected the recommended analysis per component. Expected ranges were derived from the pooled SD (95% interval); evidence was quantified by GRADE. Key Findings and Limitations: Seventy-two articles were included (10,284 participants). Expected ranges (mmol \/ 24 h unless stated): volume 1.0-2.5L, calcium 1.9-6.2, oxalate 0.2-0.6 (men) \/ 0.2-0.4 (women), urate 2.0-5.1(men)\/2.3-3.5(women), pH 5.6-6.3, citrate 1.2-4.5, creatinine 12.2-16.3(men)\/7.2-12.6(women), phosphate 19-26, sodium 98-253, potassium 28-77, magnesium 3.1-4.8, ammonium 28-46(men)\/20-40(women), chloride 84-218, sulphate 17-26(men)\/7-30(women), urea 234-445. Principal limitations were: high between-study heterogeneity (I-squared>95% for most components) and assay\/laboratory variability (most marked for citrate and potassium). Conclusions and Clinical Implications: This is the first study to attempt a robust characterization of 24-hour urine expected ranges using meta-analysis. Six of the derived expected ranges (pH, oxalate, magnesium, sulphate, urate, creatinine) were broadly concordant with existing reference ranges, providing an evidence base for those specific components.","rel_num_authors":15,"rel_authors":[{"author_name":"Kimberley Noble","author_inst":"School of Pharmacy, Newcastle University, Newcastle upon Tyne, UK"},{"author_name":"Anastasia Glubb","author_inst":"Department of Urology, Freeman Hospital, Newcastle upon Tyne, UK"},{"author_name":"Parag Roy","author_inst":"School of Pharmacy, Newcastle University, Newcastle upon Tyne, UK"},{"author_name":"Jacqueline Howard","author_inst":"Library and Information Services, Freeman Hospital, Newcastle upon Tyne, UK"},{"author_name":"Lazaros Tzelves","author_inst":"National and Kapodistrian Hospital of Athens, Greece"},{"author_name":"Steffi Yuen","author_inst":"Chinese University of Hong Kong"},{"author_name":"Paul Cook","author_inst":"University Hospital Southampton, UK"},{"author_name":"Bhaskar Somani","author_inst":"University of Southampton, UK"},{"author_name":"Daniel Fuster","author_inst":"Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland."},{"author_name":"Pietro Manuel Ferraro","author_inst":"Section of Nephrology, Department of Medicine, University degli Studi di Verona; Nephrology Unit, Azienda Ospedaliera Universitaria Integrata Verona, Italy"},{"author_name":"Gary Curhan","author_inst":"Channing Division of Network Medicine and Renal Division, Brigham and Women's Hospital; Harvard Medical School, Boston, Massachusetts, USA"},{"author_name":"Sarah A Howles","author_inst":"University of Oxford"},{"author_name":"John  A Sayer","author_inst":"Newcastle University Institute of Genetic Medicine"},{"author_name":"Oisin Kavanagh","author_inst":"School of Pharmacy, Newcastle University, Newcastle upon Tyne, UK"},{"author_name":"Robert Geraghty","author_inst":"Department of Urology, Freeman Hospital, Newcastle upon Tyne, UK"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Myocardial Stiffness Tracking & Assessment Toolkit Driven by Artificial Intelligence For Reproducible Benchmarking of Temporal Segmentation and Shear-Wave Velocity Stabilization on Synthetic Data","rel_doi":"10.64898\/2026.09.17.26363353","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363353","rel_abs":"Propose: Routine echocardiographic assessment can be affected by operator variability and time-consuming post-processing, which may limit rapid quantitative analysis. Real-time cine ultrasound demands low-latency automated processing for clinical usage. Existing approaches lack standardized evaluation frameworks, verified edge deployment, and structured reproducibility guarantees. To address these limitations, we built Myocardial Stiffness Tracking & Assessment Toolkit driven by Artificial Intelligence (MyoSTAT.AI). We report a deterministic, fully reproducible pipeline that performs real-time segmentation and SWE velocity estimation, evaluated entirely on synthetic data. Approach: Four U-Net-based architectures spanning single-frame and temporal designs were evaluated via systematic ablation: a 2D baseline, a 2.5D stacked-frame model, a 3D volumetric model, and a ConvLSTM variant. Experiments used synthetic reference corpora with split accounting the segmentation corpus contained 1,200 synthetic frames, and the SWE corpus contained 900 synthetic velocity-field cases. The SWE branch used Radon-transform-based propagation-direction estimation, time-domain shear-wave speed estimation, and configurable temporal stabilization on synthetic velocity fields. TensorRT FP16 deployment benchmarks were performed separately for the exported UNet2.5D segmentation model on RTX 3060 and Jetson Orin Nano hardware. Results: On the synthetic evaluation quantities, the ConvLSTM variant achieved the highest segmentation accuracy (Dice 0.994, IoU 0.987), an 18.6% improvement over the 2D baseline (Dice 0.808). A 2.5D model with a 3-frame temporal window achieved Dice 0.983 at substantially lower latency (433 ms vs. 1193 ms). TensorRT FP16 deployment yielded 341 FPS on the RTX 3060 and 90.4 FPS on the Jetson Orin Nano. Penalized least-squares temporal stabilization (smoothn, {lambda}=10) reduced shear-wave speed CoV by 63.8% at 2.7 ms latency overhead per frame, with no loss of edge preservation. Conclusions: We demonstrate a deterministic, reproducible computational benchmarking framework for cardiac segmentation and SWE velocity-field stabilization, evaluated entirely on synthetic data, together with preliminary inference feasibility on workstation and embedded hardware. These results represent a synthetic proof-of-concept rather than a validated clinical or operator-independent tool; acquisition of real echocardiographic data and clinical validation are required before any claim of diagnostic or deployment readiness can be made.","rel_num_authors":17,"rel_authors":[{"author_name":"Terry Tsebro","author_inst":"University of Toronto"},{"author_name":"Abdullah Safi","author_inst":"University of Toronto"},{"author_name":"Bangcheng Wang","author_inst":"University of Toronto"},{"author_name":"Luca Hutchison","author_inst":"University of Toronto"},{"author_name":"Kamil Chaudhry","author_inst":"University of Toronto"},{"author_name":"Laith Alzoubi","author_inst":"University of Toronto"},{"author_name":"Mark Noge","author_inst":"University of Toronto"},{"author_name":"Austin Hua","author_inst":"University of Toronto"},{"author_name":"Nimish Ray","author_inst":"University of Toronto"},{"author_name":"Antonin Chianale","author_inst":"University of Toronto"},{"author_name":"Parham Baghban-Bashi","author_inst":"University of Toronto"},{"author_name":"Meryem Karayunusoglu","author_inst":"University of Toronto"},{"author_name":"Yimin Xu","author_inst":"Northeastern University"},{"author_name":"Amar Saed","author_inst":"University of Toronto"},{"author_name":"Wagih Ghobriel","author_inst":"University of Toronto"},{"author_name":"Aimen Malik","author_inst":"Yale University"},{"author_name":"Dennis D. Fernandes","author_inst":"Northeastern University"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Myocardial Stiffness Tracking & Assessment Toolkit Driven by Artificial Intelligence For Reproducible Benchmarking of Temporal Segmentation and Shear-Wave Velocity Stabilization on Synthetic Data","rel_doi":"10.64898\/2026.09.17.26363353","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363353","rel_abs":"Propose: Routine echocardiographic assessment can be affected by operator variability and time-consuming post-processing, which may limit rapid quantitative analysis. Real-time cine ultrasound demands low-latency automated processing for clinical usage. Existing approaches lack standardized evaluation frameworks, verified edge deployment, and structured reproducibility guarantees. To address these limitations, we built Myocardial Stiffness Tracking & Assessment Toolkit driven by Artificial Intelligence (MyoSTAT.AI). We report a deterministic, fully reproducible pipeline that performs real-time segmentation and SWE velocity estimation, evaluated entirely on synthetic data. Approach: Four U-Net-based architectures spanning single-frame and temporal designs were evaluated via systematic ablation: a 2D baseline, a 2.5D stacked-frame model, a 3D volumetric model, and a ConvLSTM variant. Experiments used synthetic reference corpora with split accounting the segmentation corpus contained 1,200 synthetic frames, and the SWE corpus contained 900 synthetic velocity-field cases. The SWE branch used Radon-transform-based propagation-direction estimation, time-domain shear-wave speed estimation, and configurable temporal stabilization on synthetic velocity fields. TensorRT FP16 deployment benchmarks were performed separately for the exported UNet2.5D segmentation model on RTX 3060 and Jetson Orin Nano hardware. Results: On the synthetic evaluation quantities, the ConvLSTM variant achieved the highest segmentation accuracy (Dice 0.994, IoU 0.987), an 18.6% improvement over the 2D baseline (Dice 0.808). A 2.5D model with a 3-frame temporal window achieved Dice 0.983 at substantially lower latency (433 ms vs. 1193 ms). TensorRT FP16 deployment yielded 341 FPS on the RTX 3060 and 90.4 FPS on the Jetson Orin Nano. Penalized least-squares temporal stabilization (smoothn, {lambda}=10) reduced shear-wave speed CoV by 63.8% at 2.7 ms latency overhead per frame, with no loss of edge preservation. Conclusions: We demonstrate a deterministic, reproducible computational benchmarking framework for cardiac segmentation and SWE velocity-field stabilization, evaluated entirely on synthetic data, together with preliminary inference feasibility on workstation and embedded hardware. These results represent a synthetic proof-of-concept rather than a validated clinical or operator-independent tool; acquisition of real echocardiographic data and clinical validation are required before any claim of diagnostic or deployment readiness can be made.","rel_num_authors":17,"rel_authors":[{"author_name":"Terry Tsebro","author_inst":"University of Toronto"},{"author_name":"Abdullah Safi","author_inst":"University of Toronto"},{"author_name":"Bangcheng Wang","author_inst":"University of Toronto"},{"author_name":"Luca Hutchison","author_inst":"University of Toronto"},{"author_name":"Kamil Chaudhry","author_inst":"University of Toronto"},{"author_name":"Laith Alzoubi","author_inst":"University of Toronto"},{"author_name":"Mark Noge","author_inst":"University of Toronto"},{"author_name":"Austin Hua","author_inst":"University of Toronto"},{"author_name":"Nimish Ray","author_inst":"University of Toronto"},{"author_name":"Antonin Chianale","author_inst":"University of Toronto"},{"author_name":"Parham Baghban-Bashi","author_inst":"University of Toronto"},{"author_name":"Meryem Karayunusoglu","author_inst":"University of Toronto"},{"author_name":"Yimin Xu","author_inst":"Northeastern University"},{"author_name":"Amar Saed","author_inst":"University of Toronto"},{"author_name":"Wagih Ghobriel","author_inst":"University of Toronto"},{"author_name":"Aimen Malik","author_inst":"Yale University"},{"author_name":"Dennis D. Fernandes","author_inst":"Northeastern University"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Meditation Practice and Long-Term Mortality in US Adults: A Doubly Robust Analysis of Pooled National Health Interview Survey Cohorts with a Trial-Informed Bayesian Subgroup Analysis","rel_doi":"10.64898\/2026.09.17.26363306","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363306","rel_abs":"ABSTRACT Introduction: Trial evidence in older adults with hypertension suggests that meditation may lower mortality, but this association has not been tested in a nationally representative study with linked-mortality data. This study estimated meditation's association with mortality among US adults, examined variation by family income, and synthesized trial and survey evidence for the population matched to the trial evidence base. Methods: We pooled four National Health Interview Survey cohorts (2002 to 2017) with mortality follow-up through 2019 (N=90,041; 8,402 [9.3%] reported meditation practice in the past 12 months). Doubly robust survey-weighted Cox models combined stabilized inverse-probability weights with covariate adjustment, overall and by income stratum; 15 year risks were standardized using g computation, and probabilistic bias analysis addressed exposure misclassification, including a scenario by income strata. For non Hispanic Black adults [&ge;]55 years with hypertension (n=2,786), Bayesian synthesis combined subgroup estimates with a pooled randomized trial prior. Results: Over 818,248 person years of follow up, 10,027 all cause and 3,040 cardiovascular deaths occurred. Doubly robust hazard ratios (HR) were 1.02 (95% CI 0.90, 1.16) for all cause and 0.96 (95% CI 0.79, 1.16) for cardiovascular mortality. Among individuals below 200% of the federal poverty level, HRs were 0.85 (All cause: 95% CI 0.71, 1.03) and 0.80 (Cardiovascular mortality: 95% CI 0.57, 1.10), compared with 1.10 (95% CI 0.93, 1.30) and 1.02 (95% CI 0.80, 1.30) among those at\/above that threshold (interaction p=0.19 and p=0.62). In the subgroup analysis, posteriors under a 50%-discounted trial prior were 0.84 (All-cause mortality: Pr[HR<1]=0.89) and 0.70 (Cardiovascular mortality: Pr[HR<1]=0.96). Conclusions: Meditation practice showed no overall association with mortality after doubly robust adjustment. However, estimates suggesting a protective effect were concentrated among adults below 200% of the federal poverty level, and trial-informed synthesis indicated probable benefit in cardiovascular mortality in the high-risk subgroup most comparable to trial participants. These hypothesis-generating findings motivate further study of effect modification using more detailed exposure measurement.","rel_num_authors":5,"rel_authors":[{"author_name":"Lu Shi","author_inst":"Department of Health Science, College of Health Professions, Pace University, New York, NY"},{"author_name":"Yian Gu","author_inst":"Departments of Neurology and Epidemiology, Gertrude H. Sergievsky Center, and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia U"},{"author_name":"Hafsa Imtiaz","author_inst":"Department of Health Science, College of Health Professions, Pace University, New York, NY"},{"author_name":"Donglan Zhang","author_inst":"Division of Health Services Research, Department of Foundations of Medicine, NYU Grossman Long Island School of Medicine, New York, NY"},{"author_name":"Anthony D. Mancini","author_inst":"Department of Psychology, Pace University, Pleasantville, NY"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Low-Intensity Focused Ultrasound of the Amygdala in Depression and Anxiety: A First-in-Human Active-Controlled Trial","rel_doi":"10.64898\/2026.09.18.26363360","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363360","rel_abs":"ABSTRACT Background: Low intensity focused ultrasound (FUS) offers a noninvasive method for directly modulating deep brain structures with millimeter-scale precision, potentially addressing a major limitation of existing noninvasive neuromodulation approaches. The amygdala is a key node in affective neurocircuitry and a compelling target for psychiatric intervention. We conducted a first in human active controlled trial (NCT05147142) of amygdala-targeted FUS in patients with major depressive disorder, examining safety and target engagement. Methods: Ten participants with major depressive disorder completed a single-blind randomized crossover trial with blinded symptom ratings, comparing imaging guided FUS targeting the right amygdala versus left primary somatosensory cortex as an active control. FUS comprised two 10 minute applications within diagnostic ultrasound safety limits. Primary outcomes were safety and target engagement assessed with BOLD fMRI during sonication, post-sonication arterial spin labeling (ASL) and resting state functional connectivity. Secondary and exploratory outcomes included symptom change and imaging x symptom relationships. Results: Nine participants completed both sessions. No serious adverse events occurred; neurological, neuropsychological, and MRI safety assessments were unremarkable. Adverse events were more frequent after amygdala than control sonication (p=0.028); one participant experienced clinical worsening following amygdala sonication and required monitoring. Amygdala sonication produced greater perfusion change in the targeted amygdala compared to the control region (p<0.001), and ipsilateral hippocampus (p<0.001). BOLD fMRI during sonication demonstrated engagement of ventromedial prefrontal and rostral anterior cingulate regions, while post sonication resting state connectivity decreased between basolateral amygdala and sensorimotor regions (corrected ps<0.05). Symptom improvement did not differ between conditions, but exploratory imaging x symptom relationships were significant. Spontaneous reports of calm, clarity, or lightness occurred after amygdala but not control sonication (p<0.001). Conclusions: Amygdala targeted FUS produced anatomically specific, multimodal evidence of neuromodulation relative to active control, with a manageable safety profile. Convergent target and circuit level signals support further development of FUS as a precision approach for modulating deep brain targets in psychiatric disorders. Key words: low-intensity focused ultrasound, amygdala, neuroimaging, depression, anxiety","rel_num_authors":16,"rel_authors":[{"author_name":"Amanda R Arulpragasam","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Mascha van 't Wout-Frank","author_inst":"Brown University Health"},{"author_name":"Yosef A Berlow","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Emily Aiken","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Alison Gorbatov","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Ryan Van Patten","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Julia G Gillotti","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Hannah R Swearingen","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Christiana R Faucher","author_inst":"Department of Psychology, University of Minnesota-Twin Cities"},{"author_name":"Hannah Adams","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Nicole C.R. McLaughlin","author_inst":"Butler Hospital"},{"author_name":"Israel Liberzon","author_inst":"Texas A and M University Health Science Center"},{"author_name":"Jennifer Barredo","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Stephen Correia","author_inst":"Institute of Gerontology, University of Georgia"},{"author_name":"Benjamin Greenberg","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"},{"author_name":"Noah S Philip","author_inst":"Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"International trends in clozapine utilisation prevalence in adults, adolescents and older people: An observational study in 42 countries between 2015 and 2024","rel_doi":"10.64898\/2026.09.17.26363131","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363131","rel_abs":"Importance: Clozapine is the only evidence-based treatment for treatment-resistant schizophrenia (TRS), yet substantial international variation in its use has been reported. Objective: To provide a comprehensive and updated assessment of international clozapine utilisation by estimating prevalence across countries using a standardised methodology and examining factors associated with variation in use. Design, Setting, and Participants: Repeated cross-sectional study using population-based data from 2015 to 2024. Individual-level data were obtained from 36 countries and 1 special administrative region, supplemented by national clozapine consumption data from 5 additional countries. Analyses were conducted separately for adults (20-64 years; primary analysis), adolescents (10-19 years), and older adults ([&ge;]65 years). Main Outcomes and Measures: Annual outpatient clozapine utilisation prevalence per 100,000 population by age group, sex, country and calendar year. Associations between clozapine utilisation prevalence and country-level health system, demographic, and socioeconomic indicators were also examined. Results: We analysed data from more than 1.1 billion people across all inhabited continents. In 2024, crude adult clozapine use prevalence was highest in Croatia (415.3 per 100,000 population) and Finland (302.0 per 100,000), and lowest in Oman (0.5 per 100,000) and Ethiopia (0.3 per 100,000), representing a 1,384-fold difference. Across most countries, utilisation peaked among individuals aged 50 to 59 years. The male-to-female prevalence ratio ranged from 0.4 in the United Arab Emirates to 2.8 in Colombia. Among adolescents, prevalence was highest in Colombia (42.7 per 100,000) and Croatia (24.4 per 100,000), while among older adults it was highest in Croatia (406.9 per 100,000) and Iceland (339.7 per 100,000). Across all countries, adult clozapine utilisation increased by 17% (95% CI, 16%-18%), from 44.7 per 100,000 population (95% CI, 44.5-44.9) to 52.2 per 100,000 population (95% CI, 51.1-52.4). Country-specific trends ranged from a 71% decrease to a 342% increase. None of the examined indicators explained variation in clozapine utilisation across countries. Conclusion and relevance: Clozapine use increased modestly over the past decade but remained highly variable between countries. This variation was not explained by national socioeconomic, healthcare-system, or monitoring-related factors, suggesting an important role for clinical and service-level barriers. The concentration of clozapine use in later adulthood is consistent with delayed initiation and highlights opportunities to improve timely access to evidence-based treatment for TRS.","rel_num_authors":79,"rel_authors":[{"author_name":"Oliver H. F. Scholle","author_inst":"Leibniz Institute for Prevention Research and Epidemiology (BIPS), Germany"},{"author_name":"Heidi Taipale","author_inst":"University of Eastern Finland; Karolinska Institutet, Sweden; Stockholm City Council, Sweden"},{"author_name":"Michael Dorks","author_inst":"Carl von Ossietzky University Oldenburg, Germany"},{"author_name":"Jannik Ohmes","author_inst":"Carl von Ossietzky University Oldenburg, Germany"},{"author_name":"Lise Aagaard","author_inst":"Department of Law, Faculty of Business and Social Sciences, University of Southern Denmark, Denmark"},{"author_name":"Oleg Aizberg","author_inst":"Belarusian State Medical University, Belarus"},{"author_name":"Salim Al Huseini","author_inst":"Al Masarra Hospital, Ministry of Health, Oman"},{"author_name":"Mohamed A Alnor","author_inst":"The American Center for Psychiatry and Neurology, Abu Dhabi, UAE"},{"author_name":"Stojan Bajraktarov","author_inst":"University Ss Cyril and Methodius, Skopje, North Macedonia"},{"author_name":"Paolo Bertolini","author_inst":"Instituto Psiquiatrico Dr. Jose Horwitz Barak, Chile"},{"author_name":"Robert A Bittner","author_inst":"Goethe University Frankfurt, Germany; Ernst Strungmann Institute, Germany"},{"author_name":"Syed Ali Bokhari","author_inst":"Al Amal Psychiatric Hospital, Emirates Health Services, UAE"},{"author_name":"Alexandra Brazinova","author_inst":"Comenius University, Slovakia"},{"author_name":"Dagmar Breznoscakova","author_inst":"Pavol Jozef Safarik University, Slovakia"},{"author_name":"Kirsten Catthoor","author_inst":"Flemish Association of Psychiatry; ZAS Antwerp; University of Antwerp, Belgium"},{"author_name":"Marko Cavlina","author_inst":"Croatian Institute of Public Health, Croatia"},{"author_name":"Andreja Celofiga","author_inst":"University Medical Centre Maribor, Slovenia"},{"author_name":"Sherry KW Chan","author_inst":"The University of Hong Kong, Hong Kong SAR"},{"author_name":"Robert O. Cotes","author_inst":"Emory University School of Medicine, USA"},{"author_name":"Adomas Danilevicius","author_inst":"National Health Insurance Fund, Lithuania"},{"author_name":"Vlad Dionisie","author_inst":"Carol Davila University of Medicine and Pharmacy, Romania"},{"author_name":"Uwe Eichler","author_inst":"AOK Research Institute (WIdO), Germany"},{"author_name":"Zsofia Engi","author_inst":"University of Szeged, Hungary"},{"author_name":"Rifai Farid","author_inst":"RIPAS Hospital, Brunei Darussalam"},{"author_name":"Matthaus Fellinger","author_inst":"Hietzing Clinic Vienna Healthcare Group; Karl Landsteiner Institute for Mental Health, Austria"},{"author_name":"Kari Furu","author_inst":"Norwegian Institute of Public Health, Norway"},{"author_name":"Ary Gadelha","author_inst":"Universidade Federal de Sao Paulo, Brazil"},{"author_name":"Emily Griner","author_inst":"Emory University School of Medicine, USA"},{"author_name":"Larus S Gudmundsson","author_inst":"University of Iceland"},{"author_name":"Daniel Guinart","author_inst":"Hospital del Mar; Hospital del Mar Research Institute\/CIBERSAM, Spain; Hofstra\/Northwell, USA"},{"author_name":"Katarina Gvozdanovic","author_inst":"Teaching Institute of Public Health Dr. Andrija Stampar, Croatia"},{"author_name":"Yuqi Hu","author_inst":"The University of Hong Kong, Hong Kong SAR"},{"author_name":"Fuad N. Ismayilov","author_inst":"National Mental Health Center, Azerbaijan; Azerbaijan Medical University"},{"author_name":"Jamila Ismayilova","author_inst":"National Mental Health Center, Azerbaijan"},{"author_name":"SungWoo Joo","author_inst":"Asan Medical Center, University of Ulsan College of Medicine, Korea"},{"author_name":"Luuk Kalverdijk","author_inst":"University Medical Center Groningen, Netherlands"},{"author_name":"Mulualem Kelebie","author_inst":"University of Gondar, Ethiopia"},{"author_name":"Yuki Kikuchi","author_inst":"Tohoku University; Kodama Hospital, Japan"},{"author_name":"Nadzeya Kislaya","author_inst":"Republican Scientific and Practical Centre of Mental Health, Belarus"},{"author_name":"Miloslav Kopecek","author_inst":"National Institute of Mental Health; Charles University, Czech Republic"},{"author_name":"Francisco Tsz Tsun Lai","author_inst":"The University of Hong Kong, Hong Kong SAR"},{"author_name":"Hsien-Yuan Lane","author_inst":"China Medical University; China Medical University Hospital; Asia University, Taiwan"},{"author_name":"Jimmy Lee","author_inst":"Institute of Mental Health; Nanyang Technological University, Singapore"},{"author_name":"JungSun Lee","author_inst":"Asan Medical Center, University of Ulsan College of Medicine, Korea"},{"author_name":"Soffy C Lopez","author_inst":"Universidad Tecnologica de Pereira, Audifarma SA, Colombia"},{"author_name":"Jorge Machado Alba","author_inst":"Universidad Tecnologica de Pereira, Audifarma SA, Colombia"},{"author_name":"Raffael Massuda","author_inst":"Universidade Federal do Parana, Brazil"},{"author_name":"Geric Maura","author_inst":"Caisse Nationale de l'Assurance Maladie, France"},{"author_name":"Claude Shaanaell Mawa","author_inst":"Psychiatric Hospital Frombork; LuxMed Poland University of Applied Sciences, Poland"},{"author_name":"Cristian Mena","author_inst":"Instituto Psiquiatrico Dr. Jose Horwitz Barak; Universidad Finis Terrae, Chile"},{"author_name":"Georgios Mikellides","author_inst":"University of Nicosia, Cyprus"},{"author_name":"Hassan Mirza","author_inst":"Sultan Qaboos University Hospital, Oman"},{"author_name":"Philippe Mortier","author_inst":"Hospital del Mar Research Institute; CIBERESP, Spain"},{"author_name":"Peter Niemegeers","author_inst":"Flemish Association of Psychiatry; ZAS Antwerp; University of Antwerp, Belgium"},{"author_name":"Prasad S Nishtala","author_inst":"University of Bath, UK"},{"author_name":"Tina Nulle","author_inst":"State Agency of Medicines of Latvia"},{"author_name":"Uladzimir Pikirenia","author_inst":"Psychiatric Hospital Frombork, Poland"},{"author_name":"Gerald J Pruckner","author_inst":"University of Linz, Austria"},{"author_name":"Maria Gabriela Puiu","author_inst":"Carol Davila University of Medicine and Pharmacy, Romania"},{"author_name":"Julieta Ramirez","author_inst":"Hospital Jose Tiburcio Borda, Argentina"},{"author_name":"Johan Reutfors","author_inst":"Karolinska Institutet, Sweden"},{"author_name":"Ieva Saliete","author_inst":"Riga Stradins University, Latvia"},{"author_name":"Fariza Sani","author_inst":"RIPAS Hospital, Brunei Darussalam"},{"author_name":"Nynke Schuiling-Veninga","author_inst":"University of Groningen, Netherlands"},{"author_name":"Dan J Siskind","author_inst":"University of Queensland; Metro South Addiction and Mental Health Service; Queensland Centre for Mental Health Research, Australia"},{"author_name":"Lina Skiudaite","author_inst":"National Health Insurance Fund, Lithuania"},{"author_name":"Samvel Grant Sukiasyan","author_inst":"Armenian State Pedagogical University, Armenia"},{"author_name":"Charmaine Tang","author_inst":"Institute of Mental Health, Singapore"},{"author_name":"Karine Karlen Tataryan","author_inst":"Yerevan State Medical University, Armenia"},{"author_name":"David Taylor","author_inst":"South London and Maudsley NHS Foundation Trust; King's College London, UK"},{"author_name":"Antonio Teixeira Rodrigues","author_inst":"Cientis, Portugal; University of Minho, Portugal"},{"author_name":"Hiroaki Tomita","author_inst":"Tohoku University, Japan"},{"author_name":"Carla Torre","author_inst":"University of Lisbon; iMed.ULisboa, Portugal"},{"author_name":"Mike Trott","author_inst":"University of Queensland; Metro South Addiction and Mental Health Service; Queensland Centre for Mental Health Research, Australia"},{"author_name":"Fuu-Jen Tsai","author_inst":"China Medical University; China Medical University Hospital; China Medical University Children's Hospital; Asia University, Taiwan"},{"author_name":"Helene Verdoux","author_inst":"Universite Bordeaux, Inserm Bordeaux Population Health Research Center, France"},{"author_name":"Yahya Wehbeh","author_inst":"University of Nicosia Medical School, Cyprus"},{"author_name":"Ebenezer Oloyede","author_inst":"South London and Maudsley NHS Foundation Trust, UK; University of Oxford, UK"},{"author_name":"Christian J Bachmann","author_inst":"Ulm University Medical Center, Germany"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Varenicline as a Repurposable Drug Candidate for ADRD Prevention","rel_doi":"10.64898\/2026.09.17.26363232","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363232","rel_abs":"Objective: Effective strategies to prevent Alzheimer's disease and related dementias (ADRD) are limited. Implementing our Medication-Wide Association Study (MWAS+), we highlighted varenicline as a candidate. This study evaluated the association between varenicline use and risk of ADRD relative to nicotine replacement therapy (NRT). Methods: Using the All of Us Research Database, we identified adults aged 50 years or older with available lifestyle survey responses regarding tobacco use history who initiated smoking cessation therapy with either varenicline or NRT between 2006 and 2023. We limited our cohort to incident monotherapy users and designated the index date as the first prescription. Individuals with baseline ADRD or no follow-up were excluded. Baseline characteristics included demographics, comorbidities, BMI, and prior medication exposures. Outcomes were incident ADRD and a composite outcome of ADRD or death. Findings: The cohort consisted of 9,584 individuals (1,801 varenicline users and 7,783 NRT users). After propensity score matching, there were 1,758 individuals in each group with balanced baseline characteristics. Varenicline use was associated with a reduced risk of ADRD (HR 0.516, 95% CI: 0.353-0.754) and the composite outcome ADRD or death (HR 0.657, 95% CI: 0.501-0.861). Kaplan-Meier curves also demonstrated varenicline's sustained benefits through the study period. Implications: Varenicline use is associated with a lower risk of ADRD among older adults receiving smoking cessation therapy. Further investigation of varenicline as a potential strategy for ADRD prevention is warranted. These findings underscored the value of explainable AI-guided approaches to drug repurposing.","rel_num_authors":19,"rel_authors":[{"author_name":"Phillip Ma","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States"},{"author_name":"Jiaxu Zhou","author_inst":"George Washington University, Washington, DC, United States"},{"author_name":"Yan Cheng","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States"},{"author_name":"John E. McGeary","author_inst":"Providence VA Medical Center, Providence, RI, United States; Brown University, Providence, RI, United States"},{"author_name":"Tracey H Taveira","author_inst":"George Washington University, Washington, DC, United States; Providence VA Medical Center, Providence, RI, United States; Brown University, Providence, RI, Unit"},{"author_name":"Ali Ahmed","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States; Georgetown University, Washington, "},{"author_name":"Wen-Chih Wu","author_inst":"Providence VA Medical Center, Providence, RI, United States; Brown University, Providence, RI, United States"},{"author_name":"Edward Zamrini","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States; Irvine Clinical Research, Irvine, C"},{"author_name":"Brittany N. Dugger","author_inst":"Department of Pathology and Laboratory Medicine, School of Medicine, University of California, Sacramento, USA"},{"author_name":"Louise Nicole C. Sevilla","author_inst":"Department of Pathology and Laboratory Medicine, School of Medicine, University of California, Sacramento, USA"},{"author_name":"Joel Anthony Nations","author_inst":"Department of Medicine, Uniformed Services University of Health Sciences, Bethesda, USA"},{"author_name":"Yijun Shao","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States"},{"author_name":"Ying Yin","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States"},{"author_name":"Debby W. Tsuang","author_inst":"VA Puget Sound Health Care System, Seattle, WA, United States; University of Washington, Seattle, WA, United States"},{"author_name":"Mark W Logue","author_inst":"National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System; Department of Psychiatry and Medicine, Boston University Chobanian & Avedis"},{"author_name":"Siamack Ayandeh","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; University of Utah, Salt Lake City, UT, United States"},{"author_name":"Charles Faselis","author_inst":"VA Palo Alto health care, United States"},{"author_name":"Stuart J. Nelson","author_inst":"George Washington University, Washington, DC, United States"},{"author_name":"Qing Zeng-Treitler","author_inst":"Washington DC VA Medical Center, Washington, DC, United States; George Washington University, Washington, DC, United States"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Clofazimine pharmacokinetics in novel rifampicin-resistant tuberculosis regimens: an analysis of the endTB and endTB-Q trials","rel_doi":"10.64898\/2026.09.18.26363422","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.18.26363422","rel_abs":"Introduction Rifampicin-resistant tuberculosis poses a significant threat worldwide. Clofazimine is considered important for the construction of effective individualized multidrug regimens to treat rifampicin-resistant tuberculosis. Our goal was to characterize clofazimine pharmacokinetics in novel combination treatment regimens and to identify participant characteristics associated with variations in drug exposure. Methods Clofazimine pharmacokinetic data were obtained from adults and adolescents enrolled in the PandrTB pharmacokinetic sub-study of the endTB and endTB-Q Phase 3 randomized controlled therapeutic trials for rifampicin-resistant tuberculosis. Plasma concentrations were analyzed using nonlinear mixed-effects modeling to quantify clofazimine exposure and explore the impact of relevant covariates. Results 100 participants from six countries with high burdens of rifampicin-resistant tuberculosis contributed pharmacokinetic data. Their median age was 34 years, 32% were female, 18% were living with diabetes mellitus, and 18% were living with HIV. Clofazimine plasma concentration values were best described by a 2-compartment pharmacokinetic model with first-order absorption. Co-administration with delamanid and HIV co-infection resulted in a 37% increase and 20% decrease in clofazimine bioavailability, respectively. Diabetes was associated with a 43% decrease in clofazimine clearance. Clofazimine remained in the body for a median of 2.5 years (95th percentile: 0.5 to 8) following 9 months of treatment. Conclusion Co-administration with delamanid, diabetes mellitus, and HIV were associated with variation in clofazimine exposure. We estimated that clofazimine remained present in the body for longer than two years in over half of participants following 9 months of treatment. Follow-up studies are recommended to confirm these associations before adjusting clofazimine dose or clinical care decisions.","rel_num_authors":34,"rel_authors":[{"author_name":"Bernard Ngara","author_inst":"University of California San Francisco"},{"author_name":"Belen P.Solans","author_inst":"University of California San Francisco"},{"author_name":"Eunsol Yang","author_inst":"University of California San Francisco"},{"author_name":"Pieter Van Brantegem","author_inst":"University of California, San Francisco"},{"author_name":"Lorenzo Guglielmetti","author_inst":"IRCCS Sacro Cuore Don Calabria Hospital"},{"author_name":"Francis Varaine","author_inst":"Medecins Sans Frontieres, 34 Avenue Jean Jaures, 75019 Paris, France"},{"author_name":"Maelenn Gouillou","author_inst":"Epicentre"},{"author_name":"Carole  D. Mitnick","author_inst":"Brigham and Women's Hospital"},{"author_name":"Allison N. LaHood","author_inst":"Harvard Medical School Department of Global Health & Social Medicine"},{"author_name":"Michael  L. Rich","author_inst":"Harvard Medical School"},{"author_name":"Kwonjune J Seung","author_inst":"Brigham and Women's Hospital"},{"author_name":"Lubbe Wiesner","author_inst":"University of Cape Town"},{"author_name":"Loren Hans","author_inst":"University of the Western Cape Department of Dietetics and Nutrition"},{"author_name":"Rina Swart","author_inst":"University of the Western Cape"},{"author_name":"Amanzhan Abubakirov","author_inst":"Partners In Health"},{"author_name":"Kanat Khazhidinov","author_inst":"Partners In Health"},{"author_name":"Anel Belgozhanova","author_inst":"Partners In Healthm"},{"author_name":"Stephane Mpinda","author_inst":"Partners In Health"},{"author_name":"Sesomo Mohale","author_inst":"Partners In Health, , Lesotho."},{"author_name":"David Holtzman","author_inst":"Bill & Melinda Gates Medical Research Institute"},{"author_name":"Dante Vargas Vasquez","author_inst":"Hospital Nacional Hipolito Unanue"},{"author_name":"Fanny Garcia Velarde","author_inst":"Socios En Salud Sucursal Peru"},{"author_name":"Sergio Mucching Toscano","author_inst":"Socios En Salud Sucursal Peru"},{"author_name":"Annum Aftab","author_inst":"Interactive Research and Development"},{"author_name":"Mahnoor S. Arshad","author_inst":"Interactive Research and Development"},{"author_name":"Azka Ashraf","author_inst":"Indus Hospital and Health Network"},{"author_name":"Dinh Van Luong","author_inst":"National Lung Hospital"},{"author_name":"Hanh T Nguyen","author_inst":"Hanoi Lung Hospital"},{"author_name":"Ha TT. Phan","author_inst":"Center for Promotion of Advancement of Society,"},{"author_name":"Sean Wasserman","author_inst":"University of Cape Town"},{"author_name":"Nelisiwe Ntuli","author_inst":"Medecins Sans Frontieres Khayelitsha"},{"author_name":"Rada Savic","author_inst":"UCSF"},{"author_name":"Helen McIlleron","author_inst":"University of Cape Town"},{"author_name":"Gustavo E Velasquez","author_inst":"University of California, San Francisco"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Genetically Predicted Blood DNA Methylation Reveals Putative Regulatory Signals Associated with ALS Risk","rel_doi":"10.64898\/2026.09.17.26363319","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363319","rel_abs":"Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder whose genetic architecture and underlying molecular mechanisms remain incompletely understood, particularly in sporadic disease. To investigate whether genetically regulated DNA methylation may help interpret ALS susceptibility, we conducted a methylome-wide association study (MWAS) of genetically predicted blood DNA methylation using the PrediXcan framework. CpG-specific prediction models developed in the ARIES and Understanding Society cohorts were applied to ALS genome-wide association study (GWAS) summary statistics from 27,205 cases and 110,881 controls of European ancestry. In total, genetically predicted methylation at 192,378 unique CpG sites was evaluated using S-PrediXcan. At a nominal threshold of p < 0.05, 3,741 CpGs were associated with ALS risk using ARIES models and 13,127 using Understanding Society models. After Bonferroni correction, 25 CpGs across eight genomic regions remained significantly associated with ALS risk. These included signals near established ALS and ALS-frontotemporal dementia genes and loci, including C9orf72, TBK1, SCFD1, and MOB3B, as well as three CpGs mapping to WHAMM at 15q25.2, a region not previously implicated in ALS by GWAS. Predicted methylation was positively associated with ALS risk at 18 CpGs and inversely associated at seven. Complementary transcriptome-wide association analyses using GTEx v8 whole-blood gene-expression prediction models identified 11 genes associated with ALS risk after Bonferroni correction, including convergent methylation and expression signals at C9orf72. These findings add a regulatory dimension to ALS genetic studies by prioritizing CpG sites, genes, and genomic regions through which inherited variation may influence disease susceptibility. PrediXcan-based MWAS therefore provides a complementary strategy for refining genetic association signals into biologically testable candidates and identifying regulatory mechanisms for further functional investigation.","rel_num_authors":4,"rel_authors":[{"author_name":"Tianying Zhao","author_inst":"Vanderbilt University"},{"author_name":"Mariah Marie Hoffman","author_inst":"Vanderbilt Health"},{"author_name":"Gang Wu","author_inst":"St. Jude Childrens Research Hospital"},{"author_name":"Veronique Valerie Belzil","author_inst":"Vanderbilt Health"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"A longitudinal study of age-related traits and cognitive function: The Collaborative Amish Aging and Memory Project (CAAMP)","rel_doi":"10.64898\/2026.09.17.26363351","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363351","rel_abs":"INTRODUCTION: The Collaborative Amish Aging and Memory Project (CAAMP) is an ongoing longitudinal study spanning multiple sites, focused on cognitive function and age-related traits in Midwestern Amish (Ohio and Indiana) communities. The primary traits of interest include Alzheimer Disease and related dementias (ADRD), successful aging (SA), and other age-related conditions. METHODS: CAAMP integrates clinical and cognitive assessments with family history, genealogical, genomic, biospecimen, and biomarker data collected across Amish communities in Ohio and Indiana. Cognitive diagnoses are assigned through consensus adjudication using clinical, cognitive, functional, and informant data. RESULTS: To date, CAAMP has enrolled 3,978 participants (mean age 78.6 (SD = 7.9), 59.1% female, and 83% with an education level at the eighth grade), of whom 2,928 have consensus-adjudicated cognitive status. At the most recent assessment, 66.6% were cognitively unimpaired, 9.9% had mild cognitive impairment, 8.9% had Alzheimer disease, and 4.5% had cognitive impairment, but not Alzheimer disease. The remaining 1,050 did not have detailed cognitive evaluations at their enrollment. Longitudinal cognitive assessments and multiple biospecimen sample types are available for subsets of participants. CAAMP further includes extensive multigenerational pedigree information, genome-wide genotype and whole-genome sequencing data, and plasma biomarker measurements. DISCUSSION: CAAMP illuminates the genetic underpinnings of cognition and late life diseases, particularly Alzheimer Disease, by leveraging the special characteristics of a founder population. Continued study of this prospective cohort provides opportunities to identify the genetic and biological factors driving cognitive outcomes alongside other age-related conditions, advancing our understanding of both disease risk and protection.","rel_num_authors":25,"rel_authors":[{"author_name":"Dana Z Jian","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Renee A Laux","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Yeunjoo E Song","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Audrey Lynn","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Kristy Miskimen","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Alex Gulyayev","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Sarada L Fuzzell","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Sherri D Hochstetler","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Dawn Miller","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Penelope Miron","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Laura J Caywood","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Jason E Clouse","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Sharlene D Herington","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Michael B Prough","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Larry D Adams","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Yining Liu","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Noel C Moore","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Daniel A Dorfsman","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Paula Ogrocki","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Alan J Lerner","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Jeffery M Vance","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Michael L Cuccaro","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Margaret A Pericak-Vance","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"William K Scott","author_inst":"University of Miami Miller School of Medicine"},{"author_name":"Jonathan L Haines","author_inst":"Case Western Reserve University School of Medicine"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Use of Renal Duplex To Detect Renal Artery Stenosis in Fibromuscular Dysplasia","rel_doi":"10.64898\/2026.09.16.26363272","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.16.26363272","rel_abs":"Introduction: Duplex ultrasonography is widely used to evaluate renal artery stenosis (RAS), but diagnostic criteria are largely derived from atherosclerotic RAS and may not apply to fibromuscular dysplasia (FMD). We evaluated associations between renal duplex parameters and hemodynamically significant RAS in patients with FMD. Methods: Patients with renal FMD who underwent renal duplex followed by renal artery angiography within 3 months were included. Duplex parameters were compared between arteries with and without RAS (Pd\/Pa<0.9, fractional flow reserve (FFR)<0.8, systolic pressure gradient >20 mm Hg, or %stenosis >70%). Receiver operating characteristic (ROC) analysis was used to evaluate diagnostic performance. Changes following angioplasty were compared. Results: 55 renal arteries from 33 patients with renal FMD were included. Peak systolic velocity (PSV), end diastolic velocity (EDV), and acceleration time (AT) were higher in arteries with RAS. Resistive index (RI) was lower in RAS. Renal aortic ratio (RAR) did not differ between groups. PSV demonstrated good discrimination with a cut-off of 275 cm\/sec yielding 79% sensitivity, 78% specificity, and an area under the curve (AUC) of 0.81. Incorporating additional parameters did not improve performance compared with PSV alone. Following angioplasty, PSV, EDV, and AT decreased, RI increased, RAR remained unchanged. Conclusion: In renal FMD, duplex ultrasound parameters, particularly PSV and RI, are associated with hemodynamically significant RAS. However, overlap in PSV between arteries with and without RAS suggests that PSV alone may not reliably determine lesion significance. These findings support duplex ultrasonography for evaluating renal FMD while highlighting the need for FMD-specific diagnostic criteria.?","rel_num_authors":11,"rel_authors":[{"author_name":"Fahad Alkhalfan","author_inst":"Cleveland Clinic"},{"author_name":"Meghann McCarthy","author_inst":"Cleveland Clinic"},{"author_name":"Alliefair Scalise","author_inst":"Cleveland Clinic Lerner College of Medicine of Case Western Reserve University"},{"author_name":"Hannah Abroe","author_inst":"Cleveland Clinic"},{"author_name":"Anu Aggarwal","author_inst":"Cleveland Clinic"},{"author_name":"Huijun Park","author_inst":"Cleveland Clinic"},{"author_name":"Pulkit Chaudhury","author_inst":"Cleveland Clinic"},{"author_name":"Scott J Cameron","author_inst":"Cleveland Clinic Foundation"},{"author_name":"Deborah Hornacek","author_inst":"Cleveland Clinic"},{"author_name":"Christopher T. Bajzer","author_inst":"The Cleveland Clinic Foundation"},{"author_name":"Natalia Fendrikova-Mahlay","author_inst":"Cleveland Clinic Tomsich Family Department of Cardiovascular Medicine"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Matters of the Heart and Soul: The Mixed Impact of Religiosity and Spirituality on the Cardiovascular Risk Profile Over Time","rel_doi":"10.64898\/2026.09.14.26362903","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.14.26362903","rel_abs":"Aims: Religiosity and spirituality (R\/S) are generally associated with a more favourable cardiovascular risk profile, but longitudinal evidence is limited. We examined whether multidimensional R\/S predicts its future behavioural and biological components. Methods: This prospective cohort study analysed 6,844 adults aged [&ge;]50 (56% women; mean R\/S score 2.1; 20% weekly attenders; 81% Christian) from waves 4-7 of the English Longitudinal Study of Ageing (ELSA). Behavioural outcomes included smoking, exercise, alcohol intake, and fruit and vegetable consumption; biological outcomes included blood pressure (BP), haemoglobin A1c (HbA1c), and the inflammatory risk markers C-reactive protein (CRP) and fibrinogen. R\/S was assessed with four items from the Santa Clara Strength of Religious Faith Questionnaire. Hierarchical linear and logistic regressions adjusted for age, sex, wealth, education and ethnicity; biomarker models also adjusted for health behaviours and body mass index. Results: Greater spirituality (B=-0.019; 95%CI[-0.036,-0.003]), daily prayer\/meditation (B=-0.017; 95%CI[-0.032,-0.002]), participation in organized religion (B=-0.017; 95%CI[-0.032,-0.002]), and importance of religious faith (B=-0.017; 95%CI[-0.033,-0.002]) were independently associated with lower fibrinogen levels. Daily prayer\/meditation also independently predicted higher fruit and vegetable intake (B=0.004; 95%CI[0.000,0.008]). However, frequent attendance (OR=0.846; 95%CI[0.730,0.982]), the significance of faith (OR=0.935; 95%CI[0.879,0.994]), and religious purpose (OR=0.939; 95%CI[0.884,0.997]) independently reduced the odds of meeting exercise recommendations. Similarly, frequent attendance was associated with higher HbA1c (B=0.002; 95%CI[0.000,0.005]). There were no independent associations with CRP or blood pressure. Conclusion: R\/S showed mixed prospective associations with the cardiovascular risk profile: favourable for fibrinogen and fruit and vegetable intake, unfavourable for physical activity and HbA1c.","rel_num_authors":5,"rel_authors":[{"author_name":"Vinicius Vieira Neves","author_inst":"Brown University"},{"author_name":"Cesar de Oliveira","author_inst":"University College London"},{"author_name":"LaPrincess C Brewer","author_inst":"Mayo Clinic College of Medicine"},{"author_name":"Ione Jayce Ceola Schneider","author_inst":"Federal University of Santa Catarina"},{"author_name":"Andrew Steptoe","author_inst":"University College London"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"Heritability and rare variant contributions to Alzheimer disease in the Midwestern Amish","rel_doi":"10.64898\/2026.09.17.26363309","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.17.26363309","rel_abs":"Background The genetic architecture of Alzheimer disease remains incompletely understood. Founder populations such as the Amish offer a unique opportunity to identify additional genetic variation influencing the disease. Method Using extensive pedigree and genomic data from Midwestern Amish communities, we estimated both pedigree- and SNP- based heritability of AD. In addition, genome-wide association studies and gene-based rare variant tests were performed. Results Heritability estimates suggested that common variants explain much of genetic risk among APOE-{varepsilon}4 carriers, while unexplained heritability remains in non-carriers in the Amish. GWAS confirmed APOE-{varepsilon}4 as the strongest genetic determinant of AD in the Amish. Rare variant analyses identified RIN3 and PILRA as significantly associated with risk of cognitive impairment; suggestive signals including CYP24A1 were also identified. Discussion These findings highlight the contributions of common and rare variants to Alzheimer disease and suggest factors beyond common variants may contribute to disease susceptibility particularly among the APOE-{varepsilon}4 non-carriers.","rel_num_authors":30,"rel_authors":[{"author_name":"Yining Liu","author_inst":"Case Western Reserve University"},{"author_name":"Yeunjoo E. Song","author_inst":"Case Western Reserve University"},{"author_name":"Weihuan Wang","author_inst":"Case Western Reserve University"},{"author_name":"Audrey Lynn","author_inst":"Case Western Reserve University"},{"author_name":"Kristy Miskimen","author_inst":"Case Western Reserve University"},{"author_name":"Sarada L. Fuzzell","author_inst":"Case Western Reserve University"},{"author_name":"Sherri D. Hochstetler","author_inst":"Case Western Reserve University"},{"author_name":"Renee A. Laux","author_inst":"Case Western Reserve University"},{"author_name":"Dawn Miller","author_inst":"Case Western Reserve University"},{"author_name":"Penelope Miron","author_inst":"Case Western Reserve University"},{"author_name":"Laura J. Caywood","author_inst":"University of Miami"},{"author_name":"Jason E. Clouse","author_inst":"University of Miami"},{"author_name":"Sharlene D. Herinton","author_inst":"University of Miami"},{"author_name":"Ping Wang","author_inst":"Case Western Reserve University"},{"author_name":"Alex Gulyayev","author_inst":"University of Miami"},{"author_name":"Daniel A. Dorfsman","author_inst":"University of Miami"},{"author_name":"Noel C. Moore","author_inst":"Case Western Reserve University"},{"author_name":"Dana Z. Jian","author_inst":"Case Western Reserve University"},{"author_name":"Leighanne R. Main","author_inst":"Case Western Reserve University"},{"author_name":"Michael B. Prough","author_inst":"University of Miami"},{"author_name":"Andrew F. Zaman","author_inst":"University of Miami"},{"author_name":"Larry D. Adams","author_inst":"University of Miami"},{"author_name":"Patrice Whitehead","author_inst":"University of Miami"},{"author_name":"Paula Ogrocki","author_inst":"Case Western Reserve University"},{"author_name":"Alan J. Lerner","author_inst":"Case Western Reserve University"},{"author_name":"Jeffery M. Vance","author_inst":"University of Miami"},{"author_name":"Michael L. Cuccaro","author_inst":"University of Miami"},{"author_name":"William K. Scott","author_inst":"University of Miami"},{"author_name":"Margaret A. Pericak-Vance","author_inst":"University of Miami"},{"author_name":"Jonathan L. Haines","author_inst":"Case Western Reserve University"}],"rel_date":"2026-09-20","rel_site":"medrxiv"},{"rel_title":"SMORE: joint dimension reduction and cell population discovery on single-cell methylome data","rel_doi":"10.64898\/2026.09.14.751514","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751514","rel_abs":"Single-cell DNA methylation profiling technology captures novel epigenetic data modality but are challenging to analyze because of their heterogeneity, high dimensionality, and ultra-sparsity. Here we present SMORE (Single-cell MethylOme Reduction and Embedding), a computational method for joint dimensionality reduction and cell population discovery dedicated to single-cell DNA methylation data. SMORE operates on a Bayesian framework that converts methylation proportions into ordered methylation states and jointly infers a low-dimensional representation, cell populations and their number. By using low-rank latent Gaussian factorization and adopting a mixture-of-finite-mixtures prior on latent cell scores, SMORE infers cell assignments without requiring a prespecified cluster number, and propagates uncertainty from methylation measurements to cell assignments. Across simulations spanning varying sample sizes, population imbalance, signal strengths and model misspecification, SMORE accurately recovered latent population structure and outperformed existing methods. Applied to human single-cell methylation datasets from lung, peripheral blood and primary motor cortex, SMORE recovered biologically supported cell population structures. SMORE provides an uncertainty-aware framework for dimension reduction and population discovery for single-cell methylomes.","rel_num_authors":5,"rel_authors":[{"author_name":"Jingwen Deng","author_inst":"The University of Texas Health Science Center at Houston"},{"author_name":"Zixi Wang","author_inst":"The University of Texas Health Science Center at Houston"},{"author_name":"Wen Tang","author_inst":"The University of Texas Health Science Center at Houston"},{"author_name":"Guanyu Hu","author_inst":"Michigan State University"},{"author_name":"Hao Feng","author_inst":"The University of Texas Health Science Center at Houston"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Language-Model-Based Detection of Genetic Editing in Bacteria","rel_doi":"10.64898\/2026.09.17.751846","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.751846","rel_abs":"Recent advances in genome editing allow easy genetic manipulation of bacteria, providing them with new traits, some of which could be hazardous, e.g. enhanced virulence or extended resistance to antibiotics. The ability to detect artificially modified bacteria is crucial for identifying potential bio-threats. However, malicious genome editing could be challenging to trace due to the natural exchange of genes among bacteria through horizontal transfer. After curating extensive datasets including natural genomes and simulated edited genomes, we utilized a natural language processing approach to detect edited genomes. We developed a transformer-encoder-based machine-learning classifier that, instead of analyzing words in sentences, models gene families in genomes. After training the model on our datasets, it is able to accurately detect genes artificially added to bacterial genomes due to their unnatural context. Our approach provides a scalable method for identifying engineered sequences without relying on specific marker genes, with potential applications in biosecurity, agriculture, GMO regulation and more.","rel_num_authors":2,"rel_authors":[{"author_name":"Edan Gabay","author_inst":"Tel Aviv University"},{"author_name":"David Burstein","author_inst":"Tel Aviv University"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"A multivalent docking platform and Rcn1-mediated inhibition control the extent of calcineurin recruitment to the cell division site for the dephosphorylation of multiple cytokinetic proteins","rel_doi":"10.64898\/2026.09.14.751435","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751435","rel_abs":"Cytokinesis requires coordinated signaling to ensure the accurate physical separation of daughter cells. Calcineurin (CN), a conserved Ca2+\/calmodulin-dependent phosphatase, is required for cytokinesis in organisms ranging from yeast to humans, yet how CN is regulated at the division site and the substrates through which it promotes cell division remain poorly understood. Here we use the fission yeast Schizosaccharomyces pombe, which display striking cell division defects in the absence of CN, to define how CN is anchored at the cell division site. We show that CN recruitment to the cytokinetic ring (CR) requires its PxIxIT- and LxVP-binding surfaces and is mediated by multivalent interactions with the CR components paxillin-like Pxl1 and the F-BAR protein Cdc15. Disrupting these interactions nearly eliminates CN from the CR and causes gross cytokinetic defects similar to complete loss of CN function. Cell cycle stage-specific quantitative phosphoproteomics combined with proximity labeling-based proteomics were used to identify candidate CN substrates involved in cytokinesis. Validation of a cohort of these proteins localizing to the CR, including the F-BAR protein Rga7, the actin regulator Aim21 and three protein kinases, revealed that CN targets a broad network of structural and signaling components involved in cell division. We also identify the conserved CN inhibitor Rcn1 as a CN substrate and show that Rcn1 restricts CN accumulation at the CR to provide an additional layer of spatial regulation. Thus, spatial control of CN enables proper protein dephosphorylation for successful cytokinesis.","rel_num_authors":8,"rel_authors":[{"author_name":"Alaina  H. Willet","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Jun-Song Chen","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Qing Yu","author_inst":"University of Massachusetts Chan Medical School"},{"author_name":"Chloe  E. Snider","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Liping Ren","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Rahul Bhattacharjee","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Steven  P. Gygi","author_inst":"Harvard Medical School"},{"author_name":"Kathleen  L Gould","author_inst":"Vanderbilt University School of Medicine"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"A multivalent docking platform and Rcn1-mediated inhibition control the extent of calcineurin recruitment to the cell division site for the dephosphorylation of multiple cytokinetic proteins","rel_doi":"10.64898\/2026.09.14.751435","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.751435","rel_abs":"Cytokinesis requires coordinated signaling to ensure the accurate physical separation of daughter cells. Calcineurin (CN), a conserved Ca2+\/calmodulin-dependent phosphatase, is required for cytokinesis in organisms ranging from yeast to humans, yet how CN is regulated at the division site and the substrates through which it promotes cell division remain poorly understood. Here we use the fission yeast Schizosaccharomyces pombe, which display striking cell division defects in the absence of CN, to define how CN is anchored at the cell division site. We show that CN recruitment to the cytokinetic ring (CR) requires its PxIxIT- and LxVP-binding surfaces and is mediated by multivalent interactions with the CR components paxillin-like Pxl1 and the F-BAR protein Cdc15. Disrupting these interactions nearly eliminates CN from the CR and causes gross cytokinetic defects similar to complete loss of CN function. Cell cycle stage-specific quantitative phosphoproteomics combined with proximity labeling-based proteomics were used to identify candidate CN substrates involved in cytokinesis. Validation of a cohort of these proteins localizing to the CR, including the F-BAR protein Rga7, the actin regulator Aim21 and three protein kinases, revealed that CN targets a broad network of structural and signaling components involved in cell division. We also identify the conserved CN inhibitor Rcn1 as a CN substrate and show that Rcn1 restricts CN accumulation at the CR to provide an additional layer of spatial regulation. Thus, spatial control of CN enables proper protein dephosphorylation for successful cytokinesis.","rel_num_authors":8,"rel_authors":[{"author_name":"Alaina  H. Willet","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Jun-Song Chen","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Qing Yu","author_inst":"University of Massachusetts Chan Medical School"},{"author_name":"Chloe  E. Snider","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Liping Ren","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Rahul Bhattacharjee","author_inst":"Vanderbilt University School of Medicine"},{"author_name":"Steven  P. Gygi","author_inst":"Harvard Medical School"},{"author_name":"Kathleen  L Gould","author_inst":"Vanderbilt University School of Medicine"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Inflammasome Activation and IL-1\u03b2 Release in Alveolar Macrophages Infected with Pseudomonas aeruginosa is Reduced in Hypoxia","rel_doi":"10.64898\/2026.09.14.750667","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.14.750667","rel_abs":"Pseudomonas aeruginosa is an important agent of acute or chronic airway infections. A complex set of genetic and environmental factors determine the outcome of a P. aeruginosa airway infection. P. aeruginosa can undergo genetic adaptation to fine tune the expression of a type III secretion system (T3SS) and other virulence factors in response to selective pressures encountered during infection. Genetic and environmental factors predispose many patient groups for P. aeruginosa infections, including people with cystic fibrosis (pwCF). CF is a genetic disorder resulting in areas of hypoxia and thick mucus that fosters P. aeruginosa airway infection. Resident alveolar macrophages (AMs) help coordinate immune responses to P. aeruginosa in airways by producing proinflammatory cytokines such as IL-1{beta}, which can be important for infection resistance. AMs infected with laboratory strains of P. aeruginosa detect the T3SS and activate the NLRC4 inflammasome, resulting in IL-1{beta} release. Studies of inflammasome responses in AMs to a clinical CF isolate of P. aeruginosa have not been reported. Here, we characterized the CF clinical isolate DH1137 and found that it has a downregulated but functional T3SS, is adapted to grow in hypoxia, and induces significant production of the inflammasome cytokines IL-1{beta} and IL-1 during lung infection in a CF mouse model. Inflammasome gene expression was primed in AMs by LPS stimulation, and upon DH1137 infection these cells released IL-1[beta]. Intriguingly, we found that infection of AMs with DH1137 in hypoxia resulted in significantly dampened inflammasome activation compared to normoxia. These data describe a new mechanism that P. aeruginosa may exploit to evade immune detection by tissue-resident lung macrophages in the context of CF.","rel_num_authors":14,"rel_authors":[{"author_name":"Alexander Rapp","author_inst":"Dartmouth"},{"author_name":"Aurora Golden","author_inst":"Dartmouth"},{"author_name":"Arianna Reuven","author_inst":"Dartmouth"},{"author_name":"Jay Goddard","author_inst":"Dartmouth"},{"author_name":"Emily McClure","author_inst":"Dartmouth"},{"author_name":"Aimee Wilson","author_inst":"Dartmouth"},{"author_name":"Chloe Young","author_inst":"Dartmouth"},{"author_name":"Caitlin Murphy","author_inst":"Dartmouth"},{"author_name":"Taalia-Lindsay Morgan","author_inst":"Dartmouth"},{"author_name":"Andrew Olive","author_inst":"Michigan State University"},{"author_name":"Deborah Hogan","author_inst":"Dartmouth"},{"author_name":"Joshua J. Obar","author_inst":"Geisel School of Medicine at Dartmouth"},{"author_name":"Benjamin D Ross","author_inst":"Dartmouth"},{"author_name":"James B. Bliska","author_inst":"Geisel School of Medicine"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Loss of TDP-43 function drives cryptic circular RNAs in neurodegenerative diseases","rel_doi":"10.64898\/2026.09.17.752169","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.752169","rel_abs":"TAR DNA-binding protein 43 (TDP-43) is a key pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) and a critical regulator of RNA splicing. While loss of TDP-43 induces aberrant splicing in linear transcripts, its impact on circular RNA (circRNA) biogenesis remains unexplored. Here, we show that TDP-43 depletion in human neurons induces widespread circRNA changes, especially upregulation of a distinct class of cryptic circRNAs that arise specifically upon loss of TDP-43. Some of these cryptic circRNAs incorporate cryptic exons derived from intronic sequences. Notably, these cryptic circRNAs exhibit greater stability than their corresponding linear RNA isoforms and accumulate progressively in neurons. Moreover, cryptic circRNAs are elevated in postmortem brain tissues from ALS, FTD and Alzheimer's disease (AD) patients. These findings reveal a previously unrecognized role for TDP-43 in repressing cryptic circRNA formation and establish these circRNAs as stable molecular signatures of TDP-43 dysfunction.","rel_num_authors":13,"rel_authors":[{"author_name":"Chengzhang Zhu","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Zhiyan Zhao","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Bojun Song","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Yan-Ming Chen","author_inst":"University of Chicago"},{"author_name":"Yu Xiao","author_inst":"University of Chicago"},{"author_name":"Zhe Zhang","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Yingzhi Ye","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Niannian Xu","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Ruijia Zhang","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Yongxin Huang","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Juan C. Troncoso","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Chuan He","author_inst":"University of Chicago"},{"author_name":"Shuying Sun","author_inst":"Johns Hopkins University School of Medicine"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Loss of TDP-43 function drives cryptic circular RNAs in neurodegenerative diseases","rel_doi":"10.64898\/2026.09.17.752169","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.752169","rel_abs":"TAR DNA-binding protein 43 (TDP-43) is a key pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) and a critical regulator of RNA splicing. While loss of TDP-43 induces aberrant splicing in linear transcripts, its impact on circular RNA (circRNA) biogenesis remains unexplored. Here, we show that TDP-43 depletion in human neurons induces widespread circRNA changes, especially upregulation of a distinct class of cryptic circRNAs that arise specifically upon loss of TDP-43. Some of these cryptic circRNAs incorporate cryptic exons derived from intronic sequences. Notably, these cryptic circRNAs exhibit greater stability than their corresponding linear RNA isoforms and accumulate progressively in neurons. Moreover, cryptic circRNAs are elevated in postmortem brain tissues from ALS, FTD and Alzheimer's disease (AD) patients. These findings reveal a previously unrecognized role for TDP-43 in repressing cryptic circRNA formation and establish these circRNAs as stable molecular signatures of TDP-43 dysfunction.","rel_num_authors":13,"rel_authors":[{"author_name":"Chengzhang Zhu","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Zhiyan Zhao","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Bojun Song","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Yan-Ming Chen","author_inst":"University of Chicago"},{"author_name":"Yu Xiao","author_inst":"University of Chicago"},{"author_name":"Zhe Zhang","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Yingzhi Ye","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Niannian Xu","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Ruijia Zhang","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Yongxin Huang","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Juan C. Troncoso","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Chuan He","author_inst":"University of Chicago"},{"author_name":"Shuying Sun","author_inst":"Johns Hopkins University School of Medicine"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Variation in multiple classes of simple sequence repeats can alter drug susceptibility in Mycobacterium tuberculosis","rel_doi":"10.64898\/2026.09.16.752248","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.16.752248","rel_abs":"Insertions and deletions (INDELs) in simple sequence repeats (SSRs) generate relatively high-frequency reversible genetic changes that facilitate bacterial adaptation to changing environments. Analyses of global Mycobacterium tuberculosis (Mtb) isolates indicate that many SSRs are under diversifying selection, and several of the resulting INDELs in homopolymer tracts (HTs) can increase the pathogen's fitness during exposure to host and antibiotic stresses. However, the functional impact of most variable SSRs, particularly those within more complex repeat sequences than HT, remains unclear.  Here, we combine phylogenomic analysis of clinical Mtb strains from Vietnam and Peru with in vitro experimental validation of engineered strains to identify SSR INDELs that alter antibiotic susceptibility. Our findings demonstrate that INDELs across multiple SSRs of differing repeat composition are highly variable and correlate with clinical antibiotic resistance. These variants included frameshifting HT INDELs in ppe13, glpK, Rv2081c, and ppsA, and in-frame trinucleotide (triplet) SSR INDELS in ponA1, ppe53, and ppe59 that produce much more subtle changes in protein structure. Reconstruction of these INDELs in an isogenic background identified four variants that directly reduce drug potency, including a triplet SSR deletion in ppe53 that conferred intermediate resistance to isoniazid, rifampicin, and streptomycin. The clinically prevalent ppe53 CGCdel mutation shortens a polyalanine stretch adjacent to the conserved WxG domain and impairs the processing and secretion of the full-length protein. Overall, our work provides additional evidence of selective pressure across Mtb SSRs and demonstrates the significance of in-frame INDELs within triplet SSRs, highlighting their contribution to the evolution of antibiotic resistance.","rel_num_authors":8,"rel_authors":[{"author_name":"Peter  O. Oluoch","author_inst":"University of Massachusetts Medical School Department of Physiology: University of Massachusetts Chan Medical School Department of Microbiology and Physiologica"},{"author_name":"Michael  J Luna","author_inst":"University of Massachusetts Medical School Department of Physiology: University of Massachusetts Chan Medical School Department of Microbiology and Physiologica"},{"author_name":"Gavin Fujimori","author_inst":"University of Massachusetts Medical School Department of Molecular Genetics and Microbiology: University of Massachusetts Chan Medical School Department of Micr"},{"author_name":"Mayashree Das","author_inst":"University of Massachusetts Medical School Department of Physiology: University of Massachusetts Chan Medical School Department of Microbiology and Physiologica"},{"author_name":"Roger Vargas Jr.","author_inst":"Harvard Medical School"},{"author_name":"Kadamba  G Papavinasasundaram","author_inst":"University of Massachusetts Medical School Department of Molecular Genetics and Microbiology: University of Massachusetts Chan Medical School Department of Micr"},{"author_name":"Maha  R. Farhat","author_inst":"Harvard Medical School"},{"author_name":"Christopher  M. Sassetti","author_inst":"University of Massachusetts Medical School"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"E3 ubiquitin ligase SYVN1 mediates K63-linked ubiquitination of DDX3X to activate Macrophage NLRP3 Inflammasome","rel_doi":"10.64898\/2026.09.15.751797","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.15.751797","rel_abs":"DDX3X (DEAD box helicase 3, X linked) is a common and essential component for both stress granules and NLRP3 inflammasome assembly and their activation; however, the upstream cellular stress signals driving DDX3X to activate the contrasting cellular pathway remain unclear. We identified the pivotal role of the E3 ubiquitin ligase SYVN1(Synoviolin) as the upstream regulator of DDX3X and thereby controlling NLRP3 activation and stress granule assembly. We observed SYVN1 silencing in macrophages prevented both NLRP3 driven inflammation and stress granule formation. SYVN1 deficiency prevented LPS induced inflammatory lung injury and increased the survival rate of the mice. SYVN1 sustains DDX3X gene expression and promotes stimulus-dependent ubiquitination of DDX3X. Under inflammatory conditions, SYVN1 mediated 63 linked ubiquitination of DDX3X, a requirement for NLRP3 inflammasome activation. Conversely, stress conditions reduced K63 linked DDX3X ubiquitination in coordination with activity of the deubiquitinase OTUB1 (OTU domain-containing ubiquitin aldehyde-binding protein 1). Thus, the balance between SYVN1 and OTUB1 functioned to optimize DDX3X activity and activation of NLRP3 or stress granule. These findings show the upstream role of SYVN1 OTUB1 axis in integrating cellular stress signals to decide the cell fate and suggest that ubiquitination of DDX3X is a potential target for inflammasome driven inflammation.","rel_num_authors":6,"rel_authors":[{"author_name":"MOHAMMAD ANAS","author_inst":"University of Illinois Chicago"},{"author_name":"Abhalaxmi Singh","author_inst":"University of Illinois Chicago"},{"author_name":"Nithish Raj Prasad","author_inst":"University of Illinois Chicago"},{"author_name":"Joshua W. Thompson","author_inst":"University of Illinois Chicago"},{"author_name":"Chinnaswamy Tiruppathi","author_inst":"University of Illinois Chicago"},{"author_name":"Asrar B. Malik","author_inst":"Cell biologics"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Evolution of new cerebellar nuclei by excitatory progenitor diversification in the early rhombic lip","rel_doi":"10.64898\/2026.09.17.751883","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.751883","rel_abs":"The cerebellar nuclei, the output regions of the cerebellum, have evolved via repeated duplication of a conserved cell type set to produce different numbers of nuclei across species. Here, we investigate the mechanism underlying this process using developmental single-cell and spatial transcriptomics time courses in mouse and chicken. We show that new nuclei formation is governed by excitatory neurons born from nucleus-specific progenitors in the early and late rhombic lip (RL), with inhibitory neurons incorporating into established nuclear territories. Evolutionarily newer canonical cerebellar nuclei with increasingly higher-order functions are produced by diversification of the early RL, where nuclear identity and spatial organization are established in part by co-option of border formation programs in conserved progenitor cell types. In contrast, the late RL generates the higher-order subnuclei of the medial nucleus and forms a non-canonical olivocerebellar circuit. Together, our findings suggest that new brain regions can evolve through developmental diversification of excitatory progenitors and spatial segregation of conserved sister cell types with generic inhibitory neurons filling in after.","rel_num_authors":8,"rel_authors":[{"author_name":"Manjari M-G Anant","author_inst":"Johns Hopkins University"},{"author_name":"Eli Clemens Zuercher","author_inst":"Johns Hopkins University"},{"author_name":"Maggie Lowman","author_inst":"Johns Hopkins University"},{"author_name":"Caleb Shi","author_inst":"Johns Hopkins University"},{"author_name":"Dylan Z. Faltine-Gonzalez","author_inst":"Johns Hopkins University"},{"author_name":"Michael L. Piacentino","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Jean Fan","author_inst":"Johns Hopkins University"},{"author_name":"Justus M. Kebschull","author_inst":"Johns Hopkins University"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Cellular code for mnemonic pattern separation in the human hippocampus is revealed by false memories","rel_doi":"10.64898\/2026.09.18.752786","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.18.752786","rel_abs":"Theoretical models propose that pattern separation, a computation thought to be implemented by the hippocampus, allows us to differentiate between familiar and novel items. However, whether pattern separation operates in the human hippocampus remains contested, with no established single-cell correlate. We recorded the single neuron activity of 3506 neurons in the human brain while 97 patients performed a recognition memory task in which novel images similar to previously seen images led to false memories and associated behavioral errors. We identified two kinds of memory selective neurons distributed across the brain: those responding differently to falsely recognized novel and correctly recognized familiar images in a manner compatible with pattern separation, and the other signaling the subject's choice. At the population level, these cells predicted mnemonic ground truth in the hippocampus and the decision in the pre-supplementary motor area, illustrating the progression from mnemonic signals to decisions. Removing pattern separation-signaling cells abolished the continuous memory strength gradient present in the hippocampus, suggesting a role of these cells in separating memories of different strength. These results establish a single cell correlate for mnemonic pattern separation in the human hippocampus and show its behavioral relevance in episodic memory.","rel_num_authors":10,"rel_authors":[{"author_name":"Natalia Kurilenko","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Clayton Mosher","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Sophia Cheng","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Yousef Salimpour","author_inst":"Johns Hopkins University"},{"author_name":"Jonathan Daume","author_inst":"Cedars Sinai Medical Center"},{"author_name":"Chrystal M. Reed","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"William Stanley Anderson","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Taufik A Valiante","author_inst":"University of Toronto"},{"author_name":"Adam N. Mamelak","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Ueli Rutishauser","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Local translation couples synaptic activity to mitochondrial adaptation in dendrites","rel_doi":"10.64898\/2026.09.17.752159","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.17.752159","rel_abs":"Neurons rely on localized protein synthesis to rapidly adapt synaptic function to activity, yet how dendritic translation regulates mitochondrial remodeling during synaptic plasticity remains poorly understood. Here, we show that neuronal activity engages a spatially restricted translational program that couples local protein synthesis to mitochondrial function through the non-canonical translation initiation factor eIF4G2. Using proximity labeling to profile the dendritic RNA interactome, translatome, and proteome, we identify a cohort of nuclear-encoded mitochondrial mRNAs that are selectively recruited for translation following depolarization and mGluR activation. This program drives activity-dependent increases in mitochondrial membrane potential, mitochondrial abundance, and oxygen consumption. Loss of eIF4G2 abolishes these responses, whereas dendrite-specific, but not soma-restricted, rescue restores mitochondrial remodeling, demonstrating that eIF4G2 functions locally at postsynaptic sites. Mechanistically, eIF4G2 binds the 5 prime or minute untranslated regions of activity-responsive mitochondrial transcripts and promotes translation of both upstream open reading frames (uORFs) and downstream coding sequences. Using a dendritically targeted split-GFP reporter, we further show that neuronal activity induces local uORF translation to generate previously unannotated micropeptides. Together, our findings identify eIF4G2-dependent local translation as a mechanism that establishes mitochondrial competence during synaptic activity by coordinating the production of mitochondrial proteins and uORF-encoded micropeptides.","rel_num_authors":4,"rel_authors":[{"author_name":"Madison T Jones","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Natalie Noble","author_inst":"Harvard University"},{"author_name":"Robert B Darnell","author_inst":"Rockefeller Univeristy"},{"author_name":"Ezgi Hacisuleyman","author_inst":"The Wertheim UF Scripps Institute"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Single neurons in the human substantia nigra encode social learning signals","rel_doi":"10.64898\/2026.09.18.752742","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.18.752742","rel_abs":"Humans are remarkable at adapting to changing norms, yet we know little about how the human brain encodes these social signals at the single neuron level. Here, we recorded the activity of single neurons in the substantia nigra and globus pallidus in neurosurgical participants as they played an iterative ultimatum game versus human and computer avatars. Using computational modeling of behavior, we found that putative dopaminergic units in the substantia nigra tracked the valence of norm prediction errors, with greater encoding during gameplay with human versus computer avatars. Analogous analyses in the globus pallidus, a nucleus adjacent to the substantia nigra, found no significant effect. Our results identify a novel role for the substantia nigra in encoding social learning signals.","rel_num_authors":14,"rel_authors":[{"author_name":"Arianna Neal Davis","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ofer Perl","author_inst":"University of Haifa"},{"author_name":"Brian H Kopell","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Matthew Heflin","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Qi Xiu Fu","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Salman  E Qasim","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Zarghona Imtiaz","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ayaka Kato","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Soojung Na","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Navid Mikail","author_inst":"Alpha Omega Co. USA, Inc."},{"author_name":"Helen S Mayberg","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Read Montague","author_inst":"Virginia Polytechnic Institute and State University"},{"author_name":"Ignacio Saez","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Xiaosi Gu","author_inst":"Icahn School of Medicine at Mount Sinai"}],"rel_date":"2026-09-20","rel_site":"biorxiv"},{"rel_title":"Defining the Genetic and Phenotypic Landscape of Primary Immune Regulatory Disorders Using the ClinGen Validation Framework","rel_doi":"10.64898\/2026.09.11.26362285","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.11.26362285","rel_abs":"BackgroundPrimary immune regulatory disorders (PIRDs) represent a rapidly growing group of inborn errors of immunity (IEIs) characterized by infection susceptibility, autoimmunity, inflammation, and lymphoproliferation. However, the core features of the gene-disease relationships underlying these conditions are often obscured by limitations in available published data. The Clinical Genome Resource (ClinGen) is an international collaborative effort that seeks to address this challenge for PIRDs and other monogenic diseases through a standardized framework for classifying the strength of gene-disease relationships.\n\nObjectiveWe sought to systematically evaluate the evidence for proposed PIRD gene-disease relationships and identify conserved phenotypic features across this heterogeneous group of disorders.\n\nMethodsUsing the standardized ClinGen framework, the ClinGen PIRD Gene Curation Expert Panel (GCEP) identified potential gene-disease relationships for monogenic conditions characterized predominantly by immune dysregulation. We subsequently curated evidence relevant to these relationships, classified the strength of evidence for these gene-disease relationships, and evaluated clinical patterns among these conditions through standardized phenotyping using the Human Phenotype Ontology (HPO).\n\nResultsAs of April 2026, the PIRD-GCEP has curated a total of 46 genes corresponding to 49 gene-disease relationships characterized by immune dysregulation. Of these, 28 were categorized as definitive, 2 as strong, 9 as moderate, 7 as limited, and 3 as disputed. Analysis of HPO-based phenotyping revealed 3 major phenotypic clusters corresponding to lymphoproliferation and systemic inflammation, atopic and gastrointestinal inflammation, and combined immune deficiency with autoimmunity.\n\nConclusionThe PIRD-GCEP framework provides validated gene-disease classifications and identifies three distinct phenotypic clusters, facilitating improved diagnosis while revealing genes requiring further investigation to confirm their role in immune regulatory disorders.\n\nCAPSULE SUMMARYUsing the ClinGen framework, this study describes the first global initiative to validate gene-disease relationships for primary immune regulatory disorders, identifying 49 relationships and three phenotypic clusters, providing a resource for genetic testing and diagnosis.\n\nKEY MESSAGESO_LIThe PIRD-GCEP applied ClinGens standardized framework to curate 46 genes (49 gene-disease relationships) linked to primary immune regulatory disorders. Thirty of these relationships were classified as definitive or strong, giving clinicians a validated basis for variant interpretation in this heterogeneous disease group.\nC_LIO_LIStandardized HPO phenotyping revealed that, despite their genetic diversity, PIRDs converge onto a small number of clinically meaningful patterns including: (1) lymphoproliferation with systemic inflammation, (2) atopic and gastrointestinal inflammation, and (3) immune deficiency with autoimmunity.\nC_LIO_LIThis validated set of gene-disease relationships and phenotypic clusters represents a resource for the genetic testing and diagnosis of PIRDs, potentially reducing diagnostic delays and aiding in the recognition of novel PIRD gene-disease relationships.\nC_LI","rel_num_authors":31,"rel_authors":[{"author_name":"Benjamin D. Solomon","author_inst":"Division of Allergy and Immunology, Department of Pediatrics, School of Medicine, Stanford University, Palo Alto, CA, USA"},{"author_name":"Justyne Ross","author_inst":"Department of Genetics, University of North Carolina, Chapel Hill, NC, USA"},{"author_name":"Eleanor P. Fensterle","author_inst":"Independent Researcher, USA"},{"author_name":"Rasha S. Soliman","author_inst":"Department of Pulmonology, Cairo University Hospitals: Cairo, Cairo, EG"},{"author_name":"Michelle K. Paczosa","author_inst":"Quest Diagnostics, Seacaucus, NJ, USA"},{"author_name":"Alison Brittain","author_inst":"Division of Pediatric Rheumatology, Nationwide Children's Hospital, Columbus, OH, USA"},{"author_name":"Elizabeth M. Forbes","author_inst":"Immunology, Pathology Queensland, Brisbane, QLD, Australia; University of Queensland, Brisbane, QLD, Australia"},{"author_name":"Olga F. Sarmento","author_inst":"Labcorp, San Francisco, CA, USA"},{"author_name":"Ivana Stojkic","author_inst":"Division of Rheumatology, Department of Pediatrics, Nationwide Children's Hospital, Columbus, OH, USA"},{"author_name":"Shifaa Alkotob","author_inst":"Division of Allergy and Immunology, Department of Internal Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX,"},{"author_name":"Jahnavi Aluri","author_inst":"Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, OH, USA"},{"author_name":"Jorge Diogo Da Silva","author_inst":"Medical Genetics Centre Dr. Jacinto Magalh?es, Santo Ant0nio University Hospital Center, Porto, Portugal; Life and Health Sciences Research Institute (ICVS), Sc"},{"author_name":"Ana Rita Soares","author_inst":"Medical Genetics Centre Dr. Jacinto Magalh?es, Santo Antonio University Hospital Center, Porto, Portugal; Genetyca by Atrys, Porto, Portugal"},{"author_name":"Monica Sulit","author_inst":"Human Genome Sequencing Center, Baylor College of Medicine, Houston TX, USA"},{"author_name":"Anita Chandra","author_inst":"Department of Clinical Immunology, Cambridge University NHS Foundation Trust and Department of Medicine, University of Cambridge, UK"},{"author_name":"Fabian Hauck","author_inst":"Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, Ludwig-Maximilians-Universitat, Munich, Germany; University Children's Hospit"},{"author_name":"Stephen Jolles","author_inst":"Immunodeficiency Centre for Wales, University Hospital of Wales, Cardiff, UK"},{"author_name":"Paul J. Maglione","author_inst":"Section of Pulmonary, Allergy, Sleep and Critical Care, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA"},{"author_name":"Harry Lesmana","author_inst":"Department of Medical Genetics and Genomics, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA"},{"author_name":"Craig D. Platt","author_inst":"Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA USA"},{"author_name":"Markus G. Seidel","author_inst":"Styrian Children's Cancer Research Unit for Cancer and Inborn Errors of the Blood and Immunity in Children, Division of Pediatric Hematology and Oncology, Depar"},{"author_name":"Andrew L. Snow","author_inst":"Department of Pharmacology & Molecular Therapeutics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA"},{"author_name":"Kathleen E. Sullivan","author_inst":"Children's Hospital of Philadelphia. Philadelphia, PA, USA"},{"author_name":"Troy R. Torgerson","author_inst":"Allen Institute for Immunology, Seattle, WA, USA."},{"author_name":"Tiphanie P. Vogel","author_inst":"Division of Rheumatology, Department of Pediatrics, Baylor College of Medicine and Center for Human Immunobiology, Texas Children's Research Institute, Texas Ch"},{"author_name":"Klaus Warnatz","author_inst":"Department of Rheumatology and Clinical Immunology; Center for Chronic Immunodeficiency, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg,"},{"author_name":"Kejian Zhang","author_inst":"Division of Diagnostic Genetics and Genomics, Department of Pathology, University of Michigan, College of Medicine, Ann Arbor, MI, USA"},{"author_name":"Purvesh Khatri","author_inst":"Institute for Immunity, Transplantation, and Infection, School of Medicine, Stanford University, Palo Alto, USA; Division of Computational Medicine, Department "},{"author_name":"Forum Raval","author_inst":"Labcorp, San Francisco, CA, USA"},{"author_name":"Stuart G. Tangye","author_inst":"Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, NSW Australia"},{"author_name":"Roshini S. Abraham","author_inst":"Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, OH, USA"}],"rel_date":"2026-09-17","rel_site":"medrxiv"},{"rel_title":"Phenotypic and genetic characterization of different modes of lifetime nicotine use in the All of Us Research Program","rel_doi":"10.64898\/2026.09.11.26361370","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.11.26361370","rel_abs":"ObjectiveExisting genetic studies of nicotine consumption have largely focused on cigarette smoking, despite other modes emerging. Different nicotine use modes have varying use patterns and user characteristics that may contribute to distinct environmental and genetic influences. This study aims to identify the shared and specific genetic risks for five nicotine use modes.\n\nMethodsWe performed a common variant multi-ancestral genome-wide association study (cross-ancestry N = 304,213) of five types of nicotine use in the All of Us Research Program: lifetime use of electronic nicotine (e-nicotine) products, cigars, tobacco in a hookah, smokeless tobacco, or at least 100 cigarettes.\n\nResultsNicotine users, regardless of mode, were more likely to be male and of younger age (except for cigarette use), and all modes of use were positively associated with tobacco use disorder diagnoses. GWAS meta-analyses of cigarette, e-nicotine, cigar, and smokeless tobacco use identified 87, 4, 1, and 1 genome-wide risk loci, respectively (none for hookah), including previously identified genes (e.g., CHRNA4 for cigarettes). Cigarette, e-nicotine, and smokeless tobacco use showed strong genetic correlations (rg=0.82-0.92), while cigar and hookah use were strongly genetically correlated (rg=0.87). Cross-trait correlations diverged: cigarette, e-nicotine, and smokeless tobacco use showed the strongest positive correlations with psychiatric disorders, negative urgency, and neuroticism, whereas cigar and hookah use showed null-to-weak correlations with psychiatric disorders but positive correlations with sensation-seeking and openness.\n\nConclusionsOur findings reveal important phenotypic and genetic distinctions across modes of nicotine use, particularly in relation to personality traits such as impulsivity and to socioeconomic context.","rel_num_authors":8,"rel_authors":[{"author_name":"Feiyang Huang","author_inst":"Washington University School of Medicine"},{"author_name":"Pamela N Romero Villela","author_inst":"Washington University School of Medicine"},{"author_name":"Zhen Luo","author_inst":"Washington University School of Medicine"},{"author_name":"Alex P Miller","author_inst":"Indiana University School of Medicine"},{"author_name":"Pamela Madden","author_inst":"Washington University School of Medicine"},{"author_name":"Arpana Agrawal","author_inst":"Washington University School of Medicine"},{"author_name":"Alexander S Hatoum","author_inst":"Washington University School of Medicine"},{"author_name":"Emma C Johnson","author_inst":"Washington University School of Medicine"}],"rel_date":"2026-09-17","rel_site":"medrxiv"},{"rel_title":"Implementation strategies for integrating TB treatment into community pharmacies for people with TB\/HIV in Uganda using human-centered design methodology","rel_doi":"10.64898\/2026.09.14.26363070","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.14.26363070","rel_abs":"BackgroundCommunity pharmacies (private retail drug shops\/pharmacies) have emerged as a novel differentiated service delivery (DSD) model for delivering antiretroviral therapy (ART) to people with human immunodeficiency virus (HIV) and could support integrated tuberculosis (TB) medication refills. Using a Human-Centered Design (HCD) methodology, we developed an implementation strategy for integrating TB treatment into pharmacies targeting people with TB\/HIV in Kampala, Uganda.\n\nMethodsWe implemented the inspiration and ideation phases of the HCD methodology. During the inspiration phase, we identified themes describing barriers and facilitators to integrating TB treatment into community pharmacies and conducted observations at community pharmacies to understand the care pathway of people with TB\/HIV. We translated these qualitative findings into insight statements, design opportunities, and How Might We (HMW) questions. During the ideation phase, we conducted brainstorming and co-design workshops to generate and refine solutions, tested low-fidelity prototypes using ranked scores, and assessed the usability of high-fidelity prototypes using the System Usability Scale. Participants included people with TB\/HIV, TB focal persons, HIV focal persons, Ministry of Health DSD model experts, and pharmacy healthcare providers.\n\nResultsOf 26 low-fidelity prototypes, four implementation strategy components emerged: (1) raising awareness and building trust in pharmacy TB medication refills by TB and HIV focal persons, with a focus on privacy, convenience, and legitimacy; (2) standardizing TB medication refill workflows using synchronized ART\/TB refill workflows, standardard operating procedures, and visual diagrams illustrating integration of TB treatment into community pharmacies; (3) strengthening the capacity of community pharmacies through certification, accreditation, and targeted TB training; and (4) strengthening monitoring and quality assurance through standard operating procedure manuals and standardized side-effect monitoring checklists.\n\nConclusionThe adapted strategy and high-fidelity prototypes will be evaluated in a pilot randomized trial assessing the effectiveness and implementation of TB treatment integration into pharmacies for people with TB\/HIV in Kampala, Uganda.","rel_num_authors":6,"rel_authors":[{"author_name":"Jonathan Izudi","author_inst":"Mbarara University of Science and Technology"},{"author_name":"Adithya Cattamanchi","author_inst":"UCI: University of California Irvine"},{"author_name":"Christine Sekaggya-Wiltshire","author_inst":"IDI: Makerere University Infectious Diseases Institute"},{"author_name":"Rachel King","author_inst":"UCSF: University of California San Francisco"},{"author_name":"Noah Kiwanuka","author_inst":"Makerere University CHS: Makerere University College of Health Sciences"},{"author_name":"Amanda Sammann","author_inst":"UCSF: University of California San Francisco"}],"rel_date":"2026-09-17","rel_site":"medrxiv"}]}