{"gname":"Oregon Health & Science University","grp_id":"22","rels":[{"rel_title":"The TBVaxRepository: A living database of projects supporting the preparedness for adult and adolescent TB vaccine rollout","rel_doi":"10.64898\/2026.05.06.26352615","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352615","rel_abs":"Background Tuberculosis (TB) continues to cause substantial morbidity and mortality, with adults and adolescents carrying the largest burden of disease. Multiple promising novel vaccine candidates are in clinical trials, and their eventual impact will depend on effective implementation strategies. Information on TB vaccine preparedness efforts that could inform coordination remains fragmented. Methods We developed the first living and interactive online repository (https:\/\/tbvaxrepository.org\/) collating completed, ongoing, and planned adult and adolescent TB vaccine preparedness initiatives. Data were obtained through a prior scoping review, direct stakeholder engagement, international conferences, and open calls via social media and partner networks between March 2023-November 2024. Projects were categorized using the World Health Organizations (WHO) framework for TB vaccine preparedness across three thematic areas: availability, accessibility, and acceptability. Findings By December 2024, the repository included 90 projects from 119 countries. Most projects focused on health- (47%) and economic modelling (21%), demand and acceptability studies (19%) or implementation feasibility (14%). Most of the projects were situated in India (n=36), South Africa (n=34), China (n=19), Indonesia, (n=17), Kenya (n=17), Brazil (n=14), and Pakistan (n=14). Few initiatives targeted key populations such as people living with HIV, pregnant or lactating individuals, or socially marginalized and occupational high-risk groups. Research on communication strategies for facilitating uptake as part of rollout were absent. Conclusions The repository reveals both progress and gaps in global TB vaccine preparedness across WHOs three thematic areas, with particular attention to geographic coverage, and the inclusion of key populations. As novel vaccines for adults and adolescents approach potential licensure, coordinated and inclusive preparedness efforts will be critical to ensure equitable and effective rollout. This repository offers a transparent platform to strengthen collaboration, reduce duplication, and guide strategic planning in a historically underfunded field.","rel_num_authors":4,"rel_authors":[{"author_name":"Joeri  Sumina Buis","author_inst":"KNCV Tuberculosis Foundation: KNCV Tuberculosefonds"},{"author_name":"Andrew  D Kerkhoff","author_inst":"UCSF: University of California San Francisco"},{"author_name":"Christiaan Mulder","author_inst":"KNCV Tuberculosis Foundation: KNCV Tuberculosefonds"},{"author_name":"Degu Jerene","author_inst":"KNCV Tuberculosis Foundation: KNCV Tuberculosefonds"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Germline polygenic score for prostate cancer aggressiveness","rel_doi":"10.64898\/2026.05.07.26352488","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352488","rel_abs":"Background Risk stratification for prostate cancer (PCa) progression or aggressiveness is often based on clinicopathologic features, some of which may be influenced by genetic factors. We developed a novel, germline polygenic risk score (PRSagg) to predict likelihood of developing aggressive PCa. Methods PRSagg was developed using data from 38,688 patients with PCa (case-only analysis) from the Million Veteran Program (MVP) through a genome-wide search for variants associated with PCa grade group at diagnosis. We tested associations of PRSagg with grade group using the entire MVP dataset using the .632 bootstrap method. In an MVP cohort with localized PCa that was initially monitored without treatment, we tested PRSagg for association with unfavorable outcomes (subsequent development of grade group 4-5, metastasis, and\/or biochemical recurrence after definitive treatment). We performed external validation in data from patients in the PRACTICAL Consortium (n=45,214) and from participants in the ProtecT randomized trial who underwent active monitoring (n=316). Odds ratios (ORs) were calculated per standard deviation (SD) increase with 95% confidence intervals, while adjusting for age, genetic ancestry, a previously developed polygenic score for risk of PCa (PHS601), and a polygenic score for benign elevated prostate-specific antigen (PRSPSA). For the outcome of metastasis, we additionally adjusted for PSA at diagnosis. Results In the MVP training dataset, PRSagg (172 variants) was associated with higher grade group at diagnosis (OR = 1.53 [1.51-1.56]) and with increased risk of unfavorable outcomes during monitoring (OR = 1.13 [1.09-1.18]). These findings were confirmed in the external datasets. PRSagg was associated with greater odds of higher grade group at diagnosis (OR = 1.09 [1.06-1.11]). Among ProtecT participants undergoing active monitoring, PRSagg was associated with higher risk of metastasis (OR = 2.15 [1.02-3.88]). Among MVP participants with high polygenic risk of developing any PCa, the risk of aggressive disease was highest in men with high PRSagg and low genetic risk of PSA elevation. Conclusions Among men who develop PCa, a weighted sum of common germline variants (PRSagg) is independently associated with PCa aggressiveness. These findings may inform future study of germline influence on tumor evolution and risk-stratified intensity of active surveillance.","rel_num_authors":82,"rel_authors":[{"author_name":"George Jiajie Xu","author_inst":"VA San Diego Healthcare System"},{"author_name":"Roshan Karunamuni","author_inst":"VA San Diego Healthcare System"},{"author_name":"Anna M Dornisch","author_inst":"University of California San Diego"},{"author_name":"Charles A Brunette","author_inst":"VA Boston Healthcare System"},{"author_name":"Morgan E Danowski","author_inst":"VA Boston Healthcare System"},{"author_name":"Heena Desai","author_inst":"University of Pennsylvania Perelman School of Medicine"},{"author_name":"Daniel Dochtermann","author_inst":"VA Boston Healthcare System"},{"author_name":"Isla P Garraway","author_inst":"VA Greater Los Angeles Healthcare System"},{"author_name":"Richard L Hauger","author_inst":"VA San Diego Healthcare System"},{"author_name":"Adam S Kibel","author_inst":"Harvard Medical School"},{"author_name":"Julie A Lynch","author_inst":"VA Salt Lake City Healthcare System"},{"author_name":"Saiju Pyarajan","author_inst":"VA Boston Healthcare System"},{"author_name":"Brent S Rose","author_inst":"VA San Diego Healthcare System"},{"author_name":"Craig C Teerlink","author_inst":"VA Salt Lake City Healthcare System"},{"author_name":"Ole A Andreassen","author_inst":"Oslo University Hospital and University of Oslo"},{"author_name":"Anders M Dale","author_inst":"University of California San Diego"},{"author_name":"Jenny L Donovan","author_inst":"University of Bristol"},{"author_name":"Freddie Hamdy","author_inst":"University of Oxford"},{"author_name":"Linda Kachuri","author_inst":"Stanford University"},{"author_name":"Athene Lane","author_inst":"University of Bristol"},{"author_name":"Richard M Martin","author_inst":"University of Bristol"},{"author_name":"Ian G Mills","author_inst":"University of Oxford"},{"author_name":"David E Neal","author_inst":"University of Oxford"},{"author_name":"Emma L Turner","author_inst":"University of Bristol"},{"author_name":"John S Witte","author_inst":"Stanford University"},{"author_name":"Johanna Schleutker","author_inst":"University of Turku"},{"author_name":"Nora Pashayan","author_inst":"University of Cambridge"},{"author_name":"Jyotsna Batra","author_inst":"Bond University"},{"author_name":"- Australian Prostate Cancer BioResource (APCB)","author_inst":"-"},{"author_name":"B\u00f8rge G Nordestgaard","author_inst":"University of Copenhagen"},{"author_name":"Robert J Hamilton","author_inst":"Princess Margaret Cancer Centre"},{"author_name":"Alicja Wolk","author_inst":"Karolinska Institutet"},{"author_name":"Demetrius Albanes","author_inst":"National Cancer Institute"},{"author_name":"Joshua Atkins","author_inst":"University of Oxford"},{"author_name":"William J Blot","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Lorelei A Mucci","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Sune F Nielsen","author_inst":"Copenhagen University Hospital"},{"author_name":"Olivier Cussenot","author_inst":"Sorbonne Universite"},{"author_name":"Sonja I Berndt","author_inst":"National Cancer Institute"},{"author_name":"Stella Koutros","author_inst":"National Cancer Institute"},{"author_name":"Karina Dalsgaard S\u00f8rensen","author_inst":"Aarhus University Hospital"},{"author_name":"Cezary Cybulski","author_inst":"Pomeranian Medical University"},{"author_name":"Florence Menegaux","author_inst":"Universit\u00e9 Paris-Saclay"},{"author_name":"Jong Y Park","author_inst":"Moffitt Cancer Center"},{"author_name":"Robert J MacInnis","author_inst":"Cancer Council Victoria"},{"author_name":"Barry S Rosenstein","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Yong-Jie Lu","author_inst":"Queen Mary University of London"},{"author_name":"Stephen Watya","author_inst":"Uro Care"},{"author_name":"Ana Vega","author_inst":"Santiago de Compostela"},{"author_name":"- NC-LA PCaP Investigators","author_inst":"-"},{"author_name":"- The IMPACT Study Steering Committee and Collaborators","author_inst":"-"},{"author_name":"Manolis Kogevinas","author_inst":"ISGLOBAL: Instituto de Salud Global de Barcelona"},{"author_name":"Fredrik Wiklund","author_inst":"Karolinska Institutet"},{"author_name":"Anna Plym","author_inst":"Karolinska Institutet"},{"author_name":"Manuel R Teixeira","author_inst":"Porto Comprehensive Cancer Center"},{"author_name":"Luc Multigner","author_inst":"Institut de recherche en sant\u00e9, environnement et travail"},{"author_name":"Robin J Leach","author_inst":"University of Texas Health Science Center at San Antonio"},{"author_name":"Hermann Brenner","author_inst":"German Cancer Research Centre: Deutsches Krebsforschungszentrum"},{"author_name":"Esther M John","author_inst":"Stanford University"},{"author_name":"Radka Kaneva","author_inst":"Medical University of Sofia"},{"author_name":"Christopher J Logothetis","author_inst":"The University of Texas M. D. Anderson Cancer Center"},{"author_name":"Susan L Neuhausen","author_inst":"Beckman Research Institute of City of Hope"},{"author_name":"Piet Ost","author_inst":"Ghent University"},{"author_name":"Azad Razack","author_inst":"University of Malaya"},{"author_name":"Jay H Fowke","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Marija Gamulin","author_inst":"University of Zagreb School of Medicine"},{"author_name":"Nawaid Usmani","author_inst":"University of Alberta"},{"author_name":"Frank Claessens","author_inst":"KU Leuven"},{"author_name":"Jose Esteban Castelao","author_inst":"Instituto de Investigaci\u00f3n Biom\u00e9dica Galicia Sur"},{"author_name":"Gyorgy Petrovics","author_inst":"Uniformed Services University"},{"author_name":"Marie-\u00c9lise Parent","author_inst":"Institut national de la recherche scientifique"},{"author_name":"Jennifer J Hu","author_inst":"The University of Miami School of Medicine"},{"author_name":"Wei Zheng","author_inst":"Vanderbilt University Medical Center"},{"author_name":"- The Profile Study Steering Committee","author_inst":"-"},{"author_name":"- UKGPCS collaborators","author_inst":"-"},{"author_name":"Zsofia Kote-Jarai","author_inst":"The Institute of Cancer Research"},{"author_name":"Rosalind A Eeles","author_inst":"The Institute of Cancer Research"},{"author_name":"- The PRACTICAL Consortium","author_inst":"-"},{"author_name":"- VA Million Veteran Program","author_inst":"-"},{"author_name":"Kara N Maxwell","author_inst":"Corporal Michael Crescenz Veterans Affairs Medical Center"},{"author_name":"Jason L Vassy","author_inst":"VA Boston Healthcare System"},{"author_name":"Tyler M Seibert","author_inst":"VA San Diego Healthcare System"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Germline polygenic score for prostate cancer aggressiveness","rel_doi":"10.64898\/2026.05.07.26352488","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352488","rel_abs":"Background Risk stratification for prostate cancer (PCa) progression or aggressiveness is often based on clinicopathologic features, some of which may be influenced by genetic factors. We developed a novel, germline polygenic risk score (PRSagg) to predict likelihood of developing aggressive PCa. Methods PRSagg was developed using data from 38,688 patients with PCa (case-only analysis) from the Million Veteran Program (MVP) through a genome-wide search for variants associated with PCa grade group at diagnosis. We tested associations of PRSagg with grade group using the entire MVP dataset using the .632 bootstrap method. In an MVP cohort with localized PCa that was initially monitored without treatment, we tested PRSagg for association with unfavorable outcomes (subsequent development of grade group 4-5, metastasis, and\/or biochemical recurrence after definitive treatment). We performed external validation in data from patients in the PRACTICAL Consortium (n=45,214) and from participants in the ProtecT randomized trial who underwent active monitoring (n=316). Odds ratios (ORs) were calculated per standard deviation (SD) increase with 95% confidence intervals, while adjusting for age, genetic ancestry, a previously developed polygenic score for risk of PCa (PHS601), and a polygenic score for benign elevated prostate-specific antigen (PRSPSA). For the outcome of metastasis, we additionally adjusted for PSA at diagnosis. Results In the MVP training dataset, PRSagg (172 variants) was associated with higher grade group at diagnosis (OR = 1.53 [1.51-1.56]) and with increased risk of unfavorable outcomes during monitoring (OR = 1.13 [1.09-1.18]). These findings were confirmed in the external datasets. PRSagg was associated with greater odds of higher grade group at diagnosis (OR = 1.09 [1.06-1.11]). Among ProtecT participants undergoing active monitoring, PRSagg was associated with higher risk of metastasis (OR = 2.15 [1.02-3.88]). Among MVP participants with high polygenic risk of developing any PCa, the risk of aggressive disease was highest in men with high PRSagg and low genetic risk of PSA elevation. Conclusions Among men who develop PCa, a weighted sum of common germline variants (PRSagg) is independently associated with PCa aggressiveness. These findings may inform future study of germline influence on tumor evolution and risk-stratified intensity of active surveillance.","rel_num_authors":82,"rel_authors":[{"author_name":"George Jiajie Xu","author_inst":"VA San Diego Healthcare System"},{"author_name":"Roshan Karunamuni","author_inst":"VA San Diego Healthcare System"},{"author_name":"Anna M Dornisch","author_inst":"University of California San Diego"},{"author_name":"Charles A Brunette","author_inst":"VA Boston Healthcare System"},{"author_name":"Morgan E Danowski","author_inst":"VA Boston Healthcare System"},{"author_name":"Heena Desai","author_inst":"University of Pennsylvania Perelman School of Medicine"},{"author_name":"Daniel Dochtermann","author_inst":"VA Boston Healthcare System"},{"author_name":"Isla P Garraway","author_inst":"VA Greater Los Angeles Healthcare System"},{"author_name":"Richard L Hauger","author_inst":"VA San Diego Healthcare System"},{"author_name":"Adam S Kibel","author_inst":"Harvard Medical School"},{"author_name":"Julie A Lynch","author_inst":"VA Salt Lake City Healthcare System"},{"author_name":"Saiju Pyarajan","author_inst":"VA Boston Healthcare System"},{"author_name":"Brent S Rose","author_inst":"VA San Diego Healthcare System"},{"author_name":"Craig C Teerlink","author_inst":"VA Salt Lake City Healthcare System"},{"author_name":"Ole A Andreassen","author_inst":"Oslo University Hospital and University of Oslo"},{"author_name":"Anders M Dale","author_inst":"University of California San Diego"},{"author_name":"Jenny L Donovan","author_inst":"University of Bristol"},{"author_name":"Freddie Hamdy","author_inst":"University of Oxford"},{"author_name":"Linda Kachuri","author_inst":"Stanford University"},{"author_name":"Athene Lane","author_inst":"University of Bristol"},{"author_name":"Richard M Martin","author_inst":"University of Bristol"},{"author_name":"Ian G Mills","author_inst":"University of Oxford"},{"author_name":"David E Neal","author_inst":"University of Oxford"},{"author_name":"Emma L Turner","author_inst":"University of Bristol"},{"author_name":"John S Witte","author_inst":"Stanford University"},{"author_name":"Johanna Schleutker","author_inst":"University of Turku"},{"author_name":"Nora Pashayan","author_inst":"University of Cambridge"},{"author_name":"Jyotsna Batra","author_inst":"Bond University"},{"author_name":"- Australian Prostate Cancer BioResource (APCB)","author_inst":"-"},{"author_name":"B\u00f8rge G Nordestgaard","author_inst":"University of Copenhagen"},{"author_name":"Robert J Hamilton","author_inst":"Princess Margaret Cancer Centre"},{"author_name":"Alicja Wolk","author_inst":"Karolinska Institutet"},{"author_name":"Demetrius Albanes","author_inst":"National Cancer Institute"},{"author_name":"Joshua Atkins","author_inst":"University of Oxford"},{"author_name":"William J Blot","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Lorelei A Mucci","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Sune F Nielsen","author_inst":"Copenhagen University Hospital"},{"author_name":"Olivier Cussenot","author_inst":"Sorbonne Universite"},{"author_name":"Sonja I Berndt","author_inst":"National Cancer Institute"},{"author_name":"Stella Koutros","author_inst":"National Cancer Institute"},{"author_name":"Karina Dalsgaard S\u00f8rensen","author_inst":"Aarhus University Hospital"},{"author_name":"Cezary Cybulski","author_inst":"Pomeranian Medical University"},{"author_name":"Florence Menegaux","author_inst":"Universit\u00e9 Paris-Saclay"},{"author_name":"Jong Y Park","author_inst":"Moffitt Cancer Center"},{"author_name":"Robert J MacInnis","author_inst":"Cancer Council Victoria"},{"author_name":"Barry S Rosenstein","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Yong-Jie Lu","author_inst":"Queen Mary University of London"},{"author_name":"Stephen Watya","author_inst":"Uro Care"},{"author_name":"Ana Vega","author_inst":"Santiago de Compostela"},{"author_name":"- NC-LA PCaP Investigators","author_inst":"-"},{"author_name":"- The IMPACT Study Steering Committee and Collaborators","author_inst":"-"},{"author_name":"Manolis Kogevinas","author_inst":"ISGLOBAL: Instituto de Salud Global de Barcelona"},{"author_name":"Fredrik Wiklund","author_inst":"Karolinska Institutet"},{"author_name":"Anna Plym","author_inst":"Karolinska Institutet"},{"author_name":"Manuel R Teixeira","author_inst":"Porto Comprehensive Cancer Center"},{"author_name":"Luc Multigner","author_inst":"Institut de recherche en sant\u00e9, environnement et travail"},{"author_name":"Robin J Leach","author_inst":"University of Texas Health Science Center at San Antonio"},{"author_name":"Hermann Brenner","author_inst":"German Cancer Research Centre: Deutsches Krebsforschungszentrum"},{"author_name":"Esther M John","author_inst":"Stanford University"},{"author_name":"Radka Kaneva","author_inst":"Medical University of Sofia"},{"author_name":"Christopher J Logothetis","author_inst":"The University of Texas M. D. Anderson Cancer Center"},{"author_name":"Susan L Neuhausen","author_inst":"Beckman Research Institute of City of Hope"},{"author_name":"Piet Ost","author_inst":"Ghent University"},{"author_name":"Azad Razack","author_inst":"University of Malaya"},{"author_name":"Jay H Fowke","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Marija Gamulin","author_inst":"University of Zagreb School of Medicine"},{"author_name":"Nawaid Usmani","author_inst":"University of Alberta"},{"author_name":"Frank Claessens","author_inst":"KU Leuven"},{"author_name":"Jose Esteban Castelao","author_inst":"Instituto de Investigaci\u00f3n Biom\u00e9dica Galicia Sur"},{"author_name":"Gyorgy Petrovics","author_inst":"Uniformed Services University"},{"author_name":"Marie-\u00c9lise Parent","author_inst":"Institut national de la recherche scientifique"},{"author_name":"Jennifer J Hu","author_inst":"The University of Miami School of Medicine"},{"author_name":"Wei Zheng","author_inst":"Vanderbilt University Medical Center"},{"author_name":"- The Profile Study Steering Committee","author_inst":"-"},{"author_name":"- UKGPCS collaborators","author_inst":"-"},{"author_name":"Zsofia Kote-Jarai","author_inst":"The Institute of Cancer Research"},{"author_name":"Rosalind A Eeles","author_inst":"The Institute of Cancer Research"},{"author_name":"- The PRACTICAL Consortium","author_inst":"-"},{"author_name":"- VA Million Veteran Program","author_inst":"-"},{"author_name":"Kara N Maxwell","author_inst":"Corporal Michael Crescenz Veterans Affairs Medical Center"},{"author_name":"Jason L Vassy","author_inst":"VA Boston Healthcare System"},{"author_name":"Tyler M Seibert","author_inst":"VA San Diego Healthcare System"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Psychosocial mediators for the impact of personal genomic risk information on melanoma prevention and early detection behaviors","rel_doi":"10.64898\/2026.05.07.26352695","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352695","rel_abs":"Background: In the Melanoma Genomics Managing Your Risk Study, access to personal genomic risk testing led to improvements in some melanoma prevention and early detection behaviors. Purpose: We aimed to examine the hypothesized psychosocial mediators of the effects observed in the trial. Methods: Australians of European ancestry without melanoma and aged 18-69 years were recruited via the national Medicare database and randomized to receive personal genomic risk information or usual care (N=1,025). Questionnaires were administered at baseline, 1-month post-intervention, and 12-months post-baseline to assess self-reported prevention and early detection behaviors and psychosocial measures. To identify potential mediators, we first evaluated the intervention's effect on psychosocial measures and the associations between psychosocial measures and behavioral outcomes. We then estimated the natural indirect effects (NIEs) and their 95% confidence intervals (CIs) to quantify the effects mediated by potential mediators identified. Results: Among participants with high traditional melanoma risk, the intervention's effect on increased sun protection at 1-month was partially mediated by changes in perceived importance [NIE mean difference (95% CI): 0.02 (0.00, 0.04)] and perceived effectiveness [0.01 (0.00, 0.03)] of sun protection strategies. Among women, the intervention's effect on increased whole-body skin examinations at 1-month was partially mediated by perceived capability to engage in skin examinations [NIE odds ratio (95% CI): 1.08 (1.00, 1.29)] and perceived control over detecting a future melanoma [1.13 (1.03, 1.32)]. Conclusions: The effectiveness of precision prevention and early detection interventions may be enhanced by targeting key psychosocial mediators through tailored communication of personal melanoma risk.","rel_num_authors":5,"rel_authors":[{"author_name":"Sabrina E Wang","author_inst":"The Daffodil Centre, The University of Sydney, and Cancer Council NSW"},{"author_name":"David Espinoza","author_inst":"NHMRC Clinical Trials Centre, The University of Sydney"},{"author_name":"Serigne Lo","author_inst":"Melanoma Institute Australia, The University of Sydney"},{"author_name":"Amelia K Smit","author_inst":"The Daffodil Centre, The University of Sydney, and Cancer Council NSW"},{"author_name":"Anne  E. Cust","author_inst":"The Daffodil Centre, The University of Sydney, and Cancer Council NSW"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Decoding the diet-gut-liver axis: links between dietary pattern adherence, gut microbiome, and hepatic health","rel_doi":"10.64898\/2026.05.04.26352208","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.04.26352208","rel_abs":"Metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly becoming the leading cause of chronic liver disease and confers substantial cardiometabolic burden. Diet quality and gut microbiota composition have been implicated in MASLD development; however, the interplay among diet, gut microbiota, and hepatic health remains insufficiently characterized. Here, in 9,616 deeply phenotyped middle-aged participants (mean age 52 years) from the Human Phenotype Project, we investigated how five dietary quality indices capturing complementary dimensions of healthy eating, including plant-based (hPDI), Mediterranean-style (AMED), anti-inflammatory (rDII), anti-hyperinsulinemic (rEDIH), and overall quality (AHEI), relate to gut microbial composition and liver steatosis. Dietary pattern scores were derived from two-week continuous diet logs, gut microbiota was characterized by shotgun metagenomic sequencing, and hepatic health was assessed by both ultrasound-derived metrics and prevalent MASLD status. Adherence to each of the five healthy dietary patterns was inversely associated with MASLD prevalence and positively associated with liver speed of sound (SoS), an ultrasound-derived metric that correlates inversely with hepatic fat content. Across all five dietary patterns, greater adherence was consistently associated with 138 gut microbial species, including inverse associations with Flavonifractor plautii, Dysosmobacter welbionis, Ruthenibacterium lactatiformans, Bilophila wadsworthia, and Phocea massiliensis. These five species were also associated with lower liver SoS and higher odds of prevalent MASLD, emerging as potential mediators of the diet-liver relationship in cross-sectional mediation analyses after adjustment for body mass index (BMI). This study identifies candidate microbial targets for future interventional studies investigating dietary strategies for MASLD prevention.","rel_num_authors":10,"rel_authors":[{"author_name":"Keyong Deng","author_inst":"Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands"},{"author_name":"Quinten R. Ducarmon","author_inst":"Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, the Netherlands"},{"author_name":"Anastasia Godneva","author_inst":"Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. Department of Molecular Cell Biology, Weizmann Institute"},{"author_name":"Zheqing Zhang","author_inst":"Department of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University"},{"author_name":"Astrid van Hylckama Vlieg","author_inst":"Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands"},{"author_name":"Frits R. Rosendaal","author_inst":"Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands"},{"author_name":"Georg Zeller","author_inst":"Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, the Netherlands"},{"author_name":"Eran Segal","author_inst":"Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel; Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE"},{"author_name":"Ruifang Li-Gao","author_inst":"Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands"},{"author_name":"- DIYUFOOD consortium","author_inst":""}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Scalable deep-learning-based inference of time-varying transmission dynamics from outbreak phylogenies","rel_doi":"10.64898\/2026.05.07.26352673","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352673","rel_abs":"Infectious disease dynamics can be inferred from pathogen genomic data using phylodynamic methods, but the applicability of many such approaches to large data sets is constrained by computational cost. Recent deep-learning approaches to phylodynamics have improved scalability, yet challenges remain when genetic divergence is limited during fast spreading outbreaks. To address this, we use pathogen-specific models to show that deep-learning models trained on outbreak-like phylogenies can accurately estimate the reproductive number (R) when both the birth-death model and the expected phylogenetic resolution are matched to the target pathogen, highlighting the importance of realistic training conditions. Focusing on three major respiratory pathogens of public health importance (SARS-CoV-2, seasonal human influenza virus, and respiratory syncytial virus (RSV)), we introduce PhyloRt, a scalable framework for estimating the time-varying reproductive number (Rt) from large outbreak phylogenies. PhyloRt decomposes large trees into overlapping subtrees and applies a hierarchical deep-learning-based inference strategy to classify subtrees as exhibiting constant or time-varying reproduction numbers, enabling identifiable and computationally efficient estimation of Rt as a piecewise-constant trajectory through time. Applications to SARS-CoV-2 and influenza outbreaks show that PhyloRt recovers transmission dynamics consistent with estimates derived from mathematical epidemiological and Bayesian phylodynamic analyses. Our work enables scalable and rapid estimation of time-varying transmission dynamics from very large-scale outbreak genomic data sets, supporting real-time genomic epidemiology of emerging pathogens.","rel_num_authors":11,"rel_authors":[{"author_name":"RUOPENG XIE","author_inst":"University of Oxford"},{"author_name":"Anna Zhukova","author_inst":"Institut Pasteur"},{"author_name":"Pablo G. Pena","author_inst":"Real Jardin Botanico CSIC"},{"author_name":"Guillermo Iglesias","author_inst":"ETSI de Sistemas Informaticos"},{"author_name":"Shu Hu","author_inst":"Fudan University"},{"author_name":"Jiawei Wang","author_inst":"University of Bath"},{"author_name":"Tim K Tsang","author_inst":"University of Hong Kong"},{"author_name":"Vijaykrishna Dhanasekaran","author_inst":"Univesity of Hong Kong"},{"author_name":"Moritz U. G. Kraemer","author_inst":"University of Oxford"},{"author_name":"Oliver G. Pybus","author_inst":"University of Oxford"},{"author_name":"Olivier Gascuel","author_inst":"Museum National dHistoire Naturelle"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Patterns of emergency department use among young people with bipolar disorder: A data linkage cohort study","rel_doi":"10.64898\/2026.05.07.26352617","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352617","rel_abs":"Objective: To charactertise emergency department (ED) use among young people with bipolar disorder (BD) and compare patterns to those observed in anxiety, depressive, and psychotic disorders. Design, setting and participants: Data linkage study using administrative ED presentation records (January 2020 to October 2020) and a transdiagnostic youth mental health cohort of 2243 individuals aged 12-30 years in New South Wales, Australia. Main outcome measures: ED presentation patterns (any presentation, frequency, and rates) and reasons for presentation (mental health-related and non-mental health-related). Results: Of the 354 young people with BD, 309 (87.3%) presented to an ED at least once. ED presentation rates were higher for BD than for anxiety (incidence rate ratio [IRR]=1.82, p<.001) and depressive disorders (IRR=1.32, p<.001), but similar to psychotic disorders (IRR=0.91, p=.379). Differences were primarily driven by mental health-related presentations. Recurrent mental health presentations were associated with illness progression (clinical stage and functional impairment) rather than diagnosis. However, the likelihood of mental health-related presentations remained higher in BD compared with anxiety and depressive disorders after adjustment. Conclusions: Young people with BD have high rates of ED use, comparable to those with psychotic disorders. Although mental health-related presentations are more common in BD than in anxiety and depressive disorders, recurrence is largely explained by markers of illness progression. These findings highlight the need for community-based services that provide continuous and coordinated care for young people with complex mental health needs.","rel_num_authors":12,"rel_authors":[{"author_name":"Ashlee Turner Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Ian B Hickie Prof","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Mathew Varidel Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Nicholas Ho Mr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Catherine M McHugh Dr","author_inst":"Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney NSW Australia"},{"author_name":"Jacob J Crouse Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Joanne S Carpenter Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Alissa Nichles Ms","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Natalia Zmicerevska Ms","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Yun Ju (Christine) Song Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Elizabeth M Scott A\/Prof","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Frank Iorfino A\/Prof","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Patterns of emergency department use among young people with bipolar disorder: A data linkage cohort study","rel_doi":"10.64898\/2026.05.07.26352617","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352617","rel_abs":"Objective: To charactertise emergency department (ED) use among young people with bipolar disorder (BD) and compare patterns to those observed in anxiety, depressive, and psychotic disorders. Design, setting and participants: Data linkage study using administrative ED presentation records (January 2020 to October 2020) and a transdiagnostic youth mental health cohort of 2243 individuals aged 12-30 years in New South Wales, Australia. Main outcome measures: ED presentation patterns (any presentation, frequency, and rates) and reasons for presentation (mental health-related and non-mental health-related). Results: Of the 354 young people with BD, 309 (87.3%) presented to an ED at least once. ED presentation rates were higher for BD than for anxiety (incidence rate ratio [IRR]=1.82, p<.001) and depressive disorders (IRR=1.32, p<.001), but similar to psychotic disorders (IRR=0.91, p=.379). Differences were primarily driven by mental health-related presentations. Recurrent mental health presentations were associated with illness progression (clinical stage and functional impairment) rather than diagnosis. However, the likelihood of mental health-related presentations remained higher in BD compared with anxiety and depressive disorders after adjustment. Conclusions: Young people with BD have high rates of ED use, comparable to those with psychotic disorders. Although mental health-related presentations are more common in BD than in anxiety and depressive disorders, recurrence is largely explained by markers of illness progression. These findings highlight the need for community-based services that provide continuous and coordinated care for young people with complex mental health needs.","rel_num_authors":12,"rel_authors":[{"author_name":"Ashlee Turner Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Ian B Hickie Prof","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Mathew Varidel Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Nicholas Ho Mr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Catherine M McHugh Dr","author_inst":"Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney NSW Australia"},{"author_name":"Jacob J Crouse Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Joanne S Carpenter Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Alissa Nichles Ms","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Natalia Zmicerevska Ms","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Yun Ju (Christine) Song Dr","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Elizabeth M Scott A\/Prof","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"},{"author_name":"Frank Iorfino A\/Prof","author_inst":"Brain and Mind Centre, The University of Sydney, Sydney NSW Australia"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Self and Caregiver Reported Choice Making in Autistic Adults: Development and Validation of the AASPIRE Choices and Decisions Scale","rel_doi":"10.64898\/2026.05.07.26352693","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352693","rel_abs":"Self-determination has been assessed as an internal psychological construct. External factors may also affect self-determination, but opportunities to make choices and decisions remain understudied. We developed and evaluated the AASPIRE Choices and Decisions Scale (AASPIRE CDS), a new measure of autistic adults opportunities to make choices and decisions, using a community based participatory approach. We created and refined the AASPIRE CDS through an iterative process. Data, from the AASPIRE Outcomes Project, included 839 autistic adults participating through direct report, supported direct report, and caregiver report (CR). Exploratory and confirmatory analyses supported a unidimensional structure. Measurement invariance analyses supported configural, metric, and partial scalar invariance across report type without CR, and across living status, with and without CR. The AASPIRE CDS showed high internal consistency, test-retest reliability, and responsiveness to change over time. Convergent validity analyses showed that higher AASPIRE CDS scores were associated with greater self determination and communication fluency, more independent living, and fewer support needs. The AASPIRE-CDS showed weaker (albeit significant) associations with quality of life, overall health, and employment satisfaction than the self-determination measure showed with these variables. This pattern suggests that opportunities for choice-making are related to, but distinct from, commonly used measures of self-determination. Findings support the AASPIRE CDS as a valid and reliable measure of choice making opportunities in autistic adults across support needs but suggest caution interpreting CR. They underscore the importance of supporting autistic adults choice making and evaluating opportunities for choice alongside internal self determination. Future research should use larger CR samples to examine the validity of caregiver reported choice making opportunities.","rel_num_authors":15,"rel_authors":[{"author_name":"So Yoon Kim","author_inst":"Korea University"},{"author_name":"Kristen Gillespie-Lynch","author_inst":"City University of New York"},{"author_name":"Steven Kapp","author_inst":"University of Portsmouth"},{"author_name":"Liu-Qin Yang","author_inst":"Portland State University"},{"author_name":"Anna Furra Wallington","author_inst":"Academic Autism Spectrum Partnership in Research and Education"},{"author_name":"Dora Raymaker","author_inst":"Portland State University"},{"author_name":"Ian Moura","author_inst":"Brandeis University"},{"author_name":"Katherine McDonald","author_inst":"Syracuse University"},{"author_name":"Joelle Maslak","author_inst":"Academic Autism Spectrum Partnership in Research and Education"},{"author_name":"Rachel Kripke-Ludwig","author_inst":"Academic Autism Spectrum Partnership in Research and Education"},{"author_name":"Andrea Joyce","author_inst":"Academic Autism Spectrum Partnership in Research and Education"},{"author_name":"Willi Horner-Johnson","author_inst":"Oregon Health & Science University"},{"author_name":"Emanuel Frowner","author_inst":"Academic Autism Spectrum Partnership in Research and Education"},{"author_name":"Mary Baker-Ericzen","author_inst":"San Diego State University"},{"author_name":"Christina Nicolaidis","author_inst":"Portland State University"}],"rel_date":"2026-05-10","rel_site":"medrxiv"},{"rel_title":"Single-Cell Atlas of Renal Cell Carcinoma Brain Metastasis Uncovers Mechanisms of Immune Dysfunction and Resistance","rel_doi":"10.64898\/2026.05.06.722652","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.722652","rel_abs":"Brain metastasis (BM) in renal cell carcinoma (RCC) remains poorly understood and often resistant to immune checkpoint inhibitors. We generated a large single-nucleus RNA-seq data of RCC BM, profiling 14 BM samples alongside matched extracranial metastases and primary tumors. Tumor cells in BM displayed neuronal infiltration, neural-like adaptation, and marked remodeling of the microenvironment, including expansion of immunosuppressive myeloid cells and depletion of antigen-presenting dendritic cells. Tumor, immune, and stromal cells exhibited metabolic rewiring characterized by fatty-acid metabolism, oxidative phosphorylation, and MYC-driven programs. CD8 T cells showed terminal exhaustion and impaired proliferative capacity, and tertiary lymphoid structures were absent. Spatial profiling of 12 BM samples (13,128 cells) validated key cellular interactions, while ligand receptor analysis revealed immunoregulatory circuits between tumor, stromal, and immune cells. These findings define BM-specific adaptations that promote immune evasion and resistance, revealing therapeutic vulnerabilities in RCC BM.","rel_num_authors":22,"rel_authors":[{"author_name":"Mostafa I.H. Ali","author_inst":"Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA"},{"author_name":"Zeynep Feyza Akpinar","author_inst":"Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA"},{"author_name":"Jose A Ovando-Ricardez","author_inst":"Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA"},{"author_name":"Anna K. Casasent","author_inst":"Department of Hematopoietic Biology & Malignancy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Truong Nguyen Anh Lam","author_inst":"Department of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Jerome Lin","author_inst":"Department of Systems Biology, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Narmina Khanmammadova","author_inst":"Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA"},{"author_name":"Patrick K. Reville","author_inst":"Department of Medicine, Division of Hematology\/Oncology, Nuvance Health, Norwalk, CT"},{"author_name":"David J. H. Shih","author_inst":"School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China"},{"author_name":"Adeboye O. Osunkoya","author_inst":"Departments of Pathology and Urology, Emory University School of Medicine, Atlanta, GA, USA"},{"author_name":"Lisa M. Norberg","author_inst":"Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Tuan M. Tran","author_inst":"Department of Systems Biology, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Jianzhuo Li","author_inst":"Department of Systems Biology, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Anh G. Hoang","author_inst":"Department of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Sahin Hanalioglu","author_inst":"Department of Neurosurgery, Hacettepe University Faculty of Medicine, Ankara, Turkey"},{"author_name":"Mehmet Asim Bilen","author_inst":"Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA"},{"author_name":"Frederick Lang","author_inst":"Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, Texas"},{"author_name":"Jason T. Huse","author_inst":"Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Nicholas Navin","author_inst":"Department of Systems Biology, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Merve Hasanov","author_inst":"Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA"},{"author_name":"Eric Jonasch","author_inst":"Department of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"},{"author_name":"Elshad Hasanov","author_inst":"Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA"}],"rel_date":"2026-05-10","rel_site":"biorxiv"},{"rel_title":"The reliability and accuracy of recombination inferred by Shapeit2 duoHMM on whole genome sequence","rel_doi":"10.64898\/2026.05.06.723015","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.723015","rel_abs":"Few studies assessed the performance of population-based phasing combined with parental genotypes to infer recombination on whole genome sequence (WGS) data. In this study, our objective was to evaluate whether Shapeit2 duoHMM, a Hidden Markov Model using parental genotypes, infers recombination events reliably on WGS and with narrower intervals than SNP arrays. We based our analysis on the overlap between recombination events inferred by Merlin on SNP genotypes and Shapeit2 on WGS and SNP genotypes. We used a sample of 61 extended families from the GeneSTAR study with TopMED freeze 8 WGS on 580 sequenced subjects (60\\% of sample). Shapeit2 was run with a window size of 500 kilobases and 200 states on WGS. To mimic a SNP array, we extracted genotypes of 355,112 autosomal markers on the Illumina OmniExpress array. The number of recombination events per meiosis inferred by Shapeit2 on the WGS data (36.8) was aligned with the expected numbers over autosomes (35.7), although Merlin overestimated this number (115.0). 73% of Shapeit2 recombination events on WGS were detected by Merlin, a proportion rising to 91% when restricting to events also inferred by Shapeit2 on OmniExpress genotypes. Furthermore, Shapeit2 recombination intervals were narrower on WGS than OmniExpress genotypes (median of 4,530 bp vs. 49,458 bp). This suggests that Shapeit2 on WGS is a reliable and accurate method for inferring recombination events.","rel_num_authors":5,"rel_authors":[{"author_name":"Samir Oubninte","author_inst":"Laval University"},{"author_name":"Ingo Ruczinski","author_inst":"Johns Hopkins Bloomberg School of Public Health"},{"author_name":"Lisa R. Yanek","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Rasika Mathias","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Alexandre Bureau","author_inst":"Laval University"}],"rel_date":"2026-05-10","rel_site":"biorxiv"},{"rel_title":"Interactions of outer membrane lipoproteins P. aeruginosa PA3214 and E. coli PqiC with their MCE protein binding partners, PA3213 and PqiB","rel_doi":"10.64898\/2026.05.09.724024","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.09.724024","rel_abs":"Members of the Mammalian Cell Entry (MCE) superfamily interact with other proteins to form diverse architectures for the transport of hydrophobic molecules across the cell envelope in Gram-negative bacteria. Some of these trans-envelope MCE protein complexes include a PqiC-like outer membrane (OM) lipoprotein component. The best-studied member of this group of OM lipoproteins is E. coli PqiC, from the PqiABC system, which can form an octameric ring. How PqiC-like lipoproteins interact with their MCE protein binding partners to facilitate transport is not well understood. Here we report the cryo-electron microscopy structures of Pseudomonas aeruginosa PA3214, a homolog of PqiC, in the context of the full MCE transport PA3211-PA3214 system. Our structure provides insight into the biological assembly of the lipoprotein and interactions with its binding partner, MCE protein PA3213. We utilize deep mutational scanning to identify functionally important sites in E. coli PqiC in an unbiased manner. Through phenotypic and biochemical experiments, we characterize the interactions of the lipoproteins PqiC and PA3214 with their associated MCE proteins PqiB and PA3213, thus providing a model for how some MCE proteins employ a C-terminal peptide to mediate key interactions with their cognate lipoproteins at the OM.","rel_num_authors":5,"rel_authors":[{"author_name":"Sabrina I Giacometti","author_inst":"Johns Hopkins University"},{"author_name":"Nicolas Coudray","author_inst":"Johns Hopkins University"},{"author_name":"Rachel L Redler","author_inst":"Freie Universitaet Berlin"},{"author_name":"Gira Bhabha","author_inst":"Johns Hopkins University"},{"author_name":"Damian C Ekiert","author_inst":"Johns Hopkins University"}],"rel_date":"2026-05-10","rel_site":"biorxiv"},{"rel_title":"De-Darwinizing the proteome: the genome as the original germ line","rel_doi":"10.64898\/2026.05.06.723269","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.723269","rel_abs":"A hallmark of evolutionary transitions in individuality is the suppression of lower-level Darwinian dynamics through germ-soma specialization. The RNA world hypothesis posits that early life arose through ribozymes, RNA molecules that functioned as both catalysts and hereditary units, housed within protocells. This dual role is the chief appeal of the RNA world framework, because it makes ribozymes capable of open-ended Darwinian evolution. It is also its chief liability. Each ribozyme is a fully Darwinian entity: it replicates, accumulates mutations via Muller's ratchet, and can be displaced by selfish variants that replicate faster but contribute less to collective function. We show that between-protocell selection, even when strong, cannot overcome this within-cell evolutionary erosion, particularly as protocells evolve increased complexity by increasing the number of ribozyme types they contain. The origin of an informational RNA genome, translated by an ancient ribosome into protein enzymes, resolves this conflict by producing a functional workforce that is non-heritable. Protein-based enzymes are stripped of their evolutionary agency, confining heritable variation to the genome and entrenching the protocell as the primary level of Darwinian individuality. The genome, in this view, is not merely a storage device but the original germ line, and its origin marks the point at which cellular life became capable of open-ended growth in complexity.","rel_num_authors":1,"rel_authors":[{"author_name":"William Ratcliff","author_inst":"Georgia Institute of Technology"}],"rel_date":"2026-05-10","rel_site":"biorxiv"},{"rel_title":"Impact of Age on Heroin Intravenous Self-Administration in Wistar Rats","rel_doi":"10.64898\/2026.05.05.723054","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723054","rel_abs":"Background: Evidence suggests steeper accelerating opioid-related overdose, and non-medical use rates, in middle aged men in recent years compared with younger cohorts. Little is known about whether this is driven by age-related differences in the effects of opioids compared with socio-cultural factors driving non-medical consumption. Rodent models can be useful for dissociating biological from psychosocial factors, however, only minimal evidence exists on the effects of opioids in middle-age rats. Objective: To determine if the anti-nociceptive and rewarding effects of opioids differ between adult and middle-age rats. Methods: Female and male Wistar rats were obtained in early adulthood and examined across 4 to 11 months of age for nociceptive responses to heroin (0-1.56 mg\/kg, s.c.) using a warm-water tail withdrawal assay. Subgroups (N=8 per group) were initiated on intravenous self-administration (IVSA) of heroin at either 5 months or 12 months of age. Results: Anti-nociceptive effects of heroin did not differ across age. Female rats that initiated IVSA in early adulthood or middle-age obtained significantly more infusions of heroin than male rats of the same age during acquisition, and in dose-substitution under a FR1 schedule. Male, but not female, rats that initiated IVSA in middle age self-administered less heroin then rats that initiated in early adulthood; this was observed in acquisition and in dose-substitution. Discussion: This study shows that opioid reward is diminished in middle aged male rats. It also found that middle age rats can be used effectively to model opioid-related outcomes, including drug seeking using the IVSA procedure.","rel_num_authors":4,"rel_authors":[{"author_name":"Michael A Taffe","author_inst":"University of California, San Diego"},{"author_name":"Sydney L Mehl","author_inst":"University of California, San Diego"},{"author_name":"Yanabel Grant","author_inst":"University of California, San Diego"},{"author_name":"Sophia A Vandewater","author_inst":"University of California, San Diego"}],"rel_date":"2026-05-10","rel_site":"biorxiv"},{"rel_title":"IRES-TrAPPr reveals novel insights into viral and cellular mRNA translation","rel_doi":"10.64898\/2026.05.06.723280","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.723280","rel_abs":"Ribosome recruitment to human mRNAs is thought to occur primarily via cap-dependent initiation (CDI). This process is suppressed during a variety of cellular stresses, including viral infection, suggesting stress-response genes and viral mRNAs use alternative mechanisms to initiate translation. Indeed, many viruses recruit ribosomes directly via Internal Ribosome Entry Sites (IRESes). Hundreds of human mRNAs have been reported to also contain IRESes due to their ability to enhance expression in bicistronic and backspliced circRNA plasmid reporters. These DNA-based screens also reported hundreds of novel IRESes from more than fifty human viruses. However, such assays are prone to false-positives due to promoter and splicing activity, do not compare CDI and IRES translation, and lack the temporal resolution necessary for stress-response studies. To address these issues, we developed IRES-Translating Affinity Protein Profiling (IRES-TrAPPr), a massively parallel reporter assay that simultaneously quantifies CDI and IRES activity from thousands of co-transfected mRNAs. We validated this new method using luciferase assays and structure-function analyses of established viral IRESes, demonstrating exquisite sensitivity and specificity. Using IRES-TrAPPr, we quantified the activities of IRES elements from hundreds of viruses from a diversity of hosts. Our results provide evidence that viral IRESes from warm-blooded hosts have adapted higher structural stability to maintain folding at higher temperatures. Finally, we find hundreds of candidate human and viral IRESes from DNA-based screens have negligible IRES activity. Altogether, our results show that IRES-TrAPPr provides a novel, accurate platform for IRES research.","rel_num_authors":2,"rel_authors":[{"author_name":"Gemma E May","author_inst":"Carnegie Mellon University"},{"author_name":"Joel McManus","author_inst":"Carnegie Mellon University"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Building an open ecosystem for molecular neuroimaging: standards and tools from the OpenNeuroPET initiative","rel_doi":"10.64898\/2026.05.06.722876","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.722876","rel_abs":"Molecular neuroimaging with positron emission tomography (PET) and single-photon emission computed tomography (SPECT) enables quantification of specific molecular targets in the living brain. Despite its scientific impact, molecular neuroimaging research has historically faced challenges due to high costs, small sample sizes, laboratory-specific analysis pipelines, and limited large-scale data sharing. These factors have hindered reproducibility and the broader reuse of valuable PET datasets. The OpenNeuroPET initiative was established to address these barriers by developing standards, infrastructure, and open-source tools for organizing, sharing, and analyzing molecular neuroimaging data. Through collaborations across Europe and North America, OpenNeuroPET has supported the PET extension of the Brain Imaging Data Structure (PET-BIDS), providing a standardized framework for PET datasets and metadata. Building on PET-BIDS, tools such as PET2BIDS, ezBIDS, and BIDSCoin facilitate data conversion and curation. In parallel, OpenNeuro now hosts PET-BIDS datasets for open sharing, while complementary platforms such as PublicnEUro enable GDPR-compliant controlled access. Emerging open-source workflows and BIDS applications further support automated, reproducible PET preprocessing and quantitative analysis, promoting harmonized processing across centers. Together, these developments mark an important step toward an open molecular neuroimaging ecosystem in which datasets, software, and workflows can be transparently shared, reused, and scaled for collaborative research.","rel_num_authors":20,"rel_authors":[{"author_name":"Melanie Ganz","author_inst":"Neurobiology Research Unit, Rigshospitalet, Denmark; Department of Computer Science, University of Copenhagen, Denmark"},{"author_name":"Martin Norgaard","author_inst":"Department of Computer Science, University of Copenhagen, Denmark; Molecular Imaging Branch, National Institute of Mental Health (NIMH), United States"},{"author_name":"Cyril Pernet","author_inst":"Neurobiology Research Unit, Rigshospitalet, Denmark"},{"author_name":"Granville J. Matheson","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden"},{"author_name":"Anthony Galassi","author_inst":"Molecular Imaging Branch, National Institute of Mental Health (NIMH), United States"},{"author_name":"Eric G. Ceballos","author_inst":"Montreal Neurological Institute, McGill University, Canada"},{"author_name":"Paul Wighton","author_inst":"Martinos Center Massachusetts General Hospital, United States"},{"author_name":"Murat Bilgel","author_inst":"National Institute on Aging (NIA), United States"},{"author_name":"Cyrus Eierud","author_inst":"Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory "},{"author_name":"Gabriel Gonzalez-Escamilla","author_inst":"Department of Neurology, Saarland University, Homburg, Saarland, Germany"},{"author_name":"Joshua Buckholtz","author_inst":"Department of Psychology, Stanford University, United States"},{"author_name":"Ross Blair","author_inst":"Department of Psychology, Stanford University, United States"},{"author_name":"Christopher J Markiewicz","author_inst":"Department of Psychology, Stanford University, United States"},{"author_name":"Nell Hardcastle","author_inst":"Department of Psychology, Stanford University, United States"},{"author_name":"Douglas N. Greve","author_inst":"Martinos Center Massachusetts General Hospital, United States; Harvard Medical School, United States"},{"author_name":"Adam G. Thomas","author_inst":"Data Science and Sharing Team, National Institute of Mental Health (NIMH), United States"},{"author_name":"Russell A. Poldrack","author_inst":"Department of Psychology, Stanford University, United States"},{"author_name":"Vince D. Calhoun","author_inst":"Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory "},{"author_name":"Robert B. Innis","author_inst":"Molecular Imaging Branch, National Institute of Mental Health (NIMH), United States"},{"author_name":"Gitte M. Knudsen","author_inst":"Neurobiology Research Unit, Rigshospitalet, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Flowable Grafts Made from Granular Extracellular Matrix (gECM) Hydrogels Promote Integrative Repair of Articular Cartilage in a Large-Animal Model","rel_doi":"10.64898\/2026.05.05.723111","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723111","rel_abs":"Focal injuries to articular cartilage in load-bearing joints fail to heal and often progress to degeneration, underscoring the need for repair strategies that result in restored cartilage structure and function rather than fibrocartilage formation. Granular extracellular matrix (gECM) hydrogels, flowable grafts composed of densely-packed matrix particles, offer a promising approach but lack long-term functional validation in large-animal models. Here, we developed a flowable gECM hydrogel composed of decellularized cartilage microparticles incorporated within a thiol-functionalized hyaluronan matrix. Proteomic analysis confirmed enrichment of cartilage-specific gECM matrisome components. When implanted into critical-sized femoral condyle defects in a goat model and evaluated 12 months post-implantation, both gECM hydrogel and microdrilling (surgical controls) achieved >80% defect filling. However, in contrast to microdrilling, gECM repair tissue exhibited surface tribological (friction, adhesion) and compressive mechanical properties comparable to native cartilage, with a similar proteoglycan-to-collagen ratio, enrichment of type II collagen, minimal type I collagen (typical of a fibrous scar), improved quantitative MRI metrics, and evidence of lateral cartilage integration and subchondral bone remodeling. Together, these findings demonstrate that a flowable gECM hydrogel supports integrative, cartilage-like repair in a load-bearing joint, supporting advancement of this approach toward clinical translation.","rel_num_authors":18,"rel_authors":[{"author_name":"Jeanne Barthold","author_inst":"University of Colorado Boulder"},{"author_name":"Juliet Heye","author_inst":"University of Colorado Boulder"},{"author_name":"Kaitlin McCreery","author_inst":"University of Colorado Boulder"},{"author_name":"Lea Savard","author_inst":"University of Colorado Boulder"},{"author_name":"Katie Bisazza","author_inst":"Colorado State University"},{"author_name":"Emily Miller","author_inst":"University of Colorado Boulder"},{"author_name":"Hongtian Zhu","author_inst":"University of Colorado Boulder"},{"author_name":"Woowon Lee","author_inst":"University of Colorado Boulder"},{"author_name":"Maxwell C McCabe","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"David Ceja Galindo","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Shannon Blanco","author_inst":"University of Colorado Boulder"},{"author_name":"Virginia Ferguson","author_inst":"University of Colorado Boulder"},{"author_name":"Nancy Emery","author_inst":"University of Colorado Boulder"},{"author_name":"Brian C Johnstone","author_inst":"Oregon Health & Science University"},{"author_name":"Benjamin Gadomski","author_inst":"Colorado State University"},{"author_name":"Stephanie Ellyse Schneider","author_inst":"University of Colorado Boulder"},{"author_name":"Jeremiah Easley","author_inst":"Colorado State University"},{"author_name":"Corey P Neu","author_inst":"University of Colorado Boulder"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations","rel_doi":"10.64898\/2026.05.05.723059","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723059","rel_abs":"High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses' Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKB's original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.","rel_num_authors":30,"rel_authors":[{"author_name":"Linke Li","author_inst":"Massachusetts General Hospital"},{"author_name":"Ahmed Alaa","author_inst":"University of California, Berkeley"},{"author_name":"Youxin Tan","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Ilker Demirel","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Samuel Friedman","author_inst":"Broad Institute of Harvard and MIT"},{"author_name":"Qiayi Zha","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Russell P. Trac","author_inst":"University of Vermont"},{"author_name":"Kent D. Taylor","author_inst":"The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center"},{"author_name":"Bing Yu","author_inst":"University of Texas Health Science Center at Houston"},{"author_name":"Christie M. Ballantyne","author_inst":"Baylor College of Medicine"},{"author_name":"Rajat Deo","author_inst":"University of Pennsylvania"},{"author_name":"Ruth Dubin","author_inst":"University of Texas Southwestern Medical Center"},{"author_name":"Michael Y. Tsai","author_inst":"University of Minnesota Medical School"},{"author_name":"Gina M. Peloso","author_inst":"Boston University School of Public Health"},{"author_name":"Jennifer Brody","author_inst":"University of Washington"},{"author_name":"Tom Austin","author_inst":"University of Washington"},{"author_name":"Bruce M. Psaty","author_inst":"University of Washington"},{"author_name":"Jayna Nicholas","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Laura M. Raffield","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Usman Tahir","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Josef Coresh","author_inst":"NYU Grossman School of Medicine"},{"author_name":"Whitney Hornsby","author_inst":"Mass General Brigham"},{"author_name":"Andrew Chan","author_inst":"Mass General Hospital"},{"author_name":"Stephen S. Rich","author_inst":"University of Virginia"},{"author_name":"Jerome I. Rotter","author_inst":"The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center"},{"author_name":"Peter Ganz","author_inst":"University of California San Francisco"},{"author_name":"Robert Gerszten","author_inst":"Mass General Brigham"},{"author_name":"Anthony Philippakis","author_inst":"Google Ventures"},{"author_name":"Pradeep Natarajan","author_inst":"Mass General Hospital"},{"author_name":"Zhi Yu","author_inst":"Mass General Hospital"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations","rel_doi":"10.64898\/2026.05.05.723059","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723059","rel_abs":"High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses' Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKB's original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.","rel_num_authors":30,"rel_authors":[{"author_name":"Linke Li","author_inst":"Massachusetts General Hospital"},{"author_name":"Ahmed Alaa","author_inst":"University of California, Berkeley"},{"author_name":"Youxin Tan","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Ilker Demirel","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Samuel Friedman","author_inst":"Broad Institute of Harvard and MIT"},{"author_name":"Qiayi Zha","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Russell P. Trac","author_inst":"University of Vermont"},{"author_name":"Kent D. Taylor","author_inst":"The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center"},{"author_name":"Bing Yu","author_inst":"University of Texas Health Science Center at Houston"},{"author_name":"Christie M. Ballantyne","author_inst":"Baylor College of Medicine"},{"author_name":"Rajat Deo","author_inst":"University of Pennsylvania"},{"author_name":"Ruth Dubin","author_inst":"University of Texas Southwestern Medical Center"},{"author_name":"Michael Y. Tsai","author_inst":"University of Minnesota Medical School"},{"author_name":"Gina M. Peloso","author_inst":"Boston University School of Public Health"},{"author_name":"Jennifer Brody","author_inst":"University of Washington"},{"author_name":"Tom Austin","author_inst":"University of Washington"},{"author_name":"Bruce M. Psaty","author_inst":"University of Washington"},{"author_name":"Jayna Nicholas","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Laura M. Raffield","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Usman Tahir","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Josef Coresh","author_inst":"NYU Grossman School of Medicine"},{"author_name":"Whitney Hornsby","author_inst":"Mass General Brigham"},{"author_name":"Andrew Chan","author_inst":"Mass General Hospital"},{"author_name":"Stephen S. Rich","author_inst":"University of Virginia"},{"author_name":"Jerome I. Rotter","author_inst":"The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center"},{"author_name":"Peter Ganz","author_inst":"University of California San Francisco"},{"author_name":"Robert Gerszten","author_inst":"Mass General Brigham"},{"author_name":"Anthony Philippakis","author_inst":"Google Ventures"},{"author_name":"Pradeep Natarajan","author_inst":"Mass General Hospital"},{"author_name":"Zhi Yu","author_inst":"Mass General Hospital"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"A distributed neural architecture of sustained affect across external and internal experience","rel_doi":"10.64898\/2026.05.05.723090","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723090","rel_abs":"Sustained affect shapes well-being, yet its neural architecture across externally elicited and internally generated experience remains unclear. Using whole-brain functional connectivity during minutes-long naturalistic movie viewing, we derived positive and negative affective experience signatures and their underlying neural architecture. These signatures predicted valence-specific affective intensity and generalized to independent movie-viewing data and internally generated affect, discriminating sad memory and rumination from neutral distraction while tracking subjective experience. Importantly, their expression showed little relation to vigilance or cognitive demand. Characterization of these signatures revealed coherent community structure and a shared distributed backbone, alongside valence-preferential components, consistent with a partially separable architecture. Extending beyond experimentally evoked states, in four resting-state depression cohorts, these signatures distinguished patients from controls with reduced positive and elevated negative signature expression, and predicted symptom burden and anhedonia. These findings identify a generalizable distributed architecture bridging external and internal affective experience and extending to clinically relevant affective dysregulation.","rel_num_authors":11,"rel_authors":[{"author_name":"Ran Zhang","author_inst":"Southwest University"},{"author_name":"Debo Dong","author_inst":"Southwest University"},{"author_name":"Xianyang Gan","author_inst":"University of Electronic Science and Technology of China"},{"author_name":"Sarah Genon","author_inst":"Research Centre Julich"},{"author_name":"Simon B Eickhoff","author_inst":"Research Centre Julich"},{"author_name":"Ting Xu","author_inst":"Southwest University"},{"author_name":"Bing Cao","author_inst":"Southwest University"},{"author_name":"Qinghua He","author_inst":"Southwest University"},{"author_name":"Tingyong Feng","author_inst":"Southwest University"},{"author_name":"Benjamin Becker","author_inst":"The University of Hong Kong"},{"author_name":"Feng Zhou","author_inst":"Southwest University"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"A framework for quantifying the mechanics of dexterous grasp","rel_doi":"10.64898\/2026.05.05.723084","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723084","rel_abs":"A hallmark of primate behavior is the exceptional ability to dexterously grasp and manipulate objects, yet the investigation of the neural mechanisms that support manual dexterity has been hindered by technical challenges. Optical hand tracking is complicated by frequent occlusions, and contact forces are hard to measure with sufficient precision. Furthermore, while monitoring the kinematics during reaching phase, and the contact forces during object manipulation phase is difficult, joint torques are impossible to measure directly. While challenging, the ability to estimate joint torques in the complex primate hand could provide an invaluable continuous mechanical description spanning both phases. With this in mind, we have developed an experimental apparatus and data processing pipeline for quantifying these variables describing prehension. The apparatus presented objects of various sizes and orientations throughout the workspace, evoking different grasping strategies. Object surfaces were instrumented with thousands of pressure-sensitive elements, enabling high-resolution measurement of distributed contact forces. Simultaneously, eight high-speed cameras were used to reconstruct hand and arm movements with markerless tracking, triangulating 3D landmarks, and mapping them onto a musculoskeletal model, enabling estimation of time-varying joint angles. This posture quantification allowed contact forces to be automatically assigned to specific hand segments, in close agreement with manual human annotations. We used the reconstructed movements and contact forces with the musculoskeletal model of the hand to compute inverse dynamics, yielding joint torques throughout behavior, unifying the hand kinematics and grasp forces into a single physical description. Throughout the processing, we identified individual neurons in the motor cortex of monkeys that were related to grasp force, kinematics, and torques. Together, this framework enabled a comprehensive and precise physical characterization of primate manual behavior, providing a foundation for investigating the neural mechanisms of manual dexterity.","rel_num_authors":14,"rel_authors":[{"author_name":"Anton R Sobinov","author_inst":"University of Chicago"},{"author_name":"Xuan Ma","author_inst":"Northwestern University"},{"author_name":"Elizaveta V Okorokova","author_inst":"University of Chicago"},{"author_name":"Charles M Greenspon","author_inst":"University of Chicago"},{"author_name":"Caleb Raman","author_inst":"University of Chicago"},{"author_name":"Natalya Shelchkova","author_inst":"University of Chicago"},{"author_name":"Qinpu He","author_inst":"University of Chicago"},{"author_name":"Neema Darabi","author_inst":"University of Chicago"},{"author_name":"Rashi Bhatt","author_inst":"University of Chicago"},{"author_name":"Patrick Jordan","author_inst":"University of Chicago"},{"author_name":"Paul Arters","author_inst":"University of Chicago"},{"author_name":"Nicholas G Hatsopoulos","author_inst":"University of Chicago"},{"author_name":"Lee E Miller","author_inst":"Northwestern University"},{"author_name":"Sliman J Bensmaia","author_inst":"University of Chicago"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Comprehensive Lineage Tracing Maps the Landscape of Cell Fate Decisions in Mouse Embryogenesis","rel_doi":"10.64898\/2026.05.07.722278","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.722278","rel_abs":"A comprehensive cell fate map of mammalian embryogenesis has remained out of reach due to the scale, cellular diversity, and non-deterministic nature of development in utero. Here, we use PEtracer to continuously install heritable genetic marks as cells divide, reconstructing lineage trees that resolve ~75% of cell divisions across >1.5 million cells from 16 mouse embryos collected at half-day intervals from E7.5-E10.0. We pair these trees with deep transcriptional profiling to chart the landscape of cell fate decisions during gastrulation and early organogenesis. Using these data, we quantify cell fate biases, restriction timing, progenitor pool sizes, and lineage relationships across the embryo, revealing strikingly reproducible lineage architecture across replicate embryos despite the regulative flexibility of mammalian development. We further show how lineage, spatial position, and signaling jointly determine fate outcomes and timing, with their relative influence varying by tissue. This dataset provides a quantitative framework for understanding cell fate specification and a lineage-resolved reference for generating and contextualizing developmental hypotheses at organismal scale.","rel_num_authors":18,"rel_authors":[{"author_name":"William N. Colgan","author_inst":"Whitehead Institute"},{"author_name":"Luke W. Koblan","author_inst":"Whitehead Institute"},{"author_name":"JoAnne Villagrana","author_inst":"Yale School of Medicine"},{"author_name":"Tien-Chi Jason Hou","author_inst":"Yale School of Medicine"},{"author_name":"Minming Wang","author_inst":"Yale School of Medicine"},{"author_name":"Gokul Gowri","author_inst":"Whitehead Institute"},{"author_name":"Whitney Chandler","author_inst":"Whitehead Institute"},{"author_name":"Leonardo A. Sepulveda","author_inst":"Harvard University"},{"author_name":"Didar Ciftci","author_inst":"Harvard University"},{"author_name":"Karina Smolyar","author_inst":"Whitehead Institute"},{"author_name":"Alicia Young","author_inst":"Whitehead Institute"},{"author_name":"Lars Wittler","author_inst":"Max Planck Institute of Molecular Genetics"},{"author_name":"Styliani Markoulaki","author_inst":"Whitehead Institute"},{"author_name":"Kyle M Loh","author_inst":"Stanford University"},{"author_name":"Xiaowei Zhuang","author_inst":"Harvard University \/ HHMI"},{"author_name":"Nir Yosef","author_inst":"Weizmann Institute of Science"},{"author_name":"Zachary D. Smith","author_inst":"Yale School of Medicine"},{"author_name":"Jonathan S. Weissman","author_inst":"Whitehead Institute"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Comprehensive Lineage Tracing Maps the Landscape of Cell Fate Decisions in Mouse Embryogenesis","rel_doi":"10.64898\/2026.05.07.722278","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.722278","rel_abs":"A comprehensive cell fate map of mammalian embryogenesis has remained out of reach due to the scale, cellular diversity, and non-deterministic nature of development in utero. Here, we use PEtracer to continuously install heritable genetic marks as cells divide, reconstructing lineage trees that resolve ~75% of cell divisions across >1.5 million cells from 16 mouse embryos collected at half-day intervals from E7.5-E10.0. We pair these trees with deep transcriptional profiling to chart the landscape of cell fate decisions during gastrulation and early organogenesis. Using these data, we quantify cell fate biases, restriction timing, progenitor pool sizes, and lineage relationships across the embryo, revealing strikingly reproducible lineage architecture across replicate embryos despite the regulative flexibility of mammalian development. We further show how lineage, spatial position, and signaling jointly determine fate outcomes and timing, with their relative influence varying by tissue. This dataset provides a quantitative framework for understanding cell fate specification and a lineage-resolved reference for generating and contextualizing developmental hypotheses at organismal scale.","rel_num_authors":18,"rel_authors":[{"author_name":"William N. Colgan","author_inst":"Whitehead Institute"},{"author_name":"Luke W. Koblan","author_inst":"Whitehead Institute"},{"author_name":"JoAnne Villagrana","author_inst":"Yale School of Medicine"},{"author_name":"Tien-Chi Jason Hou","author_inst":"Yale School of Medicine"},{"author_name":"Minming Wang","author_inst":"Yale School of Medicine"},{"author_name":"Gokul Gowri","author_inst":"Whitehead Institute"},{"author_name":"Whitney Chandler","author_inst":"Whitehead Institute"},{"author_name":"Leonardo A. Sepulveda","author_inst":"Harvard University"},{"author_name":"Didar Ciftci","author_inst":"Harvard University"},{"author_name":"Karina Smolyar","author_inst":"Whitehead Institute"},{"author_name":"Alicia Young","author_inst":"Whitehead Institute"},{"author_name":"Lars Wittler","author_inst":"Max Planck Institute of Molecular Genetics"},{"author_name":"Styliani Markoulaki","author_inst":"Whitehead Institute"},{"author_name":"Kyle M Loh","author_inst":"Stanford University"},{"author_name":"Xiaowei Zhuang","author_inst":"Harvard University \/ HHMI"},{"author_name":"Nir Yosef","author_inst":"Weizmann Institute of Science"},{"author_name":"Zachary D. Smith","author_inst":"Yale School of Medicine"},{"author_name":"Jonathan S. Weissman","author_inst":"Whitehead Institute"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Selective Elimination of TP53 Mutant Cells by Transcript-Activated Chromatin Shredding","rel_doi":"10.64898\/2026.05.08.723607","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.08.723607","rel_abs":"Genetic mutations that drive cancer often occur in tumor suppressor proteins, including the p53 transcription factor which is altered in ~40-50% of cases1,2. However, current therapies fail to target most such mutations because the mutant proteins typically lack defined drug-binding pockets, and restoring the endogenous function has proven challenging. Here, we programmed CRISPR-Cas12a2, an RNA-guided nuclease with trans-nucleolytic cleavage activities3,4, to selectively kill cancer cells by targeting cancer-specific transcripts. This approach eliminates cells by inducing trans chromatin cleavage, triggering DNA damage and cell death. Unlike existing methods, RNA-guided Cas12a2 senses cellular RNA signatures to shred chromatin, enabling precise targeting of undruggable mutations. Transcript-activated chromatin shredding provides an innovative paradigm to develop precision disease treatments for undruggable targets.","rel_num_authors":21,"rel_authors":[{"author_name":"Jingkun Zeng","author_inst":"Gladstone Institutes; Innovative Genomics Institute, UC Berkeley"},{"author_name":"Zhiyuan Cheng","author_inst":"Gladstone Institutes"},{"author_name":"Huadong Chen","author_inst":"UCSF"},{"author_name":"Jared Thompson","author_inst":"University of Utah School of Medicine"},{"author_name":"Kadin T Crosby","author_inst":"Utah State University"},{"author_name":"Hesong Hang","author_inst":"Innovative Genomics Institute, University of California, Berkeley"},{"author_name":"Wayne Ngo","author_inst":"Gladstone Institutes; Innovative Genomics Institute, UC Berkeley"},{"author_name":"Chenglong Xia","author_inst":"Innovative Genomics Institute, UC Berkeley"},{"author_name":"Daniel Rosas-Rivera","author_inst":"Gladstone Institutes"},{"author_name":"Min Hyung Kang","author_inst":"Innovative Genomics Institute, UC Berkeley"},{"author_name":"Ying Mao","author_inst":"UCSF"},{"author_name":"Giselle Lee","author_inst":"The Francis Crick Institutes"},{"author_name":"John F.X. Diffley","author_inst":"The Francis Crick Institute"},{"author_name":"Yixuan Song","author_inst":"The Francis Crick Institute"},{"author_name":"Longhui Qiu","author_inst":"UCSF"},{"author_name":"Nathan M Krah","author_inst":"University of Utah School of Medicine"},{"author_name":"Niren Murthy","author_inst":"UC Berkeley"},{"author_name":"Ryan N Jackson","author_inst":"Utah State University"},{"author_name":"Yang Liu","author_inst":"University of Utah School of Medicine"},{"author_name":"Alan Ashworth","author_inst":"UCSF"},{"author_name":"Jennifer A Doudna","author_inst":"Gladstone Institutes; Innovative Genomics Institute, UC Berkeley; HHMI"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Selective Elimination of TP53 Mutant Cells by Transcript-Activated Chromatin Shredding","rel_doi":"10.64898\/2026.05.08.723607","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.08.723607","rel_abs":"Genetic mutations that drive cancer often occur in tumor suppressor proteins, including the p53 transcription factor which is altered in ~40-50% of cases1,2. However, current therapies fail to target most such mutations because the mutant proteins typically lack defined drug-binding pockets, and restoring the endogenous function has proven challenging. Here, we programmed CRISPR-Cas12a2, an RNA-guided nuclease with trans-nucleolytic cleavage activities3,4, to selectively kill cancer cells by targeting cancer-specific transcripts. This approach eliminates cells by inducing trans chromatin cleavage, triggering DNA damage and cell death. Unlike existing methods, RNA-guided Cas12a2 senses cellular RNA signatures to shred chromatin, enabling precise targeting of undruggable mutations. Transcript-activated chromatin shredding provides an innovative paradigm to develop precision disease treatments for undruggable targets.","rel_num_authors":21,"rel_authors":[{"author_name":"Jingkun Zeng","author_inst":"Gladstone Institutes; Innovative Genomics Institute, UC Berkeley"},{"author_name":"Zhiyuan Cheng","author_inst":"Gladstone Institutes"},{"author_name":"Huadong Chen","author_inst":"UCSF"},{"author_name":"Jared Thompson","author_inst":"University of Utah School of Medicine"},{"author_name":"Kadin T Crosby","author_inst":"Utah State University"},{"author_name":"Hesong Hang","author_inst":"Innovative Genomics Institute, University of California, Berkeley"},{"author_name":"Wayne Ngo","author_inst":"Gladstone Institutes; Innovative Genomics Institute, UC Berkeley"},{"author_name":"Chenglong Xia","author_inst":"Innovative Genomics Institute, UC Berkeley"},{"author_name":"Daniel Rosas-Rivera","author_inst":"Gladstone Institutes"},{"author_name":"Min Hyung Kang","author_inst":"Innovative Genomics Institute, UC Berkeley"},{"author_name":"Ying Mao","author_inst":"UCSF"},{"author_name":"Giselle Lee","author_inst":"The Francis Crick Institutes"},{"author_name":"John F.X. Diffley","author_inst":"The Francis Crick Institute"},{"author_name":"Yixuan Song","author_inst":"The Francis Crick Institute"},{"author_name":"Longhui Qiu","author_inst":"UCSF"},{"author_name":"Nathan M Krah","author_inst":"University of Utah School of Medicine"},{"author_name":"Niren Murthy","author_inst":"UC Berkeley"},{"author_name":"Ryan N Jackson","author_inst":"Utah State University"},{"author_name":"Yang Liu","author_inst":"University of Utah School of Medicine"},{"author_name":"Alan Ashworth","author_inst":"UCSF"},{"author_name":"Jennifer A Doudna","author_inst":"Gladstone Institutes; Innovative Genomics Institute, UC Berkeley; HHMI"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"ATR enforcement of the S\/G2 checkpoint prevents premature S phase shutdown and genome instability","rel_doi":"10.64898\/2026.05.07.723638","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723638","rel_abs":"The ATR-enforced S\/G2 checkpoint activates during DNA replication to restrain CDK1-dependent phosphorylation of FOXM1 and subsequent transactivation of the G2\/M gene network until the end of S phase. However, the extent to which this checkpoint ensures the completion of DNA replication and whether it safeguards genomic integrity has remained unknown. Here, we induce S\/G2 checkpoint failure throughout S phase in non-malignant human epithelial cells using multiple ATR pathway inhibitors. Consequently, the mitotic kinase complex cyclin B1-CDK1 prematurely shuts-down the DNA replication program, preventing the completion of genome duplication. In turn, this leads to the retention of inactive replisomes on chromatin and unfired origins into the G2 phase, which induce subsequent accumulation of pan-nuclear {gamma}H2AX and mitotic failure. Collectively, these findings indicate the S\/G2 checkpoint ensures replication completion and genome stability.","rel_num_authors":2,"rel_authors":[{"author_name":"Melissa J McEvoy","author_inst":"Oregon Health and Science University"},{"author_name":"Joshua C Saldivar","author_inst":"Oregon Health and Science University"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Cohesin bridging as a physical principle of enhancer-promoter communication","rel_doi":"10.64898\/2026.05.07.723561","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723561","rel_abs":"Central to genome function, enhancers are non-coding sequences that can control transcription from promoters hundreds of kilobases away. Yet the physical basis of this long-range communication remains unclear. A prevalent view is that enhancers activate promoters when the two elements come into spatial proximity through the 3D folding of chromatin. However, activation by spatial proximity alone has struggled to explain several core features of enhancer function. Here, we propose that the molecular motor cohesin transmits long-range enhancer action by forming bridges between enhancers and promoters during loop extrusion. In this view, rare and transient bridges carry regulatory communication, rather than mere spatial proximity. We develop a quantitative model that predicts transcriptional output from cohesin-bridging dynamics and validate it by engineering cells in which strategically positioned CTCF sites rewire loop extrusion trajectories. The model explains how enhancer action scales with genomic distance, and how it can be either facilitated or insulated by CTCF sites across two orders of magnitude, behaviors incompatible with proximity-based models. Finally, our framework reveals that CTCF sites can block enhancers bidirectionally, by either blocking or releasing cohesin loops, resolving longstanding paradoxes between their effects on transcriptional regulation and genome folding. Together, our results establish cohesin bridging as a mode of enhancer-promoter communication that can be modulated by genomic context to achieve selective and tunable transcriptional control over long genomic distances.","rel_num_authors":11,"rel_authors":[{"author_name":"Timothy C Foldes","author_inst":"MIT \/ Institut Curie"},{"author_name":"Karissa Hansen","author_inst":"University of California, San Francisco"},{"author_name":"Maxim Imakaev","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Henrik Dahl Pinholt","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Nezar Alexander Abdennur","author_inst":"UMass Chan Medical School"},{"author_name":"Geoffrey C Fudenberg","author_inst":"University of Southern California"},{"author_name":"Irie Carel","author_inst":"University of California, San Francisco"},{"author_name":"Tayma Handal","author_inst":"University of California, San Francisco"},{"author_name":"Fernanda Vargas-Romero","author_inst":"University of California, San Francisco"},{"author_name":"Elphege Nora","author_inst":"University of California, San Francisco"},{"author_name":"Leonid Mirny","author_inst":"Massachusetts Institute of Technology"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"Cohesin bridging as a physical principle of enhancer-promoter communication","rel_doi":"10.64898\/2026.05.07.723561","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723561","rel_abs":"Central to genome function, enhancers are non-coding sequences that can control transcription from promoters hundreds of kilobases away. Yet the physical basis of this long-range communication remains unclear. A prevalent view is that enhancers activate promoters when the two elements come into spatial proximity through the 3D folding of chromatin. However, activation by spatial proximity alone has struggled to explain several core features of enhancer function. Here, we propose that the molecular motor cohesin transmits long-range enhancer action by forming bridges between enhancers and promoters during loop extrusion. In this view, rare and transient bridges carry regulatory communication, rather than mere spatial proximity. We develop a quantitative model that predicts transcriptional output from cohesin-bridging dynamics and validate it by engineering cells in which strategically positioned CTCF sites rewire loop extrusion trajectories. The model explains how enhancer action scales with genomic distance, and how it can be either facilitated or insulated by CTCF sites across two orders of magnitude, behaviors incompatible with proximity-based models. Finally, our framework reveals that CTCF sites can block enhancers bidirectionally, by either blocking or releasing cohesin loops, resolving longstanding paradoxes between their effects on transcriptional regulation and genome folding. Together, our results establish cohesin bridging as a mode of enhancer-promoter communication that can be modulated by genomic context to achieve selective and tunable transcriptional control over long genomic distances.","rel_num_authors":11,"rel_authors":[{"author_name":"Timothy C Foldes","author_inst":"MIT \/ Institut Curie"},{"author_name":"Karissa Hansen","author_inst":"University of California, San Francisco"},{"author_name":"Maxim Imakaev","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Henrik Dahl Pinholt","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Nezar Alexander Abdennur","author_inst":"UMass Chan Medical School"},{"author_name":"Geoffrey C Fudenberg","author_inst":"University of Southern California"},{"author_name":"Irie Carel","author_inst":"University of California, San Francisco"},{"author_name":"Tayma Handal","author_inst":"University of California, San Francisco"},{"author_name":"Fernanda Vargas-Romero","author_inst":"University of California, San Francisco"},{"author_name":"Elphege Nora","author_inst":"University of California, San Francisco"},{"author_name":"Leonid Mirny","author_inst":"Massachusetts Institute of Technology"}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"CD1a-Mediated Presentation of Canonical Microbial Peptides to T Cells","rel_doi":"10.64898\/2026.05.05.723095","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723095","rel_abs":"Langerhans cells express the nonpolymorphic antigen-presenting molecule CD1a, positioning them as contributors to host immunity against Mycobacterium leprae in human leprosy. CD1a was originally shown to present non-canonical lipopeptide antigens such as dideoxymycobactin and chemically diverse hydrophobic ligands. Here, we generated CD4+ T cell lines from leprosy lesions that recognized M. leprae in a CD1a-restricted manner. Unexpectedly, antigen recognition was protease-sensitive, prompting biochemical purification that identified two microbial protein antigens: LppX, a 25-kDa lipoglycoprotein, and Ag85A, a 30-kDa secreted protein with no known lipid modification. Recombinant proteins activated the corresponding T cell lines in a CD1a-dependent manner. Epitope mapping identified 12-mer peptides that fully reconstituted antigenicity, were conserved between M. leprae and M. tuberculosis, and elicited robust, dose-dependent IFN-y; production and T cell proliferation, establishing that DNA-encoded, ribosomally translated peptides serve as CD1a-restricted cognate antigens. Biochemical analyses showed peptide binding to CD1a, supported by isoelectric focusing and surface plasmon resonance (KD ~75 M for Ag85A). CD1a-peptide tetramers specifically stained cognate T cells, soluble CD1a was sufficient to present peptide antigen, and transfer of the LppX-specific TCR into naive T cells restored antigen responsiveness. Using CD1a-peptide tetramers, we identified antigen-specific T cells enriched in patients undergoing reversal reactions compared with patients with lepromatous leprosy and healthy donors. The CD1a-restricted T cell lines secreted IFN-y; and IL-26, cytokines with established antimicrobial activity. Together, these findings demonstrate that CD1a can present canonical microbial peptides as part of a cell-mediated immune response in leprosy, extending the known spectrum of CD1a ligands. Because CD1a is nonpolymorphic and presents antigens to antimicrobial T cells, CD1a-peptide complexes may provide a broadly applicable platform for studying, detecting, and potentially targeting mycobacterial immunity.","rel_num_authors":27,"rel_authors":[{"author_name":"Bruno Jorge De Andrade Silva","author_inst":"Division of Dermatology, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California, USA."},{"author_name":"Annemieke de Jong","author_inst":"Department of Dermatology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York, USA."},{"author_name":"Linda A. Fischbacher","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Maria Angela M. Marques","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Annaliza Legaspi","author_inst":"Division of Dermatology, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California, USA."},{"author_name":"Adam Shahine","author_inst":"Infection and Immunity Program & Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia."},{"author_name":"Jade Kollmorgen","author_inst":"Infection and Immunity Program & Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia."},{"author_name":"Peter A. Sieling","author_inst":"NantWorks, LLC, Culver City, California, USA."},{"author_name":"Aaron Choi","author_inst":"Division of Dermatology, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California, USA."},{"author_name":"Hee Jin Kim","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Carlos Adriano Matos e Silva","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Kristofor J. Webb","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Jason Bradshaw","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Patrick J. Brennan","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Alina Marusina","author_inst":"Department of Dermatology, University of California, Davis, Sacramento, California, USA."},{"author_name":"Khiem A. Tran","author_inst":"Department of Dermatology, University of California, Davis, Sacramento, California, USA."},{"author_name":"Euzenir Nunes Sarno","author_inst":"Leprosy Laboratory, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil."},{"author_name":"Roberta Olmo Pinheiro","author_inst":"Leprosy Laboratory, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil."},{"author_name":"Dirk M. Zajonc","author_inst":"Division of Immune Regulation, La Jolla Institute for Immunology, La Jolla, California, USA."},{"author_name":"D. Branch Moody","author_inst":"Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA."},{"author_name":"Kayvan R. Niazi","author_inst":"NantWorks, LLC, Culver City, California, USA; NanoCav LLC, Culver City, California, USA."},{"author_name":"Emanual Maverakis","author_inst":"Department of Dermatology, University of California, Davis, Sacramento, California, USA."},{"author_name":"Alessandro Sette","author_inst":"Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, California, USA; Department of Medicine, University of Californ"},{"author_name":"Jamie Rossjohn","author_inst":"Infection and Immunity Program & Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia."},{"author_name":"Maria T. Ochoa","author_inst":"Department of Dermatology, University of Southern California, Los Angeles, California, USA."},{"author_name":"John T. Belisle","author_inst":"Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA."},{"author_name":"Robert L. Modlin","author_inst":"Division of Dermatology, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California, USA."}],"rel_date":"2026-05-09","rel_site":"biorxiv"},{"rel_title":"CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation","rel_doi":"10.64898\/2026.05.07.26352573","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352573","rel_abs":"AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition \"fitness\" score, then validated its utility in two external populations.\n\nMethods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition \"fitness\" score. We then assessed the associations of \"fitness\" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition \"fitness\" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition \"fitness\" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001).\n\nConclusionsWe demonstrated that a comprehensive body composition \"fitness\" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed.\n\nGraphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition \"fitness\" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR\/small\/26352573v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1694ee6org.highwire.dtl.DTLVardef@bb120dorg.highwire.dtl.DTLVardef@19e4725org.highwire.dtl.DTLVardef@50e9a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG","rel_num_authors":28,"rel_authors":[{"author_name":"Robert JH Miller","author_inst":"University of Calgary"},{"author_name":"Jirong Yi","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Aakash Shanbhag","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Krishna K Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Terrence D Ruddy","author_inst":"University of Ottawa Heart Institute"},{"author_name":"Andrew J Einstein","author_inst":"Columbia University Irving Medical Center and New York-Presbyterian Hospital"},{"author_name":"Attila Feher","author_inst":"Yale University School of Medicine"},{"author_name":"Edward J Miller","author_inst":"Yale School of Medicine"},{"author_name":"Joanna X Liang","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Giselle Ramirez","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Leandro Slipczuk","author_inst":"Montefiore Health System\/Albert Einstein College of Medicine"},{"author_name":"Mark I Travin","author_inst":"Montefiore Medical Center and Albert Einstein College of Medicine"},{"author_name":"Erick Alexanderson","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Isabel Carvajal-Juarez","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Rene R.S. Packard","author_inst":"David Geffen School of Medicine, University of California Los Angeles"},{"author_name":"Mouaz Al-Mallah","author_inst":"Houston Methodist Academic Institute"},{"author_name":"Wanda Acampa","author_inst":"University of Naples Federico II"},{"author_name":"Stacey Knight","author_inst":"Intermountain Healthcare"},{"author_name":"Viet T Le","author_inst":"Intermountain Healthcare"},{"author_name":"Steve Mason","author_inst":"Intermountain Healthcare"},{"author_name":"Samuel Wopperer","author_inst":"Mayo Clinic"},{"author_name":"Panithaya Chareonthaitawee","author_inst":"Mayo Clinic"},{"author_name":"Ronny R. Buechel","author_inst":"University Hospital Zurich"},{"author_name":"Thomas L. Rosamond","author_inst":"University of Kansas Medical Center"},{"author_name":"Daniel S. Berman","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Damini Dey","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Marcelo F. Di Carli","author_inst":"Brigham and Women's Hospital"},{"author_name":"Piotr Slomka","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation","rel_doi":"10.64898\/2026.05.07.26352573","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352573","rel_abs":"AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition \"fitness\" score, then validated its utility in two external populations.\n\nMethods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition \"fitness\" score. We then assessed the associations of \"fitness\" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition \"fitness\" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition \"fitness\" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001).\n\nConclusionsWe demonstrated that a comprehensive body composition \"fitness\" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed.\n\nGraphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition \"fitness\" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR\/small\/26352573v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1694ee6org.highwire.dtl.DTLVardef@bb120dorg.highwire.dtl.DTLVardef@19e4725org.highwire.dtl.DTLVardef@50e9a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG","rel_num_authors":28,"rel_authors":[{"author_name":"Robert JH Miller","author_inst":"University of Calgary"},{"author_name":"Jirong Yi","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Aakash Shanbhag","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Krishna K Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Terrence D Ruddy","author_inst":"University of Ottawa Heart Institute"},{"author_name":"Andrew J Einstein","author_inst":"Columbia University Irving Medical Center and New York-Presbyterian Hospital"},{"author_name":"Attila Feher","author_inst":"Yale University School of Medicine"},{"author_name":"Edward J Miller","author_inst":"Yale School of Medicine"},{"author_name":"Joanna X Liang","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Giselle Ramirez","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Leandro Slipczuk","author_inst":"Montefiore Health System\/Albert Einstein College of Medicine"},{"author_name":"Mark I Travin","author_inst":"Montefiore Medical Center and Albert Einstein College of Medicine"},{"author_name":"Erick Alexanderson","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Isabel Carvajal-Juarez","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Rene R.S. Packard","author_inst":"David Geffen School of Medicine, University of California Los Angeles"},{"author_name":"Mouaz Al-Mallah","author_inst":"Houston Methodist Academic Institute"},{"author_name":"Wanda Acampa","author_inst":"University of Naples Federico II"},{"author_name":"Stacey Knight","author_inst":"Intermountain Healthcare"},{"author_name":"Viet T Le","author_inst":"Intermountain Healthcare"},{"author_name":"Steve Mason","author_inst":"Intermountain Healthcare"},{"author_name":"Samuel Wopperer","author_inst":"Mayo Clinic"},{"author_name":"Panithaya Chareonthaitawee","author_inst":"Mayo Clinic"},{"author_name":"Ronny R. Buechel","author_inst":"University Hospital Zurich"},{"author_name":"Thomas L. Rosamond","author_inst":"University of Kansas Medical Center"},{"author_name":"Daniel S. Berman","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Damini Dey","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Marcelo F. Di Carli","author_inst":"Brigham and Women's Hospital"},{"author_name":"Piotr Slomka","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation","rel_doi":"10.64898\/2026.05.07.26352573","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352573","rel_abs":"AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition \"fitness\" score, then validated its utility in two external populations.\n\nMethods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition \"fitness\" score. We then assessed the associations of \"fitness\" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition \"fitness\" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition \"fitness\" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001).\n\nConclusionsWe demonstrated that a comprehensive body composition \"fitness\" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed.\n\nGraphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition \"fitness\" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR\/small\/26352573v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1694ee6org.highwire.dtl.DTLVardef@bb120dorg.highwire.dtl.DTLVardef@19e4725org.highwire.dtl.DTLVardef@50e9a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG","rel_num_authors":28,"rel_authors":[{"author_name":"Robert JH Miller","author_inst":"University of Calgary"},{"author_name":"Jirong Yi","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Aakash Shanbhag","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Krishna K Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Terrence D Ruddy","author_inst":"University of Ottawa Heart Institute"},{"author_name":"Andrew J Einstein","author_inst":"Columbia University Irving Medical Center and New York-Presbyterian Hospital"},{"author_name":"Attila Feher","author_inst":"Yale University School of Medicine"},{"author_name":"Edward J Miller","author_inst":"Yale School of Medicine"},{"author_name":"Joanna X Liang","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Giselle Ramirez","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Leandro Slipczuk","author_inst":"Montefiore Health System\/Albert Einstein College of Medicine"},{"author_name":"Mark I Travin","author_inst":"Montefiore Medical Center and Albert Einstein College of Medicine"},{"author_name":"Erick Alexanderson","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Isabel Carvajal-Juarez","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Rene R.S. Packard","author_inst":"David Geffen School of Medicine, University of California Los Angeles"},{"author_name":"Mouaz Al-Mallah","author_inst":"Houston Methodist Academic Institute"},{"author_name":"Wanda Acampa","author_inst":"University of Naples Federico II"},{"author_name":"Stacey Knight","author_inst":"Intermountain Healthcare"},{"author_name":"Viet T Le","author_inst":"Intermountain Healthcare"},{"author_name":"Steve Mason","author_inst":"Intermountain Healthcare"},{"author_name":"Samuel Wopperer","author_inst":"Mayo Clinic"},{"author_name":"Panithaya Chareonthaitawee","author_inst":"Mayo Clinic"},{"author_name":"Ronny R. Buechel","author_inst":"University Hospital Zurich"},{"author_name":"Thomas L. Rosamond","author_inst":"University of Kansas Medical Center"},{"author_name":"Daniel S. Berman","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Damini Dey","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Marcelo F. Di Carli","author_inst":"Brigham and Women's Hospital"},{"author_name":"Piotr Slomka","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation","rel_doi":"10.64898\/2026.05.07.26352573","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352573","rel_abs":"AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition \"fitness\" score, then validated its utility in two external populations.\n\nMethods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition \"fitness\" score. We then assessed the associations of \"fitness\" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition \"fitness\" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition \"fitness\" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001).\n\nConclusionsWe demonstrated that a comprehensive body composition \"fitness\" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed.\n\nGraphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition \"fitness\" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR\/small\/26352573v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1694ee6org.highwire.dtl.DTLVardef@bb120dorg.highwire.dtl.DTLVardef@19e4725org.highwire.dtl.DTLVardef@50e9a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG","rel_num_authors":28,"rel_authors":[{"author_name":"Robert JH Miller","author_inst":"University of Calgary"},{"author_name":"Jirong Yi","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Aakash Shanbhag","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Krishna K Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Terrence D Ruddy","author_inst":"University of Ottawa Heart Institute"},{"author_name":"Andrew J Einstein","author_inst":"Columbia University Irving Medical Center and New York-Presbyterian Hospital"},{"author_name":"Attila Feher","author_inst":"Yale University School of Medicine"},{"author_name":"Edward J Miller","author_inst":"Yale School of Medicine"},{"author_name":"Joanna X Liang","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Giselle Ramirez","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Leandro Slipczuk","author_inst":"Montefiore Health System\/Albert Einstein College of Medicine"},{"author_name":"Mark I Travin","author_inst":"Montefiore Medical Center and Albert Einstein College of Medicine"},{"author_name":"Erick Alexanderson","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Isabel Carvajal-Juarez","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Rene R.S. Packard","author_inst":"David Geffen School of Medicine, University of California Los Angeles"},{"author_name":"Mouaz Al-Mallah","author_inst":"Houston Methodist Academic Institute"},{"author_name":"Wanda Acampa","author_inst":"University of Naples Federico II"},{"author_name":"Stacey Knight","author_inst":"Intermountain Healthcare"},{"author_name":"Viet T Le","author_inst":"Intermountain Healthcare"},{"author_name":"Steve Mason","author_inst":"Intermountain Healthcare"},{"author_name":"Samuel Wopperer","author_inst":"Mayo Clinic"},{"author_name":"Panithaya Chareonthaitawee","author_inst":"Mayo Clinic"},{"author_name":"Ronny R. Buechel","author_inst":"University Hospital Zurich"},{"author_name":"Thomas L. Rosamond","author_inst":"University of Kansas Medical Center"},{"author_name":"Daniel S. Berman","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Damini Dey","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Marcelo F. Di Carli","author_inst":"Brigham and Women's Hospital"},{"author_name":"Piotr Slomka","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation","rel_doi":"10.64898\/2026.05.07.26352573","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352573","rel_abs":"AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition \"fitness\" score, then validated its utility in two external populations.\n\nMethods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition \"fitness\" score. We then assessed the associations of \"fitness\" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition \"fitness\" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition \"fitness\" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001).\n\nConclusionsWe demonstrated that a comprehensive body composition \"fitness\" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed.\n\nGraphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition \"fitness\" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR\/small\/26352573v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1694ee6org.highwire.dtl.DTLVardef@bb120dorg.highwire.dtl.DTLVardef@19e4725org.highwire.dtl.DTLVardef@50e9a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG","rel_num_authors":28,"rel_authors":[{"author_name":"Robert JH Miller","author_inst":"University of Calgary"},{"author_name":"Jirong Yi","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Aakash Shanbhag","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Krishna K Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Terrence D Ruddy","author_inst":"University of Ottawa Heart Institute"},{"author_name":"Andrew J Einstein","author_inst":"Columbia University Irving Medical Center and New York-Presbyterian Hospital"},{"author_name":"Attila Feher","author_inst":"Yale University School of Medicine"},{"author_name":"Edward J Miller","author_inst":"Yale School of Medicine"},{"author_name":"Joanna X Liang","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Giselle Ramirez","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Leandro Slipczuk","author_inst":"Montefiore Health System\/Albert Einstein College of Medicine"},{"author_name":"Mark I Travin","author_inst":"Montefiore Medical Center and Albert Einstein College of Medicine"},{"author_name":"Erick Alexanderson","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Isabel Carvajal-Juarez","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Rene R.S. Packard","author_inst":"David Geffen School of Medicine, University of California Los Angeles"},{"author_name":"Mouaz Al-Mallah","author_inst":"Houston Methodist Academic Institute"},{"author_name":"Wanda Acampa","author_inst":"University of Naples Federico II"},{"author_name":"Stacey Knight","author_inst":"Intermountain Healthcare"},{"author_name":"Viet T Le","author_inst":"Intermountain Healthcare"},{"author_name":"Steve Mason","author_inst":"Intermountain Healthcare"},{"author_name":"Samuel Wopperer","author_inst":"Mayo Clinic"},{"author_name":"Panithaya Chareonthaitawee","author_inst":"Mayo Clinic"},{"author_name":"Ronny R. Buechel","author_inst":"University Hospital Zurich"},{"author_name":"Thomas L. Rosamond","author_inst":"University of Kansas Medical Center"},{"author_name":"Daniel S. Berman","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Damini Dey","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Marcelo F. Di Carli","author_inst":"Brigham and Women's Hospital"},{"author_name":"Piotr Slomka","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation","rel_doi":"10.64898\/2026.05.07.26352573","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352573","rel_abs":"AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition \"fitness\" score, then validated its utility in two external populations.\n\nMethods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition \"fitness\" score. We then assessed the associations of \"fitness\" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition \"fitness\" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition \"fitness\" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001).\n\nConclusionsWe demonstrated that a comprehensive body composition \"fitness\" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed.\n\nGraphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition \"fitness\" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR\/small\/26352573v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1694ee6org.highwire.dtl.DTLVardef@bb120dorg.highwire.dtl.DTLVardef@19e4725org.highwire.dtl.DTLVardef@50e9a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG","rel_num_authors":28,"rel_authors":[{"author_name":"Robert JH Miller","author_inst":"University of Calgary"},{"author_name":"Jirong Yi","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Aakash Shanbhag","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Krishna K Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Terrence D Ruddy","author_inst":"University of Ottawa Heart Institute"},{"author_name":"Andrew J Einstein","author_inst":"Columbia University Irving Medical Center and New York-Presbyterian Hospital"},{"author_name":"Attila Feher","author_inst":"Yale University School of Medicine"},{"author_name":"Edward J Miller","author_inst":"Yale School of Medicine"},{"author_name":"Joanna X Liang","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Giselle Ramirez","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Leandro Slipczuk","author_inst":"Montefiore Health System\/Albert Einstein College of Medicine"},{"author_name":"Mark I Travin","author_inst":"Montefiore Medical Center and Albert Einstein College of Medicine"},{"author_name":"Erick Alexanderson","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Isabel Carvajal-Juarez","author_inst":"Ignacio Chavez National Institute of Cardiology"},{"author_name":"Rene R.S. Packard","author_inst":"David Geffen School of Medicine, University of California Los Angeles"},{"author_name":"Mouaz Al-Mallah","author_inst":"Houston Methodist Academic Institute"},{"author_name":"Wanda Acampa","author_inst":"University of Naples Federico II"},{"author_name":"Stacey Knight","author_inst":"Intermountain Healthcare"},{"author_name":"Viet T Le","author_inst":"Intermountain Healthcare"},{"author_name":"Steve Mason","author_inst":"Intermountain Healthcare"},{"author_name":"Samuel Wopperer","author_inst":"Mayo Clinic"},{"author_name":"Panithaya Chareonthaitawee","author_inst":"Mayo Clinic"},{"author_name":"Ronny R. Buechel","author_inst":"University Hospital Zurich"},{"author_name":"Thomas L. Rosamond","author_inst":"University of Kansas Medical Center"},{"author_name":"Daniel S. Berman","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Damini Dey","author_inst":"Cedars-Sinai Medical Center"},{"author_name":"Marcelo F. Di Carli","author_inst":"Brigham and Women's Hospital"},{"author_name":"Piotr Slomka","author_inst":"Cedars-Sinai Medical Center"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"Adoption and Real-World Effectiveness of Adjunctive Azithromycin for Unscheduled Cesarean Delivery: A National Difference-in-Differences Analysis","rel_doi":"10.64898\/2026.05.07.26352377","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352377","rel_abs":"Abstract Importance: Cesarean delivery is the most common surgery in the US with more than 1 million performed each year; it is also the most significant risk factor for postpartum infection. The Cesarean Section Optimal Antibiotic Prophylaxis trial demonstrated that the addition of azithromycin at the time of cesarean birth performed in labor reduces postpartum infection. Objective: To determine the real-world adoption and effect of this trial on clinical practice and postpartum infections among U.S. pregnant persons undergoing cesarean delivery in labor. Design: Difference-in-differences analysis from 2013-2024. Setting: Population-based, patient-level analysis using Epic Cosmos, a large longitudinal national electronic health record database of patients seen in health systems using Epic. Participants: Pregnant individuals who received outpatient prenatal care in the system, who labored and gave birth to a liveborn singleton infant at 24-43 weeks of gestation were included. Exclusion criteria included unknown mode of delivery and intraamniotic infection. Exposures: The treatment group included those delivered by cesarean and the control group included those who delivered vaginally. The pre-period was defined as 2013-2016, excluding a washout period from trial publication until December 31, 2016, and the post-period was defined from 2017-2024. Main Outcomes and Measures: The primary outcomes were perioperative azithromycin administration and postpartum infection within 6 weeks of delivery. Results: 1,663,341 participants were included in the final analysis. In the pre- and post-periods, azithromycin was administered in 0.01% and 0.04% of vaginal births and in 2.2% and 39.6% of cesarean births, respectively. In the pre- and post-periods, postpartum infection occurred in 2.0% and 2.7% of vaginal births and 9.2% and 8.0% of cesarean births. In the adjusted difference-in-difference analysis, the trial resulted in an absolute increase in azithromycin use by 37.6 percentage points (pp) (95% CI: 33.1 to 42.2 pp); postpartum infection decreased by 2.0 pp (95% CI: -2.5 to -1.4 pp), a relative decrease of 20%. Conclusions and Relevance: Outside the clinical trial setting, this study provides evidence that azithromycin significantly reduces postpartum infection among pregnant persons undergoing a cesarean delivery in labor.","rel_num_authors":6,"rel_authors":[{"author_name":"Taylor S Freret","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Ethan Litman","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Timothy Wen","author_inst":"University of California, San Diego"},{"author_name":"Jeanne-Marie Guise","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Sarah E Little","author_inst":"Beth Israel Deaconess Medical Center"},{"author_name":"Mark Allen Clapp","author_inst":"Massachusetts General Hospital"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"Automated Brain and CSF Volume Assessment in Infant Hydrocephalus Using Deep Learning","rel_doi":"10.64898\/2026.05.07.26352592","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352592","rel_abs":"Accurate brain and cerebrospinal fluid (CSF) volume assessment is essential for pediatric hydrocephalus management. Current clinical practice relies on linear measurements that fail to capture complex three-dimensional ventricular morphology, while quantitative volumetric assessment remains limited by laborious processing and lack of clinically optimized automated tools. This study developed a rapid, automated AI-based intracranial segmentation model suitable for clinical workflows. We retrospectively analyzed 167 T2-weighted MRI scans from infants with hydrocephalus, randomly split into training (60%), validation (20%), and hold-out test (20%) sets. All scans were manually segmented into CSF, brain parenchyma, and background. Our model integrates DenseNet and U-Net architectures with feature smoothness regularization to enhance generalizability. Performance was evaluated using Dice scores and absolute relative volume error (ARVE) compared with state-of-the-art methods. The AI model achieved Dice scores of 95.7% for CSF and 96.4% for brain parenchyma on the hold-out test set, significantly outperforming FSL FAST (85.0% and 77.9%) and contemporary deep learning approaches (90.4% and 89.7%). Processing time was 0.8 seconds per scan using GPU acceleration. The model demonstrated consistent performance across different hydrocephalus etiologies and effectively handled challenging scenarios including noise, artifacts, and variable resolution. This study successfully developed a robust MRI segmentation model demonstrating superior accuracy and efficiency compared to existing methods. By incorporating domain-specific enhancements, the model enables rapid, clinically viable brain and CSF volume estimation for pediatric hydrocephalus care.","rel_num_authors":9,"rel_authors":[{"author_name":"Mingzhao Yu","author_inst":"Boston Children's Hospital"},{"author_name":"Marcia H Yoshikawa","author_inst":"Boston Children's Hospital"},{"author_name":"Ariadna S Luviano","author_inst":"Boston Children's Hospital"},{"author_name":"Steven J Schiff","author_inst":"Yale University"},{"author_name":"Vishal Monga","author_inst":"Pennsylvania State University"},{"author_name":"Benjamin C Warf","author_inst":"Boston Children's Hospital"},{"author_name":"P. Ellen Grant","author_inst":"Boston Children's Hospital"},{"author_name":"Jason Sutin","author_inst":"Boston Children's Hospital"},{"author_name":"Pei-Yi Lin","author_inst":"Boston Children's Hospital"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"Simpler is not always better: Phylodynamic misspecification and deep-learning corrections","rel_doi":"10.64898\/2026.05.07.26352661","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.07.26352661","rel_abs":"Phylodynamics bridges the gap between epidemiology and pathogen genetic data by estimating epidemiological parameters from time-scaled pathogen phylogenies. Multi-type birth-death (MTBD) models are phylodynamic analogies of compartmental models in classical epidemiology. They serve to infer the average number of secondary infections R and the infection duration d. Moreover, more complex MTBD models add extra parameters, such as the average length of the incubation period or the proportion of superspreaders in the infected population. However, these additional parameters come at an important computational cost: Apart from the simplest, BD, model, MTBD models do not have a closed-form solution and require numerical methods for their likelihood computation. This leads to increased computational times and potential numerical errors. Therefore, the BD model remains the favorite researchers' choice for real dataset analyses, and is often applied even in cases where more complex epidemiological aspects are present. We investigated, using simulations, how model misspecification influences inference of R and d in the phylodynamic framework. We showed that the use of models not accounting for various epidemiological aspects leads to bias. In particular the simplest, BD, estimator tends to underestimate R in the presence of super-spreading or incubation, which might be dangerous from the public health prospective. However, deep-learning-based estimators for complex models, which account for multiple epidemiological factors, perform well both on the data where those factors are present and where they are absent. This advocates for the use of complex epidemiologically realistic estimators, whose design has recently become possible thanks to deep learning.","rel_num_authors":3,"rel_authors":[{"author_name":"RUOPENG XIE","author_inst":"University of Oxford"},{"author_name":"Olivier Gascuel","author_inst":"CNRS"},{"author_name":"ANNA ZHUKOVA","author_inst":"Institut Pasteur & IBENS"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"Prompt-engineering improves clinical safety of large language models for opioid equipotency conversion","rel_doi":"10.64898\/2026.05.06.26352590","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352590","rel_abs":"Background: Large language models (LLMs) are increasingly used in medical education and clinical decision-making, but their reliability in high-risk medication dosing remains unclear. Opioid rotation is a common task requiring precise calculations where errors may result in overdose or inadequate pain relief. Methods: Thirteen LLMs were tested using an API-based framework to ensure independent queries across trials. First, fictional clinical scenarios were tested to simulate real-world clinical situations involving opioid rotation; to test the effects of changes in wording, scenarios were revised into 4 vignettes showing the same clinical situation. Next, opioid pairs were tested with a random-dose paradigm across a clinically-pertinent range (5-120 mg daily morphine equivalents). LLM outputs were compared with expected values derived from reference standards. Accuracy was assessed using predefined safety thresholds: tight accuracy (0.85-1.15x expected dose) and broad accuracy (0.6-1.7x). We tested models naively and with prompts augmented with reference tables and unit explanations. Results: Naive models generally exhibited low tight-range accuracy across opioid pairs. For any given opioid pair, each model would consistently produce similar incorrect conversion ratios despite wide variability across opioid pairs and language models. Vignette wording changes accounted for 76% of within-scenario response variance. Reference-based prompt augmentation significantly improved performance, with over half of models achieving high proportions of conversions within tight accuracy for morphine equivalent conversions. Conclusions: While commercial LLMs demonstrated variable accuracy in the native state, prompt augmentation significantly improved their performance.","rel_num_authors":5,"rel_authors":[{"author_name":"Tanya Marton","author_inst":"Google"},{"author_name":"David Corpman","author_inst":"University of Washington"},{"author_name":"Lytia Lai","author_inst":"University of Washington"},{"author_name":"Rodney A Gabriel","author_inst":"University of California-San Diego"},{"author_name":"Yian Chen","author_inst":"University of Washington"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"Geospatial Impact Indexing of Agricultural Incidents: A Multi-Criteria Risk Assessment in the U.S. Midwest","rel_doi":"10.64898\/2026.05.06.26352581","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352581","rel_abs":"Traditional agricultural safety assessments often rely on raw incident counts that emphasize exposure but underrepresent outcome severity. This study presents a multi criteria impact framework to distinguish frequency driven activity patterns from severity driven risk across the U.S. Midwest. Agricultural incident records from 2012 to 2023 across seven states were analyzed using descriptive statistics, county level mapping, and quartic kernel density estimation. Comparative impact indices were constructed using Analytic Hierarchy Process (AHP) and Geometric Fuzzy AHP weighting schemes to integrate incident frequency, outcome severity, and post incident survivability. Results indicate that while overall incident frequency is strongly concentrated in northwestern Iowa, reflecting intensive agricultural activity, fatal outcomes exhibit a broader spatial footprint extending across central and northern Iowa and into central southern Minnesota. Severity weighted mapping further consolidates northwestern Iowa and the Minnesota_Iowa corridor as dominant high-impact zones. At the regional scale, Geometric Fuzzy AHP produced consistently lower mean scores and reduced dispersion than AHP, yielding smoother spatial gradients while preserving the primary hotspot structure. These findings demonstrate that frequency based mapping alone fails to capture the multi dimensional nature of agricultural risk. By explicitly linking incident locations with survival infrastructure, this research provides an evidence based framework for targeting safety interventions and improving rural emergency medical service planning.","rel_num_authors":3,"rel_authors":[{"author_name":"Ege Duran","author_inst":"University of Iowa"},{"author_name":"Omer Mermer","author_inst":"Tulane University"},{"author_name":"Ibrahim Demir","author_inst":"Tulane University"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"One-Year Brain Structural Changes Are Associated with Postoperative Delirium and Delayed Resolution of Interleukin-6","rel_doi":"10.64898\/2026.05.03.26352074","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.03.26352074","rel_abs":"BackgroundPostoperative delirium is a common complication in older adults and is associated with neuroinflammation and cognitive decline. Previous studies have shown that the number of surgical procedures is associated with hippocampal volume loss in older adults in a large-scale UK Biobank study. However, it remains unclear whether hippocampal volume loss within one year after surgery is associated with postoperative delirium.\n\nMethodsLongitudinal structural MRI data and blood biomarkers were collected before surgery and one year postoperatively from 62 participants (>65 years, 27 females) undergoing major non-intracranial surgery. Hippocampal and other subcortical volumes were quantified using FreeSurfer. Cortical thickness was measured for cortical regions defined by the Desikan-Killiany (DK) atlas. One-year structural changes were examined in relation to peak Delirium Rating Scale (DRS) scores and one-year changes in plasma interleukin (IL)-6 levels.\n\nResultsOne-year volume loss in the right hippocampus was significantly correlated with postoperative peak DRS scores and the one-year change in IL-6. Additional gray matter reductions were observed in the right putamen and the right superior parietal cortex. Right putamen volume loss was also associated with the one-year change in IL-6, while cortical thinning in the right superior parietal cortex was associated with peak DRS scores.\n\nConclusionsPostoperative delirium is associated with longitudinal gray matter loss following surgery. Delayed resolution of inflammation may also contribute to postoperative brain structural changes.\n\nClinical trial registrationNCT01980511 and NCT03124303.","rel_num_authors":12,"rel_authors":[{"author_name":"Jinglei Lv","author_inst":"1.\tCentral Clinical School, Faculty of Medicine & Health, The University of Sydney, Camperdown, NSW, Australia. 2.\tSchool of Biomedical Engineering, Faculty of "},{"author_name":"Jennifer Taylor","author_inst":"1. Central Clinical School, Faculty of Medicine & Health, The University of Sydney, Camperdown, NSW, Australia."},{"author_name":"Samantha Curtis","author_inst":"4. Royal Prince Alfred Hospital, Camperdown, NSW, Australia."},{"author_name":"Kaitlin Kramer","author_inst":"4. Royal Prince Alfred Hospital, Camperdown, NSW, Australia."},{"author_name":"David Kunkel","author_inst":"5. Department of Anaesthesiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Shalini Thakur","author_inst":"Department of Anaesthesiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Veena Nair","author_inst":"6. Department of Radiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Matthew I. Banks","author_inst":"5. Department of Anaesthesiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Robert A. Pearce","author_inst":"5. Department of Anaesthesiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Vivek Prabhakaran","author_inst":"6. Department of Radiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Richard Lennertz","author_inst":"5. Department of Anaesthesiology, University of Wisconsin, Madison, WI, USA."},{"author_name":"Robert D. Sanders","author_inst":"1.\tCentral Clinical School, Faculty of Medicine & Health, The University of Sydney, Camperdown, NSW, Australia. 3.\tBrain and Mind Centre, The University of Sydn"}],"rel_date":"2026-05-08","rel_site":"medrxiv"},{"rel_title":"Structural bias in machine learning-guided peptide design","rel_doi":"10.64898\/2026.05.06.721805","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.721805","rel_abs":"Machine learning continues to accelerate peptide and protein design through the rapid prediction and generation of sequences with desired characteristics. Many applications focus on predicting properties, functions, and structures, as well as generating point mutations and de novo designs. Nevertheless, many models prove less generalizable than initially claimed. Most predictors and generators are trained on sequential datasets, where imbalances can be addressed during preprocessing. In contrast, structural bias, a subtype of algorithmic bias arising from uneven representation of structural classes in training datasets, and the limitations of early protein structure predictors have frequently remained undetected and uncorrected. The recent surge in powerful protein structure prediction tools, such as the AlphaFold and RosettaFold series and their variants, now presents opportunities to mitigate this issue. We hypothesize that such structural sampling biases influence the downstream performance of ML models. Using antimicrobial peptides as a case study, we audited the structural biases in 16 state-of-the-art predictors for antimicrobial activity and tested whether structural information constrains their predictions. Our analysis revealed that models explicitly trained on sequential data still produce predictions biased by uneven fold representations and data leakage. These findings highlight the importance of integrating balanced structural data or implementing bias-mitigating strategies to develop agnostic models that maximize bioactive protein discovery and multi-objective optimization.","rel_num_authors":2,"rel_authors":[{"author_name":"Victor Daniel Aldas-Bulos","author_inst":"Stowers Institute for Medical Research, Kansas City, MO, USA"},{"author_name":"Fabien Plisson","author_inst":"The University of Sydney"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Structural bias in machine learning-guided peptide design","rel_doi":"10.64898\/2026.05.06.721805","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.721805","rel_abs":"Machine learning continues to accelerate peptide and protein design through the rapid prediction and generation of sequences with desired characteristics. Many applications focus on predicting properties, functions, and structures, as well as generating point mutations and de novo designs. Nevertheless, many models prove less generalizable than initially claimed. Most predictors and generators are trained on sequential datasets, where imbalances can be addressed during preprocessing. In contrast, structural bias, a subtype of algorithmic bias arising from uneven representation of structural classes in training datasets, and the limitations of early protein structure predictors have frequently remained undetected and uncorrected. The recent surge in powerful protein structure prediction tools, such as the AlphaFold and RosettaFold series and their variants, now presents opportunities to mitigate this issue. We hypothesize that such structural sampling biases influence the downstream performance of ML models. Using antimicrobial peptides as a case study, we audited the structural biases in 16 state-of-the-art predictors for antimicrobial activity and tested whether structural information constrains their predictions. Our analysis revealed that models explicitly trained on sequential data still produce predictions biased by uneven fold representations and data leakage. These findings highlight the importance of integrating balanced structural data or implementing bias-mitigating strategies to develop agnostic models that maximize bioactive protein discovery and multi-objective optimization.","rel_num_authors":2,"rel_authors":[{"author_name":"Victor Daniel Aldas-Bulos","author_inst":"Stowers Institute for Medical Research, Kansas City, MO, USA"},{"author_name":"Fabien Plisson","author_inst":"The University of Sydney"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Localized heme sensing through a ternary molecular glue","rel_doi":"10.64898\/2026.05.07.723605","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723605","rel_abs":"Molecular glues are an emerging class of therapeutics that stabilize binary interactions and thereby rewire disease-relevant protein networks. Whether glues can integrate additional information to orchestrate signaling beyond initial complex formation is unknown. Here, we report that cells use an endogenous glue strategy to sense heme, an essential metabolite with deleterious pro-oxidant properties. Distinct from other glues, heme bridges three polypeptides to trigger degradation of the transcriptional repressor BACH1 through cytoplasmic, but not mitochondrial, CUL2FEM1B. This mechanism allows cells to eliminate toxic heme in the cytoplasm by inducing expression of the heme-degrading oxygenase HMOX1, yet ignore mitochondrial heme destined for function in the electron transport chain. While protective in healthy cells, ternary glue signaling creates a therapeutic vulnerability for Acute Myeloid Leukemias dependent on high rates of ETC assembly. Molecular glues can therefore drive assembly of higher-order complexes to establish localized signaling, which offers unexplored opportunities for induced proximity therapeutics.","rel_num_authors":12,"rel_authors":[{"author_name":"Michael Heider","author_inst":"UC Berkeley"},{"author_name":"Clara Hipp","author_inst":"UC Berkeley"},{"author_name":"Zhi Yang","author_inst":"UC Berkeley"},{"author_name":"Han Xiao","author_inst":"UC Berkeley"},{"author_name":"Tobias Beschauner","author_inst":"IMP Vienna"},{"author_name":"Eddie Wehri","author_inst":"UC Berkeley"},{"author_name":"Wencke Walter","author_inst":"MLL"},{"author_name":"Rumi Sherriff","author_inst":"UC Berkeley"},{"author_name":"Srividya Chandrasekhar","author_inst":"UC Berkeley"},{"author_name":"Torsten Haferlach","author_inst":"MLL"},{"author_name":"Julia Schaletzky","author_inst":"UC Berkeley"},{"author_name":"Michael Rape","author_inst":"UC Berkeley"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"vartracker: an end-to-end tool for pathogen longitudinal variant analysis and visualisation","rel_doi":"10.64898\/2026.05.06.723370","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.723370","rel_abs":"Longitudinal sequencing can reveal fine-grained pathogen evolution during acute and chronic infections and inform public health responses. However, integrating ordered pathogen genomic data into a coherent evolutionary and clinical framework can be tedious and error-prone. We present vartracker, an open-source tool for longitudinal pathogen variant analysis and visualisation. Given an ordered sample manifest, vartracker supports three entry points: raw sequence reads, reference-aligned BAM files, or user-supplied VCF and coverage inputs. Raw-read and BAM inputs are processed through an integrated Snakemake workflow, whereas VCF mode starts from precomputed files. Variants are normalised and annotated relative to a reference genome, tracked across timepoints, and classified as original or newly emerging and as transient or persistent. Inferred amino acid changes are reported, and for SARS-CoV-2 analyses, relevant published literature for key mutations can be automatically linked through a functional database. vartracker outputs a schema-documented results table, provenance metadata for reproducibility, publication-quality static figures, and an interactive heatmap for data exploration. Although packaged with SARS-CoV-2 reference assets and initially developed for SARS-CoV-2 datasets, vartracker is pathogen-agnostic when appropriate reference data are supplied. We demonstrate its utility using SARS-CoV-2 and respiratory syncytial virus A (RSV-A) datasets. vartracker is freely available through GitHub, PyPI and Bioconda.","rel_num_authors":2,"rel_authors":[{"author_name":"Charles S.P. Foster","author_inst":"University of New South Wales"},{"author_name":"William D Rawlinson","author_inst":"Prince of Wales Hospital"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Reaction Norm Modeling of High-Dimensional Genomic and Environmental Data Improves Prediction Accuracy in Winter Wheat","rel_doi":"10.64898\/2026.05.05.722758","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722758","rel_abs":"Genomic prediction models that account genotype-by-environment (G*E) have the potential to accelerate the rate of genetic gain for yield and agronomic performance, yet relatively few studies have applied G*E prediction in public soft red winter wheat (Triticum aestivum) breeding programs. In this study, we extended a reaction norm-based genomic prediction framework by integrating weather-based environmental covariates to more effectively capture genotype-environment interactions. Key agronomic traits, including seed yield, plant height, test weight, and heading date, were evaluated across 33 environments (location-year) using over 3,200 breeding lines from the North Carolina State University small grains breeding program. Multiple genomic prediction models were compared using several cross-validation (CV) schemes representing common breeding scenarios. Across traits, the reaction norm M5 model, which incorporates both G*E and genotype-by-environmental covariate interactions (G*O), achieved the highest prediction accuracy (PA) in CV2 (predicting incomplete field trials) and CV1 for yield and test weight (predicting new lines). The highest PA was observed for test weight under CV2 (0.54) and for yield under CV1 (0.41). Under CV0 (predicting new environments), the M3 model incorporating G*E produced highest PA across traits, with the greatest accuracy for plant height (0.45), although differences among M2, M3, and M4 were small. Prediction under CV00 (predicting new lines in new environments) remained more challenging, with PA values 0.10-0.20 across traits. Overall, our results demonstrate that integrating environmental covariates into genomic prediction models can improve predictive performance across diverse wheat-growing environments in North Carolina, supporting their utility for applied breeding efforts.","rel_num_authors":6,"rel_authors":[{"author_name":"Shailesh Raj Acharya","author_inst":"North Carolina State University"},{"author_name":"Julian Garcia-Abadillo","author_inst":"University of Florida"},{"author_name":"Jeanette Lyerly","author_inst":"North Carolina State University"},{"author_name":"Gina Brown-Guedira","author_inst":"North Carolina State University"},{"author_name":"Diego Jarquin","author_inst":"University of Florida, Agronomy Department"},{"author_name":"Nonoy Bandillo","author_inst":"North Carolina State University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Genomic and Transcriptomic Basis of Salinity Tolerance in Dry Pea","rel_doi":"10.64898\/2026.05.05.722931","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722931","rel_abs":"Salinity is a major crop production constraint in dry pea (Pisum sativum L.), making the development of salt-tolerant varieties essential to improve crop productivity and land-use efficiency. The genetic mechanisms of salt tolerance in dry pea is largely unknown, and research on salt-tolerant genes is limited. In this study, we established comprehensive genomic and transcriptomic resources, along with a robust screening protocol, to dissect the genetic basis of salinity tolerance using two germplasm sets: the USDA pea diversity panel, consisting of approximately 200 globally sourced accessions, and a set of 300 modern elite lines from the NDSU Pulse Crops Breeding Program. Genetic variation for the salinity response was assessed based on ten phenotypic traits, with root dry weight, shoot dry weight, and specific root length identified as key indicators based on their heritability. Genome-wide association mapping uncovered significant genomic regions and several candidate genes linked to salt stress, with the strongest association found on chromosome 6. Overlapping QTL signals across traits suggest a shared genetic architecture underlying salinity tolerance. Field-based transcriptomic analysis further identified five putative genes involved in salinity response conserved across multiple crop species. Notably, Psat5g000800, encoding a glycosyl hydrolase gene, was markedly upregulated under salinity stress. These findings highlight the complex, multi-gene regulatory nature of salinity tolerance in dry pea and underscore the importance of functional validation of candidate genes. This study provides key insights and practical tools to support breeding efforts aimed at improving salt tolerance in dry pea.","rel_num_authors":12,"rel_authors":[{"author_name":"Shailesh Raj Acharya","author_inst":"North Carolina State University"},{"author_name":"Emmanuella Bredu","author_inst":"University of Georgia"},{"author_name":"Harry Navasca","author_inst":"North Dakota State University"},{"author_name":"Hannah Worral","author_inst":"North Dakota State University"},{"author_name":"Lisa Piche","author_inst":"North Dakota State University"},{"author_name":"Rica Amor Saludares","author_inst":"Colorado State University"},{"author_name":"Josephine Princy Johnson","author_inst":"University of Pennsylvania"},{"author_name":"Clarice Coyne","author_inst":"USDA-ARS Plant Germplasm Introduction and Testing Research Unit"},{"author_name":"Kevin Mcphee","author_inst":"Montana State University"},{"author_name":"Qi Zhang","author_inst":"North Dakota State University"},{"author_name":"Michael Ostlie","author_inst":"North Dakota State University"},{"author_name":"Nonoy Bandillo","author_inst":"North Carolina State University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"The Brain Encyclopedia Atlas Project (BEAP): A Literature-Derived Atlas of Human Functional Neuroanatomy","rel_doi":"10.64898\/2026.05.05.722843","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722843","rel_abs":"The neuroscience literature contains thousands of studies localizing cognitive, sensory, and motor functions to specific brain regions, yet this knowledge remains fragmented across experimental modalities, naming conventions, and spatial reference systems. Consequently, relating reported activations, lesions, or stimulation sites to the broader functional literature often requires substantial manual synthesis. The Brain Encyclopedia Atlas Project (BEAP) was developed to address this challenge by providing a spatially grounded framework for organizing literature-defined brain regions. BEAP is an expert-curated neuroinformatics resource that aggregates and spatially indexes literature-defined cortical and subcortical functional regions within a common anatomical reference framework. The project identifies 108 neocortical fields and 18 cerebellar fields defined through an analysis of published figures from 1,453 human studies using functional neuroimaging, intracranial electrophysiology, and cortical stimulation. These regions were manually aligned to standard anatomical templates and associated with parcels of the Human Connectome Project multimodal parcellation (MMP1). Inclusion criteria required convergent functional evidence, lesion support, and boundary-related contrasts. Additionally, 340 allocortical, diencephalic, cerebellar, and brain stem nuclei were delineated through comparison with histological atlases and research articles. The resource is publicly accessible at https:\/\/brainatlas.online\/3d-brain\/, featuring an interactive three-dimensional brain model that interfaces directly with a curated encyclopedia. This platform provides structured entries synthesizing regional functional descriptions, boundary-defining evidence, internal organization, and connectivity annotations. Furthermore, each entry is designed to evolve through community feedback via a dedicated comment section. By providing a unified spatial context at the whole-cortex scale, BEAP enables systematic comparison across studies and facilitates the identification of recurring patterns in cortical organization. It serves as an integrative resource for research and education, supporting the contextualization of neuroimaging findings and the generation of hypotheses regarding large-scale brain organization.","rel_num_authors":1,"rel_authors":[{"author_name":"Oren Poliva","author_inst":"Washington University School of Medicine in St. Louis"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Opioids modulate Curiosity-Driven Exploration in Music","rel_doi":"10.64898\/2026.05.05.722646","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722646","rel_abs":"Curiosity, a key driver of exploration and learning, is reinforced by reward-related neurochemical systems, yet the role of the opioidergic system in modulating this behavior remains unclear. Music, as a highly rewarding stimulus, offers a unique context to investigate the neurochemical basis of curiosity, particularly the unexplored role of opioids in music-driven exploration. To fill this gap, we performed a double-blind within-subject pharmacological design, in which 26 participants received, in two different sessions, either a placebo or the opioid antagonist naltrexone. During each session, participants engaged in a music exploration\/exploitation trade-off paradigm designed to assess their willingness to pay for exploring unfamiliar electronic music. Using logistic regression mixed-effects models, we found that while naltrexone did not affect overall curiosity ratings, it significantly reduced exploratory behavior in states of heightened curiosity. These findings suggest that the opioidergic system plays a critical role in regulating the relationship between curiosity and exploration, particularly in the context of novel and rewarding stimuli like music. Overall, the present research provides new and compelling evidence on the important relationship between curiosity and exploration and its regulation with the opioidergic neurotransmitter subsystem.","rel_num_authors":8,"rel_authors":[{"author_name":"Claudia Alvarez-Martin","author_inst":"Cognition and Brain Plasticity Unit, Bellvitge Biomedical Research Institute, LHospitalet de Llobregat, Barcelona, Spain"},{"author_name":"Raimund Buehler","author_inst":"Department of Clinical and Health Psychology, University of Vienna, 1010 Vienna, Austria"},{"author_name":"Xim Cerda-Company","author_inst":"Bridging Research in AI and Neuroscience, Computer Vision Center, Cerdanyola del Valles, Spain"},{"author_name":"Gemma Cardona","author_inst":"University of Barcelona"},{"author_name":"Matth\u00e4us Willeit","author_inst":"Department of Psychiatry and Psychotherapy, General Hospital Vienna, Vienna, Austria"},{"author_name":"Jacqueline Pallas Gottlieb","author_inst":"Columbia University"},{"author_name":"Giorgia Silani","author_inst":"Department of Clinical and Health Psychology, University of Vienna, 1010 Vienna, Austria"},{"author_name":"Antoni Rodriguez-Fornells","author_inst":"University of Barcelona \/ ICREA, Catalan Institution for Research and Advanced Studies"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Label-free quantitative 3D mapping of collagen architecture by holotomography","rel_doi":"10.64898\/2026.05.05.722893","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722893","rel_abs":"Quantitative label-free analysis of collagen architecture lacks physically calibrated volumetric methods. Here we present holotomography (HT), which reconstructs three-dimensional refractive-index (RI) distributions of collagen networks. Because RI scales linearly with dry mass density, HT yields fiber-level morphology and mass from a single acquisition. HT resolves 3D fibrillar structure, distinguishes subtype-specific organizational and mass differences, and tracks polymerization and cell-driven remodeling, establishing a quantitative framework for extracellular matrix analysis.","rel_num_authors":8,"rel_authors":[{"author_name":"Sehyeon Lee","author_inst":"Department of Physics, Korea Advanced Institute of Science and Technology (KAIST); KAIST Institute for Health Science and Technology, KAIST"},{"author_name":"Wei Sun Park","author_inst":"Department of Physics, Korea Advanced Institute of Science and Technology (KAIST); KAIST Institute for Health Science and Technology, KAIST"},{"author_name":"Juheon Lee","author_inst":"Department of Physics, Korea Advanced Institute of Science and Technology (KAIST); KAIST Institute for Health Science and Technology, KAIST"},{"author_name":"Juyeon Park","author_inst":"Department of Physics, Korea Advanced Institute of Science and Technology (KAIST); KAIST Institute for Health Science and Technology, KAIST"},{"author_name":"Hyeoncheol Park","author_inst":"Department of Biomedical Engineering, Johns Hopkins University; Center for Microphysiological Systems, Johns Hopkins University"},{"author_name":"Eun Hyun Ahn","author_inst":"Department of Biomedical Engineering, Johns Hopkins University; Center for Microphysiological Systems, Johns Hopkins University"},{"author_name":"Deok-Ho Kim","author_inst":"Department of Biomedical Engineering, Johns Hopkins University; Center for Microphysiological Systems, Johns Hopkins University; Department of Medicine, Johns H"},{"author_name":"YongKeun Park","author_inst":"Department of Physics, Korea Advanced Institute of Science and Technology (KAIST); KAIST Institute for Health Science and Technology, KAIST; Tomocube Inc."}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Motor abstraction training generalizes to the refinement of specific movement patterns","rel_doi":"10.64898\/2026.05.05.722946","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722946","rel_abs":"The ability to store abstract mental representations underlies generalization across virtually every domain of human cognition, from vision and language to concept learning. Yet whether the motor system generates such abstractions and whether they causally contribute to skill learning remain open questions. Here, we introduce a paradigm in which human participants learned to refine novel movement patterns by learning to precisely copy unfamiliar handwritten characters. To examine the role of motor abstractions in this form of motor learning, participants were trained on markedly rotated versions of the characters, which recruited vastly different muscle commands while still maintaining the relevant abstract movement trajectory. Across eight experiments, abstraction training drove robust skill improvements that were comparable to having repetitive practice on the canonical form of each novel character. Moreover, this learning was motoric in nature: it required neither visual feedback nor visual mental imagery and was sensitive to the sequential structure of the abstract movement trajectory. These findings establish a causal role for abstract representations in motor learning, revealing that the motor system likely deploys abstractions in the earliest stages of skill acquisition.","rel_num_authors":3,"rel_authors":[{"author_name":"Zekun Sun","author_inst":"Yale University"},{"author_name":"Zhiran Xie","author_inst":"Yale University"},{"author_name":"Samuel McDougle","author_inst":"Yale University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"A unified framework links infant vulnerability with aging-related mortality dynamics","rel_doi":"10.64898\/2026.05.05.722841","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722841","rel_abs":"A central question in Geroscience is whether early-life mortality, which declines from birth to sexual maturity, and late-life mortality, which grows exponentially in time, can be understood within a shared conceptual framework. We show that stochastic threshold models can explain both phases by incorporating heterogeneity in neonatal vulnerability. Using U.S. National Center for Health Statistics data, we find that infant mortality risk is strongly associated with neonatal clinical markers such as Apgar scores, gestational age, and birth weight, suggesting that initial physiological differences persist across early life. We show that the ~1\/t mortality decline generically arises in stochastic threshold models via depletion of the most vulnerable, across a wide range of model specifications. Incorporating this mechanism into the Saturating-Removal model captures both the early decline and the later Gompertz acceleration, reproducing the full J-shaped mortality curve. Together, our findings link neonatal vulnerability to late-life mortality dynamics within a shared stochastic framework, supporting a life-course perspective on aging and longevity.","rel_num_authors":3,"rel_authors":[{"author_name":"Ben Shenhar","author_inst":"Molecular Cell Biology, Weizmann Institute of Science"},{"author_name":"Tzipi Strauss","author_inst":"Sheba Longevity Center, Sheba Medical Center, Tel HaShomer"},{"author_name":"Uri Alon","author_inst":"Molecular Cell Biology, Weizmann Institute of Science"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"A widespread internal brain state for fentanyl withdrawal","rel_doi":"10.64898\/2026.05.04.722791","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.04.722791","rel_abs":"Opioid addiction is characterized by escalating drug use, driven in part by negative reinforcement from withdrawal, but the neural processes linking withdrawal to increased drug-taking remain poorly understood. Here, we use multisite local field potential recordings and interpretable machine learning to identify large-scale brain networks engaged by repeated opioid exposure and withdrawal. After discovering that repeated fentanyl exposure induces a progressively ramping network of widespread high beta and low gamma oscillations, we then identified a distinct brain network that selectively encodes the emergence and severity of opioid withdrawal. This network, termed EN-Withdrawal, is characterized by regional gamma oscillations and widely synchronized delta\/theta oscillations. Its activity patterns predict the emergence of spontaneous and naloxone-precipitated withdrawal across multiple independent cohorts, generalizing across mice, sex, opioids, and dosing regimens, while persisting over multiple days of withdrawal. Using a novel, data-driven severity index, we find that network activity scales with individual behavioral severity without simply reflecting ongoing somatic behaviors or general aversion, suggesting that EN-Withdrawal underlies a withdrawal-induced internal state. Strikingly, network activity predicts the escalation of fentanyl self-administration on a mouse-by-mouse basis in experienced, but not drug-naive, animals. These findings reveal a neurophysiological substrate of the negative reinforcement cycle of addiction that shapes individual vulnerability.","rel_num_authors":8,"rel_authors":[{"author_name":"Kareem Abdelaal","author_inst":"Duke University"},{"author_name":"Kathryn Walder-Christensen","author_inst":"Duke Unviversity"},{"author_name":"Cameron Blount","author_inst":"Duke University"},{"author_name":"Kellie Williford","author_inst":"Duke University"},{"author_name":"marisella Adams-Grimaldi","author_inst":"Duke University"},{"author_name":"Stephen Mague","author_inst":"Duke University"},{"author_name":"David Carlson","author_inst":"Duke University"},{"author_name":"Kafui Dzirasa","author_inst":"Duke University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Denoised MDS-UPDRS Part-III Scores Yield New Patterns of Progression Heterogeneity in Early Stage Parkinson's Disease","rel_doi":"10.64898\/2026.05.04.722810","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.04.722810","rel_abs":"Parkinson's Disease (PD) Motor Scores (MDS-UPDRS Part III) are quite noisy. This paper proposes a new methodology for processing these scores by first denoising the scores to enhance the underlying progression signal, and then conducting a high-dimensional analysis which does not sum the scores into a total movement score. The analysis gives novel insights into PD progression heterogeneity: it reveals that the heterogeneity is continuously variable rather than clustered into \"subtypes\" and that the variability is along two easily understood axes. This analysis also resolves some of the discrepancies in previously reported progression subtypes. Finally, the analysis reveals that patient-specific progression cannot be predicted from baseline using only MDS-UPDRS Part III scores.","rel_num_authors":3,"rel_authors":[{"author_name":"Jonathan Koss","author_inst":"Yale University"},{"author_name":"Sule Tinaz","author_inst":"Yale University School of Medicine"},{"author_name":"Hemant Tagare","author_inst":"Yale University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Augmenting the Bayesian Brain with learned and reusable world-model components for flexible cognition","rel_doi":"10.64898\/2026.05.06.722922","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.06.722922","rel_abs":"The Bayesian Brain hypothesis assumes that cognition relies on internal generative models of the world, yet existing implementations remain constrained by pre-specified, task-specific generative structures and computationally heavy iterative inference schemes. Here, we introduce modular neural state-space models as a scalable realization of the Bayesian Brain, replacing fixed generative structures and pre-specified inference rules with learned world-model components and amortized neural updates. This framework preserves the core commitment to explaining observations through hidden causes while making inference learned and reusable rather than pre-specified and task-specific. Our modular implementation of these models affords learned components to be seamlessly recombined and stacked across superficially different tasks that share similar latent dynamics. Such computational reuse supports zero-shot generalization and predicts selective correlations of inference parameters between tasks. We confirm these key predictions in human behavior, identifying learned and reusable world-model components as a candidate computational principle for flexible cognition.","rel_num_authors":5,"rel_authors":[{"author_name":"Charles Findling","author_inst":"University of Geneva"},{"author_name":"Junseok K. Lee","author_inst":"Ecole normale superieure"},{"author_name":"Jacob J. W. Bakermans","author_inst":"University College London"},{"author_name":"Alexandre Pouget","author_inst":"University of Geneva"},{"author_name":"Valentin Wyart","author_inst":"Ecole Normale Superieure"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Zea Lip: An atlas of glycerolipid profiles across leaf development in maize","rel_doi":"10.64898\/2026.05.07.723536","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723536","rel_abs":"Lipids are the predominant building blocks of plant membranes and are essential for plant growth and development. They are crucial for survival during times of stress as lipids are involved in multiple signaling pathways, and their relative abundances can change in response to environmental factors. To better characterize the lipid composition of the vital food crop maize, we generated a comprehensive glycerolipid atlas using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. We surveyed the lipid profiles of three different maize genotypes: B73, a temperate inbred; CML312, a subtropical inbred; and Palomero Toluqueno, an open-pollinated variety from the Mexican highlands. We collected leaf samples from 4 developmental stages and 6 leaves. From one growth stage, we also sampled along with three leaf zones: base, center, and tip. The genotype and leaf number were the major drivers of lipid differences. Phosphatidylcholine, lysophosphatidylcholine, and triacylglycerol genotypic differences were particularly high. We generated an eFP browser to be integrated into the maize genome browser, as well as a separate web interface to easily browse and compare lipid levels across tissues and genotypes, available at https:\/\/rrellan.shinyapps.io\/Zea-Lip\/.","rel_num_authors":9,"rel_authors":[{"author_name":"Karla A Juarez Nunez","author_inst":"Centro de Investigacion y de Estudios Avanzados, Instituto Politecnico Nacional (CINVESTAV-IPN"},{"author_name":"Guillaume Lobet","author_inst":"Universite catholique de Louvain"},{"author_name":"Nirwan Tandukar","author_inst":"North Carolina State University"},{"author_name":"Eric Jadidzadeh","author_inst":"University of Toronto"},{"author_name":"Asher Pasha","author_inst":"University of Toronto"},{"author_name":"Nicholas J. Provart","author_inst":"University of Toronto"},{"author_name":"James B. Holland","author_inst":"USDA-ARS"},{"author_name":"Ruben Rellan-Alvarez","author_inst":"North Carolina State University"},{"author_name":"Allison C Barnes","author_inst":"USDA-ARS"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart","rel_doi":"10.64898\/2026.05.04.721738","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.04.721738","rel_abs":"Resilience to cardiac stress is essential for health, yet the relationship between cardiomyocyte (CM) stress response and local microenvironment remains unclear. Here, we combined MERFISH spatial transcriptome profiling with Cellouette, an improved cell segmentation method, to determine CM-microenvironment relationships in a mouse model of ventricular pressure overload. We report the shape, transcription profile, spatial organization, and physical connectivity for >400,000 cells across stressed and healthy tissues. Under stress, CMs adopted a spectrum of emergent transcriptional states, with advanced states marked by a metabolic and pro-fibrotic shift. To discover CM-environment relationships, we performed a network analysis of physical cell connectivity combined with cell-type-specific profiling. We found that pro-fibrotic CM progression was tightly linked to distinct local microenvironments, and CM metabolic shifts could be inferred from transcriptional patterns in neighboring non-CM cells, revealing microenvironmental imprints of disease. We thus provide a resource for understanding the heterogeneity of outcome during cardiac pressure overload.","rel_num_authors":15,"rel_authors":[{"author_name":"Yuening Liu","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Annabelle M. Coles","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Jonah Castiglione","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Vijay Venu Thiyagarajan","author_inst":"Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX"},{"author_name":"Kalen Clifton","author_inst":"Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD"},{"author_name":"Deevanshu Goyal","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Jerry Wu","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Arlo Sheridan","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Ana Vujic","author_inst":"Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA"},{"author_name":"Kristen M. Harris","author_inst":"Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX"},{"author_name":"Uri Manor","author_inst":"Department of Cell and Developmental Biology, University of California, San Diego, La Jolla, CA"},{"author_name":"Talmo D. Pereira","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Jean Fan","author_inst":"Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD"},{"author_name":"Richard T. Lee","author_inst":"Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA"},{"author_name":"Pallav Kosuri","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart","rel_doi":"10.64898\/2026.05.04.721738","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.04.721738","rel_abs":"Resilience to cardiac stress is essential for health, yet the relationship between cardiomyocyte (CM) stress response and local microenvironment remains unclear. Here, we combined MERFISH spatial transcriptome profiling with Cellouette, an improved cell segmentation method, to determine CM-microenvironment relationships in a mouse model of ventricular pressure overload. We report the shape, transcription profile, spatial organization, and physical connectivity for >400,000 cells across stressed and healthy tissues. Under stress, CMs adopted a spectrum of emergent transcriptional states, with advanced states marked by a metabolic and pro-fibrotic shift. To discover CM-environment relationships, we performed a network analysis of physical cell connectivity combined with cell-type-specific profiling. We found that pro-fibrotic CM progression was tightly linked to distinct local microenvironments, and CM metabolic shifts could be inferred from transcriptional patterns in neighboring non-CM cells, revealing microenvironmental imprints of disease. We thus provide a resource for understanding the heterogeneity of outcome during cardiac pressure overload.","rel_num_authors":15,"rel_authors":[{"author_name":"Yuening Liu","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Annabelle M. Coles","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Jonah Castiglione","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Vijay Venu Thiyagarajan","author_inst":"Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX"},{"author_name":"Kalen Clifton","author_inst":"Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD"},{"author_name":"Deevanshu Goyal","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Jerry Wu","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Arlo Sheridan","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Ana Vujic","author_inst":"Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA"},{"author_name":"Kristen M. Harris","author_inst":"Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX"},{"author_name":"Uri Manor","author_inst":"Department of Cell and Developmental Biology, University of California, San Diego, La Jolla, CA"},{"author_name":"Talmo D. Pereira","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"},{"author_name":"Jean Fan","author_inst":"Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD"},{"author_name":"Richard T. Lee","author_inst":"Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA"},{"author_name":"Pallav Kosuri","author_inst":"Salk Institute for Biological Studies, La Jolla, CA"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Cholesteryl Ester as a Prognostic Biomarker In IDH-wildtype Glioblastoma","rel_doi":"10.64898\/2026.05.05.722825","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722825","rel_abs":"Current treatment of IDH-wildtype glioblastoma (GBM) relies on the first-line chemotherapy-temozolomide. Although MGMT methylation is routinely conducted to predict chemosensitivity, its efficacy is often compromised. Thus, there is an urgent need to discover more accurate prognostic biomarkers. Cholesteryl ester (CE) has been recently recognized as a key feature of GBM, however, its role in GBM prognosis remains poorly understood. We first employed label-free stimulated Raman scattering (SRS) imaging to quantitatively analyze CE level in intact tumor tissues obtained from IDH-wildtype GBM patients. Our result revealed significantly prolonged 2-year overall survival (OS) in patients with CE level [&ge;] 40% compared to those with CE level < 40%. CE outperformed MGMT methylation for 2-year OS prognosis (AUC: 0.836 vs. 0.763). Importantly, CE also achieved superior prognostic performance over MGMT methylation on an independent cohort, with higher sensitivity (0.856 vs. 0.667), specificity (0.833 vs. 0.583), NPV (1.00 vs. 0.667), PPV (0.833 vs. 0.583). Given synergistic effects between CE and MGMT methylation, we developed a prognostic model combining these two biomarkers. Specially, machine learning (XGBoost) model exhibited optimal performance in the training cohort (AUC: 0.920), and maintained its superior performance on the independent cohort (sensitivity: 0.946, specificity: 0.873, NPV: 1.00; PPV: 0.917). Mechanistically, integrative analysis of TCGA database linked poor prognosis to the coordinated upregulation of genes involved in cholesterol efflux, hydrolysis, transport, and inhibition of de novo synthesis, unraveling a possible underlying mechanism between poor prognosis and cholesterol metabolism. This work identified CE as a prognostic biomarker for IDH-wildtype GBM.","rel_num_authors":8,"rel_authors":[{"author_name":"nana wang","author_inst":"Beihang University"},{"author_name":"Jiejun wang","author_inst":"Beijing Anzhen Hospital"},{"author_name":"Jianlin Liu","author_inst":"Beihang University"},{"author_name":"Jinqi Zou","author_inst":"Beijing Wellmed Medical Diagnostics & Laboratory Co., Ltd"},{"author_name":"Bin Yang","author_inst":"Beihang University"},{"author_name":"Pu wang","author_inst":"Beihang University"},{"author_name":"Nan Ji","author_inst":"Beijing Tiantan Hospital"},{"author_name":"Shuhua Yue","author_inst":"Beihang University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Aneuploidy sensitizes cells to SREBP-pathway inhibition in squamous cell carcinoma","rel_doi":"10.64898\/2026.05.04.722276","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.04.722276","rel_abs":"Squamous cell carcinomas (SCCs) in the lung, head and neck, cervix, and esophagus are characterized by widespread chromosome-arm aneuploidies, most frequently recurrent 3q-gain. However, how these alterations influence cancer development and therapeutic vulnerabilities remains unclear. To identify aneuploidy-driven therapeutic targets, we performed genome-wide CRISPR interference (CRISPRi) and drug-repurposing screens in isogenic immortalized lung epithelial cells harboring chromosome 3-disomy or 3q-gain. Both screens converged on a mevalonate pathway dependency specific to 3q-gain cells, which exhibited heightened sensitivity to sterol regulatory element-binding protein (SREBP) disruption. Rescue experiments demonstrated that these vulnerabilities were on target and that pathway inhibition preferentially causes apoptosis in 3q-gain cells. Transcriptomic and lipidomic profiling revealed 3q-gain-associated alterations in SREBP activation, cholesterol and fatty-acid biosynthesis, and lipid composition. Perturbing SREBP signaling impaired viability in SCC cell lines and suppressed tumor growth in xenografts with 3q-gain. These findings identify an aneuploidy-driven, targetable vulnerability in SCC.","rel_num_authors":17,"rel_authors":[{"author_name":"Nadja Zhakula","author_inst":"Columbia University Medical Center"},{"author_name":"Sejal Jain","author_inst":"Dana-Farber Cancer Institute"},{"author_name":"Zeinab Amini-Farsani","author_inst":"Columbia University Medical Center"},{"author_name":"Jiankang Zhang","author_inst":"Columbia University Medical Center"},{"author_name":"Mari Nakamura","author_inst":"Columbia University Medical Center"},{"author_name":"Laura Byron","author_inst":"Columbia University Medical Center"},{"author_name":"Joan J. Castellano Perez","author_inst":"Columbia University Medical Center"},{"author_name":"Chloe Paolucci","author_inst":"Columbia University Medical Center"},{"author_name":"Rohan Munoth","author_inst":"Columbia University Medical Center"},{"author_name":"Fereshteh Zandkarimi","author_inst":"Columbia University Medical Center"},{"author_name":"Yuka Takemon","author_inst":"University of British Columbia"},{"author_name":"Marco Marra","author_inst":"British Columbia Cancer Research Agency"},{"author_name":"Brian Henick","author_inst":"Columbia University Medical Center"},{"author_name":"Anjali Saqi","author_inst":"Columbia University Medical Center"},{"author_name":"Tannishtha Reya","author_inst":"Columbia University Medical Center"},{"author_name":"Matthew Meyerson","author_inst":"Dana-Farber Cancer Institute"},{"author_name":"Alison M Taylor","author_inst":"Columbia University Medical Center"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Aneuploidy sensitizes cells to SREBP-pathway inhibition in squamous cell carcinoma","rel_doi":"10.64898\/2026.05.04.722276","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.04.722276","rel_abs":"Squamous cell carcinomas (SCCs) in the lung, head and neck, cervix, and esophagus are characterized by widespread chromosome-arm aneuploidies, most frequently recurrent 3q-gain. However, how these alterations influence cancer development and therapeutic vulnerabilities remains unclear. To identify aneuploidy-driven therapeutic targets, we performed genome-wide CRISPR interference (CRISPRi) and drug-repurposing screens in isogenic immortalized lung epithelial cells harboring chromosome 3-disomy or 3q-gain. Both screens converged on a mevalonate pathway dependency specific to 3q-gain cells, which exhibited heightened sensitivity to sterol regulatory element-binding protein (SREBP) disruption. Rescue experiments demonstrated that these vulnerabilities were on target and that pathway inhibition preferentially causes apoptosis in 3q-gain cells. Transcriptomic and lipidomic profiling revealed 3q-gain-associated alterations in SREBP activation, cholesterol and fatty-acid biosynthesis, and lipid composition. Perturbing SREBP signaling impaired viability in SCC cell lines and suppressed tumor growth in xenografts with 3q-gain. These findings identify an aneuploidy-driven, targetable vulnerability in SCC.","rel_num_authors":17,"rel_authors":[{"author_name":"Nadja Zhakula","author_inst":"Columbia University Medical Center"},{"author_name":"Sejal Jain","author_inst":"Dana-Farber Cancer Institute"},{"author_name":"Zeinab Amini-Farsani","author_inst":"Columbia University Medical Center"},{"author_name":"Jiankang Zhang","author_inst":"Columbia University Medical Center"},{"author_name":"Mari Nakamura","author_inst":"Columbia University Medical Center"},{"author_name":"Laura Byron","author_inst":"Columbia University Medical Center"},{"author_name":"Joan J. Castellano Perez","author_inst":"Columbia University Medical Center"},{"author_name":"Chloe Paolucci","author_inst":"Columbia University Medical Center"},{"author_name":"Rohan Munoth","author_inst":"Columbia University Medical Center"},{"author_name":"Fereshteh Zandkarimi","author_inst":"Columbia University Medical Center"},{"author_name":"Yuka Takemon","author_inst":"University of British Columbia"},{"author_name":"Marco Marra","author_inst":"British Columbia Cancer Research Agency"},{"author_name":"Brian Henick","author_inst":"Columbia University Medical Center"},{"author_name":"Anjali Saqi","author_inst":"Columbia University Medical Center"},{"author_name":"Tannishtha Reya","author_inst":"Columbia University Medical Center"},{"author_name":"Matthew Meyerson","author_inst":"Dana-Farber Cancer Institute"},{"author_name":"Alison M Taylor","author_inst":"Columbia University Medical Center"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"BRIDGE: A Multi-organ Histo-ST Foundation Model Enables Virtual Spatial Transcriptomics for Enhanced Few-shot Cancer Diagnosis","rel_doi":"10.64898\/2026.05.05.722971","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722971","rel_abs":"Recent studies have explored generating virtual spatial transcriptomics (ST) profiles from histological images, offering a promising alternative to laboratory-measured molecular profiling. However, existing approaches predominantly rely on single-organ models and require substantial organ-specific training data, restricting their accuracy under challenging few-shot conditions in clincical practice, where less than 10 slides are available for specific organs or techniques. Here, we present BRIDGE, a multi-organ foundation model pre-trained on over 600,000 paired histology-ST profiles across 13 human organs and three sequencing techniques. By robustly aligning morphological features and genomic information within a shared multi-organ latent space, BRIDGE can leverage common biological knowledge across distinct tissues to enable accurate and generalizable pan-cancer molecular profiling. Without additional organ-specific fine-tuning, BRIDGE accurately predicts the spatial expression of 80 biomarker genes, achieving an average Pearson correlation coefficient (PCC) of 0.474-a 30% improvement over existing state-of-the-art models under three clinically challenging few-shot scenarios. With generated virtual ST, BRIDGE outperforms current state-of-the-art pathology foundation models in predicting cancer survival, achieving an average concordance index (C-index) of 0.724 across six TCGA cohorts. Notably, BRIDGE maintains exceptional performance even in zero-shot scenarios involving three cancer types not seen during its training, achieving an average C-index of 0.717, thereby demonstrating its strong generalization capability that transcends organ- and subtype-specific boundaries. Moreover, BRIDGE-generated virtual spatial transcriptomes match the prognostic accuracy of bulk RNA-seq, highlighting their potential as a spatially informative alternative to laboratory sequencing. In general, BRIDGE represents a data-efficient tool in virtual ST that facilitates biomedical discoveries in clinical few-shot contexts and advances diagnosis of understudied cancers without sufficient samples.","rel_num_authors":6,"rel_authors":[{"author_name":"Zhuo Liang","author_inst":"The University of Hong Kong"},{"author_name":"WEIQIN ZHAO","author_inst":"The University of Hong Kong"},{"author_name":"Fuying Wang","author_inst":"The University of Hong Kong"},{"author_name":"Guangyong Chen","author_inst":"Zhejiang Lab"},{"author_name":"Yuanhua Huang","author_inst":"The University of Hong Kong"},{"author_name":"Lequan Yu","author_inst":"The University of Hong Kong"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Learning shapes neural codes for sensory-motor integration in the tail of the striatum","rel_doi":"10.64898\/2026.05.05.722944","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722944","rel_abs":"Separating meaningful sensory stimuli from irrelevant ones requires learning sensorimotor associations, but how sensory-linked striatal circuits acquire and maintain these associations is unclear. We longitudinally imaged direct- and indirect-pathway (D1 and A2a) spiny projection neurons (SPNs) in the tail of the striatum (TS) as mice learned to push or pull a joystick in response to auditory cues in either a stimulus-response association (go\/omit) task or a two-alternative forced choice (2AFC) task. Learning in both tasks increased the fraction and strength of task-modulated TS SPNs across the sound, action, and reward epochs, yet individual neuron selectivity often switched over days between behavioral epochs. In spite of individual neuron variability, population activity of direct and indirect pathways became aligned with characteristic behavioral features during learning: D1-SPNs dominated the action category, A2a-SPNs were biased toward the mixed category (multiple epochs), and both SPN types showed sound category specificity that depended on the sound-action association. Trial-wise modeling revealed a reweighting of behavioral predictors within the action window, with reward gaining and movement losing predictive weight. Learning the two-choice task led to a higher prevalence of association-preferring neurons and better behavioral decoding within the sound window than in the action\/reward window, reflecting a task-dependent prioritization of sensory information. Association-preferring neurons also showed a stable local distance-similarity relationship, with nearby neurons more similar than distant neurons across learning. Together, our results support a population mechanism in TS during learning in which neurons from both direct and indirect pathways are recruited and take on distinct behavioral roles that vary with performance and task complexity.","rel_num_authors":5,"rel_authors":[{"author_name":"Ivan Linares-Garcia","author_inst":"Rutgers University"},{"author_name":"Sofia E Juliani","author_inst":"Rutgers, The State University of New Jersey"},{"author_name":"Jessie Yi","author_inst":"Rutgers, The State University of New Jersey"},{"author_name":"Diego Castro","author_inst":"Rutgers, The State University of New Jersey"},{"author_name":"David J Margolis","author_inst":"Rutgers, The State University of New Jersey"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Learning shapes neural codes for sensory-motor integration in the tail of the striatum","rel_doi":"10.64898\/2026.05.05.722944","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722944","rel_abs":"Separating meaningful sensory stimuli from irrelevant ones requires learning sensorimotor associations, but how sensory-linked striatal circuits acquire and maintain these associations is unclear. We longitudinally imaged direct- and indirect-pathway (D1 and A2a) spiny projection neurons (SPNs) in the tail of the striatum (TS) as mice learned to push or pull a joystick in response to auditory cues in either a stimulus-response association (go\/omit) task or a two-alternative forced choice (2AFC) task. Learning in both tasks increased the fraction and strength of task-modulated TS SPNs across the sound, action, and reward epochs, yet individual neuron selectivity often switched over days between behavioral epochs. In spite of individual neuron variability, population activity of direct and indirect pathways became aligned with characteristic behavioral features during learning: D1-SPNs dominated the action category, A2a-SPNs were biased toward the mixed category (multiple epochs), and both SPN types showed sound category specificity that depended on the sound-action association. Trial-wise modeling revealed a reweighting of behavioral predictors within the action window, with reward gaining and movement losing predictive weight. Learning the two-choice task led to a higher prevalence of association-preferring neurons and better behavioral decoding within the sound window than in the action\/reward window, reflecting a task-dependent prioritization of sensory information. Association-preferring neurons also showed a stable local distance-similarity relationship, with nearby neurons more similar than distant neurons across learning. Together, our results support a population mechanism in TS during learning in which neurons from both direct and indirect pathways are recruited and take on distinct behavioral roles that vary with performance and task complexity.","rel_num_authors":5,"rel_authors":[{"author_name":"Ivan Linares-Garcia","author_inst":"Rutgers University"},{"author_name":"Sofia E Juliani","author_inst":"Rutgers, The State University of New Jersey"},{"author_name":"Jessie Yi","author_inst":"Rutgers, The State University of New Jersey"},{"author_name":"Diego Castro","author_inst":"Rutgers, The State University of New Jersey"},{"author_name":"David J Margolis","author_inst":"Rutgers, The State University of New Jersey"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"MYC pathway reprogramming through a TIP60 coactivator switch in neuroendocrine lineage transition in prostate cancer","rel_doi":"10.64898\/2026.05.05.723058","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723058","rel_abs":"Prostate adenocarcinomas (PRAD) can acquire resistance to androgen receptor signaling inhibitors through lineage transition to a cell state known as neuroendocrine prostate cancer (NEPC). Using a panel of isogenic PRAD and NEPC mouse tumoroids, we show that NEPC cells acquire new transcription factor (TF) dependencies that function in a previously undefined network. Through selective perturbation of each TF, we identify ASCL1 as a key regulator of NE lineage fate whereas MYCL functions downstream to drive NEPC growth\/survival by recruitment of the TIP60\/KAT5 acetyltransferase. Interestingly, while dependencies on specific TF family paralogs can vary across NEPC models, all show markedly enhanced dependency on TIP60. Moreover, the H2A.Z-acetyltransferase activity of the TIP60 complex (TIP60-C) is required for NEPC as well as the acetyl-reader BRD8, which is newly incorporated as a TIP60-C subunit with the NEPC transition. Targeted degradation studies in isogenic tumoroids reveal increased dependence on MYCL in NEPC relative to its paralog MYC in PRAD. In addition to a paralog switch (MYC to MYCL), the MYC pathway-addicted NE state is accompanied by a chaperone switch (from TIP60-C to SRCAP) for H2A.Z histone exchange and a coactivator switch (to TIP60) for MYC target gene expression. The NE-specific coupling of MYCL with TIP60 reveals a previously unappreciated opportunity to target MYC-driven NE diseases through pharmacological inhibition of TIP60.","rel_num_authors":13,"rel_authors":[{"author_name":"Zhen Sun","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Jimmy Zhao","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Zahra Khan","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Wazim Ismail","author_inst":"Mayo Clinic"},{"author_name":"Teng Han","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Subhiksha Nandakumar","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Serina Young","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Matthew Lange","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Pan Cheng","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Richard Koche","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Nikolaus Schultz","author_inst":"Memorial Sloan Kettering Cancer Center"},{"author_name":"Alexandre Gaspar-Maia","author_inst":"Mayo Clinic"},{"author_name":"Charles Sawyers","author_inst":"Memorial Sloan Kettering Cancer Center"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Intracellular photonic crystals in photosynthetic sea slugs form via a kidney-mediated biomineralisation pathway","rel_doi":"10.64898\/2026.05.07.723475","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723475","rel_abs":"Sea slugs in the Sacoglossa superorder are some of the few animals capable of photosynthesising by isolating and maintaining functional chloroplasts within their body1,2. While this ability allows some species in this superorder, such as Elysia viridis, to appear green, camouflaging themselves within their surroundings3,4, this species is marked by extremely bright, coloured regions. Here, we show that these animals produce a yet undiscovered class of photonic structure consisting of intracellular mixed amorphous CaCO3 and calcite spherical nanoparticles organised in non-closed-packed face-centred cubic (FCC) lattices and photonic glasses5. By mapping the distribution of the cells containing such architectures, we suggest that their colour is linked both to their function and to their biological formation via the animal's renal system. Using a combination of different optical methods and cryo-electron microscopy, we reveal that the biomineralisation pathway proceeds through stages of calcium ion concentration in the kidney, transport via internal vessels, and precipitation from a dense liquid-like precursor, culminating in the formation of monodisperse nanoparticles, which are the building blocks of these photonic structures.","rel_num_authors":14,"rel_authors":[{"author_name":"Samuel Humphrey","author_inst":"Max Planck Institute of Colloids and Interfaces"},{"author_name":"Xianglian He","author_inst":"Max Planck Institute of Colloids and Interfaces"},{"author_name":"Emeline Raguin","author_inst":"Max Planck Institute for Colloids and Interfaces"},{"author_name":"Johannes S. Haataja","author_inst":"Aalto University"},{"author_name":"Tobias Priemel","author_inst":"Max Planck Institute of Colloids and Interfaces"},{"author_name":"Clemens N.Z. Schmitt","author_inst":"Max Planck Institute of Colloids and Interfaces"},{"author_name":"Juliet Brodie","author_inst":"Natural History Museum, London"},{"author_name":"Heather F. Greer","author_inst":"University of Cambridge"},{"author_name":"Daniel Wangpraseurt","author_inst":"University of California San Diego"},{"author_name":"Lloyd Nelmes","author_inst":"Sea Trust"},{"author_name":"Peter Fratzl","author_inst":"Max Planck Institute of Colloids and Interfaces"},{"author_name":"Bruno Jesus","author_inst":"University of Nantes"},{"author_name":"Yu Ogawa","author_inst":"Max Planck Institute of Colloids and Interfaces"},{"author_name":"Silvia Vignolini","author_inst":"Max Planck Institute of Colloids and Interfaces"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Expansion microscopy reveals insulin granule clustering in human \u03b2-cells in type 2 diabetes","rel_doi":"10.64898\/2026.05.05.722840","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722840","rel_abs":"Aims\/hypothesis Quantitative nanoscale analysis of insulin secretory granules (ISGs) in human pancreatic tissue has been limited by the lack of imaging methods that combine high resolution with large-scale sampling. We aimed to establish expansion microscopy (ExM) as a platform for in situ, quantitative analysis of ISG organisation in human {beta}-cells and to assess whether type 2 diabetes (T2D) is associated with alterations in granule size, abundance or spatial organisation. Methods We applied Magnify ExM to PFA-fixed, paraffin-embedded pancreatic tissue sections from 6 human donors, 3 non-diabetic (ND) and 3 T2D, enabling super-resolution optical imaging of insulin-labelled granules. Insulin-positive structures were segmented and analysed using a morphometric pipeline to quantitatively assess size, shape and spatial features. Granule clustering was quantified based on combined area and roundness criteria. Results The diameter distribution of highly circular granules was similar between ND and T2D samples and estimates of granule number per cell indicated only a modest reduction in T2D (~25%). In contrast, mapping insulin-positive structures in a roundness-area space revealed a marked enrichment of large, irregular objects consistent with granule clustering in T2D. The fraction of clustered granules was significantly increased in T2D and strongly inversely correlated with insulin stimulation index (r = -0.85). Conclusions\/interpretation These results establish expansion microscopy as a powerful platform for quantitative nanoscale analysis of human pancreatic tissue and identify altered spatial organisation of insulin granules, rather than marked granule depletion, as a prominent feature associated with {beta}-cell dysfunction in T2D.","rel_num_authors":13,"rel_authors":[{"author_name":"Licia Pugliese","author_inst":"Scuola Normale Superiore"},{"author_name":"Valentina De Lorenzi","author_inst":"Scuola Normale Superiore"},{"author_name":"Gianmarco Ferri","author_inst":"Fondazione Pisana per la Scienza"},{"author_name":"Ha Vo","author_inst":"Carnegie Mellon University"},{"author_name":"Allison Lindquist","author_inst":"Carnegie Mellon University"},{"author_name":"Marta Tesi","author_inst":"University of Pisa"},{"author_name":"Carmela De Luca","author_inst":"University of Pisa"},{"author_name":"Mara Suleiman","author_inst":"University of Pisa"},{"author_name":"Lorella Marselli","author_inst":"University of Pisa"},{"author_name":"Yongxin Zhao","author_inst":"Carnegie Mellon University"},{"author_name":"Piero Marchetti","author_inst":"University of Pisa"},{"author_name":"Fabio Beltram","author_inst":"Scuola Normale Superiore"},{"author_name":"Francesco Cardarelli","author_inst":"Scuola Normale Superiore"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Understanding Substance Dependence: What Differentiates Addictive from Non-Addictive Drugs?","rel_doi":"10.64898\/2026.05.05.723067","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.723067","rel_abs":"Addiction is a global health challenge, yet the molecular features that distinguish addictive from non-addictive drugs remain incompletely understood at the pathway and circuit levels. Here, we present a systematic computational framework that integrates drug-target binding predictions (provided by FINDSITEcomb2.0) with brain-region-specific protein expression to compare addictive and non-addictive compounds. We analyzed 457 addictive and 1,774 non-addictive blood-brain barrier permeable drugs and mapped their predicted targets and associated pathways onto proteins expressed across 120 addiction-relevant brain regions. This analysis reveals widespread convergence between the two classes (addictive and non-addictive drugs) on shared molecular pathways, accompanied by distinct patterns of target and pathway engagement. Functional annotation of differentially engaged targets highlights biases toward plasticity-associated components for addictive drugs. In contrast, non-addictive drugs interact with both plasticity-associated proteins and proteins within the same molecular complex that have addiction suppression, regulatory, and homeostatic functions. Notably, both target classes co-localize within the same addiction-relevant circuits and form an integrated protein-protein interaction network. Together, these results define a differential engagement landscape that links chemical interactions to pathway-level utilization in the brain, revealing molecular features associated with differences in addiction propensity.","rel_num_authors":4,"rel_authors":[{"author_name":"Jeffrey Skolnick","author_inst":"Georgia Institute of technology"},{"author_name":"Hargobind Singh","author_inst":"Georgia Institute of Technology"},{"author_name":"Hongyi Zhou","author_inst":"Georgia Institute of technology"},{"author_name":"Samuel Skolnick","author_inst":"Center for the Study of Systems Biology Georgia Institute of Technology 950 Atlantic Dr NW Atlanta, GA 30332"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"More than an attachment module: covalent inhibitor warheads influence BTK dynamics and function.","rel_doi":"10.64898\/2026.05.07.723540","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723540","rel_abs":"Covalent inhibitors are rapidly becoming the standard of care for treatment of a range of disease states. Covalent inhibitors bind irreversibly to their target using a reactive electrophile (or warhead). Acrylamide and 2-butynamide are the most commonly used cysteine targeting electrophiles. These warheads are chosen for their efficient and selective modification of the protein and are presumed to be otherwise functionally inert. Using a panel of BTK covalent inhibitors (Tirabrutinib, Acalabrutinib, Ibrutinib and Zanubrutinib), we show that the 2-butynamide warhead on Tirabrutinib and Acalabrutinib, unlike the acrylamide warhead on Ibrutinib and Zanubrutinib, induces conformational heterogeneity in key regions required for BTK signaling. Tirabrutinib or Acalabrutinib bound BTK adopt multiple conformational states that are in dynamic exchange, show increased binding to the substrate PLCgamma; and are less effective at inhibiting PLCgamma; signaling when compared to Ibrutinib. Swapping only the warheads between Tirabrutinib and Ibrutinib leads to a corresponding switch in BTK dynamics and inhibitor efficacy. The unanticipated warhead-specific allosteric effects raise interesting possibilities regarding inhibitor-specific mechanisms of resistance.","rel_num_authors":11,"rel_authors":[{"author_name":"Raji E. Joseph","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Robert G. Britton","author_inst":"Division of Cancer Sciences, Cancer Research Centre, College of Life Sciences, University of Leicester, Leicester LE1 9HN, UK."},{"author_name":"David Yin-wei Lin","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Julien Roche","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Jeffrey A. Purslow","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"D. Bruce Fulton","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Poowadon Fukasem","author_inst":"Department of Biomedical Engineering,  School of Engineering, King Mongkuts Institute of Technology, Ladkrabang, Bangkok 10520, Thailand"},{"author_name":"M. Paul Gleeson","author_inst":"Department of Biomedical Engineering, School of Engineering, King Mongkuts Institute of Technology, Ladkrabang, Bangkok 10520, Thailand."},{"author_name":"Martin J. S. Dyer","author_inst":"The Ernest and Helen Scott Haematological Research Institute, Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, Leicester LE1"},{"author_name":"Thomas E. Wales","author_inst":"Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA."},{"author_name":"Amy H. Andreotti","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"More than an attachment module: covalent inhibitor warheads influence BTK dynamics and function.","rel_doi":"10.64898\/2026.05.07.723540","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.07.723540","rel_abs":"Covalent inhibitors are rapidly becoming the standard of care for treatment of a range of disease states. Covalent inhibitors bind irreversibly to their target using a reactive electrophile (or warhead). Acrylamide and 2-butynamide are the most commonly used cysteine targeting electrophiles. These warheads are chosen for their efficient and selective modification of the protein and are presumed to be otherwise functionally inert. Using a panel of BTK covalent inhibitors (Tirabrutinib, Acalabrutinib, Ibrutinib and Zanubrutinib), we show that the 2-butynamide warhead on Tirabrutinib and Acalabrutinib, unlike the acrylamide warhead on Ibrutinib and Zanubrutinib, induces conformational heterogeneity in key regions required for BTK signaling. Tirabrutinib or Acalabrutinib bound BTK adopt multiple conformational states that are in dynamic exchange, show increased binding to the substrate PLCgamma; and are less effective at inhibiting PLCgamma; signaling when compared to Ibrutinib. Swapping only the warheads between Tirabrutinib and Ibrutinib leads to a corresponding switch in BTK dynamics and inhibitor efficacy. The unanticipated warhead-specific allosteric effects raise interesting possibilities regarding inhibitor-specific mechanisms of resistance.","rel_num_authors":11,"rel_authors":[{"author_name":"Raji E. Joseph","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Robert G. Britton","author_inst":"Division of Cancer Sciences, Cancer Research Centre, College of Life Sciences, University of Leicester, Leicester LE1 9HN, UK."},{"author_name":"David Yin-wei Lin","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Julien Roche","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Jeffrey A. Purslow","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"D. Bruce Fulton","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."},{"author_name":"Poowadon Fukasem","author_inst":"Department of Biomedical Engineering,  School of Engineering, King Mongkuts Institute of Technology, Ladkrabang, Bangkok 10520, Thailand"},{"author_name":"M. Paul Gleeson","author_inst":"Department of Biomedical Engineering, School of Engineering, King Mongkuts Institute of Technology, Ladkrabang, Bangkok 10520, Thailand."},{"author_name":"Martin J. S. Dyer","author_inst":"The Ernest and Helen Scott Haematological Research Institute, Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, Leicester LE1"},{"author_name":"Thomas E. Wales","author_inst":"Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA."},{"author_name":"Amy H. Andreotti","author_inst":"Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA."}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Rhodopsin is a tunable capacitor buffering the toxic, desensitizing retinoids of the vertebrate eye","rel_doi":"10.64898\/2026.05.05.722510","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.05.722510","rel_abs":"Visual sensitivity creates photodamage risk, a trade-off thought to limit photo-resilience. Here we reveal that the locus of sensitivity, the visual pigment rhodopsin, moonlights as a tunable mechanism of photoprotection. Light activated rhodopsin (R*) mitigates phototoxicity and boosts rod sensitivity by serving as an overflow capacitor buffering all-trans retinal (atRAL), a toxic and desensitizing retinoid agonist that accumulates as lipofuscin, a clinical marker of macular degeneration. We show that R* stability does not guarantee increased signaling as previously proposed. Instead, across mammals R* stability reflects atRAL binding affinity (capacitance) tuned by photodamage risk. R* capacitance affords cytoprotection and, counterintuitively, promotes dark adaptation by shielding neighboring dark-state receptors from agonist interference. We treated a mouse model of defective atRAL clearance with a synthetic R* of unnaturally high atRAL capacitance. This gene therapy preserved retinal function following light damage and provided supra-physiological scotopic sensitivity despite being a signal-silent receptor, modulating endogenous R* signaling. During recent human evolution, rhodopsin mutations that enhance capacitance and cytoprotection have emerged in high irradiance environments and are now significantly associated with a 36% reduced risk of blindness. Together, our findings redefine rhodopsin as a tunable light buffer that can be leveraged to enhance photoreceptor function beyond natural limits.","rel_num_authors":18,"rel_authors":[{"author_name":"Nadir H Dbouk","author_inst":"Vanderbilt University"},{"author_name":"Madeleine Bagshaw","author_inst":"Vanderbilt University"},{"author_name":"Anamika A Bose","author_inst":"Vanderbilt University"},{"author_name":"Marselle Rasdall","author_inst":"Vanderbilt University"},{"author_name":"Audrey Arner","author_inst":"Vanderbilt University"},{"author_name":"Kun Zhao","author_inst":"Vanderbilt University"},{"author_name":"Kaitlin E Taylor","author_inst":"Vanderbilt University"},{"author_name":"Neena Praveen","author_inst":"Vanderbilt University"},{"author_name":"Weihong Huo","author_inst":"Vanderbilt University"},{"author_name":"Isabella Bautista","author_inst":"Vanderbilt University"},{"author_name":"Narmin Musayeva","author_inst":"Vanderbilt University"},{"author_name":"Liying Xue","author_inst":"Vanderbilt University"},{"author_name":"Jinger N Hayes","author_inst":"Vanderbilt University"},{"author_name":"Marin McElhinney","author_inst":"Vanderbilt University"},{"author_name":"Alexander G Bick","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Amanda J Lea","author_inst":"Vanderbilt University"},{"author_name":"Tonia S Rex","author_inst":"Vanderbilt University"},{"author_name":"Gianni M Castiglione","author_inst":"Vanderbilt University"}],"rel_date":"2026-05-08","rel_site":"biorxiv"},{"rel_title":"Serum IgG antibodies induced by the synthetic carbohydrate-based conjugate vaccine candidate SF2a-TT15 against Shigella flexneri 2a cross-react with the heterologous lipopolysaccharide of Shigella flexneri 6","rel_doi":"10.64898\/2026.05.05.26352385","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352385","rel_abs":"BackgroundShigella flexneri 2a (SF2a) and 6 (SF6) are two of the most common S. flexneri serotypes. They have distant O-specific polysaccharide (O-SP) structures. Previous studies showed no cross-reactivity or cross-protection between the two serotypes in a guinea pig model of infection. However, partial cross-reactivity and cross-protection were reported in humans immunized with a SF2a lattice-type conjugate vaccine candidate comprising the chemically detoxified lipopolysaccharide (LPS) attached to recombinant Pseudomonas aeruginosa Exoprotein A (rEPA).\n\nObjectivesThis study aimed at deciphering the possible cross-reactivity with heterologous SF6 strains of antibodies induced in humans by SF2a-TT15, a sun-type SF2a conjugate vaccine candidate featuring a non-O-acetylated synthetic oligosaccharide (OS) as surrogate of the detoxified LPS. Special focus was on the impact of the O-SP non-stoichiometric O-acetylation on cross-reactivity.\n\nMethodsSerum IgG antibody titers to LPSs from SF6 strains harboring different degrees of O-SP O-acetylation, and from Escherichia coli O147 (EC147) which shares an identical but non-O-acetylated O-SP with SF6, were measured by ELISA in 63 serum samples of volunteers receiving 2 {micro}g and 10 {micro}g OS doses of SF2a-TT15 or placebo in the frame of a phase I clinical study. Antibody in-lymphocyte-supernatants (ALS), avidity, and serum bactericidal activity (SBA) were measured in a subset of volunteers.\n\nResultsSF2a-TT15 induced cross-reacting IgG antibodies to all SF6 LPSs and EC147 LPS. A [&ge;]4-fold rise in anti-SF6 IgG titers was more frequent with the 10 {micro}g dose than with 2 {micro}g (50% vs 22%, p=0.045). Cross-reactivity rate was higher with the low O-acetylated SF6 O-SP than with the high O-acetylated one (50% versus 21%, p<0.05). Anti-SF6 responses correlated with homologous anti-SF2a LPS responses. Similar cross-reactivity was detected in ALS samples at day 7 after vaccination. Cross-reacting antibodies were partially functional against the heterologous SF6 parental strains, as shown by bactericidal activity and increased avidity.\n\nConclusionsSF2a-TT15 induces stronger SF6 cross-reactive IgG responses than the previously tested detoxified O-acetylated SF2a LPS-rEPA conjugate. While both serotypes are included in most multivalent Shigella vaccine candidates, cross-reactivity and cross-protection between SF2a and SF6 could enhance the immunogenicity and efficacy of a Shigella multivalent vaccine candidate, particularly in infants in low- and middle-income countries, the primary target population for a Shigella vaccine.","rel_num_authors":10,"rel_authors":[{"author_name":"Valeria Asato","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Shiri Meron-Sudai","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Anya Bialik","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Sophy Goren","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Shubham Mathur","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Jonas St\u00e5hle","author_inst":"Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden"},{"author_name":"G\u00f6ran Widmalm","author_inst":"Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden"},{"author_name":"Armelle Phalipon","author_inst":"Institut Pasteur, Universit\u00e9 Paris Cit\u00e9, Medical Direction, F-75015 Paris, France"},{"author_name":"Laurence A. Mulard","author_inst":"Institut Pasteur, Universit\u00e9 Paris Cit\u00e9, CNRS UMR3523, Unit\u00e9 Chimie des Biomol\u00e9cules, 28 rue du Dr Roux, F-75015 Paris, France"},{"author_name":"Dani Cohen","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Serum IgG antibodies induced by the synthetic carbohydrate-based conjugate vaccine candidate SF2a-TT15 against Shigella flexneri 2a cross-react with the heterologous lipopolysaccharide of Shigella flexneri 6","rel_doi":"10.64898\/2026.05.05.26352385","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352385","rel_abs":"BackgroundShigella flexneri 2a (SF2a) and 6 (SF6) are two of the most common S. flexneri serotypes. They have distant O-specific polysaccharide (O-SP) structures. Previous studies showed no cross-reactivity or cross-protection between the two serotypes in a guinea pig model of infection. However, partial cross-reactivity and cross-protection were reported in humans immunized with a SF2a lattice-type conjugate vaccine candidate comprising the chemically detoxified lipopolysaccharide (LPS) attached to recombinant Pseudomonas aeruginosa Exoprotein A (rEPA).\n\nObjectivesThis study aimed at deciphering the possible cross-reactivity with heterologous SF6 strains of antibodies induced in humans by SF2a-TT15, a sun-type SF2a conjugate vaccine candidate featuring a non-O-acetylated synthetic oligosaccharide (OS) as surrogate of the detoxified LPS. Special focus was on the impact of the O-SP non-stoichiometric O-acetylation on cross-reactivity.\n\nMethodsSerum IgG antibody titers to LPSs from SF6 strains harboring different degrees of O-SP O-acetylation, and from Escherichia coli O147 (EC147) which shares an identical but non-O-acetylated O-SP with SF6, were measured by ELISA in 63 serum samples of volunteers receiving 2 {micro}g and 10 {micro}g OS doses of SF2a-TT15 or placebo in the frame of a phase I clinical study. Antibody in-lymphocyte-supernatants (ALS), avidity, and serum bactericidal activity (SBA) were measured in a subset of volunteers.\n\nResultsSF2a-TT15 induced cross-reacting IgG antibodies to all SF6 LPSs and EC147 LPS. A [&ge;]4-fold rise in anti-SF6 IgG titers was more frequent with the 10 {micro}g dose than with 2 {micro}g (50% vs 22%, p=0.045). Cross-reactivity rate was higher with the low O-acetylated SF6 O-SP than with the high O-acetylated one (50% versus 21%, p<0.05). Anti-SF6 responses correlated with homologous anti-SF2a LPS responses. Similar cross-reactivity was detected in ALS samples at day 7 after vaccination. Cross-reacting antibodies were partially functional against the heterologous SF6 parental strains, as shown by bactericidal activity and increased avidity.\n\nConclusionsSF2a-TT15 induces stronger SF6 cross-reactive IgG responses than the previously tested detoxified O-acetylated SF2a LPS-rEPA conjugate. While both serotypes are included in most multivalent Shigella vaccine candidates, cross-reactivity and cross-protection between SF2a and SF6 could enhance the immunogenicity and efficacy of a Shigella multivalent vaccine candidate, particularly in infants in low- and middle-income countries, the primary target population for a Shigella vaccine.","rel_num_authors":10,"rel_authors":[{"author_name":"Valeria Asato","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Shiri Meron-Sudai","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Anya Bialik","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Sophy Goren","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Shubham Mathur","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"},{"author_name":"Jonas St\u00e5hle","author_inst":"Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden"},{"author_name":"G\u00f6ran Widmalm","author_inst":"Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden"},{"author_name":"Armelle Phalipon","author_inst":"Institut Pasteur, Universit\u00e9 Paris Cit\u00e9, Medical Direction, F-75015 Paris, France"},{"author_name":"Laurence A. Mulard","author_inst":"Institut Pasteur, Universit\u00e9 Paris Cit\u00e9, CNRS UMR3523, Unit\u00e9 Chimie des Biomol\u00e9cules, 28 rue du Dr Roux, F-75015 Paris, France"},{"author_name":"Dani Cohen","author_inst":"Department of Epidemiology and Preventive Medicine, School of Public Health, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv 69978, Isr"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"The Effect of Legalizing Online Sports Gambling on Population Mental Health","rel_doi":"10.64898\/2026.05.06.26352568","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352568","rel_abs":"ImportanceThe rapid rise of online sports gambling in the U.S. has been associated with financial harms, raising concern that it may adversely affect population mental health.\n\nObjectiveTo estimate the causal effect of state legalization of online sports gambling on population mental health, including a range of self-reported and registry-based outcomes.\n\nDesign, Setting, and ParticipantsRepeated cross-sectional study using nationally representative Behavioral Risk Factor Surveillance System (BRFSS) data from 2014-2025 and registry-based mortality records from 2012-2024. We leveraged state-level variation in the legalization of online sports gambling and applied a stacked difference-in-differences with event study design. The analytic sample included 4,660,948 BRFSS respondents and mortality records for virtually all state-years. We estimated effects on all adults and several higher-risk subgroups, including men, young men, and men with lower educational attainment.\n\nExposureState legalization of online sports gambling.\n\nMain Outcomes and MeasuresSelf-reported outcomes included poor mental health days, depressive disorder diagnoses, ever binge drinking, number of binge drinking episodes, and marijuana use. Registry-based outcomes included suicide mortality and alcohol-induced mortality per 100,000.\n\nResultsAmong 4,660,948 BRFSS respondents, 48.7% were men, 40.2% had no more than a high school education, and the mean age was 47.6 years. Legalization of online sports gambling had no discernible effect on poor mental health days of all U.S. adults (-0.01 days; 95% CI, -0.16 to 0.14; P=0.88), depressive disorder diagnoses (0.1 percentage points; 95% CI, -0.7 to 0.9; P=0.84), binge drinking, binge drinking episodes, or marijuana use. Meanwhile, mean suicide mortality was 14.1 per 100,000 and mean alcohol-induced mortality was 12.2 per 100,000. Legalization did not affect adult suicides (0.13 deaths per 100,000; 95% CI, -0.71 to 0.97; P=0.76) or alcohol-induced mortality (1.08 deaths per 100,000; 95% CI, -0.58 to 2.73; P=0.21). Results were null among men and higher-risk subgroups of men.\n\nConclusions and RelevanceThe legalization of online sports gambling has not produce detectable population-level changes in a range of mental health outcomes, including reported symptoms, diagnoses, substance use, and registry-based mortality due to suicide or alcohol, in up to 3 years of follow-up. These findings suggest that although online sports gambling may cause financial harm and severe distress for some individuals, legalization has not produced measurable average changes in population mental health over the observed follow-up period.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSHas the legalization of online sports gambling affected population-level mental health, including symptoms, diagnoses, substance use, suicides, and alcohol-induced mortality?\n\nFindingsIn this repeated cross-sectional study that applied a difference-in-differences design to more than 4.6 million individual-level survey responses and mortality records, the legalization of online sports gambling from 2018-2024 did not affect reported poor mental health days, depressive disorders, binge drinking, marijuana use, suicide mortality, or alcohol-induced mortality. Results were similar among men and higher-risk subgroups of men.\n\nMeaningThe legalization of online sports gambling has not produced detectable population-level changes in a broad range of mental health outcomes in up to 3 years of follow-up.","rel_num_authors":4,"rel_authors":[{"author_name":"Nolan M. Kavanagh","author_inst":"Harvard University"},{"author_name":"Jacob C. Jameson","author_inst":"Harvard University"},{"author_name":"Harold A. Pollack","author_inst":"University of Chicago"},{"author_name":"Nathaniel J. Glasser","author_inst":"University of Chicago"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Comparative Evaluation of Wearable Sensor Form Factors for Physiological Monitoring in Youth with Autism Spectrum Disorder","rel_doi":"10.64898\/2026.05.06.26352564","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352564","rel_abs":"Sudden behavioral outbursts in youth with autism spectrum disorder (ASD) are difficult to predict and create substantial caregiving burdens. Wearable physiological monitoring might enable prediction, but sustained use may be limited by tolerability. We evaluated adherence and data completeness in 40 youth with ASD over a two-week period across four device types (wristband, headband, adhesive chest patch, and finger ring) alongside caregiver-reported useability and comfort. Data completeness varied markedly by device, with the patch achieving the highest completeness ([~]80%), followed by the wristband ([~]60%), headband ([~]50%), and ring ([~]20%). In multivariate analyses, adherence was driven by the device form factor rather than participant-level clinical characteristics. Devices rated as more comfortable did not yield higher completeness, revealing a divergence between reported preference and actual use. These findings suggest that device choice is a key consideration for studies in ASD youths, highlighting the need for research into model stability across sensor types in neurodivergent populations.","rel_num_authors":9,"rel_authors":[{"author_name":"Caden Stewart","author_inst":"Halicioglu Data Science Institute, University of California San Diego"},{"author_name":"Abigail Albertazzi","author_inst":"Rady Childrens Hospital of San Diego"},{"author_name":"Jacqueline Tasarz","author_inst":"Rady Childrens Hospital of San Diego"},{"author_name":"Kristen Kim","author_inst":"Division of Child & Adolescent Psychiatry, Department of Psychiatry, University of California San Diego"},{"author_name":"Veronica Gandara","author_inst":"St. Josephs Medical Center Stockton"},{"author_name":"Corrine Blucher","author_inst":"Rady Childrens Institute for Genomic Medicine"},{"author_name":"Camilla C. Reyes-Martinez","author_inst":"Division of Child & Adolescent Psychiatry, Department of Psychiatry, University of California San Diego"},{"author_name":"Benjamin Smarr","author_inst":"Shiu Chen - Gene Lay Department of Bioengineering, University of California San Diego"},{"author_name":"Aaron D. Besterman","author_inst":"Division of Child & Adolescent Psychiatry, Department of Psychiatry, University of California San Diego"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Conserved neuroectodermal aging encodes primate health and longevity","rel_doi":"10.64898\/2026.05.05.26352498","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352498","rel_abs":"Neuroectoderm-derived tissues are highly metabolically active and exhibit minimal regenerative turnover, rendering them uniquely vulnerable to age-related stress while preserving undiluted degenerative signals. Yet aging dynamics in these tissues remain elusive in living primates. Here, we introduce an in vivo neuroectodermal aging clock and trace its trajectory in 66,602 human adults and six rhesus macaques across nine health and disease cohorts using an in situ optical biopsy. Through a digital histology atlas integrated with artificial intelligence, we resolve tissue representations of neuroectodermal aging within the human retina, predominantly localized to the metabolically active ganglion and bipolar cell populations and the photoreceptor complex, while demonstrating their evolutionary conservation across primate species. Neuroectodermal aging predicts health and longevity, scales across space and time, and captures preclinical aging signals within and beyond the neuroectodermal compartment. This framework is further validated in a diabetic population, where robust prognostic and dynamic sensitivity are preserved across physiological and perturbed states. Our work establishes a scalable framework for resolving neuroectodermal aging in living primates and linking tissue-level vulnerability to systemic health trajectories.","rel_num_authors":3,"rel_authors":[{"author_name":"Shaopeng Yang","author_inst":"Zhongshan Ophthalmic Center, Sun Yat-sen University"},{"author_name":"Zhuoyao Xin","author_inst":"Department of Biomedical Engineering, Johns Hopkins University"},{"author_name":"Wei Wang","author_inst":"Zhongshan Ophthalmic Center, Sun Yat-sen university"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Modeling rare coding variation on chromosome X provides insight into the genetics and differential sex prevalence of autism spectrum disorder","rel_doi":"10.64898\/2026.05.04.26352380","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.04.26352380","rel_abs":"Autism spectrum disorder (ASD) is estimated to be up to four times as common in males as in females, yet the causes of this prevalence difference are not well established. One possible driver is genetic variation on the X chromosome, as it contains genes capable of contributing to ASD (e.g., PTCHD1, MECP2) and is known to play a role in genetic disorders with differential sex prevalence (e.g., color blindness). However, a lack of power compared to the autosomes combined with the complexities of modeling its biology have led to the X being largely overlooked in sequencing studies. Here, we develop quantitative X-linked TADA, a new model designed specifically for application to this chromosome, and use it to analyze rare variation from 50,663 individuals with ASD (and 136,670 individuals total). We find 9 genes on the X associated with ASD at a false discovery rate (FDR) < 0.05 and an additional 9 genes at FDR < 0.2, with many of these previously identified as involved in specific neurodevelopmental disorders. Point estimates of the liability conferred by de novo variants on the X are similar in females and males, with both sexes estimates elevated >20% above the corresponding autosomal values. We also develop a general theory of how X-linked variation of any additive or non-additive effect influences liability and describe its implications for prevalence. Using this theory and our empirical results, we show how genetic variation on the X could contribute to the sex-differential prevalence of ASD.","rel_num_authors":15,"rel_authors":[{"author_name":"F. Kyle Satterstrom","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Kiana Jodeiry","author_inst":"Emory University School of Medicine"},{"author_name":"Behrang Mahjani","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Gad Hatem","author_inst":"Emory University School of Medicine"},{"author_name":"Se Jun Park","author_inst":"Emory University School of Medicine"},{"author_name":"Lambertus Klei","author_inst":"University of Pittsburgh"},{"author_name":"Jack M. Fu","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Emilie M. Wigdor","author_inst":"University of Oxford"},{"author_name":"- the Autism Sequencing Consortium","author_inst":""},{"author_name":"Catalina Betancur","author_inst":"Sorbonne Universite"},{"author_name":"Mark J. Daly","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Kathryn Roeder","author_inst":"Carnegie Mellon University"},{"author_name":"Bernie Devlin","author_inst":"University of Pittsburgh"},{"author_name":"Joseph D. Buxbaum","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"David J. Cutler","author_inst":"Emory University School of Medicine"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"A tool for assessing changes in food preferences and health perceptions during nutritional interventions","rel_doi":"10.64898\/2026.05.06.26352307","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352307","rel_abs":"Understanding how nutritional interventions alter food evaluations may help clarify mechanisms of dietary behavior change; however, most studies focus on intake outcomes and rarely assess within-person changes in subjective food evaluation. We developed a brief, image-based rating tool that measures two core dimensions of food evaluation, liking and perceived healthiness, using standardized food images.\n\nThe tool was piloted in adults with type 2 diabetes participating in a medically supervised intervention that included structured glucose monitoring and professional dietary guidance. Ratings were collected at baseline, post-monitoring, and follow-up. In line with the methodological aim of this study, we examined whether the tool demonstrates internal coherence, sensitivity to change, and external validity against expert ratings and physiological measures, and whether it can capture item-level patterns relevant to eating behavior.\n\nResults provide preliminary evidence that the tool is feasible, it is low-burden, and capable of detecting coherent relationships between food liking and health perceptions, including coordinated within-person changes over time and meaningful associations with external benchmarks. To support scalability and self-administration, we also developed an online smartphone-based demonstration version to exemplify the task structure and user experience. Overall, this pilot study suggests that a short, flexible rating task can serve as a practical measurement tool for tracking intervention-relevant changes in food evaluation and for informing the design of future nutritional interventions.","rel_num_authors":5,"rel_authors":[{"author_name":"Maya Bar Or","author_inst":"Tel Aviv University"},{"author_name":"Nuphar Vinegrad","author_inst":"Diabetes clinic, Soroka university Medical Center & Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel"},{"author_name":"Sara Menashe Auman","author_inst":"Diabetes clinic, Soroka university Medical Center"},{"author_name":"Idit F Liberty","author_inst":"Diabetes clinic, Soroka university Medical Center & Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel"},{"author_name":"Tom Schonberg","author_inst":"Tel Aviv University"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Generating synthetic tau-PET scans in Alzheimer's disease from MRI, blood biomarkers and demographics with deep learning","rel_doi":"10.64898\/2026.05.06.26352540","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352540","rel_abs":"Tau protein aggregation in the brain is a hallmark of Alzheimers disease (AD). Positron emission tomography (PET) is the only in vivo method to visualize tau pathology and estimate both its burden and regional distribution, but the use of tau-PET is constrained by high cost and limited accessibility. Here, we develop a deep learning model to synthesize tau-PET scans from more accessible data: structural magnetic resonance imaging (MRI), demographics, and when available, blood biomarkers. We included 5,191 participants across the AD continuum or with another neurological disorder from 13 cohorts (mean age 70 years, 51% female) and optimized a 3D U-Net neural network with residual and attention units for this task. In held-out test data, synthetic tau-PET reliably modeled tau burden, with correlations of R=0.77-0.86 with true tau-PET across individuals in common AD regions of interest. Spatial similarity between synthetic and true tau-PET was likewise high, with mean regional correlation of R=0.75. Synthetic scans also captured clinically meaningful prognostic information comparable to true tau-PET, including distinction between early (HR=12, p<0.001) and late (HR=45, p<0.001) stages of tau accumulation. These findings demonstrate that clinically informative synthetic tau-PET scans can be generated from widely available modalities using deep learning, potentially offering a scalable and cost-effective approach for estimating tau AD pathology in the brain.","rel_num_authors":23,"rel_authors":[{"author_name":"Linda Karlsson","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Olof Strandberg","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Ruben Smith","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Weizhong Tang","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Ida Arvidsson","author_inst":"Centre for Mathematical Sciences, Lund University, Lund, Sweden"},{"author_name":"Kalle Astrom","author_inst":"Centre for Mathematical Sciences, Lund University, Lund, Sweden"},{"author_name":"Kevin Oliviera Hauer","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Shorena Janelidze","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Erik Stomrud","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Sebastian Palmqvist","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Philip B Verghese","author_inst":"C2N Diagnostics LLC, St Louis, MO, USA"},{"author_name":"Joel B Braunstein","author_inst":"C2N Diagnostics LLC, St Louis, MO, USA"},{"author_name":"- Alzheimer's Disease Neuroimaging Initiative","author_inst":""},{"author_name":"- PREVENT-AD Research Group","author_inst":""},{"author_name":"Gregory Klein","author_inst":"Pharma Research and Early Development, F Hoffmann-La Roche Ltd., Basel, Switzerland"},{"author_name":"Sergey Shcherbinin","author_inst":"Eli Lilly and Company, Indianapolis, Indiana, USA"},{"author_name":"William J Jagust","author_inst":"Department of Neuroscience, University of California, Berkeley, California, USA"},{"author_name":"Sylvia Villeneuve","author_inst":"Centre for Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada."},{"author_name":"Renaud La Joie","author_inst":"Department of Neurology, Edward and Pearl Fein Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, "},{"author_name":"Gil D Rabinovici","author_inst":"Department of Neurology, Edward and Pearl Fein Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, "},{"author_name":"Niklas Mattsson-Carlgren","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Jacob W Vogel","author_inst":"Clinical Memory Research Unit, SciLifeLab, Department of Clinical Sciences in Malmo, Lund University, Lund, Sweden"},{"author_name":"Oskar Hansson","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Generating synthetic tau-PET scans in Alzheimer's disease from MRI, blood biomarkers and demographics with deep learning","rel_doi":"10.64898\/2026.05.06.26352540","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352540","rel_abs":"Tau protein aggregation in the brain is a hallmark of Alzheimers disease (AD). Positron emission tomography (PET) is the only in vivo method to visualize tau pathology and estimate both its burden and regional distribution, but the use of tau-PET is constrained by high cost and limited accessibility. Here, we develop a deep learning model to synthesize tau-PET scans from more accessible data: structural magnetic resonance imaging (MRI), demographics, and when available, blood biomarkers. We included 5,191 participants across the AD continuum or with another neurological disorder from 13 cohorts (mean age 70 years, 51% female) and optimized a 3D U-Net neural network with residual and attention units for this task. In held-out test data, synthetic tau-PET reliably modeled tau burden, with correlations of R=0.77-0.86 with true tau-PET across individuals in common AD regions of interest. Spatial similarity between synthetic and true tau-PET was likewise high, with mean regional correlation of R=0.75. Synthetic scans also captured clinically meaningful prognostic information comparable to true tau-PET, including distinction between early (HR=12, p<0.001) and late (HR=45, p<0.001) stages of tau accumulation. These findings demonstrate that clinically informative synthetic tau-PET scans can be generated from widely available modalities using deep learning, potentially offering a scalable and cost-effective approach for estimating tau AD pathology in the brain.","rel_num_authors":23,"rel_authors":[{"author_name":"Linda Karlsson","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Olof Strandberg","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Ruben Smith","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Weizhong Tang","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Ida Arvidsson","author_inst":"Centre for Mathematical Sciences, Lund University, Lund, Sweden"},{"author_name":"Kalle Astrom","author_inst":"Centre for Mathematical Sciences, Lund University, Lund, Sweden"},{"author_name":"Kevin Oliviera Hauer","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Shorena Janelidze","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Erik Stomrud","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Sebastian Palmqvist","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Philip B Verghese","author_inst":"C2N Diagnostics LLC, St Louis, MO, USA"},{"author_name":"Joel B Braunstein","author_inst":"C2N Diagnostics LLC, St Louis, MO, USA"},{"author_name":"- Alzheimer's Disease Neuroimaging Initiative","author_inst":""},{"author_name":"- PREVENT-AD Research Group","author_inst":""},{"author_name":"Gregory Klein","author_inst":"Pharma Research and Early Development, F Hoffmann-La Roche Ltd., Basel, Switzerland"},{"author_name":"Sergey Shcherbinin","author_inst":"Eli Lilly and Company, Indianapolis, Indiana, USA"},{"author_name":"William J Jagust","author_inst":"Department of Neuroscience, University of California, Berkeley, California, USA"},{"author_name":"Sylvia Villeneuve","author_inst":"Centre for Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada."},{"author_name":"Renaud La Joie","author_inst":"Department of Neurology, Edward and Pearl Fein Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, "},{"author_name":"Gil D Rabinovici","author_inst":"Department of Neurology, Edward and Pearl Fein Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, "},{"author_name":"Niklas Mattsson-Carlgren","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"},{"author_name":"Jacob W Vogel","author_inst":"Clinical Memory Research Unit, SciLifeLab, Department of Clinical Sciences in Malmo, Lund University, Lund, Sweden"},{"author_name":"Oskar Hansson","author_inst":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"Regulatory architecture underlying immune dysregulation reconstructed by single-cell multi-omics in lupus nephritis","rel_doi":"10.64898\/2026.05.06.26352515","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.06.26352515","rel_abs":"ObjectivesLupus nephritis (LN) is a severe complication of systemic lupus erythematosus with heterogeneous clinical outcomes and limited therapeutic options. Although immune dysregulation is central to LN pathogenesis, the underlying cell-type-specific regulatory mechanisms and their genetic determinants remain poorly characterized.\n\nMethodsWe generated a single-cell multi-omics atlas of peripheral blood mononuclear cells (PBMCs) from newly diagnosed, minimally treated LN patients by integrating single-cell RNA-seq (scRNA-seq) and single-nucleus ATAC-seq (snATAC-seq) profiles. To elucidate genetically driven regulatory programs in a broaden LN population, we generated a blood expression quantitative trait loci (eQTL) atlas from 99 Chinese LN patients and performed Bayesian colocalization analysis to systematically prioritize putative causal genes for LN. Finally, we investigated how fine-mapped SNPs associated with LN phenotypic manifestations exert regulatory effects within distinct single-cell chromation contexts by leveraging peak-to-gene linkages at single-cell resolution.\n\nResultsOur single-cell multi-omic dataset and orthogonal analytical approaches revealed extensive immune remodeling in LN, characterized by amplified innate immune activation and impaired adaptive immune responses, and identified transcription factors (TFs) orchestrating immune regulatory circuits. Bayesian colocalization analysis nominated 14 high-fidelity causal genes for kidney function and 23 for SLE. Integration with fine-mapped GWAS variants highlighted critical cell type convergence across autoimmune disorders and immune-mediated nephropathies, particularly within B cell subsets, where TF-driven programs delineated stage-specific differentiation networks.\n\nConclusionsTogether, these analyses reconstruct the regulatory architecture underlying immune dysregulation in LN and connect genetic variation to cell-type-specific regulation, guiding genetically informed therapeutic development.","rel_num_authors":16,"rel_authors":[{"author_name":"Huanhuan Zhao","author_inst":"Zhejiang University"},{"author_name":"Fan Yang","author_inst":"National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University of Medicine"},{"author_name":"Tingyu Chen","author_inst":"National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University of Medicine"},{"author_name":"Jian Zhang","author_inst":"Liangzhu Laboratory, Zhejiang University"},{"author_name":"Jinsong Shi","author_inst":"National Clinical Research Center of Kidney Diseases, Jinling"},{"author_name":"Xiaoyang Liu","author_inst":"Liangzhu Laboratory, Zhejiang University"},{"author_name":"Siyi Chen","author_inst":"chensyi@126.com"},{"author_name":"Ziyuan Ma","author_inst":"ziyuan.ma@rutgers.edu"},{"author_name":"Shuai Liu","author_inst":"shuailiu@zju.edu.cn"},{"author_name":"Xudong Fu","author_inst":"xudongfu@zju.edu.cn"},{"author_name":"Na Kong","author_inst":"Liangzhu Laboratory, Zhejiang University"},{"author_name":"Jin Zhang","author_inst":"Liangzhu Laboratory, Zhejiang University"},{"author_name":"Xiaomin Yu","author_inst":"Liangzhu Laboratory, Zhejiang University"},{"author_name":"Katalin Susztak","author_inst":"Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania"},{"author_name":"Xin Sheng","author_inst":"Zhejiang University"},{"author_name":"Zhihong Liu","author_inst":"Liangzhu Laboratory, Zhejiang University"}],"rel_date":"2026-05-07","rel_site":"medrxiv"},{"rel_title":"NeuroDev: etiology and experience of neurodevelopmental disorders in Kenya and South Africa","rel_doi":"10.64898\/2026.04.30.26351947","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.04.30.26351947","rel_abs":"The NeuroDev study, conducted in Kenya and South Africa, is a large-scale clinical, genetic, and epidemiologic characterization of neurodevelopmental disorders (NDDs) on the African continent. NeuroDev assessments capture birth, demographic, and developmental history; cognitive and behavioral outcomes; and physical health variables. DNA samples are collected for exome sequencing and clinical genetic analysis. This paper presents novel data from 521 children with NDDs, 739 of those childrens parents, and 255 unrelated, typically-developing children. The analyses offer unique genetic and phenotypic characterizations of NDDs in two African countries and underscore the importance of including underrepresented populations in NDD research. Ultimately, 107 children with NDDs from the NeuroDev cohort (22.1%) had likely pathogenic or pathogenic variants in established NDD genes. High rates of genetic diagnosis were associated with high rates of environmental risk factors for NDDs. All data, materials, and measures generated from this study are publicly available through the US National Institute of Mental Health.","rel_num_authors":44,"rel_authors":[{"author_name":"Patricia Kipkemoi","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Emily O Heir","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Mutaz Amin","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Sarah L Stenton","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"William Baddoo","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Harrison Brand","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston MA, USA"},{"author_name":"Zandre Bruwer","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Sam Bryant","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Eunice Chepkemoi","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Bjorn Christ","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Emma Eastman","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Claire Fourie","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Jack M Fu","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston MA, USA"},{"author_name":"Alice Galvin","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Stacey Hall","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Fatima Khan","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Heesu Ally Kim","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Collins Kipkoech","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Martha Kombe","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Racheal Mapenzi","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Brigitte Melly","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Celia van der Merwe","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Beatrice Mkubwa","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Serini Murugasen","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Katini Mwangasha","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Paul Mwangi","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Samuel Mwasambu","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Alfred Ngombo","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Javan Nyale","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Grace E VanNoy","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Ikeoluwa Osei-Owusu","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Jessica E Ringshaw","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Kathryn A Russell","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Kaitlin E Samocha","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Alba Sanchis-Juan","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston MA, USA"},{"author_name":"Moriel Singer-Berk","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Michal Zieff","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston MA, USA"},{"author_name":"Anne O Donnell-Luria","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Christina Austin-Tse","author_inst":"The Broad Institute of MIT and Harvard, Cambridge MA, USA"},{"author_name":"Charles Newton","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Amina Abubakar","author_inst":"Neuroscience Unit, KEMRI-Wellcome Trust, Center for Geographic Medicine Research Coast, Kilifi, Kenya"},{"author_name":"Kirsten A Donald","author_inst":"Department of Paediatrics and Child Health, Red Cross War Memorial Childrens Hospital, University of Cape Town, Rondebosch, South Africa"},{"author_name":"Elise B Robinson","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston MA, USA"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"The dynamic motor control index as a measure of post-stroke impairments in neuromotor control","rel_doi":"10.64898\/2026.04.30.26351964","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.04.30.26351964","rel_abs":"Measuring neuromotor control after stroke is crucial for identifying the mechanisms underlying asymmetrical walking and guiding rehabilitation. The lower extremity portion of the Fugl-Meyer (FM-LE) and the number of muscle synergies are commonly used measures, but have important limitations. The dynamic motor control index has emerged as a complementary metric, yet its relationship to established clinical measures (i.e., FM-LE), muscle synergy number, and gait biomechanics remains unclear. This study evaluated the ability of the dynamic motor control index to quantify post-stroke neuromotor impairment relative to FM-LE and muscle synergy number and examined its relationship with propulsion asymmetry. Electromyography data from 22 individuals post-stroke and 31 neurotypical controls were analyzed using non-negative matrix factorization. The dynamic motor control index and not the muscle synergy number differentiated paretic, non-paretic, and neurotypical limbs ({chi}2(2) = 27.57, p < .001). It also differed significantly between less and more impaired individuals classified by FM-LE (p = .05) and demonstrated good discriminative performance between these groups (AUC: 0.777, p = .017). The index also moderated the relationship between FM-LE and propulsion asymmetry ({Delta}R2 = 0.223, p = .007). These findings support the dynamic motor control index as a clinically relevant msarker of post-stroke neuromotor impairment and recovery.","rel_num_authors":7,"rel_authors":[{"author_name":"Ashley N Collimore-Doherty","author_inst":"Department of Physical Therapy, Boston University, Boston, MA, USA"},{"author_name":"Ruoxi Wang","author_inst":"Department of Physical Therapy, Boston University, Boston, MA, USA"},{"author_name":"David A Sherman","author_inst":"Department of Physical Therapy, Movement & Rehabilitation Sciences, Northeastern University, Boston, MA"},{"author_name":"Conor J Walsh","author_inst":"Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA"},{"author_name":"Paolo Bonato","author_inst":"Harvard Medical School, Spaulding Rehabilitation Hospital, Boston, MA, USA"},{"author_name":"Terry Ellis","author_inst":"Department of Physical Therapy, Boston University, Boston, MA, USA"},{"author_name":"Louis N Awad","author_inst":"Department of Physical Therapy, Boston University, Boston, MA, USA"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Exposome contribution to the brain metabolome: importance of body brain connection.","rel_doi":"10.64898\/2026.05.05.26352469","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352469","rel_abs":"INTRODUCTIONMounting evidence support exposome influences on brain function and health, complementing genome influences. Understanding the molecular imprint of exposome on brain metabolism and the biochemical communication between the body and brain can impact our fundamental understanding and treatment of neuropsychiatric diseases.\n\nMETHODSLeveraging two complementary metabolomics platforms, we classified 1400 features in 514 brains from the ROSMAP collection. We evaluated the origin of these compounds using literature and databases. We correlated those metabolites with cognitive function using linear models.\n\nRESULTSWe identified over 230 non-endogenous compounds in the brain, including 103 drugs and metabolites, 120 dietary and microbial products and possibly 15 compounds from environmental exposures. Over 20 dietary and gut microbial compounds showed associations with cognition.\n\nDISCUSSIONComprehensive profiling of chemicals in the brain and the link to cognitive function provides foundational work to connect body and brain in the study of AD and related dementias.","rel_num_authors":15,"rel_authors":[{"author_name":"Naama Karu","author_inst":"Tasmanian Independent Metabolomics and Analytical Chemistry Solutions"},{"author_name":"Haoqi Nina Zhao","author_inst":"UC San Diego"},{"author_name":"Richa Batra","author_inst":"Weill Cornell Medical College of Cornell University"},{"author_name":"Matthias Arnold","author_inst":"Helmholtz Zentrum Munchen - German Research Center for Environmental Health"},{"author_name":"Jan Krumsiek","author_inst":"Weill Cornell Medicine"},{"author_name":"Lurian Caetano David","author_inst":"UC San Diego"},{"author_name":"Dinesh Barupal","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Leyla Schimmel","author_inst":"Duke University"},{"author_name":"Alexandra Kueider-Paisley","author_inst":"Duke University"},{"author_name":"Colette Blach","author_inst":"Duke University"},{"author_name":"Kamil Borkowski","author_inst":"University of California Davis"},{"author_name":"Pieter Dorrestein","author_inst":"UC San Diego"},{"author_name":"David  A Bennett","author_inst":"Rush University Medical Center"},{"author_name":"Rima Kaddurah-Daouk","author_inst":"Duke University"},{"author_name":"- Alzheimer's Disease Metabolomics Consortium","author_inst":"-"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Soluble Glycoprotein 120 is associated with Coronary Artery Inflammation Measured by Pericoronary Fat Attenuation Index in People Living with HIV","rel_doi":"10.64898\/2026.05.05.26352462","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352462","rel_abs":"Persistence of HIV antigens may drive chronic inflammation, leading to early-onset comorbidity among people living with HIV. We found that the presence of soluble glycoprotein 120 in plasma is associated with increased coronary inflammation, as measured by the pericoronary fat attenuation index (PFAI), a predictor of overt cardiovascular disease.","rel_num_authors":16,"rel_authors":[{"author_name":"Pengd-Wende Habib Bousse Traore","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Kevin Boczar","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Mehdi Benlarbi","author_inst":"Centre de recherche du CHUM, and Departement of microbiology, infectiology and immunology, University of Montreal, Canada"},{"author_name":"Victoria Devine-Ducharme","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Valerie Shirobokov","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Bethlehem Mengesha","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Jonathan Richard","author_inst":"Centre de recherche du CHUM and Departement of microbiology, infectiology and immunology, University of Montreal, Canada"},{"author_name":"Nicolas Chomont","author_inst":"University de Montreal"},{"author_name":"Marc Messier-Peet","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Annie Chamberland","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Branka Vulesevic","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Mohamed El-Far","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Cecile Tremblay","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Carl Chartrand-Lefebvre","author_inst":"Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de L'Universite de Montreal, Montreal, Canada"},{"author_name":"Andres Finzi","author_inst":"University of Montreal"},{"author_name":"Madeleine Durand","author_inst":"CHUM: Centre Hospitalier de L'Universite de Montreal"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Soluble Glycoprotein 120 is associated with Coronary Artery Inflammation Measured by Pericoronary Fat Attenuation Index in People Living with HIV","rel_doi":"10.64898\/2026.05.05.26352462","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352462","rel_abs":"Persistence of HIV antigens may drive chronic inflammation, leading to early-onset comorbidity among people living with HIV. We found that the presence of soluble glycoprotein 120 in plasma is associated with increased coronary inflammation, as measured by the pericoronary fat attenuation index (PFAI), a predictor of overt cardiovascular disease.","rel_num_authors":16,"rel_authors":[{"author_name":"Pengd-Wende Habib Bousse Traore","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Kevin Boczar","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Mehdi Benlarbi","author_inst":"Centre de recherche du CHUM, and Departement of microbiology, infectiology and immunology, University of Montreal, Canada"},{"author_name":"Victoria Devine-Ducharme","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Valerie Shirobokov","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Bethlehem Mengesha","author_inst":"University of Ottawa Heart Institute, Ottawa, Canada"},{"author_name":"Jonathan Richard","author_inst":"Centre de recherche du CHUM and Departement of microbiology, infectiology and immunology, University of Montreal, Canada"},{"author_name":"Nicolas Chomont","author_inst":"University de Montreal"},{"author_name":"Marc Messier-Peet","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Annie Chamberland","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Branka Vulesevic","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Mohamed El-Far","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Cecile Tremblay","author_inst":"Centre de recherche du CHUM, Montreal, Canada"},{"author_name":"Carl Chartrand-Lefebvre","author_inst":"Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de L'Universite de Montreal, Montreal, Canada"},{"author_name":"Andres Finzi","author_inst":"University of Montreal"},{"author_name":"Madeleine Durand","author_inst":"CHUM: Centre Hospitalier de L'Universite de Montreal"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Enhancing dengue diagnosis and surveillance by integrating machine learning technologies with the NS1 rapid test kit","rel_doi":"10.64898\/2026.05.05.26352445","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352445","rel_abs":"BackgroundDengue has been a major health threat globally in recent years. In particular, dengue incidences continue to increase annually and the epidemic area has expanded primarily due to global warming. Therefore, effective case detection and surveillance strategies are crucial to tackle this global health challenge. In clinical practice, the rapid test kit detecting dengue non-structural protein 1 antigen and commonly referred as NS1, is widely employed for early diagnosis. However, real-world studies revealed that the sensitivity of the NS1 test kit ranged from approximately 61% to 95%. Since early diagnosis is really critical for disease surveillance in the early stage of a dengue epidemic, scientists have been working hard to develop novel diagnosis methods that can provide higher sensitivity levels.\n\nMethodology\/Principal FindingsIn response to this challenge, in this study, we have developed a novel diagnosis procedure that integrates machine learning technologies with the NS1 test kit. Our experimental results revealed that we would be able to raise the sensitivity of the dengue diagnosis procedure to higher than 99% by incorporating machine learning based prediction models to screen the suspected patients with a negative NS1 result. Furthermore, the relative risks between the suspected patients who were predicted to be positive and those who were predicted to be negative exceeded 4.8.\n\nConclusions\/SignificanceThese results illustrate that the proposed approach provides an effective and efficient diagnosis procedure to address the global health challenge caused by spread of dengue.\n\nAuthor SummaryThis study has aimed to enhance surveillance of the dengue disease by integrating machine learning technologies with the rapid test kit commonly employed in early diagnosis. In clinical practice, the NS1 rapid test kit is widely employed for early diagnosis. However, real-world studies revealed that a certain percentage of the patients with a negative NS1 test result, ranging from 5% to 39%, were actually infected by dengue. Since early diagnosis is critical for disease control in the early stage of a dengue epidemic, scientists have been working hard to tackle this challenge. Based on this observation, this study was launched to investigate the effects of incorporating machine learning based prediction models to further screen those patients with a negative NS1 test result. The experimental results revealed that the proposed approach was able to identify over 99% of the patients who were infected by the dengue disease. Furthermore, the risk of the suspected patients who were predicted to be positive was 4.8 times higher than the risk of those who were predicted to be negative. The experimental results illustrate that the proposed approach provides an effective and efficient diagnosis procedure to enhance surveillance of the dengue disease.","rel_num_authors":5,"rel_authors":[{"author_name":"Chun-Kai Hwang","author_inst":"National Taiwan University"},{"author_name":"Ying-Wen Chen","author_inst":"National Cheng Kung University Hospital"},{"author_name":"YU-TSENG WANG","author_inst":"National Taiwan University"},{"author_name":"Tzong-Shiann Ho","author_inst":"National Cheng Kung University Hospital"},{"author_name":"Yen-Jen Oyang","author_inst":"National Taiwan University"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Enhancing dengue diagnosis and surveillance by integrating machine learning technologies with the NS1 rapid test kit","rel_doi":"10.64898\/2026.05.05.26352445","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352445","rel_abs":"BackgroundDengue has been a major health threat globally in recent years. In particular, dengue incidences continue to increase annually and the epidemic area has expanded primarily due to global warming. Therefore, effective case detection and surveillance strategies are crucial to tackle this global health challenge. In clinical practice, the rapid test kit detecting dengue non-structural protein 1 antigen and commonly referred as NS1, is widely employed for early diagnosis. However, real-world studies revealed that the sensitivity of the NS1 test kit ranged from approximately 61% to 95%. Since early diagnosis is really critical for disease surveillance in the early stage of a dengue epidemic, scientists have been working hard to develop novel diagnosis methods that can provide higher sensitivity levels.\n\nMethodology\/Principal FindingsIn response to this challenge, in this study, we have developed a novel diagnosis procedure that integrates machine learning technologies with the NS1 test kit. Our experimental results revealed that we would be able to raise the sensitivity of the dengue diagnosis procedure to higher than 99% by incorporating machine learning based prediction models to screen the suspected patients with a negative NS1 result. Furthermore, the relative risks between the suspected patients who were predicted to be positive and those who were predicted to be negative exceeded 4.8.\n\nConclusions\/SignificanceThese results illustrate that the proposed approach provides an effective and efficient diagnosis procedure to address the global health challenge caused by spread of dengue.\n\nAuthor SummaryThis study has aimed to enhance surveillance of the dengue disease by integrating machine learning technologies with the rapid test kit commonly employed in early diagnosis. In clinical practice, the NS1 rapid test kit is widely employed for early diagnosis. However, real-world studies revealed that a certain percentage of the patients with a negative NS1 test result, ranging from 5% to 39%, were actually infected by dengue. Since early diagnosis is critical for disease control in the early stage of a dengue epidemic, scientists have been working hard to tackle this challenge. Based on this observation, this study was launched to investigate the effects of incorporating machine learning based prediction models to further screen those patients with a negative NS1 test result. The experimental results revealed that the proposed approach was able to identify over 99% of the patients who were infected by the dengue disease. Furthermore, the risk of the suspected patients who were predicted to be positive was 4.8 times higher than the risk of those who were predicted to be negative. The experimental results illustrate that the proposed approach provides an effective and efficient diagnosis procedure to enhance surveillance of the dengue disease.","rel_num_authors":5,"rel_authors":[{"author_name":"Chun-Kai Hwang","author_inst":"National Taiwan University"},{"author_name":"Ying-Wen Chen","author_inst":"National Cheng Kung University Hospital"},{"author_name":"YU-TSENG WANG","author_inst":"National Taiwan University"},{"author_name":"Tzong-Shiann Ho","author_inst":"National Cheng Kung University Hospital"},{"author_name":"Yen-Jen Oyang","author_inst":"National Taiwan University"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population","rel_doi":"10.64898\/2026.05.05.26351986","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26351986","rel_abs":"Most genome-wide association studies (GWAS) of serious mental illness (SMI) have been conducted for categorical diagnoses in samples of primarily European ancestry. The portability of findings to non-Europeans, and to SMI-related symptoms\/dimensional traits remains uncertain. In a sample of 8,666 SMI cases and controls from the Paisa region of Colombia we show that a primarily European schizophrenia GWAS polygenic risk score (PRS) predicted all SMI diagnoses in this sample, as well as symptoms (assessed in cases only) and traits assessed agnostic to SMI diagnosis: a one SD unit (SDU) increase in this PRS was associated to decreased risk in cases of suicidal thoughts (OR=0.89, 95% confidence interval 0.84-0.94), depressed mood (OR=0.90, 95% confidence interval 0.85-0.95), and increased risk of delusions (OR=1.12, 95% confidence interval 1.06-1.18) and to decreased cognition (in cases and controls) across five distinct domains (average decrease in cognition of 0.065 SDU, p<7e-05). We show that a published European GWAS of cognition predicted levels of executive function (average decrease in cognition of 0.06 SDU per unit increase in PRS, p<2e-04), but not diagnosis or symptoms. Specific loci identified in the SMI GWAS also showed association to multiple diagnoses, symptoms, and cognitive traits in Paisa. The most noteworthy result was for a locus on chromosome 7p22.3, associated in multiple SMI GWAS, that showed association in Paisa to increased risk of bipolar disorder, and to reduced complex cognition and social cognition. Our findings demonstrate wide portability from European GWAS to an admixed American sample, with associations to multiple transdiagnostic phenotypes.","rel_num_authors":22,"rel_authors":[{"author_name":"Esteban A Lopera Maya","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Susan K Service","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Mauricio Castano Ramirez","author_inst":"Department of Mental Health and Human Behavior, University of Caldas, Manizales, Colombia"},{"author_name":"Juan Camilo Mejia","author_inst":"Research Group in Psychiatry GIPSI, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia"},{"author_name":"Johanna Valencia","author_inst":"Research Group in Psychiatry GIPSI, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Juan F De la Hoz","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"},{"author_name":"Jonathan Valdez","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Marfred Munoz Umanes","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Tyler M Moore","author_inst":"Department of Psychiatry, University of Pennsylvania School of Medicine; Philadelphia, USA"},{"author_name":"Sinead Chapman","author_inst":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"author_name":"Benjamin M Neale","author_inst":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"author_name":"Carrie E Bearden","author_inst":"Department of Psychology, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Javier I Escobar","author_inst":"Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, USA"},{"author_name":"Ruben C Gur","author_inst":"Department of Psychiatry, University of Pennsylvania School of Medicine; Philadelphia, USA"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, USA"},{"author_name":"Chiara Sabatti","author_inst":"Departments of Biomedical Data Science and Statistics, Stanford University, Stanford, USA"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Carlos Lopez Jaramillo","author_inst":"Department of Psychiatry, University of Antioquia, Medellin, Colombia"},{"author_name":"Nelson B. Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population","rel_doi":"10.64898\/2026.05.05.26351986","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26351986","rel_abs":"Most genome-wide association studies (GWAS) of serious mental illness (SMI) have been conducted for categorical diagnoses in samples of primarily European ancestry. The portability of findings to non-Europeans, and to SMI-related symptoms\/dimensional traits remains uncertain. In a sample of 8,666 SMI cases and controls from the Paisa region of Colombia we show that a primarily European schizophrenia GWAS polygenic risk score (PRS) predicted all SMI diagnoses in this sample, as well as symptoms (assessed in cases only) and traits assessed agnostic to SMI diagnosis: a one SD unit (SDU) increase in this PRS was associated to decreased risk in cases of suicidal thoughts (OR=0.89, 95% confidence interval 0.84-0.94), depressed mood (OR=0.90, 95% confidence interval 0.85-0.95), and increased risk of delusions (OR=1.12, 95% confidence interval 1.06-1.18) and to decreased cognition (in cases and controls) across five distinct domains (average decrease in cognition of 0.065 SDU, p<7e-05). We show that a published European GWAS of cognition predicted levels of executive function (average decrease in cognition of 0.06 SDU per unit increase in PRS, p<2e-04), but not diagnosis or symptoms. Specific loci identified in the SMI GWAS also showed association to multiple diagnoses, symptoms, and cognitive traits in Paisa. The most noteworthy result was for a locus on chromosome 7p22.3, associated in multiple SMI GWAS, that showed association in Paisa to increased risk of bipolar disorder, and to reduced complex cognition and social cognition. Our findings demonstrate wide portability from European GWAS to an admixed American sample, with associations to multiple transdiagnostic phenotypes.","rel_num_authors":22,"rel_authors":[{"author_name":"Esteban A Lopera Maya","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Susan K Service","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Mauricio Castano Ramirez","author_inst":"Department of Mental Health and Human Behavior, University of Caldas, Manizales, Colombia"},{"author_name":"Juan Camilo Mejia","author_inst":"Research Group in Psychiatry GIPSI, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia"},{"author_name":"Johanna Valencia","author_inst":"Research Group in Psychiatry GIPSI, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Juan F De la Hoz","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"},{"author_name":"Jonathan Valdez","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Marfred Munoz Umanes","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Tyler M Moore","author_inst":"Department of Psychiatry, University of Pennsylvania School of Medicine; Philadelphia, USA"},{"author_name":"Sinead Chapman","author_inst":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"author_name":"Benjamin M Neale","author_inst":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"author_name":"Carrie E Bearden","author_inst":"Department of Psychology, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Javier I Escobar","author_inst":"Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, USA"},{"author_name":"Ruben C Gur","author_inst":"Department of Psychiatry, University of Pennsylvania School of Medicine; Philadelphia, USA"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, USA"},{"author_name":"Chiara Sabatti","author_inst":"Departments of Biomedical Data Science and Statistics, Stanford University, Stanford, USA"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Carlos Lopez Jaramillo","author_inst":"Department of Psychiatry, University of Antioquia, Medellin, Colombia"},{"author_name":"Nelson B. Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population","rel_doi":"10.64898\/2026.05.05.26351986","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26351986","rel_abs":"Most genome-wide association studies (GWAS) of serious mental illness (SMI) have been conducted for categorical diagnoses in samples of primarily European ancestry. The portability of findings to non-Europeans, and to SMI-related symptoms\/dimensional traits remains uncertain. In a sample of 8,666 SMI cases and controls from the Paisa region of Colombia we show that a primarily European schizophrenia GWAS polygenic risk score (PRS) predicted all SMI diagnoses in this sample, as well as symptoms (assessed in cases only) and traits assessed agnostic to SMI diagnosis: a one SD unit (SDU) increase in this PRS was associated to decreased risk in cases of suicidal thoughts (OR=0.89, 95% confidence interval 0.84-0.94), depressed mood (OR=0.90, 95% confidence interval 0.85-0.95), and increased risk of delusions (OR=1.12, 95% confidence interval 1.06-1.18) and to decreased cognition (in cases and controls) across five distinct domains (average decrease in cognition of 0.065 SDU, p<7e-05). We show that a published European GWAS of cognition predicted levels of executive function (average decrease in cognition of 0.06 SDU per unit increase in PRS, p<2e-04), but not diagnosis or symptoms. Specific loci identified in the SMI GWAS also showed association to multiple diagnoses, symptoms, and cognitive traits in Paisa. The most noteworthy result was for a locus on chromosome 7p22.3, associated in multiple SMI GWAS, that showed association in Paisa to increased risk of bipolar disorder, and to reduced complex cognition and social cognition. Our findings demonstrate wide portability from European GWAS to an admixed American sample, with associations to multiple transdiagnostic phenotypes.","rel_num_authors":22,"rel_authors":[{"author_name":"Esteban A Lopera Maya","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Susan K Service","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Mauricio Castano Ramirez","author_inst":"Department of Mental Health and Human Behavior, University of Caldas, Manizales, Colombia"},{"author_name":"Juan Camilo Mejia","author_inst":"Research Group in Psychiatry GIPSI, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia"},{"author_name":"Johanna Valencia","author_inst":"Research Group in Psychiatry GIPSI, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Juan F De la Hoz","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"},{"author_name":"Jonathan Valdez","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Marfred Munoz Umanes","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Tyler M Moore","author_inst":"Department of Psychiatry, University of Pennsylvania School of Medicine; Philadelphia, USA"},{"author_name":"Sinead Chapman","author_inst":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"author_name":"Benjamin M Neale","author_inst":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"author_name":"Carrie E Bearden","author_inst":"Department of Psychology, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Javier I Escobar","author_inst":"Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, USA"},{"author_name":"Ruben C Gur","author_inst":"Department of Psychiatry, University of Pennsylvania School of Medicine; Philadelphia, USA"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, USA"},{"author_name":"Chiara Sabatti","author_inst":"Departments of Biomedical Data Science and Statistics, Stanford University, Stanford, USA"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"},{"author_name":"Carlos Lopez Jaramillo","author_inst":"Department of Psychiatry, University of Antioquia, Medellin, Colombia"},{"author_name":"Nelson B. Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, USA"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"MAP3K7 novel variants in syndromic 46,XY DSD","rel_doi":"10.64898\/2026.05.05.26352427","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352427","rel_abs":"Mutations in MAP3K7 are responsible for two distinct syndromes Cardiospondylocarpofacial (CSCF) and Frontometaphyseal dysplasia 2 (FMD2). Both are characterized by skeletal malformations, facial dysmorphisms, hearing loss, and mild intellectual disability. While cardiac defects are predominant in CSCF, keloid scar is a distinct feature in FMD2. Problem with gonadal development and disorders of sexual development (DSD) have not been previously chracterized.\n\nHere we report three syndromic cases of 46,XY DSD with CSCF or FMD2, each carrying a novel heterozygous missense variants in MAP3K7 (NM_145331.3:c.250G>A; p.V84M, NM_145331.3:c.195A>G; p.I65M, and NM_145331.3: c.574A>G; p.S192G). The DSD phenotypes include cryptorchidism, micropenis, small testis, and hypospadias. In silico tools predict all three variants are deleterious. All three MAP3K7 variants occur in the kinase domain at highly conservative positions among mammals. MAP3K7 is highly expressed in human fetal Sertoli cells. MAP3K7 knock-out in HEK293T cells led to downregulation of GATA4 and FOG2 expression by RNA-Seq. Like MAP3K1, MAP3K7 phosphorylated p38 while all three MAP3K7 variants did not alter phosphorylated p38 compared to wildtype in HEK293TMAP3K7-\/- cells. Two MAP3K7 missense mutants (p.V84M and p.I65M) ectopically activate ovarian beta catenin\/ Wnt signalling in TOPFLASH assays. Our data suggest that MAP3K7 contributes to male sex differentiation by increasing expression of pro-testis genes GATA4 and FOG2 in HEK293TMAP3K7-\/- cells and antagonizing pro-ovarian beta-catenin signalling, and that one or more of these activities were likely affected in 3 cases of 46,XY DSD with CSCF\/FMD2 during sex development.","rel_num_authors":8,"rel_authors":[{"author_name":"Thanh Nha Uyen Le","author_inst":"Hudson Institute of Medical Research"},{"author_name":"Shirin M Moradifard","author_inst":"Monash University"},{"author_name":"Alejandra P Reyes","author_inst":"Genetics Department, Children Hospital of Mexico Federico Gomez, Mexico City, Mexico"},{"author_name":"Thi Bich Ngoc Can","author_inst":"Vietnam National Children Hospital, Hanoi, Vietnam"},{"author_name":"Adriana Tavares Gomes","author_inst":"Department of Pediatrics and Rady Children Hospital San Diego, University of California, San Diego, La Jolla, California, USA"},{"author_name":"Marilyn C. Jones","author_inst":"Department of Pediatrics and Rady Children Hospital San Diego, University of California, San Diego, La Jolla, California, USA"},{"author_name":"Dung Vu Chi","author_inst":"Vietnam National Children Hospital, Hanoi, Vietnam"},{"author_name":"Vincent Harley","author_inst":"Hudson Institute of Medical Research"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"An APOE*4-Informed Genomic Atlas of the X Chromosome in Alzheimer's Disease","rel_doi":"10.64898\/2026.05.05.26352461","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352461","rel_abs":"The genetic contributions of the X chromosome to Alzheimers disease (AD) remain poorly understood yet are expected to importantly shape sex differences in AD. We therefore performed large-scale X-chromosome-wide association studies (N=1,240,451), evaluating differential risk due to sex, APOE*4, and escape from X-chromosome inactivation, finding most X-linked loci appear relevant to female-biased AD etiology. In evaluating genetic pleiotropy with hormonal, lipid, and brain imaging traits, we discovered X-linked AD loci converged on white matter traits, particularly in the anterior corona radiata and splenium of the corpus callosum. Through brain-centric functional genomics analyses, we then nominated candidate causal genes, including 5 that appeared highly robust. Notably, we found the escape gene RBBP7 decreases AD risk in APOE*4 carriers likely through higher expression in excitatory neurons to counter tau-related neurodegeneration. Altogether, we provide an atlas of sex and APOE*4-informed candidate X-linked AD risk loci, genes, and mechanisms that will guide future studies.","rel_num_authors":28,"rel_authors":[{"author_name":"Noah Cook","author_inst":"Washington University in St. Louis"},{"author_name":"Youjie Zeng","author_inst":"Washington University in St. Louis"},{"author_name":"Chenyu Yang","author_inst":"Washington University in St. Louis"},{"author_name":"Zhiwen Jiang","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Ting-Chen Wang","author_inst":"Vanderbilt University"},{"author_name":"Yann Le Guen","author_inst":"Stanford University"},{"author_name":"Karly Cody","author_inst":"Stanford University"},{"author_name":"Matthew Johnson","author_inst":"Washington University in St. Louis"},{"author_name":"Rui Zhang","author_inst":"VA Boston Healthcare System"},{"author_name":"Victoria C. Merritt","author_inst":"University of California San Diego"},{"author_name":"Richard L. Hauger","author_inst":"University of California San Diego"},{"author_name":"- The VA Million Veteran Program","author_inst":""},{"author_name":"- FinnGen","author_inst":""},{"author_name":"Mary Ellen Koran","author_inst":"Mayo Clinic"},{"author_name":"Elizabeth C. Mormino","author_inst":"Stanford University"},{"author_name":"Brian Gordon","author_inst":"Washington University in St. Louis"},{"author_name":"Alex DeCasien","author_inst":"National Institute on Aging"},{"author_name":"Shea J. Andrews","author_inst":"University of California San Francisco"},{"author_name":"Logan Dumitrescu","author_inst":"Vanderbilt University"},{"author_name":"Derek B Archer","author_inst":"Vanderbilt University"},{"author_name":"Timothy J. Hohman","author_inst":"Vanderbilt University"},{"author_name":"Cyril Pottier","author_inst":"Washington University in St. Louis"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"Richard Sherva","author_inst":"Boston University School of Medicine"},{"author_name":"Mark Logue","author_inst":"Boston University School of Medicine"},{"author_name":"Valerio Napolioni","author_inst":"University of Camerino"},{"author_name":"Michael D. Greicius","author_inst":"Stanford University"},{"author_name":"Michael E. Belloy","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"An APOE*4-Informed Genomic Atlas of the X Chromosome in Alzheimer's Disease","rel_doi":"10.64898\/2026.05.05.26352461","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352461","rel_abs":"The genetic contributions of the X chromosome to Alzheimers disease (AD) remain poorly understood yet are expected to importantly shape sex differences in AD. We therefore performed large-scale X-chromosome-wide association studies (N=1,240,451), evaluating differential risk due to sex, APOE*4, and escape from X-chromosome inactivation, finding most X-linked loci appear relevant to female-biased AD etiology. In evaluating genetic pleiotropy with hormonal, lipid, and brain imaging traits, we discovered X-linked AD loci converged on white matter traits, particularly in the anterior corona radiata and splenium of the corpus callosum. Through brain-centric functional genomics analyses, we then nominated candidate causal genes, including 5 that appeared highly robust. Notably, we found the escape gene RBBP7 decreases AD risk in APOE*4 carriers likely through higher expression in excitatory neurons to counter tau-related neurodegeneration. Altogether, we provide an atlas of sex and APOE*4-informed candidate X-linked AD risk loci, genes, and mechanisms that will guide future studies.","rel_num_authors":28,"rel_authors":[{"author_name":"Noah Cook","author_inst":"Washington University in St. Louis"},{"author_name":"Youjie Zeng","author_inst":"Washington University in St. Louis"},{"author_name":"Chenyu Yang","author_inst":"Washington University in St. Louis"},{"author_name":"Zhiwen Jiang","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Ting-Chen Wang","author_inst":"Vanderbilt University"},{"author_name":"Yann Le Guen","author_inst":"Stanford University"},{"author_name":"Karly Cody","author_inst":"Stanford University"},{"author_name":"Matthew Johnson","author_inst":"Washington University in St. Louis"},{"author_name":"Rui Zhang","author_inst":"VA Boston Healthcare System"},{"author_name":"Victoria C. Merritt","author_inst":"University of California San Diego"},{"author_name":"Richard L. Hauger","author_inst":"University of California San Diego"},{"author_name":"- The VA Million Veteran Program","author_inst":""},{"author_name":"- FinnGen","author_inst":""},{"author_name":"Mary Ellen Koran","author_inst":"Mayo Clinic"},{"author_name":"Elizabeth C. Mormino","author_inst":"Stanford University"},{"author_name":"Brian Gordon","author_inst":"Washington University in St. Louis"},{"author_name":"Alex DeCasien","author_inst":"National Institute on Aging"},{"author_name":"Shea J. Andrews","author_inst":"University of California San Francisco"},{"author_name":"Logan Dumitrescu","author_inst":"Vanderbilt University"},{"author_name":"Derek B Archer","author_inst":"Vanderbilt University"},{"author_name":"Timothy J. Hohman","author_inst":"Vanderbilt University"},{"author_name":"Cyril Pottier","author_inst":"Washington University in St. Louis"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"Richard Sherva","author_inst":"Boston University School of Medicine"},{"author_name":"Mark Logue","author_inst":"Boston University School of Medicine"},{"author_name":"Valerio Napolioni","author_inst":"University of Camerino"},{"author_name":"Michael D. Greicius","author_inst":"Stanford University"},{"author_name":"Michael E. Belloy","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"An APOE*4-Informed Genomic Atlas of the X Chromosome in Alzheimer's Disease","rel_doi":"10.64898\/2026.05.05.26352461","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352461","rel_abs":"The genetic contributions of the X chromosome to Alzheimers disease (AD) remain poorly understood yet are expected to importantly shape sex differences in AD. We therefore performed large-scale X-chromosome-wide association studies (N=1,240,451), evaluating differential risk due to sex, APOE*4, and escape from X-chromosome inactivation, finding most X-linked loci appear relevant to female-biased AD etiology. In evaluating genetic pleiotropy with hormonal, lipid, and brain imaging traits, we discovered X-linked AD loci converged on white matter traits, particularly in the anterior corona radiata and splenium of the corpus callosum. Through brain-centric functional genomics analyses, we then nominated candidate causal genes, including 5 that appeared highly robust. Notably, we found the escape gene RBBP7 decreases AD risk in APOE*4 carriers likely through higher expression in excitatory neurons to counter tau-related neurodegeneration. Altogether, we provide an atlas of sex and APOE*4-informed candidate X-linked AD risk loci, genes, and mechanisms that will guide future studies.","rel_num_authors":28,"rel_authors":[{"author_name":"Noah Cook","author_inst":"Washington University in St. Louis"},{"author_name":"Youjie Zeng","author_inst":"Washington University in St. Louis"},{"author_name":"Chenyu Yang","author_inst":"Washington University in St. Louis"},{"author_name":"Zhiwen Jiang","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Ting-Chen Wang","author_inst":"Vanderbilt University"},{"author_name":"Yann Le Guen","author_inst":"Stanford University"},{"author_name":"Karly Cody","author_inst":"Stanford University"},{"author_name":"Matthew Johnson","author_inst":"Washington University in St. Louis"},{"author_name":"Rui Zhang","author_inst":"VA Boston Healthcare System"},{"author_name":"Victoria C. Merritt","author_inst":"University of California San Diego"},{"author_name":"Richard L. Hauger","author_inst":"University of California San Diego"},{"author_name":"- The VA Million Veteran Program","author_inst":""},{"author_name":"- FinnGen","author_inst":""},{"author_name":"Mary Ellen Koran","author_inst":"Mayo Clinic"},{"author_name":"Elizabeth C. Mormino","author_inst":"Stanford University"},{"author_name":"Brian Gordon","author_inst":"Washington University in St. Louis"},{"author_name":"Alex DeCasien","author_inst":"National Institute on Aging"},{"author_name":"Shea J. Andrews","author_inst":"University of California San Francisco"},{"author_name":"Logan Dumitrescu","author_inst":"Vanderbilt University"},{"author_name":"Derek B Archer","author_inst":"Vanderbilt University"},{"author_name":"Timothy J. Hohman","author_inst":"Vanderbilt University"},{"author_name":"Cyril Pottier","author_inst":"Washington University in St. Louis"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"Richard Sherva","author_inst":"Boston University School of Medicine"},{"author_name":"Mark Logue","author_inst":"Boston University School of Medicine"},{"author_name":"Valerio Napolioni","author_inst":"University of Camerino"},{"author_name":"Michael D. Greicius","author_inst":"Stanford University"},{"author_name":"Michael E. Belloy","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"An APOE*4-Informed Genomic Atlas of the X Chromosome in Alzheimer's Disease","rel_doi":"10.64898\/2026.05.05.26352461","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352461","rel_abs":"The genetic contributions of the X chromosome to Alzheimers disease (AD) remain poorly understood yet are expected to importantly shape sex differences in AD. We therefore performed large-scale X-chromosome-wide association studies (N=1,240,451), evaluating differential risk due to sex, APOE*4, and escape from X-chromosome inactivation, finding most X-linked loci appear relevant to female-biased AD etiology. In evaluating genetic pleiotropy with hormonal, lipid, and brain imaging traits, we discovered X-linked AD loci converged on white matter traits, particularly in the anterior corona radiata and splenium of the corpus callosum. Through brain-centric functional genomics analyses, we then nominated candidate causal genes, including 5 that appeared highly robust. Notably, we found the escape gene RBBP7 decreases AD risk in APOE*4 carriers likely through higher expression in excitatory neurons to counter tau-related neurodegeneration. Altogether, we provide an atlas of sex and APOE*4-informed candidate X-linked AD risk loci, genes, and mechanisms that will guide future studies.","rel_num_authors":28,"rel_authors":[{"author_name":"Noah Cook","author_inst":"Washington University in St. Louis"},{"author_name":"Youjie Zeng","author_inst":"Washington University in St. Louis"},{"author_name":"Chenyu Yang","author_inst":"Washington University in St. Louis"},{"author_name":"Zhiwen Jiang","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Ting-Chen Wang","author_inst":"Vanderbilt University"},{"author_name":"Yann Le Guen","author_inst":"Stanford University"},{"author_name":"Karly Cody","author_inst":"Stanford University"},{"author_name":"Matthew Johnson","author_inst":"Washington University in St. Louis"},{"author_name":"Rui Zhang","author_inst":"VA Boston Healthcare System"},{"author_name":"Victoria C. Merritt","author_inst":"University of California San Diego"},{"author_name":"Richard L. Hauger","author_inst":"University of California San Diego"},{"author_name":"- The VA Million Veteran Program","author_inst":""},{"author_name":"- FinnGen","author_inst":""},{"author_name":"Mary Ellen Koran","author_inst":"Mayo Clinic"},{"author_name":"Elizabeth C. Mormino","author_inst":"Stanford University"},{"author_name":"Brian Gordon","author_inst":"Washington University in St. Louis"},{"author_name":"Alex DeCasien","author_inst":"National Institute on Aging"},{"author_name":"Shea J. Andrews","author_inst":"University of California San Francisco"},{"author_name":"Logan Dumitrescu","author_inst":"Vanderbilt University"},{"author_name":"Derek B Archer","author_inst":"Vanderbilt University"},{"author_name":"Timothy J. Hohman","author_inst":"Vanderbilt University"},{"author_name":"Cyril Pottier","author_inst":"Washington University in St. Louis"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"Richard Sherva","author_inst":"Boston University School of Medicine"},{"author_name":"Mark Logue","author_inst":"Boston University School of Medicine"},{"author_name":"Valerio Napolioni","author_inst":"University of Camerino"},{"author_name":"Michael D. Greicius","author_inst":"Stanford University"},{"author_name":"Michael E. Belloy","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Impact of a Social Media Campaign on HIV-Related Stigma among Young Adults Living with HIV in Lima, Peru: A Sequential Explanatory Mixed Methods Study","rel_doi":"10.64898\/2026.05.04.26352384","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.04.26352384","rel_abs":"BackgroundStigma remains a pervasive barrier to curbing the spread of human immunodeficiency virus (HIV) among adolescents and young adults in Lima, Peru. Social media offers a promising avenue for scalable, youth-centered stigma reduction, but few interventions have been rigorously evaluated in this context.\n\nObjectiveWe evaluated the potential of a social media campaign to reduce perceived HIV-related stigma among young adults living with HIV. This involved a sequential explanatory mixed-methods study, including a randomized evaluation, followed by focus groups to understand the findings.\n\nMethods150 young adults (aged 18-29 years) living with HIV (YLWH) were randomized to receive information on social media from one of the following: (1) the control account; (2) the control account and the social media campaign accounts (Instagram and TikTok); or (3) the control account, the campaign accounts, and the accounts of participating influencers. Perceived stigma was measured via pre- and post-campaign surveys using Spanish versions of the abridged Berger HIV Stigma Scale and the Stigma Stress Scale. Focus groups and interviews were conducted with a purposive sample of participants to contextualize quantitative results. Qualitative data were analyzed using Framework Analysis.\n\nResultsMean changes in HIV Stigma and Stigma Stress scores were small and not statistically significant. Post-hoc as-treated analyses supported these findings. Fidelity to intervention allocation was low to moderate, depending on the metric considered. Qualitative data suggested that the campaign positively impacted participants perceived stigma and that personal circumstances, crossover, frequency of exposure to content, and issues related to completing study questionnaires contributed to the lack of meaningful change in stigma scores.\n\nConclusionsWhile quantitative data did not support that exposure to a social media campaign led to meaningful reductions in HIV-related stigma, qualitative data suggested that the campaign had a positive impact and that limitations in the study design, together with external factors, may have obscured benefits in quantitative analyses.","rel_num_authors":12,"rel_authors":[{"author_name":"Samara Ruberg","author_inst":"Boston University School of Public Health"},{"author_name":"Alyson Nunez","author_inst":"Harvard Medical School"},{"author_name":"Milagros Wong","author_inst":"Socios En Salud Peru"},{"author_name":"Marguerite Curtis","author_inst":"Harvard Medical School"},{"author_name":"Yihan Shi","author_inst":"Harvard Medical School"},{"author_name":"Hugo Sanchez","author_inst":"Epicentro Peru"},{"author_name":"Eduardo Matos","author_inst":"Hospital Nacional Arzobispo Loayza"},{"author_name":"Frine Samalvides","author_inst":"Universidad Peruana Cayetano Heredia"},{"author_name":"Kristin Kosyluk","author_inst":"University of South Florida"},{"author_name":"Jerome T Galea","author_inst":"University of South Florida"},{"author_name":"Renato Errea","author_inst":"Socios En Salud Peru"},{"author_name":"Molly  F Franke","author_inst":"Harvard Medical School"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Choice of estimands and estimators affected the interpretation of results for some outcomes in a cluster-randomised trial (RESTORE) due to informative cluster size","rel_doi":"10.64898\/2026.05.05.26352371","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.05.26352371","rel_abs":"Background and objectiveIn cluster-randomised trials (CRTs), different estimands can be targeted, such as the individual-or cluster-average effect. These two estimands can differ in magnitude when outcomes or treatment effects vary with cluster size (termed informative cluster size). When informative cluster size is present, commonly used estimators for CRTs, such as mixed-effects model and generalised estimating equations with an exchangeable correlation structure (termed GEEs(exch)), can be biased for both these estimands. With little documented evaluation of When informative cluster size, it is currently unknown how commonly it occurs in practice. The aim of this work was to explore whether informative cluster size is present in a published CRT and to investigate its impact on trial results.\n\nMethodsWe re-analysed the RESTORE CRT, which compared protocolised sedation with usual care for critically ill children. For each outcome, we first modelled the association between cluster size and outcome\/treatment effect; next, we assessed the impact of informative cluster size by comparing differences between (i) individual-vs. cluster-average estimates and (ii) estimates from mixed-effects models and GEEs(exch) (which can be affected by informative cluster size) to those from IEEs (which are robust to informative cluster size).\n\nResultsWe found evidence of an association between cluster size and either outcomes or treatment effects for 16\/33 outcomes (48%). This led to statistically significant differences between the individual- and cluster-average treatment effects for 5 of 33 outcomes (15%). There were >10% differences between (i) individual- and cluster-average treatment effect estimates for 17 outcomes (52%) and (ii) estimates from mixed-effects models\/GEEs(exch) and estimates from unweighted IEEs for 13 outcomes (39%). For some outcomes, differences in the choice of estimator or estimand led to differences in the interpretation of results. For example, for the outcome postextubation stridor, the individual-average estimate showed a significant harmful effect (OR=1.65, 95% CI 1.02 to 2.67), unlike the cluster-average (OR=1.38, 95% CI 0.87 to 2.19) or GEEs(exch) estimate (OR=1.57, 95% CI 0.98, 2.50).\n\nDiscussioninformative cluster size can occur in CRTs, and the use of estimators that are not clearly aligned to the target estimand can affect the interpretation of some results.\n\nWhat is new?O_ST_ABSKey findingsC_ST_ABSO_LIThis re-analysis of the RESTORE cluster randomised trial found that choice of estimand and estimator could affect the interpretation of results for some outcomes\nC_LI\n\nWhat this adds to what is knownO_LIThis work provides empirical evidence that informative cluster size can occur in cluster randomised trials, and can affect results based on the choice of estimand or estimator\nC_LI\n\nWhat is the implication and what should we change nowO_LITrialists should clearly define their target estimand and choose an estimator that is aligned to that estimand\nC_LIO_LICareful consideration of the plausibility of assumptions underpinning each estimator, including the likelihood of informative cluster size, can help ensure appropriate analysis methods are used\nC_LIO_LIWhen mixed-effects models or GEEs with an exchangeable correlation structure are used, sensitivity analyses using independence estimating equations or other appropriate methods should be used to evaluate the robustness of results to informative cluster size\nC_LI","rel_num_authors":5,"rel_authors":[{"author_name":"Dongquan Bi","author_inst":"UCL Innovative Clinical Trials Unit, London, UK"},{"author_name":"Andrew Copas","author_inst":"Medical Research Council Centre of Research Excellence in Clinical Trial Innovation (CCTI), London UK"},{"author_name":"Fan Li","author_inst":"Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA"},{"author_name":"Michael O Harhay","author_inst":"Department of Biostatistics, Epidemiology and Informatics and Palliative and Advanced Illness Research Center, Department of Medicine, University of Pennsylvani"},{"author_name":"Brennan C Kahan","author_inst":"Medical Research Council Centre of Research Excellence in Clinical Trial Innovation (CCTI), London UK"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Heterogeneous Treatment Effect for Targeted Temperature Management After Cardiac Arrest: A Causal Machine Learning Analysis","rel_doi":"10.64898\/2026.05.04.26352388","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.04.26352388","rel_abs":"ObjectivesTo determine whether heterogeneous treatment effects (HTE) explain the inconclusive results of targeted temperature management (TTM) trials after cardiac arrest, using causal machine learning across four datasets.\n\nDesignSecondary analysis of one multicenter RCT and three observational ICU cohorts using S-learner and forest-based R-learner models to estimate conditional average treatment effects (CATE).\n\nSettingTwenty-six French ICUs (HYPERION), approximately 200 U.S. ICUs (eICU-CRD), Johns Hopkins Hospital (PMAP), and Beth Israel Deaconess Medical Center (MIMIC-IV).\n\nPatientsAdults ([&ge;]18 years) with cardiac arrest; 4,507 patients across the four datasets, of whom 1,814 (40.2%) received TTM.\n\nInterventionsTTM as administered clinically or per HYPERION protocol. Ascertainment: randomization (HYPERION), treatment documentation (eICU-CRD), sustained hypothermia <36{degrees}C for >12 hours (PMAP), or documented cooling device use [&ge;]12 hours (MIMIC-IV).\n\nMeasurements and Main ResultsThe primary outcome was hospital mortality; the secondary outcome was favorable neurologic function (Cerebral Performance Category 1-2 at 90 days for HYPERION; last motor Glasgow Coma Scale = 6 for observational cohorts). Three S-learner models (XGBoost, neural network, Bayesian Additive Regression Trees) and one forest-based R-learner (CausalForestDML) estimated CATE. HTE was assessed by likelihood-ratio tests for CATExtreatment interaction, CausalForestDML 95% confidence intervals, Group Average Treatment Effects (GATES) across CATE quintiles, and SHAP feature importance. S-learner discrimination was adequate (AUROC 0.72-0.82). No model showed a significant CATExTTM interaction in any dataset (all p > 0.05). Individual CATE confidence intervals uniformly crossed zero, and GATES showed no monotonic gradient of benefit across quintiles in any dataset.\n\nConclusionsAcross four diverse datasets and multiple causal machine-learning approaches, we found no evidence of heterogeneous treatment effects for TTM after cardiac arrest. The inconclusive findings of TTM trials are unlikely explained by differential effects in identifiable subgroups defined by routinely available clinical features.\n\nKEY POINTSQuestion: Do identifiable patient subgroups derive differential benefit from targeted temperature management (TTM) after cardiac arrest?\n\nFindings: In a causal machine-learning analysis of 4,507 patients across one randomized trial and three observational ICU cohorts, no model detected significant heterogeneous TTM effects on mortality or neurologic outcome.\n\nMeaning: Conflicting TTM trial results are unlikely explained by differential effects in identifiable subgroups, weakening the rationale for personalized TTM strategies based on routinely available clinical features.","rel_num_authors":6,"rel_authors":[{"author_name":"Michel Brandao Raskin","author_inst":"Johns Hopkins University"},{"author_name":"Isalis Karhu-Leperd","author_inst":"Federal Institute of Technology Lausanne (EPFL)"},{"author_name":"Carl W Harris","author_inst":"Johns Hopkins University"},{"author_name":"Romain Pirrachio","author_inst":"University of California San Francisco"},{"author_name":"Jean Baptiste Lascarrou","author_inst":"CHU Nantes"},{"author_name":"Robert D Stevens","author_inst":"Johns Hopkins University"}],"rel_date":"2026-05-06","rel_site":"medrxiv"},{"rel_title":"Heterogeneous Treatment Effect for Targeted Temperature Management After Cardiac Arrest: A Causal Machine Learning Analysis","rel_doi":"10.64898\/2026.05.04.26352388","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.04.26352388","rel_abs":"ObjectivesTo determine whether heterogeneous treatment effects (HTE) explain the inconclusive results of targeted temperature management (TTM) trials after cardiac arrest, using causal machine learning across four datasets.\n\nDesignSecondary analysis of one multicenter RCT and three observational ICU cohorts using S-learner and forest-based R-learner models to estimate conditional average treatment effects (CATE).\n\nSettingTwenty-six French ICUs (HYPERION), approximately 200 U.S. ICUs (eICU-CRD), Johns Hopkins Hospital (PMAP), and Beth Israel Deaconess Medical Center (MIMIC-IV).\n\nPatientsAdults ([&ge;]18 years) with cardiac arrest; 4,507 patients across the four datasets, of whom 1,814 (40.2%) received TTM.\n\nInterventionsTTM as administered clinically or per HYPERION protocol. Ascertainment: randomization (HYPERION), treatment documentation (eICU-CRD), sustained hypothermia <36{degrees}C for >12 hours (PMAP), or documented cooling device use [&ge;]12 hours (MIMIC-IV).\n\nMeasurements and Main ResultsThe primary outcome was hospital mortality; the secondary outcome was favorable neurologic function (Cerebral Performance Category 1-2 at 90 days for HYPERION; last motor Glasgow Coma Scale = 6 for observational cohorts). Three S-learner models (XGBoost, neural network, Bayesian Additive Regression Trees) and one forest-based R-learner (CausalForestDML) estimated CATE. HTE was assessed by likelihood-ratio tests for CATExtreatment interaction, CausalForestDML 95% confidence intervals, Group Average Treatment Effects (GATES) across CATE quintiles, and SHAP feature importance. S-learner discrimination was adequate (AUROC 0.72-0.82). No model showed a significant CATExTTM interaction in any dataset (all p > 0.05). Individual CATE confidence intervals uniformly crossed zero, and GATES showed no monotonic gradient of benefit across quintiles in any dataset.\n\nConclusionsAcross four diverse datasets and multiple causal machine-learning approaches, we found no evidence of heterogeneous treatment effects for TTM after cardiac arrest. The inconclusive findings of TTM trials are unlikely explained by differential effects in identifiable subgroups defined by routinely available clinical features.\n\nKEY POINTSQuestion: Do identifiable patient subgroups derive differential benefit from targeted temperature management (TTM) after cardiac arrest?\n\nFindings: In a causal machine-learning analysis of 4,507 patients across one randomized trial and three observational ICU cohorts, no model detected significant heterogeneous TTM effects on mortality or neurologic outcome.\n\nMeaning: Conflicting TTM trial results are unlikely explained by differential effects in identifiable subgroups, weakening the rationale for personalized TTM strategies based on routinely available clinical features.","rel_num_authors":6,"rel_authors":[{"author_name":"Michel Brandao Raskin","author_inst":"Johns Hopkins University"},{"author_name":"Isalis Karhu-Leperd","author_inst":"Federal Institute of Technology Lausanne (EPFL)"},{"author_name":"Carl W Harris","author_inst":"Johns Hopkins University"},{"author_name":"Romain Pirrachio","author_inst":"University of California San Francisco"},{"author_name":"Jean Baptiste Lascarrou","author_inst":"CHU Nantes"},{"author_name":"Robert D Stevens","author_inst":"Johns Hopkins University"}],"rel_date":"2026-05-06","rel_site":"medrxiv"}]}