{"gname":"University of Ottawa","grp_id":"35","rels":[{"rel_title":"Increased whole body fluid volume status quantified by photon-counting detector CT in patients undergoing TAVR","rel_doi":"10.64898\/2026.05.13.26352144","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.13.26352144","rel_abs":"Background: Before transcatheter aortic valve replacement (TAVR), patients with severe aortic valve stenosis are at an increased risk of developing fluid volume overload and heart failure, which is associated with subsequent adverse outcomes after TAVR. Purpose: To quantify fluid volume status as whole-body fast-exchange extracellular volume (FE-ECV) in patients undergoing TAVR compared to healthy reference values using photon-counting CT (PCCT). Methods: Consecutive patients referred for TAVR and healthy living kidney donor candidates, respectively, underwent PCCT including the pelvis. FE-ECV (mL) was quantified using venous hematocrit, injected iodinated contrast concentration and volume, and blood iodine concentration and urinary bladder excreted iodine mass quantified in iodine map regions of interest from the inferior vena cava and covering the urinary bladder, acquired at one time point 6-10 minutes after intravenous iodinated contrast administration. Results: The study included 156 subjects (healthy: n=51, age 47{+\/-}9 years, 55% female; TAVR: n=105, age 78{+\/-}6 years, 39% female). In healthy subjects, FE-ECV was 160{+\/-}22 mL\/kg lean body mass (LBM), 95% limits 116-204 mL\/kg LBM, and was independent of age, sex, contrast agent type, and scan delay time after contrast injection (p>0.66 for all). Compared to healthy subjects, FE-ECV in patients referred for TAVR was higher (174{+\/-}34 mL\/kg LBM, p=0.01), with 19 patients (18%) exceeding the normal range. Conclusion: One in five patients referred for TAVR demonstrated increased FE-ECV, revealing a substantial prevalence of fluid overload detectable by single-time point late-phase PCCT iodine mapping.","rel_num_authors":13,"rel_authors":[{"author_name":"Nora M Kerkovits","author_inst":"Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary"},{"author_name":"Miklos Vertes","author_inst":"Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary"},{"author_name":"Samuel Beke","author_inst":"Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary"},{"author_name":"Scott Quadrelli","author_inst":"Kolling Institute, Royal North Shore Hospital, and University of Sydney, Sydney, Australia"},{"author_name":"Peter Csakai-Szoke","author_inst":"Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary"},{"author_name":"A Michael Peters","author_inst":"Department of Nuclear Medicine, King's College Hospital NHS Foundation Trust, London, United Kingdom"},{"author_name":"Lili Szaraz","author_inst":"Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary"},{"author_name":"Akos Varga-Szemes","author_inst":"Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA"},{"author_name":"Tilman Emrich","author_inst":"Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA"},{"author_name":"Balint Szilveszter","author_inst":"Heart and Vascular Center, Semmelweis University, Budapest, Hungary"},{"author_name":"Bela Merkely","author_inst":"Heart and Vascular Center, Semmelweis University, Budapest, Hungary"},{"author_name":"Pal Maurovich-Horvat","author_inst":"Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary"},{"author_name":"Martin Ugander","author_inst":"Kolling Institute, Royal North Shore Hospital, and University of Sydney, Sydney, Australia"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Higher distal proximal skin temperature is associated with reduced bedtime vigilance in young people with major depressive disorder","rel_doi":"10.64898\/2026.05.17.26353435","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353435","rel_abs":"Young people with major depressive disorder (MDD) exhibit altered thermoregulation, which has also been linked to vigilance and sustained attention. However, whether peripheral skin temperature is associated with cognitive vulnerability around sleep onset is unknown. We examined the relationship between the distal-proximal skin temperature gradient (DPG) and vigilance in 38 young people with MDD (20.1{+\/-}3.7 years, 65.9% female) using an in-laboratory protocol spanning 4h before, to 2h after, habitual sleep time. Participants were classified into DPGwarm and DPGcold subgroups based on being above or below median DPG before sleep onset. Linear mixed models adjusted for age and sex examined psychomotor vigilance task performance across timepoints. The DPGwarm subgroup (n=19) showed significantly worse performance than DPGcold (n=19) across the evening for mean reaction time (RT), reciprocal reaction time, number of lapses, and fastest 10% of RT (all p[&le;]0.003). Significant GroupxTime interactions were observed for mean RT (F(3,90.4)=5.00, p=0.003) and lapses (F(3,93.6)=6.73, p<0.001), with DPGwarm participants showing progressively worse performance approaching sleep onset. At 2h post-habitual sleep onset, DPGwarm participants exhibited slower RT ({Delta}=129ms, p<0.001) and nearly four times more lapses (14.9 vs 4.1, p<0.001). Performance decrements were not accompanied by differences in melatonin timing, subjective sleepiness or mood, suggesting DPG may index cognitive vulnerability independently. Of note, younger age was associated with greater vigilance decrements. These findings demonstrate that elevated peripheral skin temperature before sleep onset is associated with reduced vigilance in young people with MDD, and may therefore have potential utility as a non-invasive thermoregulatory biomarker of cognitive vulnerability.","rel_num_authors":10,"rel_authors":[{"author_name":"Christopher J Gordon","author_inst":"Macquarie University"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Yue Leon Guo","author_inst":"National Taiwan University College of Medicine"},{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Rebecca Robillard","author_inst":"University of Ottawa"},{"author_name":"Jacob Crouse","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Sharon L Naismith","author_inst":"The University of Sydney"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Daniel F Hermens","author_inst":"Thompson Institute, University of Sunshine Coast"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, The University of Sydney"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Higher distal proximal skin temperature is associated with reduced bedtime vigilance in young people with major depressive disorder","rel_doi":"10.64898\/2026.05.17.26353435","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353435","rel_abs":"Young people with major depressive disorder (MDD) exhibit altered thermoregulation, which has also been linked to vigilance and sustained attention. However, whether peripheral skin temperature is associated with cognitive vulnerability around sleep onset is unknown. We examined the relationship between the distal-proximal skin temperature gradient (DPG) and vigilance in 38 young people with MDD (20.1{+\/-}3.7 years, 65.9% female) using an in-laboratory protocol spanning 4h before, to 2h after, habitual sleep time. Participants were classified into DPGwarm and DPGcold subgroups based on being above or below median DPG before sleep onset. Linear mixed models adjusted for age and sex examined psychomotor vigilance task performance across timepoints. The DPGwarm subgroup (n=19) showed significantly worse performance than DPGcold (n=19) across the evening for mean reaction time (RT), reciprocal reaction time, number of lapses, and fastest 10% of RT (all p[&le;]0.003). Significant GroupxTime interactions were observed for mean RT (F(3,90.4)=5.00, p=0.003) and lapses (F(3,93.6)=6.73, p<0.001), with DPGwarm participants showing progressively worse performance approaching sleep onset. At 2h post-habitual sleep onset, DPGwarm participants exhibited slower RT ({Delta}=129ms, p<0.001) and nearly four times more lapses (14.9 vs 4.1, p<0.001). Performance decrements were not accompanied by differences in melatonin timing, subjective sleepiness or mood, suggesting DPG may index cognitive vulnerability independently. Of note, younger age was associated with greater vigilance decrements. These findings demonstrate that elevated peripheral skin temperature before sleep onset is associated with reduced vigilance in young people with MDD, and may therefore have potential utility as a non-invasive thermoregulatory biomarker of cognitive vulnerability.","rel_num_authors":10,"rel_authors":[{"author_name":"Christopher J Gordon","author_inst":"Macquarie University"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Yue Leon Guo","author_inst":"National Taiwan University College of Medicine"},{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Rebecca Robillard","author_inst":"University of Ottawa"},{"author_name":"Jacob Crouse","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Sharon L Naismith","author_inst":"The University of Sydney"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Daniel F Hermens","author_inst":"Thompson Institute, University of Sunshine Coast"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, The University of Sydney"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Higher distal proximal skin temperature is associated with reduced bedtime vigilance in young people with major depressive disorder","rel_doi":"10.64898\/2026.05.17.26353435","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353435","rel_abs":"Young people with major depressive disorder (MDD) exhibit altered thermoregulation, which has also been linked to vigilance and sustained attention. However, whether peripheral skin temperature is associated with cognitive vulnerability around sleep onset is unknown. We examined the relationship between the distal-proximal skin temperature gradient (DPG) and vigilance in 38 young people with MDD (20.1{+\/-}3.7 years, 65.9% female) using an in-laboratory protocol spanning 4h before, to 2h after, habitual sleep time. Participants were classified into DPGwarm and DPGcold subgroups based on being above or below median DPG before sleep onset. Linear mixed models adjusted for age and sex examined psychomotor vigilance task performance across timepoints. The DPGwarm subgroup (n=19) showed significantly worse performance than DPGcold (n=19) across the evening for mean reaction time (RT), reciprocal reaction time, number of lapses, and fastest 10% of RT (all p[&le;]0.003). Significant GroupxTime interactions were observed for mean RT (F(3,90.4)=5.00, p=0.003) and lapses (F(3,93.6)=6.73, p<0.001), with DPGwarm participants showing progressively worse performance approaching sleep onset. At 2h post-habitual sleep onset, DPGwarm participants exhibited slower RT ({Delta}=129ms, p<0.001) and nearly four times more lapses (14.9 vs 4.1, p<0.001). Performance decrements were not accompanied by differences in melatonin timing, subjective sleepiness or mood, suggesting DPG may index cognitive vulnerability independently. Of note, younger age was associated with greater vigilance decrements. These findings demonstrate that elevated peripheral skin temperature before sleep onset is associated with reduced vigilance in young people with MDD, and may therefore have potential utility as a non-invasive thermoregulatory biomarker of cognitive vulnerability.","rel_num_authors":10,"rel_authors":[{"author_name":"Christopher J Gordon","author_inst":"Macquarie University"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Yue Leon Guo","author_inst":"National Taiwan University College of Medicine"},{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Rebecca Robillard","author_inst":"University of Ottawa"},{"author_name":"Jacob Crouse","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Sharon L Naismith","author_inst":"The University of Sydney"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Daniel F Hermens","author_inst":"Thompson Institute, University of Sunshine Coast"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, The University of Sydney"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Higher distal proximal skin temperature is associated with reduced bedtime vigilance in young people with major depressive disorder","rel_doi":"10.64898\/2026.05.17.26353435","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353435","rel_abs":"Young people with major depressive disorder (MDD) exhibit altered thermoregulation, which has also been linked to vigilance and sustained attention. However, whether peripheral skin temperature is associated with cognitive vulnerability around sleep onset is unknown. We examined the relationship between the distal-proximal skin temperature gradient (DPG) and vigilance in 38 young people with MDD (20.1{+\/-}3.7 years, 65.9% female) using an in-laboratory protocol spanning 4h before, to 2h after, habitual sleep time. Participants were classified into DPGwarm and DPGcold subgroups based on being above or below median DPG before sleep onset. Linear mixed models adjusted for age and sex examined psychomotor vigilance task performance across timepoints. The DPGwarm subgroup (n=19) showed significantly worse performance than DPGcold (n=19) across the evening for mean reaction time (RT), reciprocal reaction time, number of lapses, and fastest 10% of RT (all p[&le;]0.003). Significant GroupxTime interactions were observed for mean RT (F(3,90.4)=5.00, p=0.003) and lapses (F(3,93.6)=6.73, p<0.001), with DPGwarm participants showing progressively worse performance approaching sleep onset. At 2h post-habitual sleep onset, DPGwarm participants exhibited slower RT ({Delta}=129ms, p<0.001) and nearly four times more lapses (14.9 vs 4.1, p<0.001). Performance decrements were not accompanied by differences in melatonin timing, subjective sleepiness or mood, suggesting DPG may index cognitive vulnerability independently. Of note, younger age was associated with greater vigilance decrements. These findings demonstrate that elevated peripheral skin temperature before sleep onset is associated with reduced vigilance in young people with MDD, and may therefore have potential utility as a non-invasive thermoregulatory biomarker of cognitive vulnerability.","rel_num_authors":10,"rel_authors":[{"author_name":"Christopher J Gordon","author_inst":"Macquarie University"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Yue Leon Guo","author_inst":"National Taiwan University College of Medicine"},{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Rebecca Robillard","author_inst":"University of Ottawa"},{"author_name":"Jacob Crouse","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Sharon L Naismith","author_inst":"The University of Sydney"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Daniel F Hermens","author_inst":"Thompson Institute, University of Sunshine Coast"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, The University of Sydney"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Gut microbiota signatures differentiate trajectory-defined response phenotypes and predict self-management outcomes in irritable bowel syndrome","rel_doi":"10.64898\/2026.05.18.26353470","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.18.26353470","rel_abs":"Background: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome (IBS) remains poorly understood. The gut microbiota may contribute to this variability, but its role in shaping symptom trajectories and responses to self-management interventions is unclear. Objective: To identify symptom trajectory phenotypes and determine whether gut microbiota composition and function distinguish these phenotypes and predict multidimensional responses to pain self-management interventions in young adults with IBS. Design: Ancillary data analysis from a randomized control trial (NCT03332537). Methods: Participants with longitudinal data (n = 62) were analyzed using longitudinal k-means clustering (KML) based on trajectories of measures in IBS quality of life (QOL), Brief Pain Inventory (BPI), and psychoneurological outcomes (anxiety, applied cognition, depression, fatigue, global health, positive affect, and sleep disturbance) over 12 weeks. Baseline differences between clusters were assessed with Wilcoxon rank-sum tests, and longitudinal changes were evaluated with linear mixed models. Gut microbiota composition and predicted functional pathways were compared between phenotypes. Bayesian Additive Regression Trees (BART) models were used to identify baseline microbial taxa and pathways predictive of longitudinal changes in QOL, BPI pain interference, and severity. Results: Two distinct trajectory-defined response phenotypes were identified: a Constrained Response Phenotype (Phenotype A, n = 35) and an Adaptive Multidomain Response Phenotype (Phenotype B, n = 27). At baseline, Phenotype B showed lower pain severity and interference, but higher levels of anxiety, depression, and fatigue compared to Phenotype A. Over 12 weeks, both phenotypes showed improvements in pain outcomes (all p < 0.05), but only Phenotype B demonstrated broad improvements across psychoneurological domains and QOL (all p < 0.05). Phenotype A exhibited more limited improvements and worsening in several psychoneurological domains. Gut microbiota functional pathways differed between phenotypes, including pathways related to xenobiotic degradation, amino acid metabolism, bile secretion, and immune-related processes (all raw p < 0.05), although these did not remain significant after multiple testing correction. Machine learning models identified distinct, phenotype-specific microbial predictors of intervention response. In Phenotype A, genera such as Alistipes and Sutterella were consistently identified across models, whereas in Phenotype B, predictors included Phascolarctobacterium, Collinsella, and Parabacteroides. Functional pathways also differed between phenotypes, suggesting distinct microbiome-linked mechanisms underlying symptom trajectories and responses to pain interventions. Conclusions: Young adults with IBS exhibit distinct multidimensional response phenotypes that are associated with differential clinical and microbiome profiles. Baseline gut microbiota composition and functional capacity demonstrate phenotype-specific predictive signatures of treatment response, supporting a microbiome-informed framework for stratifying patients and advancing personalized self-management strategies in IBS.","rel_num_authors":9,"rel_authors":[{"author_name":"Jie Chen","author_inst":"Florida State University College of Nursing"},{"author_name":"Aolan Li","author_inst":"Yale School of Nursing"},{"author_name":"Weizi Wu","author_inst":"Yale School of Nursing"},{"author_name":"Wanli Xu","author_inst":"School of Nursing, University of Connecticut"},{"author_name":"Tingting Zhao","author_inst":"School of Nursing, Columbia University"},{"author_name":"Angela R Starkweather","author_inst":"Division of Nursing Science, Rutgers School of Nursing"},{"author_name":"Leonel Rodriguez","author_inst":"Yale School of Medicine"},{"author_name":"Ming-Hui Chen","author_inst":"Department of Statistics, University of Connecticut"},{"author_name":"Xiaomei S Cong","author_inst":"Yale School of Nursing"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Gut microbiota signatures differentiate trajectory-defined response phenotypes and predict self-management outcomes in irritable bowel syndrome","rel_doi":"10.64898\/2026.05.18.26353470","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.18.26353470","rel_abs":"Background: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome (IBS) remains poorly understood. The gut microbiota may contribute to this variability, but its role in shaping symptom trajectories and responses to self-management interventions is unclear. Objective: To identify symptom trajectory phenotypes and determine whether gut microbiota composition and function distinguish these phenotypes and predict multidimensional responses to pain self-management interventions in young adults with IBS. Design: Ancillary data analysis from a randomized control trial (NCT03332537). Methods: Participants with longitudinal data (n = 62) were analyzed using longitudinal k-means clustering (KML) based on trajectories of measures in IBS quality of life (QOL), Brief Pain Inventory (BPI), and psychoneurological outcomes (anxiety, applied cognition, depression, fatigue, global health, positive affect, and sleep disturbance) over 12 weeks. Baseline differences between clusters were assessed with Wilcoxon rank-sum tests, and longitudinal changes were evaluated with linear mixed models. Gut microbiota composition and predicted functional pathways were compared between phenotypes. Bayesian Additive Regression Trees (BART) models were used to identify baseline microbial taxa and pathways predictive of longitudinal changes in QOL, BPI pain interference, and severity. Results: Two distinct trajectory-defined response phenotypes were identified: a Constrained Response Phenotype (Phenotype A, n = 35) and an Adaptive Multidomain Response Phenotype (Phenotype B, n = 27). At baseline, Phenotype B showed lower pain severity and interference, but higher levels of anxiety, depression, and fatigue compared to Phenotype A. Over 12 weeks, both phenotypes showed improvements in pain outcomes (all p < 0.05), but only Phenotype B demonstrated broad improvements across psychoneurological domains and QOL (all p < 0.05). Phenotype A exhibited more limited improvements and worsening in several psychoneurological domains. Gut microbiota functional pathways differed between phenotypes, including pathways related to xenobiotic degradation, amino acid metabolism, bile secretion, and immune-related processes (all raw p < 0.05), although these did not remain significant after multiple testing correction. Machine learning models identified distinct, phenotype-specific microbial predictors of intervention response. In Phenotype A, genera such as Alistipes and Sutterella were consistently identified across models, whereas in Phenotype B, predictors included Phascolarctobacterium, Collinsella, and Parabacteroides. Functional pathways also differed between phenotypes, suggesting distinct microbiome-linked mechanisms underlying symptom trajectories and responses to pain interventions. Conclusions: Young adults with IBS exhibit distinct multidimensional response phenotypes that are associated with differential clinical and microbiome profiles. Baseline gut microbiota composition and functional capacity demonstrate phenotype-specific predictive signatures of treatment response, supporting a microbiome-informed framework for stratifying patients and advancing personalized self-management strategies in IBS.","rel_num_authors":9,"rel_authors":[{"author_name":"Jie Chen","author_inst":"Florida State University College of Nursing"},{"author_name":"Aolan Li","author_inst":"Yale School of Nursing"},{"author_name":"Weizi Wu","author_inst":"Yale School of Nursing"},{"author_name":"Wanli Xu","author_inst":"School of Nursing, University of Connecticut"},{"author_name":"Tingting Zhao","author_inst":"School of Nursing, Columbia University"},{"author_name":"Angela R Starkweather","author_inst":"Division of Nursing Science, Rutgers School of Nursing"},{"author_name":"Leonel Rodriguez","author_inst":"Yale School of Medicine"},{"author_name":"Ming-Hui Chen","author_inst":"Department of Statistics, University of Connecticut"},{"author_name":"Xiaomei S Cong","author_inst":"Yale School of Nursing"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Gut microbiota signatures differentiate trajectory-defined response phenotypes and predict self-management outcomes in irritable bowel syndrome","rel_doi":"10.64898\/2026.05.18.26353470","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.18.26353470","rel_abs":"Background: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome (IBS) remains poorly understood. The gut microbiota may contribute to this variability, but its role in shaping symptom trajectories and responses to self-management interventions is unclear. Objective: To identify symptom trajectory phenotypes and determine whether gut microbiota composition and function distinguish these phenotypes and predict multidimensional responses to pain self-management interventions in young adults with IBS. Design: Ancillary data analysis from a randomized control trial (NCT03332537). Methods: Participants with longitudinal data (n = 62) were analyzed using longitudinal k-means clustering (KML) based on trajectories of measures in IBS quality of life (QOL), Brief Pain Inventory (BPI), and psychoneurological outcomes (anxiety, applied cognition, depression, fatigue, global health, positive affect, and sleep disturbance) over 12 weeks. Baseline differences between clusters were assessed with Wilcoxon rank-sum tests, and longitudinal changes were evaluated with linear mixed models. Gut microbiota composition and predicted functional pathways were compared between phenotypes. Bayesian Additive Regression Trees (BART) models were used to identify baseline microbial taxa and pathways predictive of longitudinal changes in QOL, BPI pain interference, and severity. Results: Two distinct trajectory-defined response phenotypes were identified: a Constrained Response Phenotype (Phenotype A, n = 35) and an Adaptive Multidomain Response Phenotype (Phenotype B, n = 27). At baseline, Phenotype B showed lower pain severity and interference, but higher levels of anxiety, depression, and fatigue compared to Phenotype A. Over 12 weeks, both phenotypes showed improvements in pain outcomes (all p < 0.05), but only Phenotype B demonstrated broad improvements across psychoneurological domains and QOL (all p < 0.05). Phenotype A exhibited more limited improvements and worsening in several psychoneurological domains. Gut microbiota functional pathways differed between phenotypes, including pathways related to xenobiotic degradation, amino acid metabolism, bile secretion, and immune-related processes (all raw p < 0.05), although these did not remain significant after multiple testing correction. Machine learning models identified distinct, phenotype-specific microbial predictors of intervention response. In Phenotype A, genera such as Alistipes and Sutterella were consistently identified across models, whereas in Phenotype B, predictors included Phascolarctobacterium, Collinsella, and Parabacteroides. Functional pathways also differed between phenotypes, suggesting distinct microbiome-linked mechanisms underlying symptom trajectories and responses to pain interventions. Conclusions: Young adults with IBS exhibit distinct multidimensional response phenotypes that are associated with differential clinical and microbiome profiles. Baseline gut microbiota composition and functional capacity demonstrate phenotype-specific predictive signatures of treatment response, supporting a microbiome-informed framework for stratifying patients and advancing personalized self-management strategies in IBS.","rel_num_authors":9,"rel_authors":[{"author_name":"Jie Chen","author_inst":"Florida State University College of Nursing"},{"author_name":"Aolan Li","author_inst":"Yale School of Nursing"},{"author_name":"Weizi Wu","author_inst":"Yale School of Nursing"},{"author_name":"Wanli Xu","author_inst":"School of Nursing, University of Connecticut"},{"author_name":"Tingting Zhao","author_inst":"School of Nursing, Columbia University"},{"author_name":"Angela R Starkweather","author_inst":"Division of Nursing Science, Rutgers School of Nursing"},{"author_name":"Leonel Rodriguez","author_inst":"Yale School of Medicine"},{"author_name":"Ming-Hui Chen","author_inst":"Department of Statistics, University of Connecticut"},{"author_name":"Xiaomei S Cong","author_inst":"Yale School of Nursing"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Instantaneous Three-Dimensional Scanning for Foot Orthosis Design: Clinical Validation of a Multicamera Photogrammetry 3D Scanner","rel_doi":"10.64898\/2026.05.13.26352176","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.13.26352176","rel_abs":"3D scanners have revolutionised how podiatrists capture foot morphology in order to design custom orthoses (insoles). While various 3D scanning technologies are used in clinical practice, they vary greatly in cost and ease of use and many of these are not specifically designed for podiatry applications. There is limited literature comparing accuracy between scanners, and many approaches require prolonged scan times during which the patient must remain still. Multicamera photogrammetry offers a promising solution by enabling high-quality, rapid 3D scanning which other devices cannot provide. This study compared the accuracy and clinical utility of four 3D scanners. One was a high accuracy reference scanner (Artec Spider) which was used as a gold standard. Two further scanners which are commonly used in the clinic were also investigated (Apple iPad 6 with Structure Sensor attachment 'iPad', and Envisic VeriScan Podiatric Scanner 'laser') and these were directly compared with a novel prototype multicamera photogrammetry 3D scanner. The left feet of 20 healthy volunteers were scanned using each of the four devices and scans were evaluated for accuracy, completeness, and acquisition and processing times. All scanners produced clinically acceptable scans, with the novel photogrammetry scanner demonstrating superior accuracy. Scan times varied significantly between scanners, with the photogrammetry device capturing scans much faster. All scanners had acceptable levels of completeness, though the iPad and photogrammetry outperformed the laser scanner. These results provide a valuable tool for clinics seeking guidance on scanner selection and highlight the benefits of instantaneous photogrammetry scanning to improve workflow efficiency and accessibility.","rel_num_authors":9,"rel_authors":[{"author_name":"Joshua A Taylor","author_inst":"Queensland University of Technology"},{"author_name":"Alexander J Terrill","author_inst":"Queensland University of Technology"},{"author_name":"Aaron Wholohan","author_inst":"Queensland University of Technology"},{"author_name":"Renee Nightingale","author_inst":"Queensland University of Technology"},{"author_name":"Ollie Nagle","author_inst":"Queensland University of Technology"},{"author_name":"Edmund Ian Marcus Pickering","author_inst":"Queensland University of Technology"},{"author_name":"David Holmes","author_inst":"Queensland University of Technology"},{"author_name":"Sean K Powell","author_inst":"Queensland University of Technology"},{"author_name":"Maria A Woodruff","author_inst":"Queensland University of Technology"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Characterising the Stability of Polygenic Risk Scores: implications for risk stratification","rel_doi":"10.64898\/2026.05.17.26353273","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353273","rel_abs":"Polygenic risk scores (PRS) improve progressively as genome-wide association studies (GWAS) increase in sample size and ancestral diversity, yet the effect of successive GWAS releases on individual PRS rankings remains poorly characterised. Here, we quantify how individual PRS rankings change across GWAS releases, whether those changes favour cases over controls, how consistently individuals maintain their relative position, and whether those in high-risk strata retain that classification over time. Using PRS derived from four GWAS releases for bipolar disorder, major depressive disorder, and schizophrenia in three Australian cohorts, we observed widespread bidirectional reclassification that exceeded the theoretical minimum of expected reclassification, and was directionally consistent with case-control status when discriminative performance improved. Rank variability was substantial and uniformly distributed across all levels of risk, rank persistence was limited across releases, and retention of high-risk classifications was variable across disorders and largely accounted for by the inter-release correlation. These findings demonstrate that individual PRS rankings are dynamic and shaped by progressive improvements in effect-size estimates, carrying important implications for PRS-based risk stratification strategies that rely on stable classifications in psychiatric research and clinical practice.","rel_num_authors":11,"rel_authors":[{"author_name":"Andreza Ferreira","author_inst":"QIMR Berghofer"},{"author_name":"Penelope A. Lind","author_inst":"QIMR Berghofer"},{"author_name":"Hayley Moody","author_inst":"Queensland University of Technology"},{"author_name":"Ian B. Hickie","author_inst":"University of Sydney"},{"author_name":"Catherine M. Olsen","author_inst":"QIMR Berghofer"},{"author_name":"David C. Whiteman","author_inst":"QIMR Berghofer"},{"author_name":"Matthew H. Law","author_inst":"QIMR Berghofer"},{"author_name":"Dan J. Siskind","author_inst":"University of Queensland"},{"author_name":"Nicholas G. Martin","author_inst":"QIMR Berghofer"},{"author_name":"Richard C. Medland","author_inst":"Queensland University of Technology"},{"author_name":"Sarah E. Medland","author_inst":"QIMR Berghofer"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Characterising the Stability of Polygenic Risk Scores: implications for risk stratification","rel_doi":"10.64898\/2026.05.17.26353273","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353273","rel_abs":"Polygenic risk scores (PRS) improve progressively as genome-wide association studies (GWAS) increase in sample size and ancestral diversity, yet the effect of successive GWAS releases on individual PRS rankings remains poorly characterised. Here, we quantify how individual PRS rankings change across GWAS releases, whether those changes favour cases over controls, how consistently individuals maintain their relative position, and whether those in high-risk strata retain that classification over time. Using PRS derived from four GWAS releases for bipolar disorder, major depressive disorder, and schizophrenia in three Australian cohorts, we observed widespread bidirectional reclassification that exceeded the theoretical minimum of expected reclassification, and was directionally consistent with case-control status when discriminative performance improved. Rank variability was substantial and uniformly distributed across all levels of risk, rank persistence was limited across releases, and retention of high-risk classifications was variable across disorders and largely accounted for by the inter-release correlation. These findings demonstrate that individual PRS rankings are dynamic and shaped by progressive improvements in effect-size estimates, carrying important implications for PRS-based risk stratification strategies that rely on stable classifications in psychiatric research and clinical practice.","rel_num_authors":11,"rel_authors":[{"author_name":"Andreza Ferreira","author_inst":"QIMR Berghofer"},{"author_name":"Penelope A. Lind","author_inst":"QIMR Berghofer"},{"author_name":"Hayley Moody","author_inst":"Queensland University of Technology"},{"author_name":"Ian B. Hickie","author_inst":"University of Sydney"},{"author_name":"Catherine M. Olsen","author_inst":"QIMR Berghofer"},{"author_name":"David C. Whiteman","author_inst":"QIMR Berghofer"},{"author_name":"Matthew H. Law","author_inst":"QIMR Berghofer"},{"author_name":"Dan J. Siskind","author_inst":"University of Queensland"},{"author_name":"Nicholas G. Martin","author_inst":"QIMR Berghofer"},{"author_name":"Richard C. Medland","author_inst":"Queensland University of Technology"},{"author_name":"Sarah E. Medland","author_inst":"QIMR Berghofer"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Urethral Morphology and Support Associated with Urinary Symptoms after Vaginal Surgery with and without Midurethral Sling","rel_doi":"10.64898\/2026.05.17.26353431","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353431","rel_abs":"Background: Midurethral sling placement is often performed during prolapse repair to treat or prevent stress urinary incontinence. However, some women experience persistent or new-onset stress or urgency urinary incontinence after surgery. It is unclear how prolapse repair, with or without a concomitant midurethral sling, alters urethral morphology and support, and how these changes relate to urinary continence outcomes. Objectives: To compare postoperative urethral morphology (dimensions, angles, shape) and support (position, mobility) after transvaginal prolapse repair with vs without a concurrent midurethral sling, and to explore associations between postoperative urethral characteristics and urinary outcomes (stress, urgency symptoms). Study Design: This ancillary analysis used magnetic resonance imaging and urinary outcome data from the Defining Mechanisms of Anterior Vaginal Wall Descent Study conducted across 8 clinical sites within the United States Pelvic Floor Disorders Network. Eighty-two women (median age, 65 years) underwent transvaginal prolapse repair (vaginal mesh hysteropexy or vaginal hysterectomy with uterosacral ligament suspension) with or without a concurrent midurethral sling between April 2013 and February 2015. Postoperative imaging at rest and during strain was performed 30-42 months after surgery (or earlier if they chose reoperation) between June 2014 and May 2018. Prolapse recurrence, defined as descent beyond the vaginal introitus during strain, was recorded. The urethra was segmented from postoperative scans to create 3-dimensional models for measuring urethral diameters, length, surface area, volume, angles, shape (principal component scores from a statistical shape model), position, and mobility (rest-to-strain displacement). Preoperative and 24-48-month postoperative urinary continence outcomes were assessed using validated questionnaires: the Urogenital Distress Inventory, Urinary Impact Questionnaire, and the Incontinence Severity Index. Comparisons of urethral and urinary outcomes by (1) midurethral sling and (2) stress urinary incontinence were made using Wilcoxon rank-sum tests, principal component analysis, and multivariate models as appropriate. Associations between urethral and urinary outcomes were evaluated with Spearmans rank correlation. Results: Forty-six women (22 hysteropexy, 24 hysterectomy) were in the sling group, and 36 (19 hysteropexy, 17 hysterectomy) were in the no-sling group. Among the 48 women without prolapse recurrence (28 sling, 20 no-sling), those with a sling (vs without) had larger urethral dimensions (all P<.03), a more anterior-superior position of the proximal urethra (indicating better bladder neck support) (P=.04), a straighter urethral shape (P=.006), and reported less bothersome postoperative stress incontinence (P=.02). Overall, 14 women (17%) experienced postoperative stress incontinence. Stress urinary incontinence was linked to a more acute proximal urethral sagittal angle (more aligned with axial plane) (P=.01), and a lower proximal urethra position (P=.04) and mid-urethra position (P=.03). Poorer stress and urgency urinary outcomes were associated with a shorter urethral length (P=.01), a more posterior-inferior urethral position (all P<.05), increased C or S-shaped urethral concavity (P=.008; P=.006), and smaller rest-to-strain displacement of the proximal (P=.03) and distal (P=.009) urethra. Conclusions: Urethral morphology and support differed with concomitant midurethral sling (vs no sling) and stress urinary incontinence after vaginal surgery. Urethral characteristics were also associated with postoperative urinary symptoms. Urethral configuration may influence urinary outcomes and could be considered during prolapse and stress urinary incontinence repairs.","rel_num_authors":12,"rel_authors":[{"author_name":"Shaniel Bowen","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Pamela Moalli","author_inst":"Magee-Womens Hospital of the University of Pittsburgh"},{"author_name":"Heidi Harvie","author_inst":"Perelman School of Medicine"},{"author_name":"Charles Rardin","author_inst":"Alpert Medical School of Brown University"},{"author_name":"Michael Hahn","author_inst":"University of California San Diego"},{"author_name":"Alison Weidner","author_inst":"Duke University"},{"author_name":"Holly Richter","author_inst":"University of Alabama at Birmingham"},{"author_name":"Tasha Serna-Gallegos","author_inst":"University of New Mexico"},{"author_name":"Donna Mazloomdoost","author_inst":"Eunice Kennedy Shriver National Institute of Child Health and Human Development"},{"author_name":"Amaanti Sridhar","author_inst":"RTI International"},{"author_name":"Marie Gantz","author_inst":"RTI International"},{"author_name":"- NICHD Pelvic Floor Disorders Network","author_inst":""}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Frontal Cortex-Subthalamic Nucleus Beta Oscillations Exhibit Phase Locking and Granger Causality in Parkinson's Disease","rel_doi":"10.64898\/2026.05.13.26348975","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.13.26348975","rel_abs":"Objective. Pathological beta oscillations are a hallmark of Parkinson's Disease (PD) and are linked with symptom severity and therapeutic efficacy of deep brain stimulation (DBS). Although some studies suggest that beta oscillations may propagate from the frontal cortex to the subthalamic nucleus (STN), direct evidence based on cortical and subcortical neural recordings remains limited. This study investigates synchrony and directionality of beta-band interactions between the frontal cortex and STN in PD. Approach. Simultaneous electrocorticography and STN local field potential recordings were obtained from three PD patients undergoing awake DBS lead placement surgery. Cortical-STN beta phase synchrony was quantified using phase locking value, and directed functional connectivity was analyzed using time-resolved bivariate Granger causality. Main results. Phase locking value mapping revealed a spatially non-uniform distribution of beta phase synchrony, with the strongest coupling localized most prominently within the precentral and superior frontal gyri. Granger causality analysis demonstrated a predominance of cortical-to-subthalamic beta-band interactions across all subjects with intermittent bidirectional coupling. Significance. These findings provide evidence that pathological beta oscillations in Parkinson's may preferentially propagate from the frontal cortex to the basal ganglia, consistent with known motor pathways. These findings are consistent with a cortical contribution to pathological beta oscillations and highlight potential methods for obtaining cortical targets for phase-dependent neuromodulation.","rel_num_authors":7,"rel_authors":[{"author_name":"Jack Coursen","author_inst":"Johns Hopkins"},{"author_name":"Toren Arginteanu","author_inst":"Johns Hopkins"},{"author_name":"Gabriele Boccardo","author_inst":"Humanitas University"},{"author_name":"Anruo Shen","author_inst":"Johns Hopkins"},{"author_name":"Kelly A Mills","author_inst":"Johns Hopkins"},{"author_name":"Yousef Salimpour","author_inst":"Johns Hopkins"},{"author_name":"William S Anderson","author_inst":"Johns Hopkins"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"The role of Lipoprotein(a) and oxidized phospholipids in modifying the effects of aspirin on major cardiovascular events and bleeding in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized clinical trial: Statistical analysis plan.","rel_doi":"10.64898\/2026.05.17.26353443","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353443","rel_abs":"Lipoprotein(a) (Lp(a)) is associated with atherothrombosis through several mechanisms, including putative antifibrinolytic properties. In the ASPREE randomized trial of daily low-dose aspirin for primary prevention in older adults, 72% of trial participants in Australia provided baseline blood samples from which Lp(a) and related oxidized phospholipids and plasminogen have been measured in a specialized laboratory at University of California San Diego. Recent findings from our group suggest that aspirin may benefit older individuals with genotypes associated with elevated lipoprotein(a). We present an analysis plan to address key hypotheses relating to whether the effects of aspirin on cardiovascular disease might vary based on a person's measured levels of lipoprotein(a), oxidized phospholipid levels present on protein carriers apoB-100 (OxPL-apoB), Lp(a) (OxPL-apo(a)) and plasminogen (OxPL-PLG), and plasminogen. The analysis plan also articulates safety analyses involving major hemorrhage.","rel_num_authors":10,"rel_authors":[{"author_name":"Rory Wolfe","author_inst":"Monash University"},{"author_name":"Harpreet Bhatia","author_inst":"University of California, San Diego"},{"author_name":"Paul Lacaze","author_inst":"Monash University"},{"author_name":"Suzanne G Orchard","author_inst":"Monash University"},{"author_name":"Alice Owen","author_inst":"Monash University"},{"author_name":"Galina Polekhina","author_inst":"Monash University"},{"author_name":"Chenglong Yu","author_inst":"Monash University"},{"author_name":"Robyn Lorraine L Woods","author_inst":"Monash University"},{"author_name":"Andrew Tonkin","author_inst":"Monash University"},{"author_name":"Sotirios Tsimikas","author_inst":"University of California, San Diego"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Evaluating Sycophancy in Frontier Models Using Persona-Driven Challenge","rel_doi":"10.64898\/2026.05.17.26353406","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.17.26353406","rel_abs":"Large language models (LLMs) are increasingly used for lay health queries, yet may abandon correct recommendations under pressure, a vulnerability termed sycophancy. We evaluated sycophancy across five frontier LLMs (Claude Opus 4.6, Claude Sonnet 4.6, GPT 5.4, Grok 4.1, Gemini 3 Flash) using 200 synthetic clinical vignettes, each anchored to a unanimous correct treatment baseline and challenged by nine personas representing both vulnerable and authority roles. Overall, 7.1% of responses were sycophantic, varying tenfold across personas (1.7 to 19.3%) and sixfold across LLMs (2.4 to 15.3%). Vulnerable personas elicited more sycophantic responses, with medical student highest at the highest rate (19.3%). In adjusted Generalized Estimating Equations models, vulnerable personas continued to be independent predictors of sycophantic responses, which is a reversal of the expected authority gradient. In adjusted GEE models, persona and LLM were both independent predictors for sycophantic responses. Persona driven sycophancy evaluation should be integrated into pre deployment safety assessment of clinical LLMs.","rel_num_authors":17,"rel_authors":[{"author_name":"Nimay Sanjay Hazare","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Neha Goel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Clara Yu","author_inst":"Division of Biology and Biological Engineering, California Institute of Technology"},{"author_name":"Shamay Agaron","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Aniket Sharma","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Prathamesh Parchure","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Dhaval Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Prem Timsina","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ben Kaplan","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Joshua Lampert","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Aditi Vakil","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Patricia Kovatch","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Bruce Darrow","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Benjamin S Glicksberg","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Alexander Charney","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Girish N Nadkarni","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ankit Sakhuja","author_inst":"Icahn School of Medicine at Mount Sinai"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Evaluating Guideline-Endorsed Probability Stratification and Aldosterone Suppression Testing for Lateralizing Primary Aldosteronism","rel_doi":"10.64898\/2026.05.14.26353176","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353176","rel_abs":"Background: Recent primary aldosteronism (PA) guidelines proposed probability-based stratifications, and use of aldosterone suppression testing, to predict lateralizing PA subtype. This guideline framework was based on very low-quality evidence. Methods: The discriminatory capacity of guideline-endorsed probability frameworks for PA subtyping were evaluated in this retrospective study of 319 PA patients, from two large tertiary centers in Bangkok, Thailand, who underwent subtyping assessments regardless of probability status. PA subtypes were determined by adrenal venous sampling (AVS) and\/or post-adrenalectomy outcomes using PASO criteria. The main objectives were to evaluate the accuracy of predicting PA subtype using: 1) guideline-endorsed classification to high, intermediate, and low probabilities of lateralization; and 2) the seated saline suppression test (SST). Results: The majority of PA patients were characterized as having intermediate probability for lateralizing PA (75%); however, lateralizing PA was ultimately confirmed in 61-78% of all patients, regardless of guideline-based probability classification. The vast majority of SST results were positive using guideline-derived criteria, regardless of probability stratification or ultimate subtype: 89.3% of patients with lateralizing PA and 80.6% of those with bilateral PA had a positive SST. Among patients with intermediate probability of lateralizing PA, where guidelines specifically endorse the value of SST, the SST had a sensitivity of 89.4% and specificity of 22.0% for detecting lateralizing PA, with 78.0% false-positive and 10.6% false-negative rates. Consistently, post-SST aldosterone concentrations exhibited near-complete overlap between those with and without lateralizing PA. Conclusion: Guideline-endorsed probability frameworks, and the use of SST, lacked discriminatory capacity to predict PA subtype.","rel_num_authors":13,"rel_authors":[{"author_name":"Manaporn Payanundana","author_inst":"Phramongkutklao Hospital, and Phramongkutklao College of Medicine, Bangkok, Thailand"},{"author_name":"Wasita Warachit Parksook","author_inst":"King Chulalonkorn Memorial Hospital, Thai Red Cross Society"},{"author_name":"Kantawich Piyanirun","author_inst":"Faculty of Medicine, Chulalongkorn University"},{"author_name":"Dutsadee Charunvarakornchai","author_inst":"Phramongkutklao Hospital, and Phramongkutklao College of Medicine, Bangkok, Thailand"},{"author_name":"Chonpiti Siriwan","author_inst":"Phramongkutklao Hospital, and Phramongkutklao College of Medicine, Bangkok, Thailand"},{"author_name":"Stefanie Parisien-La Salle","author_inst":"Division of Endocrinology, Department of Medicine, Centre Hospitalier de l'Universite de Montreal, Universite de Montreal, QC, Canada"},{"author_name":"Cheng-Hsuan Tsai","author_inst":"Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei 100, Tai"},{"author_name":"Andrew J Newman","author_inst":"Brigham and Women's Hospital"},{"author_name":"Jenifer M Brown","author_inst":"Brigham and Women's Hospital"},{"author_name":"Nattapol Sathavarodom","author_inst":"Phramongkutklao Hospital, and Phramongkutklao College of Medicine, Bangkok, Thailand"},{"author_name":"Sarat Sunthornyothin","author_inst":"Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Chulalongkorn University, and Excellence Center for Diabetes, Hormones an"},{"author_name":"Apussanee Boonyavarakul","author_inst":"Phramongkutklao Hospital, and Phramongkutklao College of Medicine, Bangkok, Thailand"},{"author_name":"Anand Vaidya","author_inst":"Brigham and Women's Hospital, Harvard Medical School"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Burden of health morbidities and associated health care costs in the Australian Genetics of Depression Study using the medication-based Rx-Risk Comorbidity Index","rel_doi":"10.64898\/2026.05.15.26353340","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353340","rel_abs":"Depression is accompanied by considerable comorbidity and excess mortality. We examined multimorbidity data using the validated pharmacy-based Rx-Risk Comorbidity Index and examined healthcare costs associated with chronic illness burden in the Australian Genetics of Depression Study (AGDS). Australian Pharmaceutical Benefits Scheme (PBS) record linkage for 15,890 AGDS participants was available from 01\/07\/2013-31\/12\/2017. Forty-six health morbidities were inferred by mapping the prescription data using Anatomical Therapeutic Chemical Classification System codes and PBS Item Codes. Morbidity prevalence rates were then compared with an unselected 10% Australian representative population sample (10PCT) with PBS claims data available from 01\/07\/2010-31\/12\/2014. The average number of inferred comorbidities was higher among AGDS participants (4.6 {+\/-} 2.9) than 10PCT individuals (3.0 {+\/-} 3.0). Excluding depression, 89.1% of AGDS participants had one or more inferred comorbidity, most commonly pain (51.0%), inflammation\/pain (40.3%), and anxiety (32.3%). In the AGDS, the number of comorbidities was higher among women compared to men and positively correlated with participant age, BMI, number of depressive episodes experienced, and annual health care costs. Compared to participants with no inferred comorbidities, the median annual health care costs were ~65% higher among those with 2-3 comorbidities. This study highlights the patterns of health morbidities experienced by individuals living with depression and shows that this chronic disease burden is significantly associated with increased health costs to the individual and the health system.","rel_num_authors":5,"rel_authors":[{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer"},{"author_name":"Ian B Hickie","author_inst":"University of Sydney"},{"author_name":"Enda M Byrne","author_inst":"The University of Queensland"},{"author_name":"Nicholas G Martin","author_inst":"QIMR Berghofer"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Exploring the Relationship Between Acute Respiratory Illnesses, blood inflammatory biomarkers, and Acute Cardiac Events through a cross-sectional study","rel_doi":"10.64898\/2026.05.15.26353350","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353350","rel_abs":"Introduction Recent respiratory illness, especially influenza, may trigger acute cardiac events via elevated inflammatory mediators. During the 2018 influenza season in Bangladesh, this study examined whether recent acute clinical respiratory illness (CRI) or laboratory-confirmed influenza was associated with elevated hs-CRP and IL-6, linked to acute cardiac events. Methods A total of 139 participants aged [&ge;]40 were recruited from a Dhaka cardiac hospital: 70 with acute myocardial infarction (AMI), 30 with other acute cardiac events, and 39 healthy individuals. CRI was defined as fever with cough and\/or respiratory symptoms within seven days. Respiratory swabs were tested for influenza, and blood was analyzed for hs-CRP and IL-6. Results Median hs-CRP and IL-6 were higher in participants with CRI or influenza but not significantly. Cardiac patients had elevated hs-CRP (9.98 mg\/L in other cardiac; 4.86 mg\/L in AMI vs. 1.73 mg\/L in healthy) and IL-6 (0.1 pg\/mL in other cardiac; 0.145 pg\/mL in AMI vs. 0.08 pg\/mL in healthy) (p<0.001). CRI was not significantly associated with elevated hs-CRP or IL-6, though influenza in healthy participants was linked to higher IL-6. Cardiac patients had a higher risk of hs-CRP [&ge;]3 mg\/L and elevated IL-6. Conclusion Cardiac patients showed significantly increased inflammatory markers, but CRI was not clearly linked to inflammation. Further research should assess biomarker utility for early cardiac risk.","rel_num_authors":11,"rel_authors":[{"author_name":"Mohammad  Abdul Aleem","author_inst":"International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"C.  Raina Macintyre","author_inst":"UNSW Medicne Kirby Institute: The Kirby Institute"},{"author_name":"Bayzidur  Ahmad Rahman","author_inst":"UNSW MEDICINE Kirby Institute NCHECR: The Kirby Institute"},{"author_name":"Mohammed  Ziaur Rahman","author_inst":"ICDDRB: International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"Mustafizur  Ahmad Rahman","author_inst":"ICDDR: International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"A.  K. M. Monwarul Islam","author_inst":"NICVD: National Institute of Cardiovascular Diseases"},{"author_name":"Probir  Kumar Ghosh","author_inst":"ICDDRB: International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"Zubair Akhtar","author_inst":"ICDDR: International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"Fahmida Chowdhury","author_inst":"ICDDR: International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"Firdausi  Ahmad Qadri","author_inst":"ICDDR: International Centre for Diarrhoeal Disease Research Bangladesh"},{"author_name":"Abrar  Ahmad Chughtai","author_inst":"UNSW: University of New South Wales"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Occupational hierarchy, racialization, and COVID-19 health outcomes among meat processing plant workers in Alberta: a community-engaged mixed-methods study","rel_doi":"10.64898\/2026.05.14.26353257","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353257","rel_abs":"Background Meat processing plants in Alberta, Canada experienced among North America's largest COVID-19 outbreaks. We examined health impacts among workers by occupational hierarchy and equity-relevant characteristics. Methods This exploratory sequential mixed-methods study was guided by community-based participatory research and the PROGRESS-Plus framework. Multilingual qualitative interviews and surveys using validated instruments were conducted among meat plant workers who experienced outbreaks. Interviews were analysed using inductive-deductive thematic analysis. Multivariable logistic regression and linear regression estimated associations between occupational group, racialization, facility, and self-reported COVID-19 diagnosis, physical and mental health, and mean Everyday Discrimination Scale score. We integrated findings using joint displays. Findings Qualitative and integrated analysis of thirty-six interviews described occupational hierarchy shaping unequal protection, limited communication, constrained agency, and psychosocial harms, amplified by income insecurity and family separation. Among 187 survey respondents, compared with general labour, skilled labour (aOR 0.38; 95% CI 0.15-0.89) and management (aOR 0.13; 95% CI 0.01-0.75) had lower odds of reported COVID-19 diagnosis. Compared with Black workers, other racialized workers had lower odds of reporting fair or poor mental (aOR 0.24; 95% CI 0.09-0.58) and physical health (aOR 0.20; 95% CI 0.06-0.54). Compared with workers from the primary facility, others reported lower mean everyday discrimination scores ({beta} = -0.54; 95% CI -0.96 to -0.12). Interpretation COVID-19 harms followed workplace social hierarchies. Pandemic preparedness should combine infection-control measures with paid sick leave and income protection, multilingual communication, enforceable anti-discrimination standards, and independent reporting mechanisms. Funding Canadian Institutes for Health Research (CIHR Application no. 469206). Keywords COVID-19, immigrant workers, migrants, essential workers, health equity, occupational health, PROGRESS Plus","rel_num_authors":16,"rel_authors":[{"author_name":"Mohammad Yasir Essar","author_inst":"University of Calgary"},{"author_name":"Eric Norrie","author_inst":"University of Calgary"},{"author_name":"Edna Ramirez Cerino","author_inst":"University of Calgary"},{"author_name":"Minnella Antonio","author_inst":"University of Calgary"},{"author_name":"Ammar Saad","author_inst":"University of Ottawa"},{"author_name":"Mussie Yemane","author_inst":"University of Calgary"},{"author_name":"Linda Holdbrook","author_inst":"University of Calgary"},{"author_name":"Adanech Sahilie","author_inst":"University of Calgary"},{"author_name":"Michael Youssef","author_inst":"University of Calgary"},{"author_name":"Nour Hassan","author_inst":"University of Calgary"},{"author_name":"Olivia Magwood","author_inst":"Bruyere Health Research Institute"},{"author_name":"Samuel T. Edwards","author_inst":"Oregon Health & Science University"},{"author_name":"Denise Spitzer","author_inst":"University of Alberta"},{"author_name":"Annalee Coakley","author_inst":"University of Calgary"},{"author_name":"Kevin Pottie","author_inst":"Western University"},{"author_name":"Gabriel E. Fabreau","author_inst":"University of Calgary"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Occupational hierarchy, racialization, and COVID-19 health outcomes among meat processing plant workers in Alberta: a community-engaged mixed-methods study","rel_doi":"10.64898\/2026.05.14.26353257","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353257","rel_abs":"Background Meat processing plants in Alberta, Canada experienced among North America's largest COVID-19 outbreaks. We examined health impacts among workers by occupational hierarchy and equity-relevant characteristics. Methods This exploratory sequential mixed-methods study was guided by community-based participatory research and the PROGRESS-Plus framework. Multilingual qualitative interviews and surveys using validated instruments were conducted among meat plant workers who experienced outbreaks. Interviews were analysed using inductive-deductive thematic analysis. Multivariable logistic regression and linear regression estimated associations between occupational group, racialization, facility, and self-reported COVID-19 diagnosis, physical and mental health, and mean Everyday Discrimination Scale score. We integrated findings using joint displays. Findings Qualitative and integrated analysis of thirty-six interviews described occupational hierarchy shaping unequal protection, limited communication, constrained agency, and psychosocial harms, amplified by income insecurity and family separation. Among 187 survey respondents, compared with general labour, skilled labour (aOR 0.38; 95% CI 0.15-0.89) and management (aOR 0.13; 95% CI 0.01-0.75) had lower odds of reported COVID-19 diagnosis. Compared with Black workers, other racialized workers had lower odds of reporting fair or poor mental (aOR 0.24; 95% CI 0.09-0.58) and physical health (aOR 0.20; 95% CI 0.06-0.54). Compared with workers from the primary facility, others reported lower mean everyday discrimination scores ({beta} = -0.54; 95% CI -0.96 to -0.12). Interpretation COVID-19 harms followed workplace social hierarchies. Pandemic preparedness should combine infection-control measures with paid sick leave and income protection, multilingual communication, enforceable anti-discrimination standards, and independent reporting mechanisms. Funding Canadian Institutes for Health Research (CIHR Application no. 469206). Keywords COVID-19, immigrant workers, migrants, essential workers, health equity, occupational health, PROGRESS Plus","rel_num_authors":16,"rel_authors":[{"author_name":"Mohammad Yasir Essar","author_inst":"University of Calgary"},{"author_name":"Eric Norrie","author_inst":"University of Calgary"},{"author_name":"Edna Ramirez Cerino","author_inst":"University of Calgary"},{"author_name":"Minnella Antonio","author_inst":"University of Calgary"},{"author_name":"Ammar Saad","author_inst":"University of Ottawa"},{"author_name":"Mussie Yemane","author_inst":"University of Calgary"},{"author_name":"Linda Holdbrook","author_inst":"University of Calgary"},{"author_name":"Adanech Sahilie","author_inst":"University of Calgary"},{"author_name":"Michael Youssef","author_inst":"University of Calgary"},{"author_name":"Nour Hassan","author_inst":"University of Calgary"},{"author_name":"Olivia Magwood","author_inst":"Bruyere Health Research Institute"},{"author_name":"Samuel T. Edwards","author_inst":"Oregon Health & Science University"},{"author_name":"Denise Spitzer","author_inst":"University of Alberta"},{"author_name":"Annalee Coakley","author_inst":"University of Calgary"},{"author_name":"Kevin Pottie","author_inst":"Western University"},{"author_name":"Gabriel E. Fabreau","author_inst":"University of Calgary"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Occupational hierarchy, racialization, and COVID-19 health outcomes among meat processing plant workers in Alberta: a community-engaged mixed-methods study","rel_doi":"10.64898\/2026.05.14.26353257","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353257","rel_abs":"Background Meat processing plants in Alberta, Canada experienced among North America's largest COVID-19 outbreaks. We examined health impacts among workers by occupational hierarchy and equity-relevant characteristics. Methods This exploratory sequential mixed-methods study was guided by community-based participatory research and the PROGRESS-Plus framework. Multilingual qualitative interviews and surveys using validated instruments were conducted among meat plant workers who experienced outbreaks. Interviews were analysed using inductive-deductive thematic analysis. Multivariable logistic regression and linear regression estimated associations between occupational group, racialization, facility, and self-reported COVID-19 diagnosis, physical and mental health, and mean Everyday Discrimination Scale score. We integrated findings using joint displays. Findings Qualitative and integrated analysis of thirty-six interviews described occupational hierarchy shaping unequal protection, limited communication, constrained agency, and psychosocial harms, amplified by income insecurity and family separation. Among 187 survey respondents, compared with general labour, skilled labour (aOR 0.38; 95% CI 0.15-0.89) and management (aOR 0.13; 95% CI 0.01-0.75) had lower odds of reported COVID-19 diagnosis. Compared with Black workers, other racialized workers had lower odds of reporting fair or poor mental (aOR 0.24; 95% CI 0.09-0.58) and physical health (aOR 0.20; 95% CI 0.06-0.54). Compared with workers from the primary facility, others reported lower mean everyday discrimination scores ({beta} = -0.54; 95% CI -0.96 to -0.12). Interpretation COVID-19 harms followed workplace social hierarchies. Pandemic preparedness should combine infection-control measures with paid sick leave and income protection, multilingual communication, enforceable anti-discrimination standards, and independent reporting mechanisms. Funding Canadian Institutes for Health Research (CIHR Application no. 469206). Keywords COVID-19, immigrant workers, migrants, essential workers, health equity, occupational health, PROGRESS Plus","rel_num_authors":16,"rel_authors":[{"author_name":"Mohammad Yasir Essar","author_inst":"University of Calgary"},{"author_name":"Eric Norrie","author_inst":"University of Calgary"},{"author_name":"Edna Ramirez Cerino","author_inst":"University of Calgary"},{"author_name":"Minnella Antonio","author_inst":"University of Calgary"},{"author_name":"Ammar Saad","author_inst":"University of Ottawa"},{"author_name":"Mussie Yemane","author_inst":"University of Calgary"},{"author_name":"Linda Holdbrook","author_inst":"University of Calgary"},{"author_name":"Adanech Sahilie","author_inst":"University of Calgary"},{"author_name":"Michael Youssef","author_inst":"University of Calgary"},{"author_name":"Nour Hassan","author_inst":"University of Calgary"},{"author_name":"Olivia Magwood","author_inst":"Bruyere Health Research Institute"},{"author_name":"Samuel T. Edwards","author_inst":"Oregon Health & Science University"},{"author_name":"Denise Spitzer","author_inst":"University of Alberta"},{"author_name":"Annalee Coakley","author_inst":"University of Calgary"},{"author_name":"Kevin Pottie","author_inst":"Western University"},{"author_name":"Gabriel E. Fabreau","author_inst":"University of Calgary"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Altered neurodevelopmental trajectories of brain structure in Tourette syndrome and Chronic Tic Disorders","rel_doi":"10.64898\/2026.05.16.26353368","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.16.26353368","rel_abs":"Tourette syndrome (TS) is a neurodevelopmental disorder characterized by symptoms that emerge in childhood and often improve or even disappear in adulthood, providing a model for understanding how altered brain development shapes neural structure and function. We investigate brain structural alterations in TS and Chronic Tic Disorders (TS\/CTD) across development, presenting the largest structural neuroimaging analysis for TS\/CTD to date (1,803 individuals from the ENIGMA-TS Working Group), and integrating with large-scale genomewide association studies. Nonlinear age effects were observed in cortical thickness across development and in thalamic volume in children, indicating altered trajectories of brain maturation . Pediatric and adult TS\/CTD showed distinct structural patterns, with widespread alterations in childhood and more focal changes in adulthood. Children also showed the most prominent effects highlighting the involvement of orbitofrontal cortex and putamen, alongside additional regions such as frontal and paralimbic areas. Genetic pleiotropy analyses identified overlap between TS\/CTD-associated genetic effects on brain structure and neuroanatomical differences. Cross-disorder comparisons revealed correlations with ADHD and OCD and age-related patterns. These findings demonstrate altered neurodevelopmental trajectories in TS\/CTD and implicate systems underlying inhibitory control and urge regulation.","rel_num_authors":89,"rel_authors":[{"author_name":"Yin Jin","author_inst":"Purdue University"},{"author_name":"Yuxin Guo","author_inst":"Purdue University"},{"author_name":"Jonathan M. Koller","author_inst":"Washington University in St. Louis"},{"author_name":"Sarah C. Grossen","author_inst":"Washington Univeristy in St. Louis"},{"author_name":"Anne Uhlmann","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Natalie J. Forde","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands"},{"author_name":"Jade-Jocelyne Zouki","author_inst":"Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia"},{"author_name":"Renzo Torrecuso","author_inst":"Max Planck Institute for Human Cognitive and Brain Sciences"},{"author_name":"Karsten M\u00fceller","author_inst":"1) Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; 2) Department of Neurology, Charles University, First Faculty of Medicine and "},{"author_name":"Juan F. F. Martin-Rodriguez","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Pablo Franco-Rosado","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Michel Grothe","author_inst":"Instituto de Biomedicina de Sevilla (IBiS)"},{"author_name":"Catharina Cramer","author_inst":"Hannover Medical School"},{"author_name":"Anne Kleine B\u00fcning","author_inst":"Hannover Medical School"},{"author_name":"Heike Eichele","author_inst":"Department og Biological and Medical Psychology, University of Bergen, Norway"},{"author_name":"Stefano Palmucci","author_inst":"Department of Medical Surgical Sciences and Advanced Technologies, Radiology Unit 1; University of Catania, Italy"},{"author_name":"Adriana Prato","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Federica Saia","author_inst":"University of Catania"},{"author_name":"Silvia Tommasin","author_inst":"The Sapienza University of Rome"},{"author_name":"Giulia Conte","author_inst":"The Sapienza University of Rome"},{"author_name":"Katharina A. Schindlbeck","author_inst":"Department of Psychiatry and Psychotherapy,LMU University Hospital, LMU Munich"},{"author_name":"Christos Ganos","author_inst":"Charite, University Medicine Berlin"},{"author_name":"Shukti Zimmermann","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany, Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich "},{"author_name":"Tanja Veselinovi\u0107","author_inst":"RWTH Aachen University"},{"author_name":"Yulia Worbe","author_inst":"Department of Clinical Neurophysiology, Sorbonne Universite, APHP - Saint Antoine Hospital, Paris France ; Paris Brain Institute - Salpetriere Hospital, Paris, "},{"author_name":"Andreas Hartmann","author_inst":"Department of Neurology, Pitie-Salpetriere Hospital, Paris, France"},{"author_name":"Apostolia Topaloudi","author_inst":"Purdue University"},{"author_name":"Mary Kaka","author_inst":"Purdue University"},{"author_name":"Guangxin Chen","author_inst":"Purdue University"},{"author_name":"Qingyi Zhong","author_inst":"Purdue University"},{"author_name":"Yuqi Zhang","author_inst":"Purdue University"},{"author_name":"Natalia Szejko","author_inst":"Department of Child Psychiatry, Babinski Hospital, Lodz; Department of Experimental and Clinical Pharmacology, Center for Preclinical Research and Technology CE"},{"author_name":"Piotr Janik","author_inst":"Medical University of Warsaw"},{"author_name":"Nanette M. M. Debes","author_inst":"Department of Pediatrics, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark; Department of Clinical Medicine, University of Copenhagen, Cope"},{"author_name":"Zeynep Tumer","author_inst":"Department of Clinical Genetics, Kennedy Center, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"},{"author_name":"Tomasz Wola\u0144czyk","author_inst":"Medical University of Warsaw"},{"author_name":"Gary A. Heiman","author_inst":"Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854"},{"author_name":"Hreinn Stefansson","author_inst":"Amgen deCODE genetics, Iceland"},{"author_name":"Helga Ask","author_inst":"PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health"},{"author_name":"Ole A. Andreassen","author_inst":"Centre for Precision Psychiatry, University of Oslo, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway"},{"author_name":"Anders D. B\u00f8rglum","author_inst":"1) Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark. 2) The Lundbeck Foundation Initiative for Integrative Psychiatric Research, i"},{"author_name":"Joseph D. Buxbaum","author_inst":"Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY, USA"},{"author_name":"Elizabeth C. Corfield","author_inst":"1) PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health; 2) Psychiatric Genetic Epidemiology Group, Research Departm"},{"author_name":"Mark Daly","author_inst":"Harvard Medical School, USA,  Massachusetts General Hospital, USA"},{"author_name":"Dorothy E. Grice","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029"},{"author_name":"David Mataix-Cols","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland."},{"author_name":"Christian R\u00fcck","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Matthew Halvorsen","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Lea K. Davis","author_inst":"1. Professor of Medicine, Department of Medicine, Division of Data Driven and Digital Medicine; 2. Windreich Department of AI and Human Health, Icahn School of "},{"author_name":"James J. Crowley","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Manuel Mattheisen","author_inst":"1) Department of Community Health and Epidemiology and Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada; 2) Institute of Psychiat"},{"author_name":"Dongmei Yu","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA; Stanley Cen"},{"author_name":"Carol A. Mathews","author_inst":"University of Florida, Department of Psychiatry, Genetics Institute, Center for OCD, Anxiety and Related Disorders, Evelyn F and William L McKnight Brain Instit"},{"author_name":"Jeremiah M. Scharf","author_inst":"1) Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical Scho"},{"author_name":"- The members of the Tourette International TS-EUROTRAIN\/TSGeneSEE","author_inst":"-"},{"author_name":"- TAA Neuroimaging Consortium","author_inst":"-"},{"author_name":"- Collaborative Genetics Consortium","author_inst":"-"},{"author_name":"- TAAICG","author_inst":"-"},{"author_name":"- EMTICS","author_inst":"-"},{"author_name":"- ENIGMA-TS Working Group","author_inst":"-"},{"author_name":"Dan J. Stein","author_inst":"SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town"},{"author_name":"Irene Neuner","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany,Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich G"},{"author_name":"Richard Musil","author_inst":"Ludwig-Maximilians-University of Munich"},{"author_name":"Francesco Cardona","author_inst":"The Sapienza University of Rome"},{"author_name":"Danielle C. Cath","author_inst":"University of Groningen, university Medical Center Groningen, department of Psychiatry &Drenthe MHC, Groningen, the Netherlands"},{"author_name":"Dick J. Veltman","author_inst":"Dept. of Psychiatry, Amsterdam University Medical Center, location VUmc, Amsterdam"},{"author_name":"Tim J. Silk","author_inst":"1.Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia, 2. Developmental Imaging, Murdoch Children'"},{"author_name":"Alexander M\u00fcnchau","author_inst":"Institute of Systems Motor Science, University of L\u00fcbeck, L\u00fcbeck, Germany; Centre for Rare Diseases, University Hospital Schleswig-Holstein, L\u00fcbeck, Germany"},{"author_name":"Julius Verrel","author_inst":"Institute of Systems Motor Science, University L\u00fcbeck, L\u00fcbeck, Germany"},{"author_name":"Valerie C. Brandt","author_inst":"University of Southampton"},{"author_name":"Tamara Hershey","author_inst":"Departments of Radiology and Psychiatry, Washington University School of Medicine"},{"author_name":"Deanna J. Greene","author_inst":"University of California, San Diego"},{"author_name":"Bradley L. Schlaggar","author_inst":"1. Kennedy Krieger Institute, Baltimore MD 21205. 2. Departments of Neurology and Pediatrics, Johns Hopkins University School of Medicine, Baltimore MD 21205"},{"author_name":"Jan Buitelaar","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre"},{"author_name":"Barbara Franke","author_inst":"Departments of Genetics and of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CentreRadboud University"},{"author_name":"Sophia Thomopoulos","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Renata Rizzo","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Andrea Dietrich","author_inst":"University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pieter J. Hoekstra","author_inst":"University of Groningen, University Medical Center Groningen, Department of Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pablo Mir","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, IBiS\/Hospital Universitario Virgen del Rocio\/CSIC\/Universid"},{"author_name":"Veit Roessner","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Odile A. van den Heuvel","author_inst":"Dept. Psychiatry, Dept. Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience"},{"author_name":"Kirsten R. M\u00fcller-Vahl","author_inst":"Hannover Medical School"},{"author_name":"Harald E. M\u00f6ller","author_inst":"NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany"},{"author_name":"Neda Jahanshad","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Paul M. Thompson","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Kevin J. Black","author_inst":"Departments of Psychiatry, Neurology, Radiology and Neuroscience, Washington University in St. Louis"},{"author_name":"Peristera Paschou","author_inst":"Purdue University"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Altered neurodevelopmental trajectories of brain structure in Tourette syndrome and Chronic Tic Disorders","rel_doi":"10.64898\/2026.05.16.26353368","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.16.26353368","rel_abs":"Tourette syndrome (TS) is a neurodevelopmental disorder characterized by symptoms that emerge in childhood and often improve or even disappear in adulthood, providing a model for understanding how altered brain development shapes neural structure and function. We investigate brain structural alterations in TS and Chronic Tic Disorders (TS\/CTD) across development, presenting the largest structural neuroimaging analysis for TS\/CTD to date (1,803 individuals from the ENIGMA-TS Working Group), and integrating with large-scale genomewide association studies. Nonlinear age effects were observed in cortical thickness across development and in thalamic volume in children, indicating altered trajectories of brain maturation . Pediatric and adult TS\/CTD showed distinct structural patterns, with widespread alterations in childhood and more focal changes in adulthood. Children also showed the most prominent effects highlighting the involvement of orbitofrontal cortex and putamen, alongside additional regions such as frontal and paralimbic areas. Genetic pleiotropy analyses identified overlap between TS\/CTD-associated genetic effects on brain structure and neuroanatomical differences. Cross-disorder comparisons revealed correlations with ADHD and OCD and age-related patterns. These findings demonstrate altered neurodevelopmental trajectories in TS\/CTD and implicate systems underlying inhibitory control and urge regulation.","rel_num_authors":89,"rel_authors":[{"author_name":"Yin Jin","author_inst":"Purdue University"},{"author_name":"Yuxin Guo","author_inst":"Purdue University"},{"author_name":"Jonathan M. Koller","author_inst":"Washington University in St. Louis"},{"author_name":"Sarah C. Grossen","author_inst":"Washington Univeristy in St. Louis"},{"author_name":"Anne Uhlmann","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Natalie J. Forde","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands"},{"author_name":"Jade-Jocelyne Zouki","author_inst":"Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia"},{"author_name":"Renzo Torrecuso","author_inst":"Max Planck Institute for Human Cognitive and Brain Sciences"},{"author_name":"Karsten M\u00fceller","author_inst":"1) Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; 2) Department of Neurology, Charles University, First Faculty of Medicine and "},{"author_name":"Juan F. F. Martin-Rodriguez","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Pablo Franco-Rosado","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Michel Grothe","author_inst":"Instituto de Biomedicina de Sevilla (IBiS)"},{"author_name":"Catharina Cramer","author_inst":"Hannover Medical School"},{"author_name":"Anne Kleine B\u00fcning","author_inst":"Hannover Medical School"},{"author_name":"Heike Eichele","author_inst":"Department og Biological and Medical Psychology, University of Bergen, Norway"},{"author_name":"Stefano Palmucci","author_inst":"Department of Medical Surgical Sciences and Advanced Technologies, Radiology Unit 1; University of Catania, Italy"},{"author_name":"Adriana Prato","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Federica Saia","author_inst":"University of Catania"},{"author_name":"Silvia Tommasin","author_inst":"The Sapienza University of Rome"},{"author_name":"Giulia Conte","author_inst":"The Sapienza University of Rome"},{"author_name":"Katharina A. Schindlbeck","author_inst":"Department of Psychiatry and Psychotherapy,LMU University Hospital, LMU Munich"},{"author_name":"Christos Ganos","author_inst":"Charite, University Medicine Berlin"},{"author_name":"Shukti Zimmermann","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany, Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich "},{"author_name":"Tanja Veselinovi\u0107","author_inst":"RWTH Aachen University"},{"author_name":"Yulia Worbe","author_inst":"Department of Clinical Neurophysiology, Sorbonne Universite, APHP - Saint Antoine Hospital, Paris France ; Paris Brain Institute - Salpetriere Hospital, Paris, "},{"author_name":"Andreas Hartmann","author_inst":"Department of Neurology, Pitie-Salpetriere Hospital, Paris, France"},{"author_name":"Apostolia Topaloudi","author_inst":"Purdue University"},{"author_name":"Mary Kaka","author_inst":"Purdue University"},{"author_name":"Guangxin Chen","author_inst":"Purdue University"},{"author_name":"Qingyi Zhong","author_inst":"Purdue University"},{"author_name":"Yuqi Zhang","author_inst":"Purdue University"},{"author_name":"Natalia Szejko","author_inst":"Department of Child Psychiatry, Babinski Hospital, Lodz; Department of Experimental and Clinical Pharmacology, Center for Preclinical Research and Technology CE"},{"author_name":"Piotr Janik","author_inst":"Medical University of Warsaw"},{"author_name":"Nanette M. M. Debes","author_inst":"Department of Pediatrics, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark; Department of Clinical Medicine, University of Copenhagen, Cope"},{"author_name":"Zeynep Tumer","author_inst":"Department of Clinical Genetics, Kennedy Center, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"},{"author_name":"Tomasz Wola\u0144czyk","author_inst":"Medical University of Warsaw"},{"author_name":"Gary A. Heiman","author_inst":"Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854"},{"author_name":"Hreinn Stefansson","author_inst":"Amgen deCODE genetics, Iceland"},{"author_name":"Helga Ask","author_inst":"PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health"},{"author_name":"Ole A. Andreassen","author_inst":"Centre for Precision Psychiatry, University of Oslo, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway"},{"author_name":"Anders D. B\u00f8rglum","author_inst":"1) Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark. 2) The Lundbeck Foundation Initiative for Integrative Psychiatric Research, i"},{"author_name":"Joseph D. Buxbaum","author_inst":"Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY, USA"},{"author_name":"Elizabeth C. Corfield","author_inst":"1) PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health; 2) Psychiatric Genetic Epidemiology Group, Research Departm"},{"author_name":"Mark Daly","author_inst":"Harvard Medical School, USA,  Massachusetts General Hospital, USA"},{"author_name":"Dorothy E. Grice","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029"},{"author_name":"David Mataix-Cols","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland."},{"author_name":"Christian R\u00fcck","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Matthew Halvorsen","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Lea K. Davis","author_inst":"1. Professor of Medicine, Department of Medicine, Division of Data Driven and Digital Medicine; 2. Windreich Department of AI and Human Health, Icahn School of "},{"author_name":"James J. Crowley","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Manuel Mattheisen","author_inst":"1) Department of Community Health and Epidemiology and Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada; 2) Institute of Psychiat"},{"author_name":"Dongmei Yu","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA; Stanley Cen"},{"author_name":"Carol A. Mathews","author_inst":"University of Florida, Department of Psychiatry, Genetics Institute, Center for OCD, Anxiety and Related Disorders, Evelyn F and William L McKnight Brain Instit"},{"author_name":"Jeremiah M. Scharf","author_inst":"1) Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical Scho"},{"author_name":"- The members of the Tourette International TS-EUROTRAIN\/TSGeneSEE","author_inst":"-"},{"author_name":"- TAA Neuroimaging Consortium","author_inst":"-"},{"author_name":"- Collaborative Genetics Consortium","author_inst":"-"},{"author_name":"- TAAICG","author_inst":"-"},{"author_name":"- EMTICS","author_inst":"-"},{"author_name":"- ENIGMA-TS Working Group","author_inst":"-"},{"author_name":"Dan J. Stein","author_inst":"SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town"},{"author_name":"Irene Neuner","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany,Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich G"},{"author_name":"Richard Musil","author_inst":"Ludwig-Maximilians-University of Munich"},{"author_name":"Francesco Cardona","author_inst":"The Sapienza University of Rome"},{"author_name":"Danielle C. Cath","author_inst":"University of Groningen, university Medical Center Groningen, department of Psychiatry &Drenthe MHC, Groningen, the Netherlands"},{"author_name":"Dick J. Veltman","author_inst":"Dept. of Psychiatry, Amsterdam University Medical Center, location VUmc, Amsterdam"},{"author_name":"Tim J. Silk","author_inst":"1.Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia, 2. Developmental Imaging, Murdoch Children'"},{"author_name":"Alexander M\u00fcnchau","author_inst":"Institute of Systems Motor Science, University of L\u00fcbeck, L\u00fcbeck, Germany; Centre for Rare Diseases, University Hospital Schleswig-Holstein, L\u00fcbeck, Germany"},{"author_name":"Julius Verrel","author_inst":"Institute of Systems Motor Science, University L\u00fcbeck, L\u00fcbeck, Germany"},{"author_name":"Valerie C. Brandt","author_inst":"University of Southampton"},{"author_name":"Tamara Hershey","author_inst":"Departments of Radiology and Psychiatry, Washington University School of Medicine"},{"author_name":"Deanna J. Greene","author_inst":"University of California, San Diego"},{"author_name":"Bradley L. Schlaggar","author_inst":"1. Kennedy Krieger Institute, Baltimore MD 21205. 2. Departments of Neurology and Pediatrics, Johns Hopkins University School of Medicine, Baltimore MD 21205"},{"author_name":"Jan Buitelaar","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre"},{"author_name":"Barbara Franke","author_inst":"Departments of Genetics and of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CentreRadboud University"},{"author_name":"Sophia Thomopoulos","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Renata Rizzo","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Andrea Dietrich","author_inst":"University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pieter J. Hoekstra","author_inst":"University of Groningen, University Medical Center Groningen, Department of Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pablo Mir","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, IBiS\/Hospital Universitario Virgen del Rocio\/CSIC\/Universid"},{"author_name":"Veit Roessner","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Odile A. van den Heuvel","author_inst":"Dept. Psychiatry, Dept. Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience"},{"author_name":"Kirsten R. M\u00fcller-Vahl","author_inst":"Hannover Medical School"},{"author_name":"Harald E. M\u00f6ller","author_inst":"NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany"},{"author_name":"Neda Jahanshad","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Paul M. Thompson","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Kevin J. Black","author_inst":"Departments of Psychiatry, Neurology, Radiology and Neuroscience, Washington University in St. Louis"},{"author_name":"Peristera Paschou","author_inst":"Purdue University"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Altered neurodevelopmental trajectories of brain structure in Tourette syndrome and Chronic Tic Disorders","rel_doi":"10.64898\/2026.05.16.26353368","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.16.26353368","rel_abs":"Tourette syndrome (TS) is a neurodevelopmental disorder characterized by symptoms that emerge in childhood and often improve or even disappear in adulthood, providing a model for understanding how altered brain development shapes neural structure and function. We investigate brain structural alterations in TS and Chronic Tic Disorders (TS\/CTD) across development, presenting the largest structural neuroimaging analysis for TS\/CTD to date (1,803 individuals from the ENIGMA-TS Working Group), and integrating with large-scale genomewide association studies. Nonlinear age effects were observed in cortical thickness across development and in thalamic volume in children, indicating altered trajectories of brain maturation . Pediatric and adult TS\/CTD showed distinct structural patterns, with widespread alterations in childhood and more focal changes in adulthood. Children also showed the most prominent effects highlighting the involvement of orbitofrontal cortex and putamen, alongside additional regions such as frontal and paralimbic areas. Genetic pleiotropy analyses identified overlap between TS\/CTD-associated genetic effects on brain structure and neuroanatomical differences. Cross-disorder comparisons revealed correlations with ADHD and OCD and age-related patterns. These findings demonstrate altered neurodevelopmental trajectories in TS\/CTD and implicate systems underlying inhibitory control and urge regulation.","rel_num_authors":89,"rel_authors":[{"author_name":"Yin Jin","author_inst":"Purdue University"},{"author_name":"Yuxin Guo","author_inst":"Purdue University"},{"author_name":"Jonathan M. Koller","author_inst":"Washington University in St. Louis"},{"author_name":"Sarah C. Grossen","author_inst":"Washington Univeristy in St. Louis"},{"author_name":"Anne Uhlmann","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Natalie J. Forde","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands"},{"author_name":"Jade-Jocelyne Zouki","author_inst":"Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia"},{"author_name":"Renzo Torrecuso","author_inst":"Max Planck Institute for Human Cognitive and Brain Sciences"},{"author_name":"Karsten M\u00fceller","author_inst":"1) Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; 2) Department of Neurology, Charles University, First Faculty of Medicine and "},{"author_name":"Juan F. F. Martin-Rodriguez","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Pablo Franco-Rosado","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Michel Grothe","author_inst":"Instituto de Biomedicina de Sevilla (IBiS)"},{"author_name":"Catharina Cramer","author_inst":"Hannover Medical School"},{"author_name":"Anne Kleine B\u00fcning","author_inst":"Hannover Medical School"},{"author_name":"Heike Eichele","author_inst":"Department og Biological and Medical Psychology, University of Bergen, Norway"},{"author_name":"Stefano Palmucci","author_inst":"Department of Medical Surgical Sciences and Advanced Technologies, Radiology Unit 1; University of Catania, Italy"},{"author_name":"Adriana Prato","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Federica Saia","author_inst":"University of Catania"},{"author_name":"Silvia Tommasin","author_inst":"The Sapienza University of Rome"},{"author_name":"Giulia Conte","author_inst":"The Sapienza University of Rome"},{"author_name":"Katharina A. Schindlbeck","author_inst":"Department of Psychiatry and Psychotherapy,LMU University Hospital, LMU Munich"},{"author_name":"Christos Ganos","author_inst":"Charite, University Medicine Berlin"},{"author_name":"Shukti Zimmermann","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany, Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich "},{"author_name":"Tanja Veselinovi\u0107","author_inst":"RWTH Aachen University"},{"author_name":"Yulia Worbe","author_inst":"Department of Clinical Neurophysiology, Sorbonne Universite, APHP - Saint Antoine Hospital, Paris France ; Paris Brain Institute - Salpetriere Hospital, Paris, "},{"author_name":"Andreas Hartmann","author_inst":"Department of Neurology, Pitie-Salpetriere Hospital, Paris, France"},{"author_name":"Apostolia Topaloudi","author_inst":"Purdue University"},{"author_name":"Mary Kaka","author_inst":"Purdue University"},{"author_name":"Guangxin Chen","author_inst":"Purdue University"},{"author_name":"Qingyi Zhong","author_inst":"Purdue University"},{"author_name":"Yuqi Zhang","author_inst":"Purdue University"},{"author_name":"Natalia Szejko","author_inst":"Department of Child Psychiatry, Babinski Hospital, Lodz; Department of Experimental and Clinical Pharmacology, Center for Preclinical Research and Technology CE"},{"author_name":"Piotr Janik","author_inst":"Medical University of Warsaw"},{"author_name":"Nanette M. M. Debes","author_inst":"Department of Pediatrics, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark; Department of Clinical Medicine, University of Copenhagen, Cope"},{"author_name":"Zeynep Tumer","author_inst":"Department of Clinical Genetics, Kennedy Center, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"},{"author_name":"Tomasz Wola\u0144czyk","author_inst":"Medical University of Warsaw"},{"author_name":"Gary A. Heiman","author_inst":"Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854"},{"author_name":"Hreinn Stefansson","author_inst":"Amgen deCODE genetics, Iceland"},{"author_name":"Helga Ask","author_inst":"PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health"},{"author_name":"Ole A. Andreassen","author_inst":"Centre for Precision Psychiatry, University of Oslo, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway"},{"author_name":"Anders D. B\u00f8rglum","author_inst":"1) Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark. 2) The Lundbeck Foundation Initiative for Integrative Psychiatric Research, i"},{"author_name":"Joseph D. Buxbaum","author_inst":"Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY, USA"},{"author_name":"Elizabeth C. Corfield","author_inst":"1) PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health; 2) Psychiatric Genetic Epidemiology Group, Research Departm"},{"author_name":"Mark Daly","author_inst":"Harvard Medical School, USA,  Massachusetts General Hospital, USA"},{"author_name":"Dorothy E. Grice","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029"},{"author_name":"David Mataix-Cols","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland."},{"author_name":"Christian R\u00fcck","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Matthew Halvorsen","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Lea K. Davis","author_inst":"1. Professor of Medicine, Department of Medicine, Division of Data Driven and Digital Medicine; 2. Windreich Department of AI and Human Health, Icahn School of "},{"author_name":"James J. Crowley","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Manuel Mattheisen","author_inst":"1) Department of Community Health and Epidemiology and Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada; 2) Institute of Psychiat"},{"author_name":"Dongmei Yu","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA; Stanley Cen"},{"author_name":"Carol A. Mathews","author_inst":"University of Florida, Department of Psychiatry, Genetics Institute, Center for OCD, Anxiety and Related Disorders, Evelyn F and William L McKnight Brain Instit"},{"author_name":"Jeremiah M. Scharf","author_inst":"1) Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical Scho"},{"author_name":"- The members of the Tourette International TS-EUROTRAIN\/TSGeneSEE","author_inst":"-"},{"author_name":"- TAA Neuroimaging Consortium","author_inst":"-"},{"author_name":"- Collaborative Genetics Consortium","author_inst":"-"},{"author_name":"- TAAICG","author_inst":"-"},{"author_name":"- EMTICS","author_inst":"-"},{"author_name":"- ENIGMA-TS Working Group","author_inst":"-"},{"author_name":"Dan J. Stein","author_inst":"SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town"},{"author_name":"Irene Neuner","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany,Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich G"},{"author_name":"Richard Musil","author_inst":"Ludwig-Maximilians-University of Munich"},{"author_name":"Francesco Cardona","author_inst":"The Sapienza University of Rome"},{"author_name":"Danielle C. Cath","author_inst":"University of Groningen, university Medical Center Groningen, department of Psychiatry &Drenthe MHC, Groningen, the Netherlands"},{"author_name":"Dick J. Veltman","author_inst":"Dept. of Psychiatry, Amsterdam University Medical Center, location VUmc, Amsterdam"},{"author_name":"Tim J. Silk","author_inst":"1.Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia, 2. Developmental Imaging, Murdoch Children'"},{"author_name":"Alexander M\u00fcnchau","author_inst":"Institute of Systems Motor Science, University of L\u00fcbeck, L\u00fcbeck, Germany; Centre for Rare Diseases, University Hospital Schleswig-Holstein, L\u00fcbeck, Germany"},{"author_name":"Julius Verrel","author_inst":"Institute of Systems Motor Science, University L\u00fcbeck, L\u00fcbeck, Germany"},{"author_name":"Valerie C. Brandt","author_inst":"University of Southampton"},{"author_name":"Tamara Hershey","author_inst":"Departments of Radiology and Psychiatry, Washington University School of Medicine"},{"author_name":"Deanna J. Greene","author_inst":"University of California, San Diego"},{"author_name":"Bradley L. Schlaggar","author_inst":"1. Kennedy Krieger Institute, Baltimore MD 21205. 2. Departments of Neurology and Pediatrics, Johns Hopkins University School of Medicine, Baltimore MD 21205"},{"author_name":"Jan Buitelaar","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre"},{"author_name":"Barbara Franke","author_inst":"Departments of Genetics and of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CentreRadboud University"},{"author_name":"Sophia Thomopoulos","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Renata Rizzo","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Andrea Dietrich","author_inst":"University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pieter J. Hoekstra","author_inst":"University of Groningen, University Medical Center Groningen, Department of Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pablo Mir","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, IBiS\/Hospital Universitario Virgen del Rocio\/CSIC\/Universid"},{"author_name":"Veit Roessner","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Odile A. van den Heuvel","author_inst":"Dept. Psychiatry, Dept. Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience"},{"author_name":"Kirsten R. M\u00fcller-Vahl","author_inst":"Hannover Medical School"},{"author_name":"Harald E. M\u00f6ller","author_inst":"NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany"},{"author_name":"Neda Jahanshad","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Paul M. Thompson","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Kevin J. Black","author_inst":"Departments of Psychiatry, Neurology, Radiology and Neuroscience, Washington University in St. Louis"},{"author_name":"Peristera Paschou","author_inst":"Purdue University"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Altered neurodevelopmental trajectories of brain structure in Tourette syndrome and Chronic Tic Disorders","rel_doi":"10.64898\/2026.05.16.26353368","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.16.26353368","rel_abs":"Tourette syndrome (TS) is a neurodevelopmental disorder characterized by symptoms that emerge in childhood and often improve or even disappear in adulthood, providing a model for understanding how altered brain development shapes neural structure and function. We investigate brain structural alterations in TS and Chronic Tic Disorders (TS\/CTD) across development, presenting the largest structural neuroimaging analysis for TS\/CTD to date (1,803 individuals from the ENIGMA-TS Working Group), and integrating with large-scale genomewide association studies. Nonlinear age effects were observed in cortical thickness across development and in thalamic volume in children, indicating altered trajectories of brain maturation . Pediatric and adult TS\/CTD showed distinct structural patterns, with widespread alterations in childhood and more focal changes in adulthood. Children also showed the most prominent effects highlighting the involvement of orbitofrontal cortex and putamen, alongside additional regions such as frontal and paralimbic areas. Genetic pleiotropy analyses identified overlap between TS\/CTD-associated genetic effects on brain structure and neuroanatomical differences. Cross-disorder comparisons revealed correlations with ADHD and OCD and age-related patterns. These findings demonstrate altered neurodevelopmental trajectories in TS\/CTD and implicate systems underlying inhibitory control and urge regulation.","rel_num_authors":89,"rel_authors":[{"author_name":"Yin Jin","author_inst":"Purdue University"},{"author_name":"Yuxin Guo","author_inst":"Purdue University"},{"author_name":"Jonathan M. Koller","author_inst":"Washington University in St. Louis"},{"author_name":"Sarah C. Grossen","author_inst":"Washington Univeristy in St. Louis"},{"author_name":"Anne Uhlmann","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Natalie J. Forde","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands"},{"author_name":"Jade-Jocelyne Zouki","author_inst":"Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia"},{"author_name":"Renzo Torrecuso","author_inst":"Max Planck Institute for Human Cognitive and Brain Sciences"},{"author_name":"Karsten M\u00fceller","author_inst":"1) Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; 2) Department of Neurology, Charles University, First Faculty of Medicine and "},{"author_name":"Juan F. F. Martin-Rodriguez","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Pablo Franco-Rosado","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio\/CSIC\/Universidad de"},{"author_name":"Michel Grothe","author_inst":"Instituto de Biomedicina de Sevilla (IBiS)"},{"author_name":"Catharina Cramer","author_inst":"Hannover Medical School"},{"author_name":"Anne Kleine B\u00fcning","author_inst":"Hannover Medical School"},{"author_name":"Heike Eichele","author_inst":"Department og Biological and Medical Psychology, University of Bergen, Norway"},{"author_name":"Stefano Palmucci","author_inst":"Department of Medical Surgical Sciences and Advanced Technologies, Radiology Unit 1; University of Catania, Italy"},{"author_name":"Adriana Prato","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Federica Saia","author_inst":"University of Catania"},{"author_name":"Silvia Tommasin","author_inst":"The Sapienza University of Rome"},{"author_name":"Giulia Conte","author_inst":"The Sapienza University of Rome"},{"author_name":"Katharina A. Schindlbeck","author_inst":"Department of Psychiatry and Psychotherapy,LMU University Hospital, LMU Munich"},{"author_name":"Christos Ganos","author_inst":"Charite, University Medicine Berlin"},{"author_name":"Shukti Zimmermann","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany, Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich "},{"author_name":"Tanja Veselinovi\u0107","author_inst":"RWTH Aachen University"},{"author_name":"Yulia Worbe","author_inst":"Department of Clinical Neurophysiology, Sorbonne Universite, APHP - Saint Antoine Hospital, Paris France ; Paris Brain Institute - Salpetriere Hospital, Paris, "},{"author_name":"Andreas Hartmann","author_inst":"Department of Neurology, Pitie-Salpetriere Hospital, Paris, France"},{"author_name":"Apostolia Topaloudi","author_inst":"Purdue University"},{"author_name":"Mary Kaka","author_inst":"Purdue University"},{"author_name":"Guangxin Chen","author_inst":"Purdue University"},{"author_name":"Qingyi Zhong","author_inst":"Purdue University"},{"author_name":"Yuqi Zhang","author_inst":"Purdue University"},{"author_name":"Natalia Szejko","author_inst":"Department of Child Psychiatry, Babinski Hospital, Lodz; Department of Experimental and Clinical Pharmacology, Center for Preclinical Research and Technology CE"},{"author_name":"Piotr Janik","author_inst":"Medical University of Warsaw"},{"author_name":"Nanette M. M. Debes","author_inst":"Department of Pediatrics, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark; Department of Clinical Medicine, University of Copenhagen, Cope"},{"author_name":"Zeynep Tumer","author_inst":"Department of Clinical Genetics, Kennedy Center, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"},{"author_name":"Tomasz Wola\u0144czyk","author_inst":"Medical University of Warsaw"},{"author_name":"Gary A. Heiman","author_inst":"Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854"},{"author_name":"Hreinn Stefansson","author_inst":"Amgen deCODE genetics, Iceland"},{"author_name":"Helga Ask","author_inst":"PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health"},{"author_name":"Ole A. Andreassen","author_inst":"Centre for Precision Psychiatry, University of Oslo, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway"},{"author_name":"Anders D. B\u00f8rglum","author_inst":"1) Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark. 2) The Lundbeck Foundation Initiative for Integrative Psychiatric Research, i"},{"author_name":"Joseph D. Buxbaum","author_inst":"Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY, USA"},{"author_name":"Elizabeth C. Corfield","author_inst":"1) PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health; 2) Psychiatric Genetic Epidemiology Group, Research Departm"},{"author_name":"Mark Daly","author_inst":"Harvard Medical School, USA,  Massachusetts General Hospital, USA"},{"author_name":"Dorothy E. Grice","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029"},{"author_name":"David Mataix-Cols","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland."},{"author_name":"Christian R\u00fcck","author_inst":"Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Swede"},{"author_name":"Matthew Halvorsen","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Lea K. Davis","author_inst":"1. Professor of Medicine, Department of Medicine, Division of Data Driven and Digital Medicine; 2. Windreich Department of AI and Human Health, Icahn School of "},{"author_name":"James J. Crowley","author_inst":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"},{"author_name":"Manuel Mattheisen","author_inst":"1) Department of Community Health and Epidemiology and Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada; 2) Institute of Psychiat"},{"author_name":"Dongmei Yu","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA; Stanley Cen"},{"author_name":"Carol A. Mathews","author_inst":"University of Florida, Department of Psychiatry, Genetics Institute, Center for OCD, Anxiety and Related Disorders, Evelyn F and William L McKnight Brain Instit"},{"author_name":"Jeremiah M. Scharf","author_inst":"1) Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical Scho"},{"author_name":"- The members of the Tourette International TS-EUROTRAIN\/TSGeneSEE","author_inst":"-"},{"author_name":"- TAA Neuroimaging Consortium","author_inst":"-"},{"author_name":"- Collaborative Genetics Consortium","author_inst":"-"},{"author_name":"- TAAICG","author_inst":"-"},{"author_name":"- EMTICS","author_inst":"-"},{"author_name":"- ENIGMA-TS Working Group","author_inst":"-"},{"author_name":"Dan J. Stein","author_inst":"SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town"},{"author_name":"Irene Neuner","author_inst":"Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany,Institute of Neuroscience and Medicine 4, Forschungszentrum J\u00fclich G"},{"author_name":"Richard Musil","author_inst":"Ludwig-Maximilians-University of Munich"},{"author_name":"Francesco Cardona","author_inst":"The Sapienza University of Rome"},{"author_name":"Danielle C. Cath","author_inst":"University of Groningen, university Medical Center Groningen, department of Psychiatry &Drenthe MHC, Groningen, the Netherlands"},{"author_name":"Dick J. Veltman","author_inst":"Dept. of Psychiatry, Amsterdam University Medical Center, location VUmc, Amsterdam"},{"author_name":"Tim J. Silk","author_inst":"1.Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Burwood, Australia, 2. Developmental Imaging, Murdoch Children'"},{"author_name":"Alexander M\u00fcnchau","author_inst":"Institute of Systems Motor Science, University of L\u00fcbeck, L\u00fcbeck, Germany; Centre for Rare Diseases, University Hospital Schleswig-Holstein, L\u00fcbeck, Germany"},{"author_name":"Julius Verrel","author_inst":"Institute of Systems Motor Science, University L\u00fcbeck, L\u00fcbeck, Germany"},{"author_name":"Valerie C. Brandt","author_inst":"University of Southampton"},{"author_name":"Tamara Hershey","author_inst":"Departments of Radiology and Psychiatry, Washington University School of Medicine"},{"author_name":"Deanna J. Greene","author_inst":"University of California, San Diego"},{"author_name":"Bradley L. Schlaggar","author_inst":"1. Kennedy Krieger Institute, Baltimore MD 21205. 2. Departments of Neurology and Pediatrics, Johns Hopkins University School of Medicine, Baltimore MD 21205"},{"author_name":"Jan Buitelaar","author_inst":"Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre"},{"author_name":"Barbara Franke","author_inst":"Departments of Genetics and of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CentreRadboud University"},{"author_name":"Sophia Thomopoulos","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Renata Rizzo","author_inst":"Deparment of Clinical and Experimental Medicine, Child and Adolescent Neurology and Psichiatry Catania University"},{"author_name":"Andrea Dietrich","author_inst":"University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pieter J. Hoekstra","author_inst":"University of Groningen, University Medical Center Groningen, Department of Psychiatry & Accare Child Study Center, Groningen, Netherlands"},{"author_name":"Pablo Mir","author_inst":"1. Unidad de Trastornos del Movimiento, Servicio de Neurologia, Instituto de Biomedicina de Sevilla, IBiS\/Hospital Universitario Virgen del Rocio\/CSIC\/Universid"},{"author_name":"Veit Roessner","author_inst":"Department of Child and Adolescent Psychiatry, TU Dresden"},{"author_name":"Odile A. van den Heuvel","author_inst":"Dept. Psychiatry, Dept. Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience"},{"author_name":"Kirsten R. M\u00fcller-Vahl","author_inst":"Hannover Medical School"},{"author_name":"Harald E. M\u00f6ller","author_inst":"NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany"},{"author_name":"Neda Jahanshad","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Paul M. Thompson","author_inst":"Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California"},{"author_name":"Kevin J. Black","author_inst":"Departments of Psychiatry, Neurology, Radiology and Neuroscience, Washington University in St. Louis"},{"author_name":"Peristera Paschou","author_inst":"Purdue University"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Socio-geographic factors associated with Lyme disease in children","rel_doi":"10.64898\/2026.05.15.26353361","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353361","rel_abs":"Objective: Lyme disease diagnosis in children is challenging due to atypical presentations and testing limitations. We sought to evaluate the association between Lyme disease and socio-geographic risk factors in children. Materials and methods: We enrolled children undergoing evaluation for acute Lyme disease at one of eight Pedi Lyme Net pediatric emergency departments located in high Lyme disease incidence states over a ten-year period (2015-2024). We defined a case of Lyme disease with an erythema migrans (EM) lesion or a positive two-tier serology result in a child with signs and\/or symptoms of acute disease. We linked each childs primary residential county to the following factors: urban-rural residence, socioeconomic status, population-level disease incidence, wildland-urban interface, and \"Lyme disease\" Google searches. We performed a multi-level logistic regression analysis to evaluate associations between Lyme disease and county factors after adjusting for individual demographics. Results: Among 5,529 children enrolled, 1,396 (25.2%) had Lyme disease: 101 (7.2%) with early-localized disease, 584 (41.8%) with early-disseminated disease, and 711 (50.9%) with late-disseminated disease. Rural residence (aOR 1.9, 95% CI 1.3-2.9), higher socioeconomic advantage (aOR 1.3, 95% CI 1.1-1.4), more \"Lyme disease\" Google searches (aOR 1.1, 95% CI 1.0-1.2), and higher wildland urban interface (aOR 1.2, 95% CI: 1.0-1.4) were independently associated with Lyme disease. Conclusion: Incorporating socio-geographic factors alongside clinical data may augment diagnostic risk assessment in children with suspected Lyme disease. However, these factors should be incorporated carefully to ensure clinical assessments are not based on a childs geographic location alone.","rel_num_authors":14,"rel_authors":[{"author_name":"Cara Wychgram","author_inst":"Johns Hopkins University Bloomberg School of Public Health"},{"author_name":"Alexandra  T. Geanacopoulos","author_inst":"Boston Children's Hospital"},{"author_name":"Alison  W. Rebman","author_inst":"Johns Hopkins Medicine"},{"author_name":"Laura  L. Chapman","author_inst":"Rhode Island Hospital"},{"author_name":"Rebecca  S. Green","author_inst":"Childrens Hospital of Philadelphia"},{"author_name":"Desiree  N. Neville","author_inst":"Children's Hospital of Pittsburgh of UPMC"},{"author_name":"Amy  D. Thompson","author_inst":"Nemours Children's Hospital Delaware"},{"author_name":"Meagan  M. Ladell","author_inst":"Milwaukee Campus-Children's Wisconsin: Milwaukee Hospital-Children's Wisconsin"},{"author_name":"Anupam  B. Kharbanda","author_inst":"Children's Minnesota"},{"author_name":"Kenneth  D. Mandl","author_inst":"Boston Children's Hospital"},{"author_name":"Frank  C. Curriero","author_inst":"Johns Hopkins University Bloomberg School of Public Health"},{"author_name":"John  N. Aucott","author_inst":"Johns Hopkins Medicine"},{"author_name":"Lise  E. Nigrovic","author_inst":"Boston Children's Hospital"},{"author_name":"- Pedi Lyme Net","author_inst":"-"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Aldosterone-targeted Therapy after Primary Aldosteronism Testing in Resistant Hypertension: A Nationwide Cohort Study","rel_doi":"10.64898\/2026.05.16.26353384","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.16.26353384","rel_abs":"Background: Primary aldosteronism (PA) testing is recommended for patients with resistant hypertension but remains underused, and evidence linking aldosterone-targeted therapy to improved cardiovascular and renal outcomes is limited. Methods: In a nationwide cohort of patients with resistant hypertension between 2001 and 2022, we assessed PA testing and subsequent mineralocorticoid receptor antagonist (MRA) use and adrenalectomy. Among tested patients, time-dependent Cox models were used to assess associations between treatment exposure and mortality, major adverse cardiovascular events (MACE) and renal outcomes. Results: Among 254,338 patients, only 2.0% were tested for PA. Tested patients had a higher prevalence of hypokalemia and cardiometabolic comorbidities. In the overall tested population, MRA use was not associated with lower risks of cardiovascular or renal outcomes. However, when testing resulted in an established PA diagnosis, the use of both MRA (hazard ratio [HR] 0.60, 95% CI 0.42-0.86) and adrenalectomy (HR 0.33, 95% CI 0.20-0.54) were associated with a reduced risk of MACE compared with no aldosterone-targeted therapy. Similar results were observed regarding mortality. Adrenalectomy was associated with lower risk of MACE (HR 0.55, 95% CI 0.30-0.99), all-cause mortality (HR 0.52, 95% CI 0.29-0.93) and renal outcomes (HR 0.37, 95% CI 0.17-0.80) compared with MRA in patients with a diagnosis of PA. Conclusions: PA remains markedly underrecognized in resistant hypertension. Among patients with resistant hypertension who did undergo PA testing with establishment of a PA diagnosis, aldosterone-targeted therapy resulted in lower risk of adverse cardiorenal outcomes and death when compared to conventional antihypertensive therapy.","rel_num_authors":10,"rel_authors":[{"author_name":"Cheng-Hsuan Tsai","author_inst":"National Taiwan University Hospital"},{"author_name":"Yu-Ching Chang","author_inst":"National Taiwan University Hospital Hsin-Chu Branch"},{"author_name":"Chin Chen Chang","author_inst":"National Taiwan University Hospital"},{"author_name":"Yi-Yao Chang","author_inst":"Far Eastern Memorial Hospital"},{"author_name":"Uei-Lin Chen","author_inst":"Min-Sheng General Hospital"},{"author_name":"Jeff Shih-Chieh Chueh","author_inst":"National Taiwan University Hospital"},{"author_name":"Jenifer Brown","author_inst":"Brigham and Women's Hospital"},{"author_name":"Vin-Cent Wu","author_inst":"National Taiwan University Hospital"},{"author_name":"Yen-Hung Lin","author_inst":"National Taiwan University College of Medicine and Hospital"},{"author_name":"Anand Vaidya","author_inst":"Brigham and Women's Hospital, Harvard Medical School"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Phase-targeted modulation of essential tremor with transcranial magnetic stimulation of motor cortex","rel_doi":"10.64898\/2026.05.11.26347791","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.11.26347791","rel_abs":"Neural oscillations provide temporal frameworks for coordinating communication within and across distributed brain networks. In essential tremor (ET), pathological synchronization within the cerebello-thalamo-cortical circuit produces rhythmic activity that manifests as an involuntary action tremor. Although deep brain stimulation can effectively suppress tremor, its invasiveness and cost highlight the need for non-invasive interventions capable of selectively modulating pathological oscillations. Transcranial magnetic stimulation (TMS) offers a non-invasive means of engaging cortical circuits, yet conventional stimulation protocols are delivered independently of the ongoing neural dynamics. Such open-loop approaches ignore the temporal structure of tremor-related activity, potentially stimulating during both amplifying and suppressing phases of the oscillation. To address this, we compared two phase-targeted TMS paradigms: first-pulse phase-locked TMS (First-pulse-TMS), in which only the initial pulse of a stimulation train is aligned to the tremor phase, and cycle-by-cycle phase-locked TMS (Continuous-TMS), in which each pulse is continuously triggered based on real-time tremor phase. Ten patients with ET underwent stimulation guided by peripheral tremor recordings using an accelerometer, with tremor phase estimated in real time via the Oscilltrack algorithm. Sixty-four trains of TMS pulses were delivered at nine discrete phase bins of the tremor cycle, such that each phase bin was repeated approximately seven times. Continuous-TMS maintained accurate phase-locking across consecutive cycles (mean phase-locking value ~0.9), whereas First-pulse-TMS exhibited progressive drift over time and low phase consistency (mean phase-locking value <0.2). The circular concentration of stimulation phase was significantly greater for Continuous-TMS than First-pulse-TMS (Mann-Whitney U-test, p < 0.001), indicating a significant difference in overall phase-locking accuracy between the two protocols. Critically, Continuous-TMS, unlike First-pulse-TMS, induced bidirectional, phase-dependent modulation of tremor amplitude. Circular-linear modelling revealed a sinusoidal relationship between stimulation phase and changes in tremor amplitude, with tremor amplification and suppression occurring at opposite phases of the cycle. Covariates including baseline tremor amplitude and trial number were accounted for. In some people, tremor suppression outlasted the stimulation period, suggesting phase-locked TMS may be a potentially useful therapeutic tool. By enabling reliable, phase-specific stimulation of the tremor cycle, Continuous-TMS allows identification of the individual phase that produces maximal tremor suppression, supporting the development of personalized, phase-specific neuromodulation strategies. This proof-of-principle study demonstrates that temporally precise, closed-loop TMS can interact with pathological oscillations in real time, providing a mechanistic framework for probing oscillatory contributions to motor symptoms and a scalable therapeutic approach for ET and other oscillopathies.","rel_num_authors":18,"rel_authors":[{"author_name":"Valentina Mancini","author_inst":"Oxford University"},{"author_name":"Isaac Grennan","author_inst":"Oxford University"},{"author_name":"Nicholas Shackle","author_inst":"Oxford University"},{"author_name":"Talia Vasaturo-Kolodner","author_inst":"Oxford University"},{"author_name":"Priya Sharma","author_inst":"Oxford University"},{"author_name":"Alina Siekmann","author_inst":"Oxford University"},{"author_name":"Sagel Kundieko","author_inst":"Oxford University"},{"author_name":"Fabio Ferrandes","author_inst":"Oxford University"},{"author_name":"Lara Biller","author_inst":"Oxford University"},{"author_name":"Karen Wendt","author_inst":"Oxford University"},{"author_name":"Kawsar Ali","author_inst":"Oxford University"},{"author_name":"Dan Rogers","author_inst":"Oxford University"},{"author_name":"Nagaraja Sarangmat","author_inst":"Oxford University"},{"author_name":"Ashwini Oswal","author_inst":"Oxford University"},{"author_name":"Timothy Denison","author_inst":"Oxford University"},{"author_name":"Hayriye Cagnan","author_inst":"Imperial College"},{"author_name":"Andrew Sharott","author_inst":"Oxford University"},{"author_name":"Charlotte Jane Stagg","author_inst":"Oxford University"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"A Randomized Controlled Trial Comparing Soy-Pea Protein to Animal Protein in Adults with Crohns Disease","rel_doi":"10.64898\/2026.05.20.26353678","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.20.26353678","rel_abs":"Background and Aims: Diet plays a critical role in managing Crohns disease (CD) inflammation. We assessed whether dietary replacement of animal protein (AnimalP) by soy-pea protein (SoyP) decreases the pro-inflammatory potential of gut microbiota and intestinal inflammation in CD patients. Design: In an open-label, randomized controlled feeding trial at University Hospitals Cleveland Medical Center, CD participants and healthy controls were randomized (1:1) to a soy-pea or animal protein diet for 7-days. Primary outcomes were the absolute difference (d7-d0) in; Crohns Disease Activity Index (CDAI) score and fecal myeloperoxidase (MPO). Secondary outcomes included fecal calprotectin (FC) and high-sensitivity C-reactive protein (hsCRP). Murine fecal transplantation experiments were performed to determine the inflammatory potential of diet-altered gut microbiota. Results: The study randomized 66 participants and 60 were included in the final analysis (n=31 CD, n=29 HC). After 7 days, CD-SoyP participants were more likely than CD-AnimalP to show reductions in HBI (RR=4.68, 95% CI: 1.22-17.98, P=0.009) and fecal MPO (RR=2.30, 95% CI: 1.04-4.85, P=0.032), with a similar directional trend for CDAI (RR=1.52, 95% CI: 0.89-2.58, P=0.135). No participants experienced worsening of CDAI. The rank-based composite CDAI-MPO score was lower in the CD-SoyP vs CD-AnimalP group (median [IQR]: 5 [4-6] vs 8 [7-9]; P=0.012). Stratified analyses showed significant reductions in fecal MPO among CD participants with lower baseline disease activity (CDAI <150; P<0.0001), but not in those with higher activity (P=0.799) Conclusion: Short-term addition of plant-based soy-pea protein within a controlled diet exerted a beneficial, anti-inflammatory effect in CD, with evidence of greater effects among participants with lower baseline disease activity. ClinicalTrials.gov, Number NCT04065048.","rel_num_authors":13,"rel_authors":[{"author_name":"Abigail R Basson","author_inst":"Case Western Reserve University"},{"author_name":"Jeffry Katz","author_inst":"University Hospitals Cleveland Medical Center"},{"author_name":"Vu Nguyen","author_inst":"University Hospitals Cleveland Medical Center"},{"author_name":"Drishtant Singh","author_inst":"Case Western Reserve University"},{"author_name":"Paola Menghini","author_inst":"Case Western Reserve University"},{"author_name":"Adrian Gomez-Nguyen","author_inst":"Case Western Reserve University"},{"author_name":"Jennifer Sieg","author_inst":"Case Western Reserve University"},{"author_name":"Madison Bell","author_inst":"Case Western Reserve University"},{"author_name":"Kavitha Thamma","author_inst":"Case Western Reserve University"},{"author_name":"Gina Ponzani","author_inst":"Case Western Reserve University"},{"author_name":"Abdullah Osme","author_inst":"Case Western Reserve University"},{"author_name":"Alexander Rodriguez-Palacios","author_inst":"Case Western Reserve University School of Medicine"},{"author_name":"Fabio Cominelli","author_inst":"University Hospitals Cleveland Medical Center"}],"rel_date":"2026-05-20","rel_site":"medrxiv"},{"rel_title":"Energetic gradients emerge in developing motor-microtubule structures","rel_doi":"10.64898\/2026.05.18.725774","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725774","rel_abs":"Living matter produces a variety of beautiful spatiotemporal structures and patterns that are not enduringly present in their nonliving counterparts. These ordered, non-equilibrium steady states are often sustained through the consumption of energy. Here, we investigate the energetic cost of assembling an ordered aster from an initially disordered, uniform mixture of cytoskeletal microtubules and kinesin motors. Using a calibrated fluorescent ATP reporter, we measure reproducible radial ATP gradients on scales of tens of microns that establish within, and persist over, tens of minutes, alongside coupled spatial gradients in motor density. These appreciable gradients are predicted by a reaction-diffusion model that acknowledges the localization of ATP consumption to regions where both molecular motors and microtubules are sufficiently abundant to encourage consumption, as confirmed by finite element modeling. With our results, we compare the power per volume required by our cytoskeletal networks with the known power per volume expenditure in cells. Comparison of our measured results with estimates of the dissipative processes available to motor-microtubule mixtures leads to the hypothesis that maintaining spatial motor gradients dominates the energetic demand in this system. Our direct quantification of energetic fluxes across space unlocks future explorations of what steady states are accessible to cells, and how the cytoskeleton drives broad spatial organization.","rel_num_authors":10,"rel_authors":[{"author_name":"Ana Isabel Duarte","author_inst":"California Institute of Technology"},{"author_name":"Gabriel L Salmon","author_inst":"California Institute of Technology and NSF-Simons National Institute for Theory and Mathematics"},{"author_name":"Heun Jin Lee","author_inst":"California Institute of Technology"},{"author_name":"Bibi Najma","author_inst":"Brigham and Women's Hospital"},{"author_name":"Minakshi Ashok","author_inst":"California Institute of Technology"},{"author_name":"Soichi Hirokawa","author_inst":"Institut de Biologie du Developpement de Marseille"},{"author_name":"Henk W Ch Postma","author_inst":"California State University Northridge"},{"author_name":"Rachel A Banks","author_inst":"California Institute of Technology"},{"author_name":"Matt Thomson","author_inst":"California Institute of Technology"},{"author_name":"Rob Phillips","author_inst":"California Institute of Technology"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Morphometric analysis reveals that the chick cranial neural tube expands as an active shell.","rel_doi":"10.64898\/2026.05.18.726048","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.726048","rel_abs":"Embryonically, the vertebrate brain begins as an approximately uniform, fluid-filled epithelial tube that undergoes rapid volumetric expansion and regionalization to form the morphologically distinct primary brain vesicles. Hydrostatic pressure from fluid secretion into the inner lumen generates tension in the neural tube that has been implicated as a potential driver of cell proliferation during these early stages of brain development. However, a quantitatively rigorous view of 3D morphology and cellular proliferation has remained elusive. Here, we provide a standardized mapping for the mechanical and biological landscape of the developing neuroepithelium along anatomical axes. Using this 3D morphometric framework in chicken embryos, we show that localized curvature characterizes compartmental boundaries. While rapid inflation would typically be expected to stretch and thin the epithelium, we find the opposite: global expansion is coupled with significant tissue thickening, identifying the early brain as an active shell. Moreover, spatial patterns of thickness remain invariant to local curvature. Our results demonstrate a decoupling of geometry and growth, showing that spatially stable distributions of tissue thickness and mitotic activity are maintained throughout massive volumetric expansion, independent of the dramatic geometric reorganization driven by luminal pressure. We conclude that, while tension in the neuroepithelium may contribute to proliferative growth at some level, biological pre-pattern likely plays a driving role in the regionalized expansion of the early embryonic brain.","rel_num_authors":3,"rel_authors":[{"author_name":"Nimesh Chahare","author_inst":"Columbia University"},{"author_name":"Chieko Imamura","author_inst":"Columbia University"},{"author_name":"Nandan Nerurkar","author_inst":"Columbia University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Phylogenetically estimated neutral rates and fitness effects of mutations to influenza proteins","rel_doi":"10.64898\/2026.05.18.725477","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725477","rel_abs":"Influenza virus's rapid evolution is shaped by both neutral mutation and selection. Phylogenetics can be used to study these processes, but this approach has typically only been applied to a few thousand influenza genome sequences at once. Here, we built phylogenetic trees with >100,000 influenza sequences, and then used these trees to estimate neutral rates of mutations to the virus's genome. Neutral rates varied by up to ~100-fold among the 12 nucleotide mutation types (A-to-C, A-to-G, etc.). These rates were highly correlated among influenza, SARS-CoV-2, and HIV, though more nuanced context-dependent patterns showed marked differences between influenza and SARS-CoV-2. We also estimated fitness effects of mutations by comparing the number of times a mutation was observed to occur along the branches of a tree to the number of times we expect it to have occurred under neutrality. We estimated effects for ~33,000 nonsynonymous and ~8,000 synonymous mutations spanning all influenza proteins. This compendium of estimated effects helps map the relationship between sequence and fitness in a natural setting, including regions where synonymous mutations are under functional constraint, and for proteins with limited experimentally measured effects. We built interactive heatmaps of the estimated fitness effects to help readers explore these data (see https:\/\/matsen.group\/flu-mut-rates). Altogether, this work places influenza's mutation rates in a broader cross-viral context and deepens our understanding of how mutation and selection shape influenza evolution in nature at a site-specific level.","rel_num_authors":8,"rel_authors":[{"author_name":"Hugh K Haddox","author_inst":"Fred Hutch Cancer Center"},{"author_name":"Angie S Hinrichs","author_inst":"University of California at Santa Cruz"},{"author_name":"Chris Jennings-Shaffer","author_inst":"Fred Hutch Cancer Center"},{"author_name":"Karrington Johnson","author_inst":"Fred Hutch Cancer Center"},{"author_name":"Chelsea T Benton","author_inst":"Fred Hutch Cancer Center"},{"author_name":"Jared G Galloway","author_inst":"Fred Hutch Cancer Center"},{"author_name":"Jesse D Bloom","author_inst":"Fred Hutch Cancer Center"},{"author_name":"Frederick A Matsen IV","author_inst":"Fred Hutch Cancer Center"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Biocosm: A Simulation Environment for Designing Energy-Constrained Ethological Sensors","rel_doi":"10.64898\/2026.05.18.725991","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725991","rel_abs":"Long-duration ethological sensing increasingly depends on miniaturized, battery-constrained devices that must decide when to observe, transmit, store, compute, or sleep. These policy decisions shape not only device lifetime, but also which biological events are ultimately available for inference. Here we present \\biocosm, a digital twin framework for simulating the measurement process in energy-constrained ethological instrumentation. biocosm separates the latent biological world from the observation model, sensing policy, energy model, and analysis layer, allowing researchers to evaluate how alternative sensing strategies transform true behavioral interactions into observed data. Although motivated by wireless proximity logging, the framework is hardware-agnostic: beaconing, listening, sensing, storage, and computation are represented as parameterized state\/action costs rather than as fixed properties of one device architecture. This structure supports reproducible design-space exploration, policy comparison, and sensitivity analysis before field deployment. biocosm is grounded in prior work on animal proximity loggers, low-power wireless discovery and energy modeling, agent-based ethological simulation, and digital twin methods in medicine and neurotechnology. Framing measurement as a coupled world--observation--policy system makes instrumentation choices explicit and quantifiable.","rel_num_authors":1,"rel_authors":[{"author_name":"Matt Gaidica","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Informational blueprints reveal condition-dependent gene regulatory architectures","rel_doi":"10.64898\/2026.05.18.726006","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.726006","rel_abs":"While coding regions in the genome have a direct interpretation in terms of protein products, significant fractions are non-coding and yet control essential biological functions. Unlike the genetic code, there is no \"lookup table\" that identifies where regulatory proteins, known as transcription factors (TFs), bind. Here, we extract these binding sites by distilling sequences of nucleotide letters into collective coordinates (hyperletters) representing the binding sites that are active under specific environmental conditions. Going beyond local information footprints between individual bases and expression levels, our information blueprint algorithm compresses the global information by optimising filters that simultaneously scan an entire promoter sequence. Inspired by renormalisation-group techniques, we identify TF binding sites as coarse-grained variables combining groups of correlated mutations with the highest collective impact on gene expression. We validate our approach on experimental data for E. coli and discover novel regulatory elements illustrating its deployment at scale across growth conditions.","rel_num_authors":7,"rel_authors":[{"author_name":"Doruk Efe Gokmen","author_inst":"University of Chicago"},{"author_name":"Rosalind Wenshan Pan","author_inst":"California Institute of Technology"},{"author_name":"Tom Roeschinger","author_inst":"Caltech"},{"author_name":"Stephen Quake","author_inst":"Stanford University"},{"author_name":"Hernan Garcia","author_inst":"University of California Berkeley"},{"author_name":"Rob Phillips","author_inst":"Caltech"},{"author_name":"Vincenzo Vitelli","author_inst":"University of Chicago"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Informational blueprints reveal condition-dependent gene regulatory architectures","rel_doi":"10.64898\/2026.05.18.726006","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.726006","rel_abs":"While coding regions in the genome have a direct interpretation in terms of protein products, significant fractions are non-coding and yet control essential biological functions. Unlike the genetic code, there is no \"lookup table\" that identifies where regulatory proteins, known as transcription factors (TFs), bind. Here, we extract these binding sites by distilling sequences of nucleotide letters into collective coordinates (hyperletters) representing the binding sites that are active under specific environmental conditions. Going beyond local information footprints between individual bases and expression levels, our information blueprint algorithm compresses the global information by optimising filters that simultaneously scan an entire promoter sequence. Inspired by renormalisation-group techniques, we identify TF binding sites as coarse-grained variables combining groups of correlated mutations with the highest collective impact on gene expression. We validate our approach on experimental data for E. coli and discover novel regulatory elements illustrating its deployment at scale across growth conditions.","rel_num_authors":7,"rel_authors":[{"author_name":"Doruk Efe Gokmen","author_inst":"University of Chicago"},{"author_name":"Rosalind Wenshan Pan","author_inst":"California Institute of Technology"},{"author_name":"Tom Roeschinger","author_inst":"Caltech"},{"author_name":"Stephen Quake","author_inst":"Stanford University"},{"author_name":"Hernan Garcia","author_inst":"University of California Berkeley"},{"author_name":"Rob Phillips","author_inst":"Caltech"},{"author_name":"Vincenzo Vitelli","author_inst":"University of Chicago"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Informational blueprints reveal condition-dependent gene regulatory architectures","rel_doi":"10.64898\/2026.05.18.726006","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.726006","rel_abs":"While coding regions in the genome have a direct interpretation in terms of protein products, significant fractions are non-coding and yet control essential biological functions. Unlike the genetic code, there is no \"lookup table\" that identifies where regulatory proteins, known as transcription factors (TFs), bind. Here, we extract these binding sites by distilling sequences of nucleotide letters into collective coordinates (hyperletters) representing the binding sites that are active under specific environmental conditions. Going beyond local information footprints between individual bases and expression levels, our information blueprint algorithm compresses the global information by optimising filters that simultaneously scan an entire promoter sequence. Inspired by renormalisation-group techniques, we identify TF binding sites as coarse-grained variables combining groups of correlated mutations with the highest collective impact on gene expression. We validate our approach on experimental data for E. coli and discover novel regulatory elements illustrating its deployment at scale across growth conditions.","rel_num_authors":7,"rel_authors":[{"author_name":"Doruk Efe Gokmen","author_inst":"University of Chicago"},{"author_name":"Rosalind Wenshan Pan","author_inst":"California Institute of Technology"},{"author_name":"Tom Roeschinger","author_inst":"Caltech"},{"author_name":"Stephen Quake","author_inst":"Stanford University"},{"author_name":"Hernan Garcia","author_inst":"University of California Berkeley"},{"author_name":"Rob Phillips","author_inst":"Caltech"},{"author_name":"Vincenzo Vitelli","author_inst":"University of Chicago"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Niche constraints drive differences between mycorrhizal fungal guilds in future range shifts","rel_doi":"10.64898\/2026.05.18.725971","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725971","rel_abs":"Mycorrhizal fungi are a diverse and ubiquitous group of critical plant symbionts whose distribution strongly influences ecosystem function across the globe. Yet, until now, we do not have quantitative data on the range sizes of different mycorrhizal fungal taxa, limiting our capacity to forecast future shifts in community composition and function. Here, we use 121,079 DNA sequence-derived observations to map the distribution of 621 common mycorrhizal fungal taxa and forecast future changes to their range sizes. We demonstrate that climate and soil factors, particularly mean annual temperature and soil organic carbon, exert major control over mycorrhizal fungal distributions, and the ecological niches of mycorrhizal fungi consistently differ between arbuscular and ectomycorrhizal functional guilds. Arbuscular mycorrhizal fungal taxa generally occupy a wider niche breadth than ectomycorrhizal fungi, occurring across larger ranges of climate, soil, plant cover, topography, and disturbance conditions. Our models also predict widespread decreases in the range size of mycorrhizal fungal taxa under projected future global climates, with average ranges decreasing by 12.6% or ~7.5 million km2. This decrease in projected range size will be most pronounced for ectomycorrhizal fungi, strongly linked to constraints from their smaller overall niches. By generating a global atlas of common mycorrhizal fungi and their associated environmental niche, we establish a critical baseline for widely suspected declines in global fungal biodiversity.","rel_num_authors":20,"rel_authors":[{"author_name":"Joseph Edwards","author_inst":"Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville"},{"author_name":"Johan van den Hoogen","author_inst":"Institute of Integrative Biology, ETH Zurich"},{"author_name":"Thomas Lauber","author_inst":"Institute of Integrative Biology, ETH Zurich"},{"author_name":"Christine Hawkes","author_inst":"Department of Plant and Microbial Biology, North Carolina State University"},{"author_name":"Mark Anthony","author_inst":"Center for Microbiology and Environmental Systems Science, University of Vienna"},{"author_name":"Camille Delavaux","author_inst":"Department of Terrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW"},{"author_name":"Justin Stewart","author_inst":"Amsterdam Institute for Life and Environment (A-LIFE), Section Ecology & Evolution, Vrije Universiteit Amsterdam"},{"author_name":"Kathleen Treseder","author_inst":"Department of Ecology and Evolutionary Biology, University of California, Irvine"},{"author_name":"Xiao Feng","author_inst":"Department of Biology, University of North Carolina"},{"author_name":"Monica Papes","author_inst":"Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville"},{"author_name":"Robert Muscarella","author_inst":"Department of Ecology and Genetics, Uppsala Universitet"},{"author_name":"Petr Kohout","author_inst":"Institute of Microbiology of the Czech Academy of Sciences"},{"author_name":"Petr Baldrian","author_inst":"Institute of Microbiology of the Czech Academy of Sciences"},{"author_name":"Toby Kiers","author_inst":"Department of Ecological Sciences, Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam"},{"author_name":"Thomas Crowther","author_inst":"Institute of Integrative Biology, ETH Zurich"},{"author_name":"Colin Averill","author_inst":"Funga Public Benefit Corporation"},{"author_name":"Brandon Matheny","author_inst":"Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville"},{"author_name":"Michael van Nuland","author_inst":"Society for the Protection of Underground Networks (SPUN)"},{"author_name":"Clara Qin","author_inst":"Society for the Protection of Underground Networks (SPUN)"},{"author_name":"Stephanie Kivlin","author_inst":"Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Decoding heterogeneous aging clocks and disease risk stratification using a metabolomic foundation model","rel_doi":"10.64898\/2026.05.18.725977","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725977","rel_abs":"Metabolomic aging clocks estimate biological age by modeling metabolite concentrations, thereby capturing aging signals from healthspan and adverse outcomes. However, existing clocks generally assume homogeneous aging trajectories and yield only a single age acceleration metric, limiting their capacity to capture inter-individual metabolic heterogeneity and characterize nuanced individual-level representations. To address these limitations, we proposed MetFoundation, a metabolomic foundation model pre-trained on nuclear magnetic resonance (NMR) metabolomic profiles from over 430,000 participants in UK Biobank via self-supervised learning. This large-scale pre-training enables MetFoundation to learn a metabolomic representation space that captures the complex, nonlinear structure of systemic metabolism as reflected in NMR data. Building on MetFoundation, we developed a mortality-informed metabolomic aging clock by fine-tuning an attached survival module, deriving age acceleration that demonstrates significant associations with multiple age-related diseases and factors. More importantly, we utilized embeddings generated by MetFoundation to identify metabolic subtypes, resulting in 13 distinct subtypes with differential susceptibility profiles for major age-related diseases, particularly dementia and diabetes. This finding empirically demonstrated profound metabolic heterogeneity across populations, persisting even at comparable levels of age acceleration. To enhance clinical applicability, we further employed contrastive learning to distill a lightweight model that approximates the learned metabolomic representation space using only routine blood test measurements as inputs. Both hold-out testing within UK Biobank and the external validation in China Health and Retirement Longitudinal Study replicated similar disease onset patterns across the identified subtypes, underscoring the robust generalizability of MetFoundation and the translational potential of the discovered metabolic subtypes.","rel_num_authors":5,"rel_authors":[{"author_name":"Yu Xu","author_inst":"Department of Computer Science, Hong Kong Baptist University"},{"author_name":"Bohao Zou","author_inst":"Department of Computer Science, Hong Kong Baptist University"},{"author_name":"Guoxiang Xie","author_inst":"Human Metabolomics Institute, Inc."},{"author_name":"Wei Jia","author_inst":"Department of Pharmacology and Pharmacy, The University of Hong Kong"},{"author_name":"Lu Zhang","author_inst":"Department of Computer Science, Hong Kong Baptist University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Nucleolar Dynamics During Oogenesis","rel_doi":"10.64898\/2026.05.19.726235","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726235","rel_abs":"Ribosome biogenesis is a conserved and highly regulated process that starts in the nucleolus, a membrane-less multi-phase organelle. Although the architecture of the nucleolus is known to change due to perturbations, how nucleolar organization is modulated during physiological processes to meet changing translational demands remains unclear. Here, we use zebrafish oogenesis as a developmental context requiring a rapid expansion of translational capacity to investigate the regulation of nucleolar architecture. We show nucleoli undergo coordinated changes in number, size, subnuclear localization, and layering throughout oogenesis. We further demonstrate that nucleoli form around extrachromosomal DNA circles that contain the rDNA locus. Notably, mouse oocytes undergo similar developmental changes in nucleolar layering and phase organization, indicating that remodeling of nucleolar condensates is a conserved feature of oogenesis. These findings reveal previously unexplored regulation of nucleolar architecture as developmental adaptations to changing biosynthetic needs.","rel_num_authors":17,"rel_authors":[{"author_name":"Ruoyu Li","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Grace McKown","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Dai Tsuchiya","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Mark Mattingly","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Anna Galligos","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Michay Diez","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Jui Feng Lu","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Mary Cathleen McKinney","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Sean McKinney","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Boris Rubinstein","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Timothy J Corbin","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Melainia McClain","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Carrie Carmichael","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Victoria A Hassebroek","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Stephanie H Nowotarski","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Jennifer  L Gerton","author_inst":"Stowers Institute for Medical Research"},{"author_name":"Kamena Kostova","author_inst":"Stowers Institute for Medical Research"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Age-dependent PD-1 induction restricts IL-2-driven effector T cell responses during La Crosse virus infection in mice","rel_doi":"10.64898\/2026.05.18.725972","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725972","rel_abs":"Age is a major determinant of disease severity following La Crosse virus (LACV) infection, yet the immunological mechanisms underlying heightened susceptibility in children remains poorly defined. Here, we show that acute LACV infection in weanling mice induces T cell dysfunction characterized by early PD-1 upregulation and impaired effector differentiation despite evidence of activation. This state is associated with reduced IL-2-dependent STAT5 signaling, indicating a failure to respond to available cytokine cues. Although regulatory T cells expand and exhibit elevated CD25 expression, their depletion increases IL-2 levels without restoring antiviral T cell responses or viral control. In contrast, PD-1 blockade partially restores T cell activation, and combined PD-1 blockade with CD25 targeting enables robust effector differentiation and improved viral control. These findings demonstrate that checkpoint signaling limits T cell responsiveness to IL-2, uncoupling activation from differentiation and driving age-dependent susceptibility to LACV infection.","rel_num_authors":3,"rel_authors":[{"author_name":"Reem Alatrash","author_inst":"Rutgers Biomedical and Health Sciences"},{"author_name":"Sanjana Iyer","author_inst":"Rutgers Biomedical and Health Sciences"},{"author_name":"Bobby Brooke Herrera","author_inst":"Rutgers Biomedical and Health Sciences"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"A Liver-Targeted Copper Supplement Reduces Metabolic Dysfunction-Associated Liver Steatosis by Increasing Lipolysis and Fatty Acid Oxidation","rel_doi":"10.64898\/2026.05.18.725917","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725917","rel_abs":"Abstract: Metabolic-associated steatotic liver disease (MASLD) is a prevalent liver disease driven by complex dysregulation of hepatic lipid metabolism. Here we show that copper deficiency is a nutrient vulnerability in steatotic liver disease and that selective liver-targeted copper supplementation can reduce excess lipid accumulation. Analysis of steatotic patient and mouse tissues identify widespread alterations in hepatic copper homeostasis markers. Integrated multi-omics analyses reveal that copper induces lipolysis of PLIN2-containing lipid droplets while lipid importer CD36 is downregulated. We show that copper inhibits cAMP hydrolase activity of PDE3B, thus activating PKA-mediated HSL and AMPK activation upstream of lipolysis. Fatty acids liberated through lipolysis are subsequently degraded via enhanced mitochondrial fatty acid oxidation, supported by energetic rewiring toward oxidative phosphorylation (OXPHOS) with increased copper-dependent complex IV and SOD1 activity. Our findings establish a multi-pronged mechanism by which hepatic copper supplementation coordinately regulates lipid metabolism in response to steatosis and unveils a therapeutic metallomedicine strategy to rewire lipid regulation.","rel_num_authors":14,"rel_authors":[{"author_name":"Jaehee Kim","author_inst":"Princeton University"},{"author_name":"Vanha N. Pham","author_inst":"Princeton University"},{"author_name":"Timothy A. Su","author_inst":"University of California, Riverside"},{"author_name":"Irene Liparulo","author_inst":"University of California, Berkeley"},{"author_name":"Diyala S. Shihadih","author_inst":"University of California, Berkeley"},{"author_name":"Tong Xiao","author_inst":"Princeton University"},{"author_name":"Xiao Xie","author_inst":"Princeton University"},{"author_name":"Yuichi Aki","author_inst":"Princeton University"},{"author_name":"Aidan T. Pezacki","author_inst":"Princeton University"},{"author_name":"Wendy Cao","author_inst":"University of California, Berkeley"},{"author_name":"James A. Olzmann","author_inst":"University of California, Berkeley"},{"author_name":"Joshua D. Rabinowitz","author_inst":"Princeton University"},{"author_name":"Andreas Stahl","author_inst":"University of California, Berkeley"},{"author_name":"Christopher J. Chang","author_inst":"Princeton University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"The CK2 and DBT kinases promote temperature compensation of the Drosophila circadian clock via distinct pathways","rel_doi":"10.64898\/2026.05.18.725963","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725963","rel_abs":"Circadian (~24 h) rhythms are essential for the survival of most organisms, as they optimize physiology and behavior with the time of day. They are defined by three fundamental properties: they are driven by a self-sustained molecular oscillator, entrained by environmental cues such as light and temperature, and temperature-compensated, whereby circadian period remains close to 24 h over a physiological range of temperatures. The molecular basis of temperature compensation remains incompletely understood. Here, we build on previous studies supporting a conserved and important role for phosphorylation-dependent mechanisms in the control of temperature compensation. We found that reducing the activity of two highly conserved circadian kinases, DBT (casein kinase [CK] 1) and CK2, disrupts temperature compensation in Drosophila. Genetic analyses indicate that DBT and CK2 act through distinct pathways that have additive effects on temperature compensation. DBT acts through the perShort phosphorylation cluster and the S47 phosphodegron of the core clock protein PER, both of which are required for normal thermal compensation. In contrast, CK2 acts through a phosphocluster in TIM as well as PER S45 residue. Interestingly, simultaneous disruption of both pathways causes accumulation of hyperphosphorylated PER, which is inefficiently cleared from the nucleus of circadian pacemaker neurons. Combined with previous work, our findings support a central and unifying role for nuclear PER phosphorylation dynamics in buffering circadian period against environmental temperature fluctuations.","rel_num_authors":3,"rel_authors":[{"author_name":"Yongliang Xia","author_inst":"Umass Chan Medical School"},{"author_name":"Victoria Louis","author_inst":"UMass Chan Medical School"},{"author_name":"Patrick Emery","author_inst":"University of Massachusetts Medical School"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Loss of ASIC1A-dependent inhibitory neuron activity in basolateral amygdala is associated with increased CO2-evoked jumping","rel_doi":"10.64898\/2026.05.18.725939","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725939","rel_abs":"Abstract Background: Responding appropriately to threats is critical for survival. Dysregulated defensive responses are core features of psychiatric illnesses including panic disorder and post-traumatic stress disorder. Carbon dioxide (CO2) inhalation evokes defensive behaviors in both humans and mice. Here we investigated the role of acid-sensing ion channels (ASICs) in CO2-evoked jumping in mice. Methods: Defensive behaviors (jumping and freezing) were assessed in response to CO2 inhalation and basolateral amygdala (BLA) acidification. We tested the role of ASICs using global knockout mice and Asic1aloxP\/loxP mice transduced with AAV-CMV-Cre or AAV-CaMKII-Cre in the BLA. Effects of CO2 on single neuron firing and local field potentials were studied via BLA microwire arrays. Results: ASIC1A disruption increased CO2-evoked jumping while reducing freezing, paralleled by increased BLA c-Fos induction. Acidification of the BLA recapitulated these effects. Virus-mediated ASIC1A disruption in BLA did not resolve the locus of ASIC1A action in jumping. CO2 inhalation suppressed firing in most BLA neurons, though a small number increased firing. ASIC1A disruption enhanced CO2-induced suppression of narrow waveform neurons (putative interneurons), and facilitated excitation of wide waveform neurons (putative principal neurons). Additionally, CO2 produced concentration-dependent broadband power suppression with selective theta enhancement, effects that were augmented by ASIC1A disruption. Conclusions: Together, these findings suggest that ASIC1A promotes interneuron activity during acidosis and that its loss may reduce inhibition of principal neuron output, shifting defensive responses from freezing toward jumping. These results advance our understanding of how brain pH and ASICs regulate defensive behavior, with potential implications for understanding dysregulated defensive responses.","rel_num_authors":16,"rel_authors":[{"author_name":"Rebecca J Taugher-Hebl","author_inst":"University of Iowa"},{"author_name":"Aubrey C Chan","author_inst":"University of Iowa"},{"author_name":"Collin J Kreple","author_inst":"University of Wisconsin"},{"author_name":"Ali Ghobbeh","author_inst":"University of Iowa"},{"author_name":"Grace Z Wang","author_inst":"University of Iowa"},{"author_name":"Gail IS Harmata","author_inst":"University of Iowa"},{"author_name":"Mackenzie M Conlon","author_inst":"University of Iowa"},{"author_name":"Subhash C Gupta","author_inst":"University of Iowa"},{"author_name":"Rong Fan","author_inst":"University of Iowa"},{"author_name":"Ramkumar Kuruba","author_inst":"University of Iowa"},{"author_name":"Margaret P Price","author_inst":"University of Iowa"},{"author_name":"Jeffrey Long","author_inst":"University of Iowa"},{"author_name":"Young-cho Kim","author_inst":"University of Iowa"},{"author_name":"Brian James Dlouhy","author_inst":"University of Iowa"},{"author_name":"Nandakumar Narayanan","author_inst":"University of Iowa"},{"author_name":"John A Wemmie","author_inst":"University of Iowa"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Occupationally Relevant Wildfire Smoke Inhalation Impairs Nitric Oxide Signaling and Promotes Progressive Aortic Stiffening in Hypercholesterolemic Mice","rel_doi":"10.64898\/2026.05.18.725908","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725908","rel_abs":"Background. Wildland firefighters experience repeated occupational exposure to wildfire smoke at high particulate matter (PM) concentrations, leading to elevated cardiovascular disease risk and hypertension prevalence. However, the pathophysiological processes linking cumulative smoke inhalation to vascular damage and blood pressure elevation remain poorly characterized. To evaluate these effects under controlled exposure conditions, we used a preclinical exposure model calibrated to match the cumulative PM burden deposited in wildland firefighter airways over 7-14 years of service. Male apolipoprotein E knockout (Apoe-\/-) mice underwent whole-body inhalation of Douglas fir smoke or filtered air for 2 hours\/day, 5 days\/week, for 8 or 16 weeks at target PM concentrations of 40 mg\/m3. Results. Prolonged smoke exposure induced sustained elevation of circulating tumor necrosis factor-alpha (TNF-), interleukin-1 beta (IL-1{beta}), and interleukin-6 (IL-6), coupled with diffused nuclear factor kappa B (NF-{kappa}B) activation throughout the aortic wall. Smoke inhalation disrupted endothelial adherens junctions, upregulated intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), and promoted monocyte recruitment to aortic tissues, concurrent with enhanced monocyte chemoattractant protein-1 (MCP-1) expression. Oxidative stress was evidenced by increased nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunit 2 (NOX2) expression, elevated superoxide levels, and endothelial nitric oxide synthase (eNOS) uncoupling in the aorta, leading to lipid peroxidation and accompanied by intimal apoptosis. These inflammatory and oxidative perturbations occurred alongside a pro-fibrotic phenotypic shift characterized by transforming growth factor beta 1 (TGF-{beta}1) upregulation, myofibroblast differentiation, and progressive collagen accumulation in medial and adventitial compartments of the aortic wall. Functionally, smoke exposure progressively impaired aortic cyclic distensibility through combined wall thickening and circumferential tissue stiffening, while severely attenuating endothelium-dependent and nitric oxide (NO)-mediated vasodilation. These functional and structural shifts culminated in elevated systolic and diastolic blood pressures. While endothelial dysfunction reached maximal impairment by 8 weeks, aortic stiffening continued to worsen through 16 weeks of exposure, demonstrating differential temporal progression of vascular damage. Conclusions. These findings demonstrate that occupationally relevant wildfire smoke exposure produces convergent inflammatory, oxidative, and profibrotic vascular remodeling with progressive loss of arterial compliance and impaired endothelium-dependent vasodilation, underscoring potential vascular targets for cardiovascular health surveillance and risk mitigation in wildland firefighters.","rel_num_authors":10,"rel_authors":[{"author_name":"Jacqueline Matz","author_inst":"Northeastern University"},{"author_name":"Victoria A Williams","author_inst":"Northeastern University"},{"author_name":"Matthew J Eden","author_inst":"Northeastern University"},{"author_name":"Hannah Wilker","author_inst":"Northeastern University"},{"author_name":"Simone Sabnis","author_inst":"Northeastern University"},{"author_name":"Ye Chen","author_inst":"Tufts Medical Center"},{"author_name":"Paola Sebastiani","author_inst":"Tufts Medical Center"},{"author_name":"Michael J Gollner","author_inst":"University of California, Berkeley"},{"author_name":"Jessica Oakes","author_inst":"Northeastern University"},{"author_name":"Chiara Bellini","author_inst":"Northeastern University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Occupationally Relevant Wildfire Smoke Inhalation Impairs Nitric Oxide Signaling and Promotes Progressive Aortic Stiffening in Hypercholesterolemic Mice","rel_doi":"10.64898\/2026.05.18.725908","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725908","rel_abs":"Background. Wildland firefighters experience repeated occupational exposure to wildfire smoke at high particulate matter (PM) concentrations, leading to elevated cardiovascular disease risk and hypertension prevalence. However, the pathophysiological processes linking cumulative smoke inhalation to vascular damage and blood pressure elevation remain poorly characterized. To evaluate these effects under controlled exposure conditions, we used a preclinical exposure model calibrated to match the cumulative PM burden deposited in wildland firefighter airways over 7-14 years of service. Male apolipoprotein E knockout (Apoe-\/-) mice underwent whole-body inhalation of Douglas fir smoke or filtered air for 2 hours\/day, 5 days\/week, for 8 or 16 weeks at target PM concentrations of 40 mg\/m3. Results. Prolonged smoke exposure induced sustained elevation of circulating tumor necrosis factor-alpha (TNF-), interleukin-1 beta (IL-1{beta}), and interleukin-6 (IL-6), coupled with diffused nuclear factor kappa B (NF-{kappa}B) activation throughout the aortic wall. Smoke inhalation disrupted endothelial adherens junctions, upregulated intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), and promoted monocyte recruitment to aortic tissues, concurrent with enhanced monocyte chemoattractant protein-1 (MCP-1) expression. Oxidative stress was evidenced by increased nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunit 2 (NOX2) expression, elevated superoxide levels, and endothelial nitric oxide synthase (eNOS) uncoupling in the aorta, leading to lipid peroxidation and accompanied by intimal apoptosis. These inflammatory and oxidative perturbations occurred alongside a pro-fibrotic phenotypic shift characterized by transforming growth factor beta 1 (TGF-{beta}1) upregulation, myofibroblast differentiation, and progressive collagen accumulation in medial and adventitial compartments of the aortic wall. Functionally, smoke exposure progressively impaired aortic cyclic distensibility through combined wall thickening and circumferential tissue stiffening, while severely attenuating endothelium-dependent and nitric oxide (NO)-mediated vasodilation. These functional and structural shifts culminated in elevated systolic and diastolic blood pressures. While endothelial dysfunction reached maximal impairment by 8 weeks, aortic stiffening continued to worsen through 16 weeks of exposure, demonstrating differential temporal progression of vascular damage. Conclusions. These findings demonstrate that occupationally relevant wildfire smoke exposure produces convergent inflammatory, oxidative, and profibrotic vascular remodeling with progressive loss of arterial compliance and impaired endothelium-dependent vasodilation, underscoring potential vascular targets for cardiovascular health surveillance and risk mitigation in wildland firefighters.","rel_num_authors":10,"rel_authors":[{"author_name":"Jacqueline Matz","author_inst":"Northeastern University"},{"author_name":"Victoria A Williams","author_inst":"Northeastern University"},{"author_name":"Matthew J Eden","author_inst":"Northeastern University"},{"author_name":"Hannah Wilker","author_inst":"Northeastern University"},{"author_name":"Simone Sabnis","author_inst":"Northeastern University"},{"author_name":"Ye Chen","author_inst":"Tufts Medical Center"},{"author_name":"Paola Sebastiani","author_inst":"Tufts Medical Center"},{"author_name":"Michael J Gollner","author_inst":"University of California, Berkeley"},{"author_name":"Jessica Oakes","author_inst":"Northeastern University"},{"author_name":"Chiara Bellini","author_inst":"Northeastern University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Prediction of Transcription Factor DNA Binding Affinity with High-Throughput Kd Measurements and Deep Learning","rel_doi":"10.64898\/2026.05.18.725930","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725930","rel_abs":"Transcription factors (TFs) regulate gene expression through specific interactions with genomic DNA. While TF binding motifs from public databases describe sequence preferences, quantifying genome-wide affinity (Kd) is highly desirable for a more accurate thermodynamic description. Here, we report ivtFOODIE (in vitro FOOtprinting with DeamInasE), an assay that leverages deaminase-mediated cytosine-to-uracil conversion to measure Kd values for a given TF across accessible genomic regions from human cells. By pre-training on TF binding sites from JASPAR and fine-tuning with our ivtFOODIE data from 46 TFs representing 13 different DNA-binding domains (DBDs), we developed Seq2Kd, a deep learning model capable of predicting a TF's absolute binding affinity on DNA sequences. Seq2Kd enables de novo motif discovery of ~500 previously uncharacterized human TFs and reveals the effects of genetic variation both in TF-coding regions and DNA-binding sites on gene expression and disease susceptibility. By correlating predicted affinity changes with the sign and magnitude of expression quantitative trait locus (eQTL) effects, we stratified TFs into activator-like and repressor-like groups. Compared to clinically benign variants, pathogenic single-nucleotide variants (SNVs) within regulatory and protein-coding regions show significantly larger predicted shifts in Kd. We provide an interactive web portal, the ENcyclopedia of Transcription-factor Interactions with Regulatory Elements (ENTIRE), which integrates the Seq2Kd model with the ivtFOODIE dataset. This resource offers thermodynamic prediction for TF-DNA interactions for functional genomics and human disease.","rel_num_authors":22,"rel_authors":[{"author_name":"Zhi Wang","author_inst":"Changping Laboratory, Beijing, P. R. China; Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, P. R. China ."},{"author_name":"Di Wang","author_inst":"Changping Laboratory, Beijing, P. R. China; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, P. R. China"},{"author_name":"Ke Shen","author_inst":"Changping Laboratory, Beijing, P. R. China; Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, P. R. China"},{"author_name":"Junchen Luo","author_inst":"Changping Laboratory, Beijing, P. R. China; College of Future Technology, Peking University, Beijing, P. R. China"},{"author_name":"Xinyao Wang","author_inst":"Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, P. R. China"},{"author_name":"Nan Wu","author_inst":"Department of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China ."},{"author_name":"Yunzhi Lang","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Xiangyu Wang","author_inst":"College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China"},{"author_name":"Jun Ren","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Wenyang Dong","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Lu Pan","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Gang Li","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Dubai Li","author_inst":"Changping Laboratory, Beijing, P. R. China;"},{"author_name":"Chen Xie","author_inst":"Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, P. R. China"},{"author_name":"Zhen Zhang","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Yitong Lyu","author_inst":"hong kong"},{"author_name":"Shijun Yu","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Liuying Shan","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Nannan Zhang","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Jian Yan","author_inst":"Hong Kong"},{"author_name":"Mingchen Chen","author_inst":"Changping Laboratory, Beijing, P. R. China"},{"author_name":"Xiaoliang Sunney Xie","author_inst":"Changping Laboratory, Beijing, P. R. China"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Deciphering interaction syntax via decoupling intrinsic lineages and niche pressure","rel_doi":"10.64898\/2026.05.18.725889","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725889","rel_abs":"Spatial transcriptomics enables the mapping of gene expression within intact tissues, yet a fundamental gap remains between knowing where cells are and understanding how they interact. A cell's measured transcriptome reflects both its intrinsic lineage identity and niche pressure. Here we introduce TRINUS, a self-supervised model that deciphers interaction syntax by generative decoupling of a cell's intrinsic lineage identity from the extrinsic niche pressure. TRINUS maintains a library of context-free cell prototypes to isolate lineage identity while modeling cooperative interaction dependencies among neighbors. We validated TRINUS on synthetic datasets with known interaction logic and benchmarked it against existing methods with superior performance in cell clustering and spatial domain detection. Applied across diverse platforms and biological systems, TRINUS resolves multi-level interaction syntax and maps tissue-wide interaction patterns in colorectal cancer, and identifies stage-specific signaling dependencies and time-dependent receptor windows during mouse organogenesis. We also show TRINUS's bidirectional in silico engineering capability in the ovarian tumor microenvironment, where forward perturbation revealed subtype-specific macrophage immunosuppressive programs via virtual transplantation and inverse design identified molecular modifications in macrophages predicted to rescue adjacent T-cell function. Collectively, TRINUS provides a practical tool for interaction syntax discovery and predictive tissue engineering on spatial transcriptomics data.","rel_num_authors":6,"rel_authors":[{"author_name":"Qirui Guo","author_inst":"Peking University"},{"author_name":"Wenhao Zhong","author_inst":"Peking University"},{"author_name":"Zhiwei Zeng","author_inst":"Peking University"},{"author_name":"Qing Nie","author_inst":"University of California Irvine"},{"author_name":"Peijie Zhou","author_inst":"Peking University"},{"author_name":"Lei Zhang","author_inst":"Peking University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"BMP signaling during gastrulation pre-patterns the dorsal spinal cord","rel_doi":"10.64898\/2026.05.18.726076","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.726076","rel_abs":"The classic model of dorsal spinal cord patterning proposes that roofplate-derived BMP patterns dorsal interneuron subtypes in a concentration-dependent manner. However, genetic perturbations of BMP pathway components produce variable effects, challenging this model. Here we implemented single-cell profiling, fate mapping, and mosaic perturbations to determine when BMP signaling patterns dorsal neural fates in vivo. Contrary to the classic model, we demonstrate that dorsal fates are patterned by BMP signaling during gastrulation. Following neural tube formation, BMP signaling continues but plays limited roles in domain specification and maturation. Fate mapping revealed that dorsal progenitors originate from the ventral gastrula, adopting BMP-dependent transcriptional states that prime dorsal neural fate. We propose that dorsal neural fates are initially patterned by gastrulation-stage sources of BMP, prior to roofplate induction.","rel_num_authors":2,"rel_authors":[{"author_name":"Hannah Greenfeld","author_inst":"UCSF"},{"author_name":"Daniel E Wagner","author_inst":"UCSF"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Domain-adversarial learning predicts clinically actionable drug combination synergy in leukemia patients using bulk transcriptomics data","rel_doi":"10.64898\/2026.05.18.725869","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725869","rel_abs":"Deep learning has gained popularity in drug combination synergy prediction; however, DL models require large training datasets from cell line pharmacogenomic screens that poorly capture the heterogeneity in transcriptomic features and phenotypic responses seen in patients. To that end, we developed a domain-adversarial neural network (DANN) for personalized drug synergy prediction that accounts for systematic differences between cell line and patient domains. In applications to AML and CLL patient samples, we demonstrate how DANN boosts prediction accuracy under realistic data constraints. The model predictions demonstrated elevated synergy among clinically used combinations, such as venetoclax-based regimens, supporting its ability to identify both pharmaceutically and clinically meaningful combinations. DANN estimates prediction uncertainty and prioritizes high-confidence combination predictions to aid clinical translation. Together, DANN provides a systematic approach to improving accuracy and reliability in cross-domain drug synergy prediction, advancing the development of methods that are aligned with the translational requirements of precision hematology.","rel_num_authors":11,"rel_authors":[{"author_name":"Jie Zhu","author_inst":"University of Helsinki"},{"author_name":"Weikaixin Kong","author_inst":"University of Helsinki"},{"author_name":"Thi Huong Lan Do","author_inst":"University Hospital Zurich and University of Zurich"},{"author_name":"Sandra Kummer","author_inst":"University Hospital Zurich and University of Zurich"},{"author_name":"Jarno Kivioja","author_inst":"University Hospital Zurich and University of Zurich"},{"author_name":"Rafael Romero-Becerra","author_inst":"University of Oslo"},{"author_name":"Juho Rousu","author_inst":"Aalto University"},{"author_name":"Mitro Miihkinen","author_inst":"University of Helsinki: Helsingin Yliopisto"},{"author_name":"Jeffrey Tyner","author_inst":"Oregon Health & Science University"},{"author_name":"Thorsten Zenz","author_inst":"University Hospital Zurich and University of Zurich"},{"author_name":"Tero Aittokallio","author_inst":"University of Helsinki"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"In situ molecular architecture of the mammalian sperm nuclear vacuole","rel_doi":"10.64898\/2026.05.18.725999","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725999","rel_abs":"Direct identification of macromolecular complexes in their native context remains a major barrier to unbiased biological discovery. This challenge is particularly acute in mammalian sperm nuclei, in which condensed chromatin is interspersed with poorly understood phase-separated compartments termed nuclear vacuoles. Vacuoles are associated with reduced fertilization efficiency, yet their composition remains unclear. Here we combine high-resolution in situ cryo-electron tomography (cryo-ET) with AlphaFold docking to identify vacuole components as proteasomes, the proteasome activator PA200, and ferritin. In situ structures at resolutions up to 3.8 [A] reveal distinct proteasome-PA200 associations and gating states, consistent with a stepwise activation mechanism. Ferritin assemblies exhibit heterogeneous mineralization states and directly contact chromatin. Together, these findings establish the molecular organization of sperm nuclear vacuoles and implicate protein turnover and metal homeostasis in shaping the nuclear landscape, while demonstrating the power of in situ cryo-ET to resolve protein identity and conformational dynamics in native cellular environments.","rel_num_authors":10,"rel_authors":[{"author_name":"Julian R. Braxton","author_inst":"California Institute of Technology"},{"author_name":"Songrong Qu","author_inst":"California Institute of Technology"},{"author_name":"Will M. Skinner","author_inst":"University of California Berkeley"},{"author_name":"Momoko Shiozaki","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Nikki Jean","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Rui Yan","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Xiaowei Zhao","author_inst":"Janelia Research Campus"},{"author_name":"Zhiheng Yu","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Polina V. Lishko","author_inst":"University of California Berkeley"},{"author_name":"Zhen Chen","author_inst":"California Institute of Technology"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"In situ molecular architecture of the mammalian sperm nuclear vacuole","rel_doi":"10.64898\/2026.05.18.725999","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725999","rel_abs":"Direct identification of macromolecular complexes in their native context remains a major barrier to unbiased biological discovery. This challenge is particularly acute in mammalian sperm nuclei, in which condensed chromatin is interspersed with poorly understood phase-separated compartments termed nuclear vacuoles. Vacuoles are associated with reduced fertilization efficiency, yet their composition remains unclear. Here we combine high-resolution in situ cryo-electron tomography (cryo-ET) with AlphaFold docking to identify vacuole components as proteasomes, the proteasome activator PA200, and ferritin. In situ structures at resolutions up to 3.8 [A] reveal distinct proteasome-PA200 associations and gating states, consistent with a stepwise activation mechanism. Ferritin assemblies exhibit heterogeneous mineralization states and directly contact chromatin. Together, these findings establish the molecular organization of sperm nuclear vacuoles and implicate protein turnover and metal homeostasis in shaping the nuclear landscape, while demonstrating the power of in situ cryo-ET to resolve protein identity and conformational dynamics in native cellular environments.","rel_num_authors":10,"rel_authors":[{"author_name":"Julian R. Braxton","author_inst":"California Institute of Technology"},{"author_name":"Songrong Qu","author_inst":"California Institute of Technology"},{"author_name":"Will M. Skinner","author_inst":"University of California Berkeley"},{"author_name":"Momoko Shiozaki","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Nikki Jean","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Rui Yan","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Xiaowei Zhao","author_inst":"Janelia Research Campus"},{"author_name":"Zhiheng Yu","author_inst":"Janelia Research Campus, Howard Hughes Medical Institute"},{"author_name":"Polina V. Lishko","author_inst":"University of California Berkeley"},{"author_name":"Zhen Chen","author_inst":"California Institute of Technology"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Conserved structural features of the lncRNA HOTAIR in breast cancer cells","rel_doi":"10.64898\/2026.05.18.725451","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725451","rel_abs":"Long noncoding RNAs (lncRNAs) regulate diverse cellular processes and are frequently implicated in disease, but their functional mechanisms often remain elusive. One such lncRNA, HOTAIR (Hox transcript antisense intergenic RNA), is a ~2.1 kb mammalian transcript whose overexpression promotes invasion and metastasis in breast cancer. However, the mechanisms by which HOTAIR influences gene regulation in cancer are poorly understood. To approach this problem through a structural lens, we determined the full-length in cellulo secondary structure of HOTAIR using chemical probing in a metastatic breast cancer cell line. The resulting structure shows that HOTAIR adopts a multidomain architecture and has local structural features unique to the cellular context. Comparison between in vitro and in cellulo chemical probing identifies regions of differential accessibility that may indicate context-dependent molecular interactions or folding. Conservation analyses further reveal that HOTAIR is conserved across primates with evidence of structural covariation in specific domains. Together, these results provide a roadmap for future mechanistic studies of structure-function relationships in HOTAIR and its contribution to gene regulation in cancer.","rel_num_authors":4,"rel_authors":[{"author_name":"Zion R Perry","author_inst":"Yale University"},{"author_name":"Anish Beeram","author_inst":"Yale University"},{"author_name":"Logan Lee","author_inst":"Yale University"},{"author_name":"Anna Marie Pyle","author_inst":"Yale University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Quantifying uncertainty in drift diffusion models of decision making under temporal dependence and parameter variability","rel_doi":"10.64898\/2026.05.17.722295","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.722295","rel_abs":"Decision-making behavior changes over time, exhibiting temporal correlation and nonstationarity. Existing drift diffusion model (DDM) fitting methods either do not provide uncertainty quantification for parameter estimates, or rely on restrictive assumptions that decisions are independent and that parameters remain constant over time, potentially underestimating uncertainty. To address these limitations, we propose a computationally efficient method for estimating analytic uncertainties in DDM parameters that are robust to temporal dependence and unmodeled parameter variability, while explicitly modeling nonstationary variability through covariates. We apply this method to rat decision-making in a two-alternative forced-choice (2AFC) visual task, revealing dynamic decision-making states across multiple timescales. A Python implementation of the method is provided.","rel_num_authors":3,"rel_authors":[{"author_name":"Gabriel Riegner","author_inst":"University of California, San Diego"},{"author_name":"Armin Schwartzman","author_inst":"University of California, San Diego"},{"author_name":"Pamela Reinagel","author_inst":"University of California, San Diego"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"A closer look at plankton: potential interactions inferred from centimeter-scale in situ observations","rel_doi":"10.64898\/2026.05.18.725820","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725820","rel_abs":"Plankton are essential to marine ecosystems, supporting food webs and mediating biogeochemical processes such as carbon export to depth. Their spatial distribution influences ecosystem dynamics and serves as an indicator of environmental change. Although drifting plankton could be expected to exhibit random distribution, numerous studies have revealed significant heterogeneity in their spatial patterns. However, very few studies targeted plankton distribution at the centimeter scale in situ, despite its importance for understanding biological processes. We argue that centimeter-scale distances in plankton could reveal potential ecological interactions. Using an extensive in situ dataset of 18 million planktonic organisms collected by the In Situ Ichthyoplankton Imaging System (ISIIS), which images multiple organisms simultaneously and preserves their positions in the water column, we analyzed centimeter-scale distances in plankton. By comparing observed distances with those expected under a random distribution, we assessed potential interactions at three levels: among all organisms, within plankton groups and across groups. Our results show that planktonic organisms exhibit non-random distributions at the centimeter scale, with smaller distances than expected, suggesting potential ecological interactions. Notably, distances up to 11 cm were the most informative, which is much larger than typical interaction distances in plankton. Additionally, observed distances were compatible with a simple attraction model. Finally, we propose the non-randomness of distances as a novel metric of interaction strength in plankton ecological networks and compare it against classical empirical or co-occurrence networks. These results offer new insights into in situ interactions and how they shape plankton distribution at centimeter scale.","rel_num_authors":4,"rel_authors":[{"author_name":"Thelma Panaiotis","author_inst":"National Oceanography Centre"},{"author_name":"Jean-Olivier Irisson","author_inst":"Laboratoire d'Oceanographie de Villefranche, Sorbonne Universite, 06230 Villefranche-sur-Mer, France"},{"author_name":"Mara Freilich","author_inst":"Brown University"},{"author_name":"B.B. Cael","author_inst":"Department of the Geophysical Sciences, University of Chicago, 60637 Chicago, IL, USA"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"A closer look at plankton: potential interactions inferred from centimeter-scale in situ observations","rel_doi":"10.64898\/2026.05.18.725820","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725820","rel_abs":"Plankton are essential to marine ecosystems, supporting food webs and mediating biogeochemical processes such as carbon export to depth. Their spatial distribution influences ecosystem dynamics and serves as an indicator of environmental change. Although drifting plankton could be expected to exhibit random distribution, numerous studies have revealed significant heterogeneity in their spatial patterns. However, very few studies targeted plankton distribution at the centimeter scale in situ, despite its importance for understanding biological processes. We argue that centimeter-scale distances in plankton could reveal potential ecological interactions. Using an extensive in situ dataset of 18 million planktonic organisms collected by the In Situ Ichthyoplankton Imaging System (ISIIS), which images multiple organisms simultaneously and preserves their positions in the water column, we analyzed centimeter-scale distances in plankton. By comparing observed distances with those expected under a random distribution, we assessed potential interactions at three levels: among all organisms, within plankton groups and across groups. Our results show that planktonic organisms exhibit non-random distributions at the centimeter scale, with smaller distances than expected, suggesting potential ecological interactions. Notably, distances up to 11 cm were the most informative, which is much larger than typical interaction distances in plankton. Additionally, observed distances were compatible with a simple attraction model. Finally, we propose the non-randomness of distances as a novel metric of interaction strength in plankton ecological networks and compare it against classical empirical or co-occurrence networks. These results offer new insights into in situ interactions and how they shape plankton distribution at centimeter scale.","rel_num_authors":4,"rel_authors":[{"author_name":"Thelma Panaiotis","author_inst":"National Oceanography Centre"},{"author_name":"Jean-Olivier Irisson","author_inst":"Laboratoire d'Oceanographie de Villefranche, Sorbonne Universite, 06230 Villefranche-sur-Mer, France"},{"author_name":"Mara Freilich","author_inst":"Brown University"},{"author_name":"B.B. Cael","author_inst":"Department of the Geophysical Sciences, University of Chicago, 60637 Chicago, IL, USA"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Benchmarking Static Gene Regulatory Network Reconstruction and Dynamic Transition Probing in Single-Cell Foundation Models.","rel_doi":"10.64898\/2026.05.17.725083","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725083","rel_abs":"Single-cell foundation models may encode gene regulatory information, but it remains unclear which model components capture this signal and how it compares with conventional inference methods. Here, we introduce a unified benchmark that evaluates gene regulatory network (GRN) reconstruction from six single-cell foundation models and three classical baselines across six datasets and four reference network types. We disentangle three sources of regulatory signal within each model--pretrained token embeddings, final-layer hidden states, and attention-derived scores. Under a strict zero-shot setting, scGPT token-embedding similarity outperforms classical baselines on STRING and ChIP-seq references, recovers core transcription factors, and best preserves reference network topology. Moreover, static GRNs cannot test whether learned gene-gene relationships are predictive of expression dynamics, we therefore introduce dynamic transition probing, which iteratively applies a model's reconstruction head to drive early-cell profiles toward late-cell states without temporal supervision. We find pretrained models capture meaningful developmental transitions, with scFoundation showing the strongest overall performance. Together, our results show that single-cell foundation models encode transferable regulatory and dynamical priors, but how well these priors can be recovered depends on model architecture, pretraining design, and extraction strategy.","rel_num_authors":5,"rel_authors":[{"author_name":"zhongni Ye","author_inst":"University of Electronic Science and Technology of China"},{"author_name":"Ning Yang","author_inst":"Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies"},{"author_name":"Xiaojing Yang","author_inst":"Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies"},{"author_name":"Xiaowei Mao","author_inst":"University of Electronic Science and Technology of China"},{"author_name":"Chao Tang","author_inst":"Peking University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Force-Gated Thrombosis (FGT): A Non-Equilibrium Mechanical Theory of Shear-Induced Blood Clot Initiation","rel_doi":"10.64898\/2026.05.17.725779","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725779","rel_abs":"Arterial thrombosis is initiated when mechanical forces in flowing blood exceed the activation thresholds of platelets and von Willebrand factor (vWF). Despite extensive experimental characterization of shear-induced platelet aggregation, a unified theoretical framework that maps hemodynamic forcing onto clot nucleation is lacking. Here we present Force-Gated Thrombosis (FGT), a non-equilibrium mechanical theory that treats thrombus formation as a continuous phase transition driven by an effective mechanical forcing Sigma = sigma + alpha |grad sigma| + beta epsilon, which combines local wall shear stress sigma, shear gradient |grad sigma|, and extensional strain rate {varepsilon}. We introduce a dimensionless Thrombosis Number Theta = (Sigma\/Sigma_c)(P\/P_0)^m(C\/C_0)^n, which incorporates platelet concentration P and coagulation factor concentration C, and governs the transition between stable flow (Theta < 1) and active clot growth (Theta > 1). The thrombus density is represented by a scalar order parameter phi_F whose dynamics follow a Ginzburg--Landau free energy functional. For a simplified stenosed artery we derive an analytic closed-form thrombosis onset criterion and a critical flow rate Qc = (pi R_0^3 \/ 4mu) Sigma_c (1 - delta)^3, where delta is stenosis severity. Linear stability analysis shows that perturbations grow at rate omega(k) = Lambda(Theta) - D_phi k^2, becoming unstable when (Theta > 1). Near threshold the clot volume fraction scales as phi_F ~ (Theta - 1)^(1\/2), a mean-field critical exponent consistent with Ginzburg--Landau theory. Systematic comparison with fifteen published experimental and computational datasets spanning shear rates from 100 to 15,000 s^-1 confirms that FGT correctly predicts the existence, location, and approximate severity of pathological thrombus formation across diverse vascular geometries. The theory provides a quantitative bridge between single-molecule mechanobiology and macroscale clinical thrombosis, and yields experimentally testable predictions distinguishing FGT from purely biochemical models.","rel_num_authors":5,"rel_authors":[{"author_name":"Xiaochen Liu","author_inst":"THE UNIVERSITY OF SYDNEY"},{"author_name":"Yuxin Chen","author_inst":"THE UNIVERSITY OF SYDNEY"},{"author_name":"Siyuan Zhuang","author_inst":"The University of Sydney"},{"author_name":"Daniele Vigolo","author_inst":"The University of Sydney"},{"author_name":"Ken-Tye Yong","author_inst":"THE UNIVERSITY OF SYDNEY"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Widespread use of invalid statistical tests in biomedical machine learning","rel_doi":"10.64898\/2026.05.17.724301","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.724301","rel_abs":"Machine learning is accelerating biomedical research. Cross-validation is widely used to compare predictive performance -- not only to benchmark algorithms, but also to inform scientific applications, such as ranking biomarkers. However, prediction performance estimates across cross-validation folds are not independent. Standard tests for comparing prediction performance (e.g., paired t-test) assume independence and can therefore inflate false positive rates. In a PRISMA-guided meta-analysis of 210 studies (impact factor [&ge;]15, 1 June 2020 - 1 June 2025), we find that 97% ignored fold dependence when comparing prediction performance. This problem is ubiquitous across scientific fields and unaffected by impact factor, rigor-promoting policies, or open science practices. Simulations across 420 scenarios spanning four diverse datasets show that ignoring fold dependence leads to invalid false positive control in most settings. Repeated cross-validation further compounds this problem, with false positive rates rising toward 100% as the number of repetitions grows. Existing fold-dependence-aware tests rely on strong assumptions because the variance of fold-level statistics and the between-fold correlation cannot be disentangled under standard cross-validation. We therefore propose the SHARP (Split-HAlf RePeated) test, a simple modification to standard cross-validation that enables direct estimation of variance and correlation. Benchmarked against 12 tests, SHARP provides the best overall balance of false-positive control, statistical power, and confidence-interval calibration across simulation schemes. We conclude by providing best practices and reporting guidelines for valid model comparison inference in biomedical machine learning and beyond.","rel_num_authors":44,"rel_authors":[{"author_name":"Tianchu Zeng","author_inst":"National University of Singapore"},{"author_name":"Hetu Li","author_inst":"National University of Singapore"},{"author_name":"Shaoshi Zhang","author_inst":"National University of Singapore"},{"author_name":"Yan Quan Tan","author_inst":"National University of Singapore"},{"author_name":"Fang Tian","author_inst":"National University of Singapore"},{"author_name":"Csaba Orban","author_inst":"National University of Singapore"},{"author_name":"Lijun An","author_inst":"National University of Singapore"},{"author_name":"Wanyu Che","author_inst":"National University of Singapore"},{"author_name":"Jingwen Cheng","author_inst":"National University of Singapore"},{"author_name":"Joanna Su Xian Chong","author_inst":"National University of Singapore"},{"author_name":"Niousha Dehestani","author_inst":"National University of Singapore"},{"author_name":"Zijian Dong","author_inst":"National University of Singapore"},{"author_name":"Xin Li","author_inst":"National University of Singapore"},{"author_name":"Zhizhou Li","author_inst":"National University of Singapore"},{"author_name":"Mervyn Jun Rui Lim","author_inst":"National University of Singapore"},{"author_name":"Yi Lin","author_inst":"National University of Singapore"},{"author_name":"Qinrui Ling","author_inst":"University of Science and Technology of China"},{"author_name":"Zijie Ling","author_inst":"National University of Singapore"},{"author_name":"Xi Zhi Low","author_inst":"National University of Singapore"},{"author_name":"Sina Mansour L.","author_inst":"The University of Melbourne"},{"author_name":"Kwun Kei Ng","author_inst":"National University of Singapore"},{"author_name":"Thuan Tinh Nguyen","author_inst":"National University of Singapore"},{"author_name":"Leon Qi Rong Ooi","author_inst":"National University of Singapore"},{"author_name":"Shreya Pande","author_inst":"National University of Singapore"},{"author_name":"Xing Qian","author_inst":"National University of Singapore"},{"author_name":"Jingxuan Ruan","author_inst":"National University of Singapore"},{"author_name":"Ziwen Wang","author_inst":"National University of Singapore"},{"author_name":"Yapei Xie","author_inst":"National University of Singapore"},{"author_name":"Chen Zhang","author_inst":"National University of Singapore"},{"author_name":"Yichi Zhang","author_inst":"National University of Singapore"},{"author_name":"Kaustubh Patil","author_inst":"Research Center Julich"},{"author_name":"Linden Parkes","author_inst":"Rutgers University"},{"author_name":"Elvisha Dhamala","author_inst":"Feinstein Institutes for Medical Research"},{"author_name":"Sidhant Chopra","author_inst":"The University of Melbourne"},{"author_name":"Andrew Zalesky","author_inst":"The University of Melbourne"},{"author_name":"Avram Holmes","author_inst":"Rutgers University"},{"author_name":"Simon Eickhoff","author_inst":"Research Center Julich"},{"author_name":"Juan Helen Zhou","author_inst":"National University of Singapore"},{"author_name":"Olivier Renaud","author_inst":"University of Geneva"},{"author_name":"Nico Dosenbach","author_inst":"Washington University, St Louis"},{"author_name":"Konrad Paul Kording","author_inst":"Northwestern University"},{"author_name":"Danilo Bzdok","author_inst":"McGill University"},{"author_name":"Thomas Nichols","author_inst":"University of Oxford"},{"author_name":"B.T. Thomas Yeo","author_inst":"National University of Singapore"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Widespread use of invalid statistical tests in biomedical machine learning","rel_doi":"10.64898\/2026.05.17.724301","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.724301","rel_abs":"Machine learning is accelerating biomedical research. Cross-validation is widely used to compare predictive performance -- not only to benchmark algorithms, but also to inform scientific applications, such as ranking biomarkers. However, prediction performance estimates across cross-validation folds are not independent. Standard tests for comparing prediction performance (e.g., paired t-test) assume independence and can therefore inflate false positive rates. In a PRISMA-guided meta-analysis of 210 studies (impact factor [&ge;]15, 1 June 2020 - 1 June 2025), we find that 97% ignored fold dependence when comparing prediction performance. This problem is ubiquitous across scientific fields and unaffected by impact factor, rigor-promoting policies, or open science practices. Simulations across 420 scenarios spanning four diverse datasets show that ignoring fold dependence leads to invalid false positive control in most settings. Repeated cross-validation further compounds this problem, with false positive rates rising toward 100% as the number of repetitions grows. Existing fold-dependence-aware tests rely on strong assumptions because the variance of fold-level statistics and the between-fold correlation cannot be disentangled under standard cross-validation. We therefore propose the SHARP (Split-HAlf RePeated) test, a simple modification to standard cross-validation that enables direct estimation of variance and correlation. Benchmarked against 12 tests, SHARP provides the best overall balance of false-positive control, statistical power, and confidence-interval calibration across simulation schemes. We conclude by providing best practices and reporting guidelines for valid model comparison inference in biomedical machine learning and beyond.","rel_num_authors":44,"rel_authors":[{"author_name":"Tianchu Zeng","author_inst":"National University of Singapore"},{"author_name":"Hetu Li","author_inst":"National University of Singapore"},{"author_name":"Shaoshi Zhang","author_inst":"National University of Singapore"},{"author_name":"Yan Quan Tan","author_inst":"National University of Singapore"},{"author_name":"Fang Tian","author_inst":"National University of Singapore"},{"author_name":"Csaba Orban","author_inst":"National University of Singapore"},{"author_name":"Lijun An","author_inst":"National University of Singapore"},{"author_name":"Wanyu Che","author_inst":"National University of Singapore"},{"author_name":"Jingwen Cheng","author_inst":"National University of Singapore"},{"author_name":"Joanna Su Xian Chong","author_inst":"National University of Singapore"},{"author_name":"Niousha Dehestani","author_inst":"National University of Singapore"},{"author_name":"Zijian Dong","author_inst":"National University of Singapore"},{"author_name":"Xin Li","author_inst":"National University of Singapore"},{"author_name":"Zhizhou Li","author_inst":"National University of Singapore"},{"author_name":"Mervyn Jun Rui Lim","author_inst":"National University of Singapore"},{"author_name":"Yi Lin","author_inst":"National University of Singapore"},{"author_name":"Qinrui Ling","author_inst":"University of Science and Technology of China"},{"author_name":"Zijie Ling","author_inst":"National University of Singapore"},{"author_name":"Xi Zhi Low","author_inst":"National University of Singapore"},{"author_name":"Sina Mansour L.","author_inst":"The University of Melbourne"},{"author_name":"Kwun Kei Ng","author_inst":"National University of Singapore"},{"author_name":"Thuan Tinh Nguyen","author_inst":"National University of Singapore"},{"author_name":"Leon Qi Rong Ooi","author_inst":"National University of Singapore"},{"author_name":"Shreya Pande","author_inst":"National University of Singapore"},{"author_name":"Xing Qian","author_inst":"National University of Singapore"},{"author_name":"Jingxuan Ruan","author_inst":"National University of Singapore"},{"author_name":"Ziwen Wang","author_inst":"National University of Singapore"},{"author_name":"Yapei Xie","author_inst":"National University of Singapore"},{"author_name":"Chen Zhang","author_inst":"National University of Singapore"},{"author_name":"Yichi Zhang","author_inst":"National University of Singapore"},{"author_name":"Kaustubh Patil","author_inst":"Research Center Julich"},{"author_name":"Linden Parkes","author_inst":"Rutgers University"},{"author_name":"Elvisha Dhamala","author_inst":"Feinstein Institutes for Medical Research"},{"author_name":"Sidhant Chopra","author_inst":"The University of Melbourne"},{"author_name":"Andrew Zalesky","author_inst":"The University of Melbourne"},{"author_name":"Avram Holmes","author_inst":"Rutgers University"},{"author_name":"Simon Eickhoff","author_inst":"Research Center Julich"},{"author_name":"Juan Helen Zhou","author_inst":"National University of Singapore"},{"author_name":"Olivier Renaud","author_inst":"University of Geneva"},{"author_name":"Nico Dosenbach","author_inst":"Washington University, St Louis"},{"author_name":"Konrad Paul Kording","author_inst":"Northwestern University"},{"author_name":"Danilo Bzdok","author_inst":"McGill University"},{"author_name":"Thomas Nichols","author_inst":"University of Oxford"},{"author_name":"B.T. Thomas Yeo","author_inst":"National University of Singapore"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Widespread use of invalid statistical tests in biomedical machine learning","rel_doi":"10.64898\/2026.05.17.724301","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.724301","rel_abs":"Machine learning is accelerating biomedical research. Cross-validation is widely used to compare predictive performance -- not only to benchmark algorithms, but also to inform scientific applications, such as ranking biomarkers. However, prediction performance estimates across cross-validation folds are not independent. Standard tests for comparing prediction performance (e.g., paired t-test) assume independence and can therefore inflate false positive rates. In a PRISMA-guided meta-analysis of 210 studies (impact factor [&ge;]15, 1 June 2020 - 1 June 2025), we find that 97% ignored fold dependence when comparing prediction performance. This problem is ubiquitous across scientific fields and unaffected by impact factor, rigor-promoting policies, or open science practices. Simulations across 420 scenarios spanning four diverse datasets show that ignoring fold dependence leads to invalid false positive control in most settings. Repeated cross-validation further compounds this problem, with false positive rates rising toward 100% as the number of repetitions grows. Existing fold-dependence-aware tests rely on strong assumptions because the variance of fold-level statistics and the between-fold correlation cannot be disentangled under standard cross-validation. We therefore propose the SHARP (Split-HAlf RePeated) test, a simple modification to standard cross-validation that enables direct estimation of variance and correlation. Benchmarked against 12 tests, SHARP provides the best overall balance of false-positive control, statistical power, and confidence-interval calibration across simulation schemes. We conclude by providing best practices and reporting guidelines for valid model comparison inference in biomedical machine learning and beyond.","rel_num_authors":44,"rel_authors":[{"author_name":"Tianchu Zeng","author_inst":"National University of Singapore"},{"author_name":"Hetu Li","author_inst":"National University of Singapore"},{"author_name":"Shaoshi Zhang","author_inst":"National University of Singapore"},{"author_name":"Yan Quan Tan","author_inst":"National University of Singapore"},{"author_name":"Fang Tian","author_inst":"National University of Singapore"},{"author_name":"Csaba Orban","author_inst":"National University of Singapore"},{"author_name":"Lijun An","author_inst":"National University of Singapore"},{"author_name":"Wanyu Che","author_inst":"National University of Singapore"},{"author_name":"Jingwen Cheng","author_inst":"National University of Singapore"},{"author_name":"Joanna Su Xian Chong","author_inst":"National University of Singapore"},{"author_name":"Niousha Dehestani","author_inst":"National University of Singapore"},{"author_name":"Zijian Dong","author_inst":"National University of Singapore"},{"author_name":"Xin Li","author_inst":"National University of Singapore"},{"author_name":"Zhizhou Li","author_inst":"National University of Singapore"},{"author_name":"Mervyn Jun Rui Lim","author_inst":"National University of Singapore"},{"author_name":"Yi Lin","author_inst":"National University of Singapore"},{"author_name":"Qinrui Ling","author_inst":"University of Science and Technology of China"},{"author_name":"Zijie Ling","author_inst":"National University of Singapore"},{"author_name":"Xi Zhi Low","author_inst":"National University of Singapore"},{"author_name":"Sina Mansour L.","author_inst":"The University of Melbourne"},{"author_name":"Kwun Kei Ng","author_inst":"National University of Singapore"},{"author_name":"Thuan Tinh Nguyen","author_inst":"National University of Singapore"},{"author_name":"Leon Qi Rong Ooi","author_inst":"National University of Singapore"},{"author_name":"Shreya Pande","author_inst":"National University of Singapore"},{"author_name":"Xing Qian","author_inst":"National University of Singapore"},{"author_name":"Jingxuan Ruan","author_inst":"National University of Singapore"},{"author_name":"Ziwen Wang","author_inst":"National University of Singapore"},{"author_name":"Yapei Xie","author_inst":"National University of Singapore"},{"author_name":"Chen Zhang","author_inst":"National University of Singapore"},{"author_name":"Yichi Zhang","author_inst":"National University of Singapore"},{"author_name":"Kaustubh Patil","author_inst":"Research Center Julich"},{"author_name":"Linden Parkes","author_inst":"Rutgers University"},{"author_name":"Elvisha Dhamala","author_inst":"Feinstein Institutes for Medical Research"},{"author_name":"Sidhant Chopra","author_inst":"The University of Melbourne"},{"author_name":"Andrew Zalesky","author_inst":"The University of Melbourne"},{"author_name":"Avram Holmes","author_inst":"Rutgers University"},{"author_name":"Simon Eickhoff","author_inst":"Research Center Julich"},{"author_name":"Juan Helen Zhou","author_inst":"National University of Singapore"},{"author_name":"Olivier Renaud","author_inst":"University of Geneva"},{"author_name":"Nico Dosenbach","author_inst":"Washington University, St Louis"},{"author_name":"Konrad Paul Kording","author_inst":"Northwestern University"},{"author_name":"Danilo Bzdok","author_inst":"McGill University"},{"author_name":"Thomas Nichols","author_inst":"University of Oxford"},{"author_name":"B.T. Thomas Yeo","author_inst":"National University of Singapore"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Sustained immune activation suppresses planarian regeneration","rel_doi":"10.64898\/2026.05.17.725704","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725704","rel_abs":"Tissue injury immediately triggers immune defenses to prevent infection, a process that can paradoxically interfere with repair. Yet, how some organisms resolve this tension to fully regenerate remains poorly understood. Planarians, flatworms capable of regenerating any body part, offer a unique model for studying how robust immunity coexists with extensive regenerative capacity. Here, we show that the planarian immediate injury response is dominated by the robust upregulation of immune and stress-related genes, demonstrating that defense mechanisms are intrinsically wired into wound sensing. By uncoupling immune activation from tissue injury using exposure to heat-inactivated bacteria, we found that immune stimulation alone induced a transcriptional program mirroring central aspects of the early injury response. Prolonged immune activation led to progressive, host-driven tissue lysis that was fully reversible upon removal of the stimulus. Single-cell profiling identified distinct epidermal and phagocytic subpopulations as the central mediators of this \"defense-first\" response. Furthermore, we identified foxF-1-regulated phagocytes as critical drivers of immune resolution, as suppressing foxF-1 markedly increased vulnerability to noninfectious immune challenge. Finally, we demonstrated that sustained immune hyperactivation delayed regenerative progression by approximately 50%. Together, our findings establish the resolution of immune activity as a critical prerequisite for regeneration and define sustained immune activation as a fundamental constraint on tissue repair.","rel_num_authors":2,"rel_authors":[{"author_name":"Noam Hendin","author_inst":"Tel Aviv University"},{"author_name":"Omri Wurtzel","author_inst":"Tel Aviv University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Elimination of senescent cells by mechanical cell competition","rel_doi":"10.64898\/2026.05.18.725837","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725837","rel_abs":"Cellular senescence, a hallmark of aging, leads to the accumulation of apoptosis-resistant cells that compromise tissue homeostasis. While senescent cells are known to influence neighboring cells through the senescence-associated secretory phenotype (SASP), the precise nature of the interactions between senescent and normal cells remains elusive. Here we show that progerin-induced senescent cells undergo apoptosis when co-cultured with normal cells. This elimination requires direct cell-cell contact and is mediated by the JNK and p38-MAPK pathways, leading to p53 upregulation and p21 downregulation in progerin-expressing cells. Furthermore, neighboring normal cells exert persistent mechanical compression on progerin-expressing cells prior to their elimination, consistent with mechanical cell competition. In contrast, p16-induced senescent cells resist elimination under the same co-culture conditions, maintaining high p21 levels. Our findings reveal a non-cell-autonomous mechanism for senescent cell clearance, providing new insights into the maintenance of tissue homeostasis during aging.","rel_num_authors":7,"rel_authors":[{"author_name":"Yuping Pan","author_inst":"Mechanobiology Institute, National University of Singapore"},{"author_name":"Mattheus Xing Rong Foo","author_inst":"Skin Research Institute of Singapore"},{"author_name":"Vinod S\/O Prabhakaran","author_inst":"Mechanobiology Institute, National University of Singapore"},{"author_name":"Kashish Jain","author_inst":"Mechanobiology Institute, National University of Singapore"},{"author_name":"Pakorn Kanchanawong","author_inst":"Mechanobiology Institute, National University of Singapore"},{"author_name":"Oliver Dreesen","author_inst":"Skin Research Institute of Singapore"},{"author_name":"Yusuke Toyama","author_inst":"Mechanobiology Institute, National University of Singapore"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Candida glabrata YPK2 is a multidrug susceptibility locus","rel_doi":"10.64898\/2026.05.15.725557","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.15.725557","rel_abs":"The biological conservation between fungi and mammals due to a common ancestor has made development of selective antifungal drugs a difficult challenge. Further complicating this situation is the selection of antifungal drug-resistant organisms during drug treatment. The pathogenic yeast Nakaseomyces glabratus (called here Candida glabrata) presents an especially challenging organism due to its tendency to frequently lose susceptibility to the major antifungal drug class the azoles. Additionally, C. glabrata develops resistance to echinocandin drugs, a second, more recently described antifungal agent at 10 times the rate of other organisms. Previous work has established that the sterol responsive transcriptional regulator Upc2A is a key determinant of azole susceptibility in C. glabrata and plays a role in echinocandin resistance. We used a biochemical approach to identify proteins that co-purified with Upc2A and identified the Ypk2 AGC kinase as an interacting protein. Strains lacking YPK2 exhibited increased susceptibility to fluconazole and the echinocandin caspofungin. A ypk2D strain failed to normally induce transcription of several ERG genes but exhibited normal induction of the CDR1 ATP-binding cassette transporter gene. Isogenic ypk2 D strains were also highly susceptible to the three major classes of antifungal drugs, indicating that this kinase behaves as a multidrug susceptibility factor. RNA-seq analyses indicated that the transcriptional response to exposure is different for each drug and each response is differentially altered upon loss of Ypk2. Our data indicate that Ypk2 plays an important role in coordinating gene expression that impacts susceptibility to all major antifungal drug classes.","rel_num_authors":5,"rel_authors":[{"author_name":"Lucia Simonicova","author_inst":"The University of Iowa"},{"author_name":"Thomas P. Conway","author_inst":"University of Iowa"},{"author_name":"Axel A. Brakhage","author_inst":"University of Jena"},{"author_name":"Thomas Krueger","author_inst":"University of Jena"},{"author_name":"W. Scott Moye-Rowley","author_inst":"The University of Iowa"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"A Deterministically Synchronized Widefield Imaging and Virtual Reality Platform for Multimodal Brain Behavior Recording","rel_doi":"10.64898\/2026.05.17.725707","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725707","rel_abs":"Objective: Simultaneous recording of brain activity, behaviour, and virtual environments is essential for understanding large scale neural dynamics during behaviour. However, existing systems often rely on software-based synchronization or post hoc alignment, introducing latency, jitter, and drift that obscure fast brain behavior interactions. Approach: Here, we present a deterministically synchronized widefield calcium imaging platform that unifies neural imaging, high speed behavioural monitoring, and closed-loop virtual reality (VR) under a shared hardware defined clock. This system enables millisecond precision temporal alignment across modalities, including dual wavelength hemodynamic correction, pupil and orofacial tracking, locomotion sensing, and VR rendering. Main results: The platform achieves stable hardware level synchronization across neural imaging, behavioural recordings, and VR rendering without reliance on software timestamps. It supports widefield imaging rates up to 100 Hz and integrates seamlessly with both ViRMEn and Blender VR engines, exhibiting a mean locomotion to VR update latency of ~1.5 ms. Multimodal recordings during VR navigation demonstrate robust temporal alignment between cortical activity, facial dynamics, pupil signals, and locomotion. Significance: This system provides a deterministic multimodal framework for studying brain behaviour relationships during active behaviour. By enabling millisecond precision synchronization across neural imaging, behaviour, and virtual environments, this platform enables causal investigation of brain behaviour interactions at millisecond precision and provides a foundation for next-generation closed loop neuroengineering experiments.","rel_num_authors":8,"rel_authors":[{"author_name":"Miguel Maldonado","author_inst":"Cleveland Clinic Research"},{"author_name":"Omer Faruk Dinc","author_inst":"Cleveland Clinic Research"},{"author_name":"Macit Emre Lacin","author_inst":"Cleveland Clinic Research"},{"author_name":"Tenesha Connor","author_inst":"Cleveland Clinic Research"},{"author_name":"Frederick Bell","author_inst":"Cleveland Clinic Research"},{"author_name":"berfin dinc","author_inst":"Cleveland Clinic Research"},{"author_name":"Kemal Ozdemirli","author_inst":"Cleveland Clinic Research"},{"author_name":"Murat Yildirim","author_inst":"Cleveland Clinic Research"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Elevated conformational dynamics makes ACKR3 activation-prone and G protein-incompetent","rel_doi":"10.64898\/2026.05.17.725760","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725760","rel_abs":"The atypical receptor ACKR3 works together with the canonical chemokine receptor CXCR4 to drive cell migration along gradients of their shared agonist CXCL12. CXCR4 promotes chemotaxis by activating canonical G protein pathways and recruiting {beta}-arrestins. ACKR3 indirectly regulates CXCR4-mediated chemotaxis by scavenging CXCL12. Unlike canonical chemokine receptors, ACKR3 does not couple to G proteins and instead is 100% biased towards {beta}-arrestins. CXCR4 activation by CXCL12 is exquisitely sensitive to subtle changes in both receptor and ligand. By contrast, ACKR3 is activation-prone: it recruits {beta}-arrestins in response to many ligands and is much less sensitive to mutations, suggesting distinct activation mechanisms compared to CXCR4. To explore the basis of these differences, we compared the dynamics of ACKR3 and CXCR4 complexes with chemokines using molecular dynamic (MD) simulations. Ten-microsecond atomistic MD simulations revealed that CXCR4 adopts a stable active state when bound to WT CXCL12 but transitions to an inactive state when in complex with the antagonist variant, [P2G]CXCL12. By comparison, ACKR3 exhibits a variable transmembrane (TM) 6 state distribution and persistently ''active'' TM7 when complexed with either WT CXCL12 or [P2G]CXCL12, the latter retaining substantial agonistic activity at ACKR3. We further identified ligand-mediated residue interaction networks in the TM core that regulate TM6 and TM7 activation in CXCR4 but are absent or disrupted in ACKR3, resulting in less constrained receptor dynamics. These findings were validated by BRET-based assays with CXCL12 and ACKR3 mutants. Together, the data suggests that the unique conformational dynamics of ACKR3 govern its activation propensity, its ligand promiscuity, and its atypical effector coupling.","rel_num_authors":8,"rel_authors":[{"author_name":"Kai Wang","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Tony Ngo","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Ekta Khare","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Rezvan Chitsazi","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Suchismita Roy","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Christopher T Schafer","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Tracy M Handel","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"},{"author_name":"Irina Kufareva","author_inst":"Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"A reduced order multibody model of the foot and ankle complex based on kinematic synergies","rel_doi":"10.64898\/2026.05.17.725725","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725725","rel_abs":"Background and Objective: The foot and ankle complex is a highly articulated and mechanically constrained system, often simplified as a chain of few rigid segments, neglecting many bone to bone motions and raising questions about the accurate representation of interaction with ground. This study proposes a new reduced order multibody formulation that captures intrinsic kinematic constraints of the foot through motion synergies. Methods: Bones kinematic coupling, or motion synergies, were experimentally derived from weight bearing CT scans using principal component analysis. These couplings were embedded in a synergy based multibody kinematic optimization framework describing the foot and ankle with five degrees of freedom: ankle flexion; foot adduction, pronation, and arching; and toe flexion. Model accuracy was evaluated against bone level experimental kinematics. The model was applied to gait data from healthy, flat, and diabetic feet and compared with a standard multi segment foot model, assessing robustness by progressively reducing the number of skin markers. Results: Average errors were about 1{degrees} and 0.5mm when using subject specific synergies and below 7 {degrees} and 4mm when scaling the generic model, matching or exceeding the accuracy of existing models. Reliable reconstruction was obtained using only four foot markers. In clinical gait analysis, the model showed superior discrimination between populations and enabled assessment of transverse arch deformation, not accessible with conventional models. Conclusion: The proposed synergy based model provides an accurate, low complexity framework for reconstructing bone level foot and ankle kinematics, substantially simplifying gait analysis while improving biomechanical interpretability. This framework supports future integration with dynamic models aimed at studying load transmission in the foot.","rel_num_authors":6,"rel_authors":[{"author_name":"Michele Conconi","author_inst":"Department of Industrial Engineering, University of Bologna, Italy"},{"author_name":"Luca Modenese","author_inst":"Graduate School of Biomedical Engineering, University of New South Wales"},{"author_name":"Gian Marco Barbieri","author_inst":"Department of Industrial Engineering, University of Bologna, Italy"},{"author_name":"Alberto Leardini","author_inst":"Movement Analysis Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy"},{"author_name":"Claudio Belvedere","author_inst":"Movement Analysis Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy"},{"author_name":"Nicola Sancisi","author_inst":"Department of Industrial Engineering, University of Bologna, Italy"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"C. elegans small heat-shock protein HSP-12.6 has a highly specialized protective function towards muscle thick filaments in vivo","rel_doi":"10.64898\/2026.05.17.725775","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.17.725775","rel_abs":"Small heat-shock proteins (sHSPs) are an ancient and diverse class of molecular chaperones, acting as a first line of defense against proteotoxic stresses. While the canonical sHSPs prevent uncontrollable aggregation of a broad range of non-native substrates, a subset of sHSPs do not exhibit this broad activity in vitro, and their functions in vivo are poorly understood. Interestingly, several such sHSPs are selectively expressed in muscle tissues, including by myogenic programs, indicating likely functional roles. We examined in vivo function of C. elegans HSP-12.6, which possesses no chaperone activity in vitro but regulates lifespan, and is developmentally induced in the muscles of long-lived dauer animals. We found that HSP-12.6 exhibits exceptional selectivity in protecting the muscle function against folding or assembly mutations in thick filament proteins, but not in thin filament or non-filament proteins. This reflected its exclusive chaperone-like binding to the healthy myosin-containing thick filaments, and to their aggregates. HSP-12.6 did not bind other muscle structures or aggregates, including those of thin filaments, and retained its selectivity to either healthy thick filaments or their aggregates when challenged with a toxic aggregation-prone polyQ protein. Our data establish HSP-12.6 as a highly-selective myoprotective chaperone, with client spectrum distinct from other sHSPs.","rel_num_authors":7,"rel_authors":[{"author_name":"Abigail Fern","author_inst":"Biology Department, Drexel University"},{"author_name":"Jasmine Alexander-Floyd","author_inst":"SK Pharmteco"},{"author_name":"Anhelina Volchok","author_inst":"Medical Sciences Division, University of Oxford"},{"author_name":"Susan M Cahill","author_inst":"Biology Department, Drexel University"},{"author_name":"Srikar Donepudi","author_inst":"Department of Medicine, Rutgers New Jersey Medical School"},{"author_name":"Jana Smuts","author_inst":"Neurobiology and Anatomy Department, Drexel University"},{"author_name":"Tali Gidalevitz","author_inst":"Biology Department, Drexel University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Somatic mutations reveal the ontogeny of human microglia","rel_doi":"10.64898\/2026.05.19.726366","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726366","rel_abs":"Microglia are the resident hematopoietic cells of the central nervous system1. In mice, microglia seed the brain during embryogenesis and can be maintained throughout life with minimal input from adult hematopoiesis2-4. The origins of human microglia are less clear, but recent evidence suggests that marrow-derived cells may be able to supplement the human microglial pool in certain individuals5,6. Here, to investigate the ontogeny of human microglia, we develop a method that uses the collection of accumulated somatic mutations which uniquely labels each clone of cells to track the infiltration of marrow-derived cells into the human brain. Applying this method to 20 aged individuals, we find evidence of an influx of marrow-derived cells into the brain in all examined individuals. Single cell analysis, including single cell lineage tracing using mitochondrial DNA variants, demonstrates that these infiltrating cells are nearly identical to microglia and can comprise a large fraction of the microglial pool. Analysis of large-scale sequencing cohorts demonstrates a protective association between most types of clonal hematopoiesis and Alzheimer's disease. In sum, this work uncovers a widespread influx of myeloid cells into the healthy human brain which serves to reinforce the pool of human microglia and becomes common with aging.","rel_num_authors":38,"rel_authors":[{"author_name":"Julia Belk","author_inst":"Stanford University"},{"author_name":"Yaowen Zhang","author_inst":"Stanford University"},{"author_name":"Quanming Shi","author_inst":"Stanford University"},{"author_name":"Lisa Ma","author_inst":"Stanford University"},{"author_name":"Raja Kalluru","author_inst":"Stanford University"},{"author_name":"Alejandro Medina Enciso","author_inst":"Stanford University"},{"author_name":"Emily Reilly","author_inst":"Stanford University"},{"author_name":"Jacob Weiss","author_inst":"Stanford University"},{"author_name":"Rui Li","author_inst":"Stanford University"},{"author_name":"Anna Eastman","author_inst":"Stanford University"},{"author_name":"Nicole Womack-Gambrel","author_inst":"Stanford University"},{"author_name":"Debasmita Paul","author_inst":"Stanford University"},{"author_name":"Arnav Chakravarthy","author_inst":"Stanford University"},{"author_name":"Syed Bukhari","author_inst":"Stanford University"},{"author_name":"Dipabarna Bhattacharya","author_inst":"Stanford University"},{"author_name":"Suyash Raj","author_inst":"Stanford University"},{"author_name":"Daniel Richard","author_inst":"Stanford University"},{"author_name":"Simone Brioschi","author_inst":"Washington University School of Medicine in Saint Louis"},{"author_name":"Matthew Chrostek","author_inst":"Stanford University"},{"author_name":"Daniel Nachun","author_inst":"Stanford University"},{"author_name":"Christopher Arends","author_inst":"Stanford University"},{"author_name":"Jayakrishnan Gopakumar","author_inst":"Stanford University"},{"author_name":"Isak Tengesdal","author_inst":"Stanford University"},{"author_name":"Ademar Bynum","author_inst":"Stanford University"},{"author_name":"Shaneice Mitchell","author_inst":"Stanford University"},{"author_name":"Katalin Sandor","author_inst":"Stanford University"},{"author_name":"Badri Vardarajan","author_inst":"Columbia University"},{"author_name":"Inma Cobos","author_inst":"Stanford University"},{"author_name":"Donald Born","author_inst":"Stanford University"},{"author_name":"Anne Brunet","author_inst":"Stanford University"},{"author_name":"Marco Colonna","author_inst":"Washington University School of Medicine in Saint Louis"},{"author_name":"Hannes Vogel","author_inst":"Stanford University"},{"author_name":"Thomas Montine","author_inst":"Stanford University"},{"author_name":"Jody Hooper","author_inst":"Stanford University"},{"author_name":"Irving Weissman","author_inst":"Stanford University"},{"author_name":"C. Dirk Keene","author_inst":"University of Washington"},{"author_name":"Howard Chang","author_inst":"Stanford University"},{"author_name":"Siddhartha Jaiswal","author_inst":"Stanford University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Somatic mutations reveal the ontogeny of human microglia","rel_doi":"10.64898\/2026.05.19.726366","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726366","rel_abs":"Microglia are the resident hematopoietic cells of the central nervous system1. In mice, microglia seed the brain during embryogenesis and can be maintained throughout life with minimal input from adult hematopoiesis2-4. The origins of human microglia are less clear, but recent evidence suggests that marrow-derived cells may be able to supplement the human microglial pool in certain individuals5,6. Here, to investigate the ontogeny of human microglia, we develop a method that uses the collection of accumulated somatic mutations which uniquely labels each clone of cells to track the infiltration of marrow-derived cells into the human brain. Applying this method to 20 aged individuals, we find evidence of an influx of marrow-derived cells into the brain in all examined individuals. Single cell analysis, including single cell lineage tracing using mitochondrial DNA variants, demonstrates that these infiltrating cells are nearly identical to microglia and can comprise a large fraction of the microglial pool. Analysis of large-scale sequencing cohorts demonstrates a protective association between most types of clonal hematopoiesis and Alzheimer's disease. In sum, this work uncovers a widespread influx of myeloid cells into the healthy human brain which serves to reinforce the pool of human microglia and becomes common with aging.","rel_num_authors":38,"rel_authors":[{"author_name":"Julia Belk","author_inst":"Stanford University"},{"author_name":"Yaowen Zhang","author_inst":"Stanford University"},{"author_name":"Quanming Shi","author_inst":"Stanford University"},{"author_name":"Lisa Ma","author_inst":"Stanford University"},{"author_name":"Raja Kalluru","author_inst":"Stanford University"},{"author_name":"Alejandro Medina Enciso","author_inst":"Stanford University"},{"author_name":"Emily Reilly","author_inst":"Stanford University"},{"author_name":"Jacob Weiss","author_inst":"Stanford University"},{"author_name":"Rui Li","author_inst":"Stanford University"},{"author_name":"Anna Eastman","author_inst":"Stanford University"},{"author_name":"Nicole Womack-Gambrel","author_inst":"Stanford University"},{"author_name":"Debasmita Paul","author_inst":"Stanford University"},{"author_name":"Arnav Chakravarthy","author_inst":"Stanford University"},{"author_name":"Syed Bukhari","author_inst":"Stanford University"},{"author_name":"Dipabarna Bhattacharya","author_inst":"Stanford University"},{"author_name":"Suyash Raj","author_inst":"Stanford University"},{"author_name":"Daniel Richard","author_inst":"Stanford University"},{"author_name":"Simone Brioschi","author_inst":"Washington University School of Medicine in Saint Louis"},{"author_name":"Matthew Chrostek","author_inst":"Stanford University"},{"author_name":"Daniel Nachun","author_inst":"Stanford University"},{"author_name":"Christopher Arends","author_inst":"Stanford University"},{"author_name":"Jayakrishnan Gopakumar","author_inst":"Stanford University"},{"author_name":"Isak Tengesdal","author_inst":"Stanford University"},{"author_name":"Ademar Bynum","author_inst":"Stanford University"},{"author_name":"Shaneice Mitchell","author_inst":"Stanford University"},{"author_name":"Katalin Sandor","author_inst":"Stanford University"},{"author_name":"Badri Vardarajan","author_inst":"Columbia University"},{"author_name":"Inma Cobos","author_inst":"Stanford University"},{"author_name":"Donald Born","author_inst":"Stanford University"},{"author_name":"Anne Brunet","author_inst":"Stanford University"},{"author_name":"Marco Colonna","author_inst":"Washington University School of Medicine in Saint Louis"},{"author_name":"Hannes Vogel","author_inst":"Stanford University"},{"author_name":"Thomas Montine","author_inst":"Stanford University"},{"author_name":"Jody Hooper","author_inst":"Stanford University"},{"author_name":"Irving Weissman","author_inst":"Stanford University"},{"author_name":"C. Dirk Keene","author_inst":"University of Washington"},{"author_name":"Howard Chang","author_inst":"Stanford University"},{"author_name":"Siddhartha Jaiswal","author_inst":"Stanford University"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Shared book reading promotes experience-dependent autonomic synchrony in parent-preterm infant dyads","rel_doi":"10.64898\/2026.05.19.726001","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726001","rel_abs":"Preterm birth is associated with alterations in early caregiver-infant regulation, with potential consequences for socio-emotional and physiological development. However, the mechanisms through which early interactional experience shapes these processes remain unclear. Here, we tested whether a structured dyadic intervention could modify co-regulatory dynamics across physiological, behavioral, and relational levels. Fifty-four 7-month-old preterm infants and their parents were assigned to either a shared book reading intervention (n = 22) or an active control condition based on a shared building activity (n = 32) and compared with 39 full-term infants. The intervention consisted of an 8-week program of shared book reading, designed to structure parent-infant interaction. Physiological synchrony was assessed at the dyadic level, alongside infants' autonomic regulation and cardiovascular signal complexity. Behavioral engagement and parental attachment representations were also evaluated. Results showed that mother-infant physiological synchrony emerged selectively within the interactional context trained by the intervention and only in the intervention group. This context-specific synchrony was accompanied by modulation of vagal activity and increased cardiovascular complexity in preterm infants, consistent with enhanced flexibility of autonomic control. At the behavioral and relational levels, intervention infants showed increased initiating joint attention, while parents reported higher secure attachment. These findings support a model of experience-dependent early synchrony, in which repeated dyadic interaction through shared book reading shapes the coupling between interpersonal coordination and individual physiological regulation. By linking synchrony, autonomic flexibility, and social engagement, this study identifies a mechanism through which early caregiving experience can organize developmental trajectories following prematurity.","rel_num_authors":12,"rel_authors":[{"author_name":"Laura Lavezzo","author_inst":"Department of Information Engineering, University of Pisa"},{"author_name":"Ben Meuleman","author_inst":"Department of Psychology and Educational Sciences and Swiss Center for Affective Sciences (CISA), Campus Biotech, University of Geneva"},{"author_name":"Didier Grandjean","author_inst":"Department of Psychology and Educational Sciences and Swiss Center for Affective Sciences (CISA)"},{"author_name":"Edouard Gentaz","author_inst":"Department of Psychology and Educational Sciences and Swiss Center for Affective Sciences (CISA), Campus Biotech"},{"author_name":"Sylvain Delplanque","author_inst":"Department of Psychology and Educational Sciences and Swiss Center for Affective Sciences (CISA), Campus Biotech"},{"author_name":"Leonardo Ceravolo","author_inst":"Department of Psychology and Educational Sciences and Swiss Center for Affective Sciences (CISA), Campus Biotech"},{"author_name":"Enzo Pasquale Scilingo","author_inst":"Department of Information Engineering, University of Pisa"},{"author_name":"Petra H\u00fcppi","author_inst":"Department of Paediatrics, Gynaecology and Obstetrics, University of Geneva"},{"author_name":"Francisca Barcos-Munoz","author_inst":"Neonatal Intensive Care Unit, University Hospital of Geneva"},{"author_name":"Cristina Borradori-Tolsa","author_inst":"Department of Paediatrics, Gynaecology and Obstetrics, University of Geneva"},{"author_name":"Mimma Nardelli","author_inst":"Department of Information Engineering, University of Pisa"},{"author_name":"Manuela Filippa","author_inst":"Department of Psychology and Educational Sciences and Swiss Center for Affective Sciences (CISA), Campus Biotech, University of Geneva"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa","rel_doi":"10.64898\/2026.05.19.726084","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726084","rel_abs":"The rise of antibiotic-resistant bacterial infections has driven renewed interest in bacteriophage therapy, where viruses that specifically kill bacteria are used as targeted antimicrobials. Pseudomonas aeruginosa, a WHO critical-priority pathogen that causes severe infections in hospitalized and immunocompromised patients, presents a major challenge for phage therapy because of its extraordinary genetic diversity. Phages effective against one bacterial strain often fail against others, and existing cross-resistance-profiling approaches require iterative empirical testing of each new patient isolate. To establish a genome-based framework for rapid phage-isolate matching, we assembled a collection of 95 genomically diverse P. aeruginosa phages representing 20 genera and tested each against 99 genetically diverse clinical isolates, generating 9,405 infection outcome measurements. Bacterial O-antigen serotype emerged as the dominant determinant of strain susceptibility, while defense systems, anti-defense systems, and prophage burden contributed smaller strain-specific effects. The full curated multivariate model explained 47% of strain-susceptibility variance. Machine-learning models integrating these features and pangenome-derived gene clusters reached a per-strain AUROC of 0.86. In an in vivo proof-of-concept test against a single held-out strain, the ML-designed cocktail produced a [~]12-fold greater median CFU reduction than the expert-designed cocktail (q = 0.045), with both cocktails substantially reducing burden relative to the untreated control ([~]113-fold for ML, [~]9-fold for CG). SHAP analysis of the model identified bacterial surface-architecture genes (LPS biosynthesis, outer membrane proteins, type IV pili) as the dominant predictors, with defense-system content modulating which specific phages succeed against a strain rather than uniformly damping susceptibility. Together, these results establish a genome-based framework for predicting phage susceptibility in genetically diverse clinical isolates.","rel_num_authors":20,"rel_authors":[{"author_name":"Denish Piya","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Avery James Cameron Noonan","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Hemaa Selvakumar","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Mohamad Alayouni","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Sarshad Koderi Valappil","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Flavien Maucourt","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Isabella Murray","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Madeline Svab","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Collis Bousliman","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Matthew Heidenblut","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Britney Orihuela","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Alexey Kazakov","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Hans Carlson","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Yiyan Yao","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Emerson Smith","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Simon Roux","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Adam Deutschbauer","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Jamie Inman","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Adam P Arkin","author_inst":"Lawrence Berkeley National Laboratory"},{"author_name":"Vivek K Mutalik","author_inst":"Lawrence Berkeley National Laboratory"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Electrical and chemical synapses share similar organizational principle","rel_doi":"10.64898\/2026.05.19.726377","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726377","rel_abs":"Electrical transmission is mediated by intercellular channels that cluster into structures known as gap junctions (GJ). In vertebrates, GJ channels are encoded by the gene family of connexin (Cx) proteins that assemble as hexamers, termed hemichannels, in the pre- and postsynaptic membranes, and that subsequently dock to form GJ channels. Auditory contacts on the fish Mauthner cells serve as model to study the properties and organization of vertebrate electrical synapses. Electrical transmission at these synapses is mediated by multiple co-existing GJs at which the presence of intercellular channels is regulated by a molecular scaffold. Zebrafish contain four homologs of the neuronal Cx36: Cx35.5 and Cx35.1 (gjd2a and b, respectively), and Cx34.1 and Cx34.7 (gjd1a and b). Cx mutations suggested that GJs are formed by heterotypic channels made of presynaptic Cx35.5 and postsynaptic Cx34.1. Using transgenic fish in which Cxs were tagged, we found that a second Cx, Cx34.7, is present together with Cx34.1 on the postsynaptic side at some but not all GJs at these terminals. When exogenously expressed, both Cx34.1 and Cx34.7 formed heterotypic functional channels with Cx35.5, each with substantially different voltage-dependent properties, indicating they can serve differential functions. However, we previously demonstrated that electrical transmission is lost in Cx34.1 but not Cx34.7 null mutants, suggesting that Cx34.7 cannot compensate for the loss of Cx34, despite the intrinsic ability of Cx34.1 and Cx34.7 to create functional channels. The findings reveal an unanticipated functional organization in the electrical synapse, where Cx34.1 is obligatory and Cx34.7 accessory, roles that appear to be defined by the postsynaptic molecular scaffold, with two postsynaptic Cxs possibly assembling under specific functional contexts. Thus, our results indicate that electrical synapses share an organizational motif with chemical synapses, akin to how they combine postsynaptic receptor types to modify synaptic function.","rel_num_authors":8,"rel_authors":[{"author_name":"Hannah Hoff","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Sundas Ijaz","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Fabio A. Echeverry","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Stephan Tetenborg","author_inst":"University of Houston"},{"author_name":"Ya-Ping Lin","author_inst":"University of Houston"},{"author_name":"John O'Brien","author_inst":"University of Houston"},{"author_name":"Vytas Verselis","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Alberto E. Pereda","author_inst":"Albert Einstein College of Medicine"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Shiny AMMOA: an interactive platform for integrative multi-omics analysis of murine aging","rel_doi":"10.64898\/2026.05.18.726091","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.726091","rel_abs":"Aging is accompanied by complex, tissue-specific molecular changes across multiple biological layers, yet integrative analysis of multi-omics datasets remains challenging for many experimental researchers due to technical and computational barriers. Here, I present Shiny Aging Murine Multi-Omic Analyzer (Shiny AMMOA), a graphical user interface (GUI)-based, user-friendly analytical platform that enables interactive exploration of murine aging-associated bulk transcriptomic, proteomic, and metabolomic datasets. Shiny AMMOA integrates publicly available multi-omics resources within a unified R Shiny framework and supports end-to-end analyses, including differential expression testing, pathway enrichment analysis, and pathway-level visualization across individual and multiple omics layers. Using representative use cases, I demonstrate that Shiny AMMOA recapitulates key findings from original source studies and facilitates intuitive discovery of tissue-, pathway-, and modality-specific aging signatures, including age-associated alterations in unfolded protein response, extracellular matrix organization, and metabolic pathways across specific tissues and omics layers. The platform further enables integrated visualization of molecular changes across omics layers on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway diagrams, supporting hypothesis generation at the systems level. By democratizing access to integrative multi-omics analysis while preserving analytical rigor, Shiny AMMOA provides an extensible resource for experimental biologists and aging researchers to interrogate large-scale public datasets, prioritize biological pathways, and accelerate translation of multi-omics insights into testable experimental hypotheses. Shiny AMMOA is available at https:\/\/github.com\/M-Ninomiya-Kanda\/Shiny_AMMOA_local, and a lightweight web-based demonstration version with limited functionality is available at https:\/\/m-ninomiya-kanda.shinyapps.io\/shiny_ammoa_web\/.","rel_num_authors":1,"rel_authors":[{"author_name":"Mayuka Ninomiya Kanda","author_inst":"University of California, Berkeley"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Visuospatial coding by theta oscillations in human hippocampus","rel_doi":"10.64898\/2026.05.19.725196","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.725196","rel_abs":"The hippocampus has been proposed to support visual processing and perception, challenging longstanding accounts that emphasize navigation or declarative memory. A key prediction of visual-processing accounts is that the hippocampus should exhibit similar visuospatial coding properties to those of higher-order visual neocortical areas, such as sensitivity to the size of visual stimuli and contralateral visual field biases. We tested for these properties using intracranial EEG to measure hippocampal neural activity during a retinotopic mapping task. The hippocampus exhibited characteristic slow (~2 Hz) and fast (~8 Hz) theta oscillations throughout the task. Fast theta was responsive to the presence but not the amount of visual stimulation. In contrast, slow theta did not generally respond to stimulus presence but scaled with the size of the visual stimulus, consistent with larger receptive fields. Slow theta also showed a contralateral bias, an effect that was specific to the right hippocampus. None of these effects were attributable to microsaccades or performance of the concurrent vigilance task. These findings provide electrophysiological evidence for visual field coding by human hippocampus, supporting accounts of hippocampal function that emphasize its role atop the visual hierarchy. Visual processing of this kind may combine with self-motion, memory, and other signals to support the broader spatial and mnemonic functions with which hippocampal theta oscillations have long been associated.","rel_num_authors":14,"rel_authors":[{"author_name":"Kenneth Rostowsky","author_inst":"University of Chicago"},{"author_name":"Naoum P Issa","author_inst":"University of Chicago"},{"author_name":"Shasha Wu","author_inst":"University of Chicago"},{"author_name":"James X Tao","author_inst":"University of Chicago"},{"author_name":"Hiba A Haider","author_inst":"University of Chicago"},{"author_name":"Sandra L Rose","author_inst":"University of Chicago"},{"author_name":"Peter C Warnke","author_inst":"University of Chicago"},{"author_name":"David Satzer","author_inst":"University of Chicago"},{"author_name":"Rodrigo M Braga","author_inst":"Northwestern University"},{"author_name":"Stephan U Schuele","author_inst":"Northwestern University"},{"author_name":"Anna Shinn","author_inst":"Northwestern University"},{"author_name":"Lingxiao Shi","author_inst":"Northwestern University"},{"author_name":"Joel L Voss","author_inst":"University of Chicago"},{"author_name":"James E Kragel","author_inst":"University of Chicago"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Monosynaptic connections link functionally similar regions in human cortex","rel_doi":"10.64898\/2026.05.19.726279","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.19.726279","rel_abs":"The functional organization of human cortex has been mapped in considerable detail1-5, yet the axonal connections linking these areas remain largely unknown. This gap precludes inferring either the computational pathways through cortical networks or the principles governing why each area connects to its particular target regions. Here, in patients undergoing intracranial monitoring for epilepsy, we used concurrent electrical stimulation and functional magnetic resonance imaging (es-fMRI), validated previously against tracer studies in nonhuman primates6, to map anatomical connectivity of cortical sites across the whole brain, and combined these maps with task and resting-state fMRI in the same individuals. Es-fMRI revealed four main findings. First, connectivity followed an asymmetric functional-similarity principle: connected sites tended to share similar functional profiles, but, because connectivity is sparse, most pairs of functionally similar sites were not connected. Second, although connectivity also declines with distance7, the functional profile explained three times as much variance in connectivity as distance did, and long-range connections were the most functionally specific. Third, es-fMRI revealed direct monosynaptic links between established functional regions, including between the fusiform face area (FFA)2 and the temporoparietal junction (TPJ)3 for social cognition. Fourth, resting-state functional connectivity (rsFC) of a stimulation site was only weakly correlated with that site's es-fMRI connectivity. Together, these results provide a first principled link between anatomical connectivity and functional organization in the human cortex, and establish es-fMRI as a scalable approach to building a tracer-grade connectome of the human brain.","rel_num_authors":23,"rel_authors":[{"author_name":"Rui Xu","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Alan Bush","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Atsushi Takahashi","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Nathaniel Sisterson","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Ashley Walton","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Samuel Hutchinson","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Alexandra Kammen","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Clemens Neudorfer","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Vasileios Kokkinos","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Pranav Nanda","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Niharika Jhingan","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Ammar Marvi","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Alexander Fung","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Suseendrakumar Duraivel","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Eghbal Hosseini","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Colton Casto","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Claudia Valenzuela","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Seonghwan Yee","author_inst":"Department of Radiology, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"John Kirsch","author_inst":"Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA"},{"author_name":"Evelina Fedorenko","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Nancy G. Kanwisher","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"Robert Desimone","author_inst":"McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"author_name":"R. Mark Richardson","author_inst":"Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA"}],"rel_date":"2026-05-20","rel_site":"biorxiv"},{"rel_title":"Statin Exposure and Risk of Dialysis in Type 2 Diabetes: A Real-World Cohort Study","rel_doi":"10.64898\/2026.05.14.26353258","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353258","rel_abs":"Background: Renal effects of statins in type 2 diabetes mellitus (T2DM) remain uncertain. We evaluated whether statin exposure is associated with time to dialysis initiation. Methods: We conducted a retrospective cohort study of adults with T2DM, indexing follow-up at diagnosis during first hospital admission (day 0) between january 2017 and march 2025. Statin use was modeled as time-varying from statin days; (classified in 3 categories: baseline users, new users, and never users). The primary outcome was dialysis. Analysis estimated cause-specific hazards, censoring deaths; proportional hazards were checked with prespecified windows of statin exposure (0?1, 1?3, > 3 years). Competing-risk analyses (Fine?Gray) assessed the sub-distribution hazard of dialysis with death as a competing event in two models: (i) prevalent users at baseline and (ii) new-users with post-initiation intervals of 30 and 90 days. An Observational Medical Outcomes Partnership Common Data Model standardized dataset of a Brazilian quaternary hospital, and the Real-World Data tool MD Clone were used in the study. Results: Of 36,246 adults identified, 32,125 entered the time-varying cohort (39,943 risk intervals; 656 dialysis events); median follow-up among censored patients was 753 days. At baseline, 70.3% never used statins, 5.5% were users (? 0 days), and 24.2% initiated after diagnosis. Crude dialysis incidence was 4.51 vs. 12.31 per 1,000 patient-years during unexposed vs. exposed time. In the adjusted time-varying Cox model, current statin exposure was associated with a modestly higher hazard of dialysis (HR = 1.043, 95% CI 1.011?1.077). In the new-users analysis, HRs were 0.83 (95% CI 0.66?1.05), and 0.73 (95% CI 0.57?0.92) with a 30-day and 90-day intervals, respectively. Conclusions: In this retrospective cohort of hospitalized diabetic patients at baseline, statin initiation at least 90-days in advance is associated with reduced indication of renal replacement therapy.","rel_num_authors":7,"rel_authors":[{"author_name":"cesar truyts","author_inst":"Hospital Israelita Albert Einstein"},{"author_name":"Amanda Rabelo","author_inst":"Sociedade Beneficente Israelita Brasileira Albert Einstein"},{"author_name":"Maria Tereza Abrahao","author_inst":"Hospital Israelita Albert Einstein"},{"author_name":"Mateus de Lima Freitas","author_inst":"Hospital Israelita Albert Einstein"},{"author_name":"Edson Amaro Junior","author_inst":"Hospital Israelita Albert Einstein"},{"author_name":"Rog\u00e9rio Passos","author_inst":"Hospital Israelita Albert Einstein, S\u00e3o Paulo, SP, Brazil"},{"author_name":"Adriano Jose Pereira","author_inst":"Hospital Israelita Albert Einstein"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Prognostic Impact of Early Lactate Trajectory Among Patients Admitted with Cardiogenic Shock","rel_doi":"10.64898\/2026.05.14.26353259","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353259","rel_abs":"Background: The importance of lactate trajectory during the first day of cardiogenic shock is increasingly recognized. We aimed to assess the association between admission-day lactate trajectory and in-hospital mortality, and to identify same-day interventions predictive of lactate clearance. Methods: We analyzed adult patients admitted with cardiogenic shock between October 2015 and June 2023, using the Vizient(R) Clinical Data Base. Early lactate clearance was defined as lactate <2.5 mmol\/L by the end of the admission day. We used multivariable logistic regression to assess the association between lactate change and in-hospital mortality, and to identify interventions associated with lactate clearance. Results: Among 40,434 patients with cardiogenic shock, 30.1% achieved same-day lactate normalization, which was associated with lower in-hospital mortality (aOR 0.51; 95% CI 0.48-0.54). Lactate change showed the greatest prognostic importance, with observed mortality exceeding 80% among those with lactate increase >5 mmol\/L regardless of baseline values. After adjustment, lactate change showed a positive exponential relationship with mortality, with aORs ranging from 0.25 (95% CI 0.23-0.27) for a -10 mmol\/L change to 3.99 (95% CI 3.58-4.40) for a +10 mmol\/L change. The intervention most strongly associated with early lactate clearance was pulmonary artery catheter (PAC; aOR 1.28 [95% CI 1.19-1.37]). Conclusions: Nearly 1 in 3 patients with cardiogenic shock achieved early lactate clearance, which was associated with lower mortality. The magnitude of lactate change had profound prognostic implications regardless of the initial value. Among day 1 interventions, PAC use had the strongest association with lactate clearance.","rel_num_authors":12,"rel_authors":[{"author_name":"Cesar Caraballo","author_inst":"Yale School of Medicine"},{"author_name":"Angela M Victoria-Castro","author_inst":"Yale School of Medicine"},{"author_name":"Aniket Shitalkumar Rali","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Eric J. Hall","author_inst":"University of Texas Southwestern Medical Center"},{"author_name":"Israel Safiriyu","author_inst":"Yale University School of Medicine"},{"author_name":"Jason Neil Katz","author_inst":"NYU Grossman School of Medicine & Bellevue Hospital"},{"author_name":"Ann Gage","author_inst":"TriStar Centennial Medical Center"},{"author_name":"Andrew Philip Notarianni","author_inst":"Yale School of Medicine"},{"author_name":"David M Dudzinski","author_inst":"Massachusetts General Hospital"},{"author_name":"Carlos L Alviar","author_inst":"New York University"},{"author_name":"Guido Tavazzi","author_inst":"Universita degli Studi di Pavia Dipartimento di Scienze Clinico Chirurgiche Diagnostiche e Pediatriche"},{"author_name":"P. Elliott Miller","author_inst":"Yale University School of Medicine"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Prognostic Impact of Early Lactate Trajectory Among Patients Admitted with Cardiogenic Shock","rel_doi":"10.64898\/2026.05.14.26353259","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353259","rel_abs":"Background: The importance of lactate trajectory during the first day of cardiogenic shock is increasingly recognized. We aimed to assess the association between admission-day lactate trajectory and in-hospital mortality, and to identify same-day interventions predictive of lactate clearance. Methods: We analyzed adult patients admitted with cardiogenic shock between October 2015 and June 2023, using the Vizient(R) Clinical Data Base. Early lactate clearance was defined as lactate <2.5 mmol\/L by the end of the admission day. We used multivariable logistic regression to assess the association between lactate change and in-hospital mortality, and to identify interventions associated with lactate clearance. Results: Among 40,434 patients with cardiogenic shock, 30.1% achieved same-day lactate normalization, which was associated with lower in-hospital mortality (aOR 0.51; 95% CI 0.48-0.54). Lactate change showed the greatest prognostic importance, with observed mortality exceeding 80% among those with lactate increase >5 mmol\/L regardless of baseline values. After adjustment, lactate change showed a positive exponential relationship with mortality, with aORs ranging from 0.25 (95% CI 0.23-0.27) for a -10 mmol\/L change to 3.99 (95% CI 3.58-4.40) for a +10 mmol\/L change. The intervention most strongly associated with early lactate clearance was pulmonary artery catheter (PAC; aOR 1.28 [95% CI 1.19-1.37]). Conclusions: Nearly 1 in 3 patients with cardiogenic shock achieved early lactate clearance, which was associated with lower mortality. The magnitude of lactate change had profound prognostic implications regardless of the initial value. Among day 1 interventions, PAC use had the strongest association with lactate clearance.","rel_num_authors":12,"rel_authors":[{"author_name":"Cesar Caraballo","author_inst":"Yale School of Medicine"},{"author_name":"Angela M Victoria-Castro","author_inst":"Yale School of Medicine"},{"author_name":"Aniket Shitalkumar Rali","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Eric J. Hall","author_inst":"University of Texas Southwestern Medical Center"},{"author_name":"Israel Safiriyu","author_inst":"Yale University School of Medicine"},{"author_name":"Jason Neil Katz","author_inst":"NYU Grossman School of Medicine & Bellevue Hospital"},{"author_name":"Ann Gage","author_inst":"TriStar Centennial Medical Center"},{"author_name":"Andrew Philip Notarianni","author_inst":"Yale School of Medicine"},{"author_name":"David M Dudzinski","author_inst":"Massachusetts General Hospital"},{"author_name":"Carlos L Alviar","author_inst":"New York University"},{"author_name":"Guido Tavazzi","author_inst":"Universita degli Studi di Pavia Dipartimento di Scienze Clinico Chirurgiche Diagnostiche e Pediatriche"},{"author_name":"P. Elliott Miller","author_inst":"Yale University School of Medicine"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Comprehensive adjudication identifies 111 high-confidence loci for Alzheimer's disease and related dementias","rel_doi":"10.64898\/2026.05.14.26353247","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353247","rel_abs":"Background: The Alzheimer's Disease Sequencing Project Gene Verification Committee developed a systematic framework to adjudicate genetic evidence for AD and related dementias, addressing wide variation in association quality. Methods: Phase 1 established tiered criteria by evaluating 23 nominated loci across study designs. Phase 2 applied this framework to 29 large-scale genome-wide studies published since 2015, tiering 163 unique loci. Results: Phase 1 yielded 17 high-confidence loci (12 linked to specific genes), and Phase 2 identified 111 high-confidence loci\/genes with replicated associations across ancestries and convergent single-variant\/variant-set evidence. Prioritized loci highlight APP processing, microglial immunity, and lipid metabolism pathways, including genes not captured by existing resources like Agora or Open Targets. Summarized results can be viewed at https:\/\/topgenes.niagads.org\/. Conclusion: This rigorously adjudicated catalog represents the most comprehensive AD\/ADRD genetics resource to date, providing a foundation for functional validation and therapeutic discovery with broad applicability to complex diseases.","rel_num_authors":14,"rel_authors":[{"author_name":"Yuk Yee Leung","author_inst":"University of Pennsylvania"},{"author_name":"Edoardo M Marcora","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Adam Naj","author_inst":"University of pennsylvania"},{"author_name":"Tulsi Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Kathy Sedgwick","author_inst":"Lumina Corps"},{"author_name":"Zivadin Katanic","author_inst":"University of Pennsylvania"},{"author_name":"Ryan M Corces","author_inst":"Gladstone Institute of Neurological Disease"},{"author_name":"Li-San Wang","author_inst":"University of Pennsylvania"},{"author_name":"Richard C Mayeux","author_inst":"Columbia University"},{"author_name":"Alison  M Goate","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Lindsay Farrer","author_inst":"Boston University School of Medicine"},{"author_name":"Gerard  D. Schellenberg","author_inst":"University of Pennsylvania Perelman School of Medicine"},{"author_name":"Brian Kunkle","author_inst":"University of Miami"},{"author_name":"Badri N Vardarajan","author_inst":"Columbia University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Comprehensive adjudication identifies 111 high-confidence loci for Alzheimer's disease and related dementias","rel_doi":"10.64898\/2026.05.14.26353247","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353247","rel_abs":"Background: The Alzheimer's Disease Sequencing Project Gene Verification Committee developed a systematic framework to adjudicate genetic evidence for AD and related dementias, addressing wide variation in association quality. Methods: Phase 1 established tiered criteria by evaluating 23 nominated loci across study designs. Phase 2 applied this framework to 29 large-scale genome-wide studies published since 2015, tiering 163 unique loci. Results: Phase 1 yielded 17 high-confidence loci (12 linked to specific genes), and Phase 2 identified 111 high-confidence loci\/genes with replicated associations across ancestries and convergent single-variant\/variant-set evidence. Prioritized loci highlight APP processing, microglial immunity, and lipid metabolism pathways, including genes not captured by existing resources like Agora or Open Targets. Summarized results can be viewed at https:\/\/topgenes.niagads.org\/. Conclusion: This rigorously adjudicated catalog represents the most comprehensive AD\/ADRD genetics resource to date, providing a foundation for functional validation and therapeutic discovery with broad applicability to complex diseases.","rel_num_authors":14,"rel_authors":[{"author_name":"Yuk Yee Leung","author_inst":"University of Pennsylvania"},{"author_name":"Edoardo M Marcora","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Adam Naj","author_inst":"University of pennsylvania"},{"author_name":"Tulsi Patel","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Kathy Sedgwick","author_inst":"Lumina Corps"},{"author_name":"Zivadin Katanic","author_inst":"University of Pennsylvania"},{"author_name":"Ryan M Corces","author_inst":"Gladstone Institute of Neurological Disease"},{"author_name":"Li-San Wang","author_inst":"University of Pennsylvania"},{"author_name":"Richard C Mayeux","author_inst":"Columbia University"},{"author_name":"Alison  M Goate","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Lindsay Farrer","author_inst":"Boston University School of Medicine"},{"author_name":"Gerard  D. Schellenberg","author_inst":"University of Pennsylvania Perelman School of Medicine"},{"author_name":"Brian Kunkle","author_inst":"University of Miami"},{"author_name":"Badri N Vardarajan","author_inst":"Columbia University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"OmicsPred as a centralised resource for genetic prediction of multi-omic traits","rel_doi":"10.64898\/2026.05.15.26353298","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353298","rel_abs":"Genetic prediction of multi-omic data has emerged as a cost-effective alternative to direct omics profiling, particularly useful for identifying molecular features associated with disease susceptibility. However, despite its popularity, multi-omic imputation models are fragmented across studies, hindering findability, accessibility, interoperability and re-use. To address this, we developed OmicsPred (https:\/\/www.omicspred.org), a centralised platform for the deposition and dissemination of genetic prediction models of multi-omic traits. OmicsPred unifies the most commonly used molecular imputation models (e.g. from PredictDB) and other published studies totalling 3,339,469 prediction models spanning transcriptomic, proteomic, and metabolomic traits (as of May 2026). Each model is accompanied by metadata describing score development and predictive performance, and distributed in formats compatible with popular analytic tools, such as PGS Catalog Calculator and MetaXcan. To demonstrate the utility of the resource for systematic target discovery, we perform a multi-omic phenome-wide association analysis in Million Veterans Program data.","rel_num_authors":9,"rel_authors":[{"author_name":"Carles Foguet","author_inst":"University of Cambridge, Cambridge, UK"},{"author_name":"Laurent Gil","author_inst":"Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK"},{"author_name":"Yu Xu","author_inst":"University of Cambridge, Cambridge, UK"},{"author_name":"Sof\u00eda Salazar-Maga\u00f1a","author_inst":"University of Chicago, Chicago, IL, USA"},{"author_name":"Scott C. Rtichie","author_inst":"University of Cambridge, Cambridge, UK"},{"author_name":"Elodie Persyn","author_inst":"University of Cambridge, Cambridge, UK"},{"author_name":"Hae Kyung Im","author_inst":"University of Chicago, Chicago, IL, USA"},{"author_name":"Michael Inouye","author_inst":"University of Cambridge, Cambridge, UK"},{"author_name":"Samuel A. Lambert","author_inst":"University of Cambridge, Cambridge, UK"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"FAMES: Federated additive model using piecewise exponential survival data","rel_doi":"10.64898\/2026.05.15.26353335","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353335","rel_abs":"Introduction In analyses of time-to-event data, clinical characteristics can have non-linear impacts on survival outcomes, and understanding this dynamic behavior is crucial for producing real-world evidence (RWE). Nonetheless, estimating these dynamic effects is inherently challenging when utilizing real-world data (RWD), especially since sharing individual-level patient data (IPD) is heavily restricted due to regulatory limitations. Additionally, computational difficulties are exacerbated by the high dimensionality, inter-dependency, rarity, sparsity, and scarcity of features. While data augmentation through collaboration across multiple sites might address these challenges, such collaboration is often infeasible and hindered by regulatory measures that protect patient privacy, thereby preventing the sharing of IPD between sites. Objectives To address this challenge, we propose a privacy-preserving regularized algorithm that eliminates the necessity of aggregating any protected health information across sites. This algorithm employs a penalized federated additive model utilizing piecewise exponential survival (FAMES) data and estimates non-linear effects of features while accounting for non-varying confounding effects. The model is flexible and can accommodate both multiple and multivariate smooth effects simultaneously. Methods The proposed model transforms survival data into a piecewise exponential data (PED) structure and casts the semi-parametric optimization problem into a generalized additive modeling framework assuming Poisson distribution. The model uses orthonormal splines to approximate non-linear effects and incorporates L2-norm based penalty terms to control the smoothness and goodness-of-fit of these effects. The algorithm is optimized using site-specific aggregated summary statistics and is solved iteratively through the Newton-Raphson method. Results The model is employed to assess the smooth effects of clinical features, such as age and numeric laboratory values, on overall survival using RWD from approximately 874 newly diagnosed Acute Myeloid Leukemia (AML) patients treated at seven distinct sites in the United States. The model exhibited non-linear smooth effects for lactate dehydrogenase, platelets, and others underscoring their strong association with disease prognosis. The model demonstrates a lossless property, providing estimates of smooth and fixed effects that are comparable to those derived from the pooled PED. Additionally, the inference of parameters for testing the nullity of effects remains consistent. This model is communication-efficient, necessitating roughly twelve rounds of communication across sites. Conclusion We anticipate that this model can facilitate multisite collaboration and enable smaller sites to participate in generating and validating RWE, especially for rare diseases. While the model was applied within the context of AML, it is disease-agnostic and can be implemented in any other clinical context and across various sites globally without losing any generality.","rel_num_authors":7,"rel_authors":[{"author_name":"Nazmul Islam","author_inst":"RefinedScience"},{"author_name":"Chongliang Luo","author_inst":"Division of Public Health Sciences, Washington University, St. Louis, Missouri, USA"},{"author_name":"Jiayi Tong","author_inst":"School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Grant Weller","author_inst":"RefinedScience, Aurora, Colorado, USA"},{"author_name":"Daniel A Polleya","author_inst":"Division of Hematology, Department of Medicine, University of Colorado Anschutz Campus, Aurora, Colorado, USA"},{"author_name":"Andrew Kent","author_inst":"Division of Hematology, Department of Medicine, University of Colorado Anschutz Campus, Aurora, Colorado, USA"},{"author_name":"Steven Bair","author_inst":"Division of Hematology, Department of Medicine, University of Colorado Anschutz Campus, Aurora, Colorado, USA"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"FAMES: Federated additive model using piecewise exponential survival data","rel_doi":"10.64898\/2026.05.15.26353335","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353335","rel_abs":"Introduction In analyses of time-to-event data, clinical characteristics can have non-linear impacts on survival outcomes, and understanding this dynamic behavior is crucial for producing real-world evidence (RWE). Nonetheless, estimating these dynamic effects is inherently challenging when utilizing real-world data (RWD), especially since sharing individual-level patient data (IPD) is heavily restricted due to regulatory limitations. Additionally, computational difficulties are exacerbated by the high dimensionality, inter-dependency, rarity, sparsity, and scarcity of features. While data augmentation through collaboration across multiple sites might address these challenges, such collaboration is often infeasible and hindered by regulatory measures that protect patient privacy, thereby preventing the sharing of IPD between sites. Objectives To address this challenge, we propose a privacy-preserving regularized algorithm that eliminates the necessity of aggregating any protected health information across sites. This algorithm employs a penalized federated additive model utilizing piecewise exponential survival (FAMES) data and estimates non-linear effects of features while accounting for non-varying confounding effects. The model is flexible and can accommodate both multiple and multivariate smooth effects simultaneously. Methods The proposed model transforms survival data into a piecewise exponential data (PED) structure and casts the semi-parametric optimization problem into a generalized additive modeling framework assuming Poisson distribution. The model uses orthonormal splines to approximate non-linear effects and incorporates L2-norm based penalty terms to control the smoothness and goodness-of-fit of these effects. The algorithm is optimized using site-specific aggregated summary statistics and is solved iteratively through the Newton-Raphson method. Results The model is employed to assess the smooth effects of clinical features, such as age and numeric laboratory values, on overall survival using RWD from approximately 874 newly diagnosed Acute Myeloid Leukemia (AML) patients treated at seven distinct sites in the United States. The model exhibited non-linear smooth effects for lactate dehydrogenase, platelets, and others underscoring their strong association with disease prognosis. The model demonstrates a lossless property, providing estimates of smooth and fixed effects that are comparable to those derived from the pooled PED. Additionally, the inference of parameters for testing the nullity of effects remains consistent. This model is communication-efficient, necessitating roughly twelve rounds of communication across sites. Conclusion We anticipate that this model can facilitate multisite collaboration and enable smaller sites to participate in generating and validating RWE, especially for rare diseases. While the model was applied within the context of AML, it is disease-agnostic and can be implemented in any other clinical context and across various sites globally without losing any generality.","rel_num_authors":7,"rel_authors":[{"author_name":"Nazmul Islam","author_inst":"RefinedScience"},{"author_name":"Chongliang Luo","author_inst":"Division of Public Health Sciences, Washington University, St. Louis, Missouri, USA"},{"author_name":"Jiayi Tong","author_inst":"School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Grant Weller","author_inst":"RefinedScience, Aurora, Colorado, USA"},{"author_name":"Daniel A Polleya","author_inst":"Division of Hematology, Department of Medicine, University of Colorado Anschutz Campus, Aurora, Colorado, USA"},{"author_name":"Andrew Kent","author_inst":"Division of Hematology, Department of Medicine, University of Colorado Anschutz Campus, Aurora, Colorado, USA"},{"author_name":"Steven Bair","author_inst":"Division of Hematology, Department of Medicine, University of Colorado Anschutz Campus, Aurora, Colorado, USA"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Calibrated Prediction Intervals for Polygenic Scores: Updated Comparisons, Contextual Calibration, and Data Normalization","rel_doi":"10.64898\/2026.05.15.26353336","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353336","rel_abs":"Calibrated prediction intervals for polygenic scores (PGS) are essential for communicating individual-level uncertainty in genomic medicine. We present updated comparisons of two methods for constructing such intervals: CalPred, a parametric approach, and PredInterval, a non-parametric approach. Our results show that both methods can achieve calibrated coverage, although CalPred additionally requires a sufficiently large calibration set. The two methods also exhibit complementary trade-offs with respect to dataset size and risk identification. We further show that contextual calibration, as introduced in Hou et al. and followed in Shi et al., is most naturally achieved through appropriate phenotype normalization and data preprocessing. Apparent miscalibration can arise from inadequate normalization or from providing contextual information to some methods but not others. In UK Biobank, standard GWAS phenotype normalization procedures are sufficient to achieve contextual calibration for traits analyzed. In the extreme simulations of Hou et al. and Shi et al., supplying contextual covariates to PredInterval restores contextual calibration without normalization, and appropriate normalization can achieve contextual calibration without supplying covariates, while also substantially improving upstream tasks including association power and PGS accuracy. Together, these results underscore the central role of phenotype normalization and data preprocessing in GWAS analyses, including reliable uncertainty quantification for PGS.","rel_num_authors":3,"rel_authors":[{"author_name":"Xu Chang","author_inst":"University of Michigan"},{"author_name":"Siyu Hou","author_inst":"Yale University"},{"author_name":"Xiang Zhou","author_inst":"Yale University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"A Multi-Context Regulome-Wide Association Atlas for Genetic Studies of Aging Brain Disorders","rel_doi":"10.64898\/2026.05.15.26353329","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353329","rel_abs":"Genome-wide association studies have identified risk loci for aging brain disorders, but mechanistic interpretation depends on linking these loci to genes and to the tissues, cell types, and molecular modalities in which those genes act. Here we introduce FunGen-xQTL Multi-Brain (FGMB), a multi-context regulome-wide association atlas for transcriptome-wide association studies (TWAS) built from molecular datasets assembled by the ADSP Functional Genomics Consortium. FGMB provides cis-genetic prediction models for 17,375 protein-coding genes across 36 molecular datasets, 18 contexts, and 3 regulatory modalities, yielding more than 293,000 imputable gene-level or splice-event models. FGMB evaluates eight established and newer Bayesian or multivariate prediction methods, including cross-context models that borrow information across tissues and cell types. Applied to Alzheimer's disease, FGMB identified 327 TWAS associations and used joint fine-mapping of variants and predicted molecular traits to prioritize 146 gene--molecular-trait pairs, distinguishing regulatory associations from linkage disequilibrium (LD) hitchhiking.","rel_num_authors":14,"rel_authors":[{"author_name":"Chunming Liu","author_inst":"Clemson University"},{"author_name":"Anqi Wang","author_inst":"Columbia University"},{"author_name":"Hao Sun","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Kaixuan Luo","author_inst":"University of Chicago"},{"author_name":"Sheng Qian","author_inst":"University of Chicago"},{"author_name":"Yining Li","author_inst":"Columbia University"},{"author_name":"Xin He","author_inst":"University of Chicago"},{"author_name":"Phillip De Jager","author_inst":"Columbia University"},{"author_name":"David  A Bennett","author_inst":"Rush University Medical Center"},{"author_name":"Minghui Wang","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"- The Alzheimer's Disease Functional Genomics Consortium","author_inst":""},{"author_name":"Gao Wang","author_inst":"Columbia University"},{"author_name":"Fabio Morgante","author_inst":"Clemson University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"A Multi-Context Regulome-Wide Association Atlas for Genetic Studies of Aging Brain Disorders","rel_doi":"10.64898\/2026.05.15.26353329","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353329","rel_abs":"Genome-wide association studies have identified risk loci for aging brain disorders, but mechanistic interpretation depends on linking these loci to genes and to the tissues, cell types, and molecular modalities in which those genes act. Here we introduce FunGen-xQTL Multi-Brain (FGMB), a multi-context regulome-wide association atlas for transcriptome-wide association studies (TWAS) built from molecular datasets assembled by the ADSP Functional Genomics Consortium. FGMB provides cis-genetic prediction models for 17,375 protein-coding genes across 36 molecular datasets, 18 contexts, and 3 regulatory modalities, yielding more than 293,000 imputable gene-level or splice-event models. FGMB evaluates eight established and newer Bayesian or multivariate prediction methods, including cross-context models that borrow information across tissues and cell types. Applied to Alzheimer's disease, FGMB identified 327 TWAS associations and used joint fine-mapping of variants and predicted molecular traits to prioritize 146 gene--molecular-trait pairs, distinguishing regulatory associations from linkage disequilibrium (LD) hitchhiking.","rel_num_authors":14,"rel_authors":[{"author_name":"Chunming Liu","author_inst":"Clemson University"},{"author_name":"Anqi Wang","author_inst":"Columbia University"},{"author_name":"Hao Sun","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Kaixuan Luo","author_inst":"University of Chicago"},{"author_name":"Sheng Qian","author_inst":"University of Chicago"},{"author_name":"Yining Li","author_inst":"Columbia University"},{"author_name":"Xin He","author_inst":"University of Chicago"},{"author_name":"Phillip De Jager","author_inst":"Columbia University"},{"author_name":"David  A Bennett","author_inst":"Rush University Medical Center"},{"author_name":"Minghui Wang","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"- The Alzheimer's Disease Functional Genomics Consortium","author_inst":""},{"author_name":"Gao Wang","author_inst":"Columbia University"},{"author_name":"Fabio Morgante","author_inst":"Clemson University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"A Multi-Context Regulome-Wide Association Atlas for Genetic Studies of Aging Brain Disorders","rel_doi":"10.64898\/2026.05.15.26353329","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353329","rel_abs":"Genome-wide association studies have identified risk loci for aging brain disorders, but mechanistic interpretation depends on linking these loci to genes and to the tissues, cell types, and molecular modalities in which those genes act. Here we introduce FunGen-xQTL Multi-Brain (FGMB), a multi-context regulome-wide association atlas for transcriptome-wide association studies (TWAS) built from molecular datasets assembled by the ADSP Functional Genomics Consortium. FGMB provides cis-genetic prediction models for 17,375 protein-coding genes across 36 molecular datasets, 18 contexts, and 3 regulatory modalities, yielding more than 293,000 imputable gene-level or splice-event models. FGMB evaluates eight established and newer Bayesian or multivariate prediction methods, including cross-context models that borrow information across tissues and cell types. Applied to Alzheimer's disease, FGMB identified 327 TWAS associations and used joint fine-mapping of variants and predicted molecular traits to prioritize 146 gene--molecular-trait pairs, distinguishing regulatory associations from linkage disequilibrium (LD) hitchhiking.","rel_num_authors":14,"rel_authors":[{"author_name":"Chunming Liu","author_inst":"Clemson University"},{"author_name":"Anqi Wang","author_inst":"Columbia University"},{"author_name":"Hao Sun","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Kaixuan Luo","author_inst":"University of Chicago"},{"author_name":"Sheng Qian","author_inst":"University of Chicago"},{"author_name":"Yining Li","author_inst":"Columbia University"},{"author_name":"Xin He","author_inst":"University of Chicago"},{"author_name":"Phillip De Jager","author_inst":"Columbia University"},{"author_name":"David  A Bennett","author_inst":"Rush University Medical Center"},{"author_name":"Minghui Wang","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Carlos Cruchaga","author_inst":"Washington University St. Louis"},{"author_name":"- The Alzheimer's Disease Functional Genomics Consortium","author_inst":""},{"author_name":"Gao Wang","author_inst":"Columbia University"},{"author_name":"Fabio Morgante","author_inst":"Clemson University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Negative Contextual Valence Unmasks Altered Counterfactual Decision-Making in Major Depressive Disorder","rel_doi":"10.64898\/2026.05.15.26353249","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353249","rel_abs":"Background: While counterfactual thinking ('what could have been') guides adaptive decision-making, it remains unclear how this process is altered by the negative biases and motivational deficits characteristic of Major Depressive Disorder (MDD). Methods: We used a sequential economic decision-making task designed to emulate a volatile stock market to assess choice behavior in adults with or without MDD (Total N=178); a subset of these participants completed the task during functional MRI (N=53). The task allowed participants to make either positive ('invest') or negative ('short') bets, under either positive or negative contextual valence, defined by whether the immediately preceding stock price change was positive or negative. Fictive errors were defined as the difference between realized and best-possible outcomes. Results: Across the full cohort, group differences in behavioral adjustments to fictive error signals emerged exclusively under negative contextual valence, when stock prices decreased. Compared with controls, participants with MDD showed heightened sensitivity to invest-and-loss fictive errors, reflected in a greater reduction in subsequent bets (interaction beta = -0.63, p < .001), but blunted adjustment to short-and-gain fictive errors (beta = -0.86, p < .001). In the imaging cohort, blunted short-and-gain adjustment was accompanied by heightened anterior cingulate (ACC) activity and attenuated ventromedial prefrontal (vmPFC)-to-ACC coupling in MDD. vmPFC activity following negative market returns also tracked depression symptom severity. Conclusions: Depression selectively disrupts the use of counterfactual outcomes to guide adaptive choice under negative contextual valence, implicating altered frontocingulate function in maladaptive decision-making.","rel_num_authors":8,"rel_authors":[{"author_name":"Avijit Chowdhury","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Philipp Neukam","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ofer Perl","author_inst":"University of Haifa"},{"author_name":"Matthew Heflin","author_inst":"Yale School of Medicine"},{"author_name":"Yael Jacob","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Laurel S. Morris","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Xiaosi Gu","author_inst":"Yale School of Medicine"},{"author_name":"James W. Murrough MD, PhD","author_inst":"Icahn School of Medicine at Mount Sinai"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Predicting Intensive Care Readmission Among Hospitalized Children","rel_doi":"10.64898\/2026.05.15.26353330","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.15.26353330","rel_abs":"Objective: Readmissions to the PICU are associated with increased morbidity and mortality. A prediction model that can identify children at risk of readmission at the time of transfer can allow providers to intervene and potentially improve patient outcomes. The objective of this study was to derive and validate machine learning models to predict PICU readmission at the time of transfer. Design: Retrospective observational cohort study Setting: Three quaternary care PICUs in the city of Chicago Patients: All children admitted to the PICU between 2012 and 2019. Measurements: The primary outcome was unplanned readmission to the PICU within 48 hours of transfer to the inpatient ward. Predictor variables included vital signs, patient characteristics, and laboratory results. We developed and externally validated four models to predict PICU readmission: logistic regression, elastic net, random forest, and XGBoost. Main Results: This study included 35,601 patients, with readmission rates ranging from 2.2-3.7% by site. The performance of models during internal validation was consistent at the three sites, with the area under the receiver operating characteristic (AUC) values between 0.70 and 0.73 and no difference across the four models. Model performance decreased significantly during external validation (AUCs of 0.60-0.69). The variables most important to the prediction differed at each site. Conclusion: Machine learning models for predicting readmissions to the PICU have limited generalizability. Locally derived models demonstrated modest performance in our study and could potentially inform provider decision-making if prospectively validated. Externally developed models are unlikely to perform well at predicting PICU readmissions.","rel_num_authors":7,"rel_authors":[{"author_name":"Ahmed Arshad","author_inst":"University of Oklahoma"},{"author_name":"Kyle A Carey","author_inst":"University of Chicago"},{"author_name":"Latasha A Daniels","author_inst":"Ann & Robert H. Lurie Children's Hospital"},{"author_name":"Priti Jani","author_inst":"University of Chicago"},{"author_name":"Emily Gilbert","author_inst":"Loyola University"},{"author_name":"Lazaro Nelson Sanchez-Pinto","author_inst":"Ann & Robert H. Lurie Children's Hospital"},{"author_name":"Anoop Mayampurath","author_inst":"University of Wisconsin-Madison"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Predicting Distant Melanoma Metastasis at Diagnosis Using Machine Learning","rel_doi":"10.64898\/2026.05.14.26353271","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353271","rel_abs":"Distant melanoma metastasis at the time of diagnosis is uncommon, but has major implications for patient prognosis and treatment selection. However, few tools can reliably predict the risk of distant metastasis at initial presentation. Here, we developed and evaluated machine learning models to predict distant melanoma metastasis using routinely captured clinicopathologic and demographic variables across all histologic subtypes. Using the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program from 2010-2022, we identified adults aged 20 to 90 years with melanoma as the first and only primary malignancy (n=51,285). Explainable Boosting Machine achieved a strong balance of discrimination and precision (AUROC = 0.947, AUPRC = 0.610, Precision = 0.793, Brier = 0.015). At 90% sensitivity, specificity was 0.843 with consistent performance across cross-validation folds. Clinicopathologic variables, including T stage, Breslow thickness, ulceration, and mitotic activity, contributed the largest share of predictive signal across descriptive, regression-based, and SHAP analyses, with smaller contributions from demographic factors. Decision curve analysis supported clinical utility, showing a net reduction of 88.3 per 100 patients and a standardized net benefit of 0.541. This model could be used to identify patients at sufficiently elevated risk to justify staging PET\/CT despite otherwise localized clinical presentation. Cost-consequence analysis further showed that imaging true- and false-positive patients at 85% to 95% sensitivity threshold nearly doubled downstream imaging cost. We deployed the final model as an online calculator to support exploration of individualized risk estimates (https:\/\/melanoma-calculator.streamlit.app\/).","rel_num_authors":8,"rel_authors":[{"author_name":"Jeff Jeong Hun Kim","author_inst":"University of Illinois Chicago"},{"author_name":"James W.Y. Lee","author_inst":"Carle Illinois College of Medicine"},{"author_name":"Heidi Yuan","author_inst":"University of Illinois Chicago"},{"author_name":"Chen Han","author_inst":"University of Illinois Chicago"},{"author_name":"Mehrdad Zandigohar","author_inst":"University of Illinois Chicago"},{"author_name":"Roger Haber","author_inst":"University of Illinois Chicago"},{"author_name":"Maria Tsoukas","author_inst":"University of Illinois Chicago"},{"author_name":"Kamran Avanaki","author_inst":"University of Illinois Chicago"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Genomic epidemiology as a tool for understanding drivers of hepatitis A community outbreaks in Massachusetts and New Hampshire","rel_doi":"10.64898\/2026.05.14.26352933","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26352933","rel_abs":"Despite the existence of an effective vaccine, the United States continues to experience outbreaks of hepatitis A, including in Massachusetts (MA) and New Hampshire (NH) in 2018 and again in MA in 2023. To clarify the relationship between these outbreaks and better understand their drivers, we generated hepatitis A virus whole genome sequences from reported cases and analyzed them using open-source genotyping tools developed and released as part of this study. We found that the 2018 and 2023 outbreaks were caused by distinct viral strains, despite affecting individuals with similar demographic characteristics and reported risk factors. Detailed analysis of genomic and epidemiologic data further resolved transmission patterns within and across outbreaks, showing that experiencing homelessness and prior use of drugs were associated with increased transmission while also revealing transmission between individuals with and without these risk factors, as well as spread across state borders. Together, these findings demonstrate the value of broadly accessible genomic tools for understanding hepatitis A outbreaks and illustrate how whole genome analysis can complement epidemiological investigation by resolving transmission patterns and outbreak drivers that can inform public health interventions.","rel_num_authors":36,"rel_authors":[{"author_name":"Lydia A Krasilnikova","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Lindsay Bouton","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Taylor M Brock-Fisher","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Emily Decker","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Mary Godec","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Zachary Thompson","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Emily Dart","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Fengxiang Gao","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Adrianne Gladden-Young","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Katelyn S Messer","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Josh Norville","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Ivan Specht","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Anthony Osinski","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Jinfeng Li","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Carrie Lones","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Katherine C DeRuff","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Katherine J Siddle","author_inst":"Department of Molecular Microbiology and Immunology, Brown University"},{"author_name":"Daniel Church","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Christopher Benton","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Katrina Hansen","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Hannah Bowen","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Sanjib Bhattacharyya","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Nicolas Epie","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Catherine M Brown","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Lawrence C Madoff","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Bronwyn L MacInnis","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Glen R Gallagher","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Sandra Smole","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Christine Bean","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Elizabeth A Talbot","author_inst":"New Hampshire Division of Public Health, Department of Health and Human Services"},{"author_name":"Meagan Burns","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Matthew Doucette","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Esther Fortes","author_inst":"Massachusetts Department of Public Health"},{"author_name":"Daniel J Park","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Pardis C Sabeti","author_inst":"Broad Institute of MIT and Harvard"},{"author_name":"Shirlee Wohl","author_inst":"Massachusetts Department of Public Health"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"MR-Guided PET Denoising and Resolution Enhancement Improves Visual Interpretation and Preserves Quantitative Behavior Across Amyloid Tracers","rel_doi":"10.64898\/2026.05.14.26353149","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353149","rel_abs":"Background: Amyloid-beta PET provides critical biomarker data for Alzheimer's disease diagnosis and anti-amyloid therapy evaluation, yet low spatial resolution and partial volume effects result in decreased interpretability, particularly in cases with low or borderline cortical amyloid burden. While quantitative metrics (SUVr, Centiloid) aid in interpretation of amyloid burden, disagreement between visual reads and quantitative burden does occur, further blurring the line between positive or negative scans. We evaluated whether a vendor-neutral MR-guided PET denoising and resolution enhancement method (MRG) that uses Bowsher regularization improves image interpretability and reader performance while preserving established quantitative biomarkers across multiple amyloid tracers, leading to increased concordance among visual reads and quantitative metrics. Methods: Standard (STN) and MRG PET images were compared for four tracers ([18F]AV-45 ([18F]florbetapir, FBP), [18F]florbetaben (FBB), [18F]flutemetamol (FMM), and [11C]Pittsburgh compound-B (PiB) collectively from 24 MRI and 33 PET scanners. Quantitative equivalence was assessed by comparing Standardized Uptake Value ratio (SUVr) and Centiloid scores. In three of the four tracers (FBP, FBB, FMM), visual-quantitative concordance (AUC) and reader performance were evaluated in a blinded multi-reader study by four highly experienced brain PET readers who assessed image quality, artifact severity, reader confidence, and binary amyloid positivity. Results: Across all tracers, MRG preserved quantitative SUVr and Centiloid metrics relative to STN (R2 >0.90 for all tracers) without introducing bias to the SUVr metric. Concordance between visual reads and quantitative burden measures significantly improved with MRG. In the multi-reader study, MRG resulted in significantly higher image quality, lower artifact burden, and greater reader confidence compared to STN (p < 0.0001). Reader accuracy increased from 0.89 to 0.94, and the false-negative rate decreased from 0.08 to 0.04. Crucially, improvements in reader confidence, accuracy, and the reduction in false negative reads were most pronounced in cases with low amyloid burden near the threshold of visual positivity. Conclusions: MRG denoising and resolution enhancement improved perceived image quality, reader confidence, and accuracy for amyloid PET while preserving standard quantitative behavior across tracers. By improving cortical definition in visually challenging low-burden cases without disrupting established SUVr\/Centiloid behavior, MRG may reduce visual-quantitative discordance and support more confident amyloid PET interpretation near the threshold of positivity.","rel_num_authors":9,"rel_authors":[{"author_name":"Caroline Szujewski","author_inst":"Microstructure Imaging, Inc., 370 Jay St FL7, Brooklyn, NY 11201, USA"},{"author_name":"Timothy M Shepherd","author_inst":"Department of Radiology, NYU Langone Health, New York, NY, USA"},{"author_name":"Munir Ghesani","author_inst":"Department of Radiology, Mount Sinai Health System, New York, NY, USA"},{"author_name":"Maria Ponisio","author_inst":"Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA"},{"author_name":"William Lavely","author_inst":"Northside Radiology Associates, Atlanta, GA, USA"},{"author_name":"Georg Schramm","author_inst":"Department of Imaging and Pathology, KU Leuven, Leuven, Belgium"},{"author_name":"Ariane Bollack","author_inst":"GE HealthCare, Chalfont St Giles HP8 4SP, UK"},{"author_name":"Benjamin Ades-aron","author_inst":"Microstructure Imaging, Inc., 370 Jay St FL7, Brooklyn, NY 11201, USA"},{"author_name":"Gregory Lemberskiy","author_inst":"Microstructure Imaging, Inc., 370 Jay St FL7, Brooklyn, NY 11201, USA"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Prevalence, Genetics, and Imaging Characteristics of Patients with Mitral Valve Prolapse and Arrhythmogenic Right Ventricular Cardiomyopathy","rel_doi":"10.64898\/2026.05.14.26353246","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353246","rel_abs":"Background: Concomitant arrhythmogenic right ventricular cardiomyopathy (ARVC) and mitral valve prolapse (MVP) has only been described in case reports. Little is known about genetic and phenotypic characteristics of these patients. Objective: To describe the prevalence, genetics, and imaging characteristics of MVP in ARVC patients. Methods: We identified 111 definite ARVC cases through medical record review, arrhythmia\/cardiomyopathy targeted gene panels, and contrast cardiac magnetic resonance data. MVP was diagnosed on echocardiography as mitral leaflet displacement greater than 2 mm above the annular plane in systole, with borderline MVP defined as less than or equal to 2 mm. Results: We found MVP\/borderline MVP in 14% of ARVC patients. Cardiac arrest occurred in 20% of those with MVP\/borderline MVP compared to 16% without valve abnormalities. Among 69 ARVC patients with identified genetic variants, PKP2 mutations were highly prevalent (64%), particularly in those with MVP (83%). Most MVPs had posterior prolapse (73%) and trace\/mild mitral regurgitation (87%). None had mitral annular disjunction. ARVCs with MVP had higher LV mass (93 vs. 75 g\/m2, p = 0.02) and a higher prevalence of LV wall motion abnormalities (27% vs. 5%, p = 0.02) compared to ARVCs without valve abnormalities. Conclusions: MVP is prevalent in ARVC and characterized by PKP2 variants in most cases. Typical features of arrhythmic MVP like bileaflet involvement and annular disjunction are rare in ARVC with MVP; features of arrhythmogenic left-sided cardiomyopathy (increased LV mass index and wall motion abnormalities) are more common. Further studies are needed to understand the role of MVP in arrhythmic risk stratification of ARVC.","rel_num_authors":7,"rel_authors":[{"author_name":"Amy Hannah Rich","author_inst":"University of California, San Francisco"},{"author_name":"Lionel Tastet","author_inst":"Institut universitaire de cardiologie et de pneumologie de Quebec"},{"author_name":"Luca Cristin","author_inst":"University of California, San Francisco"},{"author_name":"Rohit Jhawar","author_inst":"University of California, San Francisco"},{"author_name":"Janet J. Tang","author_inst":"University of California, San Francisco"},{"author_name":"Melvin Scheinman","author_inst":"University of California, San Francisco"},{"author_name":"Francesca Delling","author_inst":"University of California, San Francisco"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Prevalence, Genetics, and Imaging Characteristics of Patients with Mitral Valve Prolapse and Arrhythmogenic Right Ventricular Cardiomyopathy","rel_doi":"10.64898\/2026.05.14.26353246","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353246","rel_abs":"Background: Concomitant arrhythmogenic right ventricular cardiomyopathy (ARVC) and mitral valve prolapse (MVP) has only been described in case reports. Little is known about genetic and phenotypic characteristics of these patients. Objective: To describe the prevalence, genetics, and imaging characteristics of MVP in ARVC patients. Methods: We identified 111 definite ARVC cases through medical record review, arrhythmia\/cardiomyopathy targeted gene panels, and contrast cardiac magnetic resonance data. MVP was diagnosed on echocardiography as mitral leaflet displacement greater than 2 mm above the annular plane in systole, with borderline MVP defined as less than or equal to 2 mm. Results: We found MVP\/borderline MVP in 14% of ARVC patients. Cardiac arrest occurred in 20% of those with MVP\/borderline MVP compared to 16% without valve abnormalities. Among 69 ARVC patients with identified genetic variants, PKP2 mutations were highly prevalent (64%), particularly in those with MVP (83%). Most MVPs had posterior prolapse (73%) and trace\/mild mitral regurgitation (87%). None had mitral annular disjunction. ARVCs with MVP had higher LV mass (93 vs. 75 g\/m2, p = 0.02) and a higher prevalence of LV wall motion abnormalities (27% vs. 5%, p = 0.02) compared to ARVCs without valve abnormalities. Conclusions: MVP is prevalent in ARVC and characterized by PKP2 variants in most cases. Typical features of arrhythmic MVP like bileaflet involvement and annular disjunction are rare in ARVC with MVP; features of arrhythmogenic left-sided cardiomyopathy (increased LV mass index and wall motion abnormalities) are more common. Further studies are needed to understand the role of MVP in arrhythmic risk stratification of ARVC.","rel_num_authors":7,"rel_authors":[{"author_name":"Amy Hannah Rich","author_inst":"University of California, San Francisco"},{"author_name":"Lionel Tastet","author_inst":"Institut universitaire de cardiologie et de pneumologie de Quebec"},{"author_name":"Luca Cristin","author_inst":"University of California, San Francisco"},{"author_name":"Rohit Jhawar","author_inst":"University of California, San Francisco"},{"author_name":"Janet J. Tang","author_inst":"University of California, San Francisco"},{"author_name":"Melvin Scheinman","author_inst":"University of California, San Francisco"},{"author_name":"Francesca Delling","author_inst":"University of California, San Francisco"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Wastewater Surveillance as an Event Detection System: Outbreak and Peak Detection of SARS-CoV-2 Across 281 U.S. Counties","rel_doi":"10.64898\/2026.05.14.26353186","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353186","rel_abs":"Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.","rel_num_authors":4,"rel_authors":[{"author_name":"Nicholas B Link","author_inst":"Network Science Institute, Northeastern University"},{"author_name":"Raul Garrido","author_inst":"Network Science Institute, Northeastern University; Physics Department, Northeastern University"},{"author_name":"Anjalika Nande","author_inst":"Nuffield Department of Primary Care Health Sciences, University of Oxford; Institute for Computational Medicine, Johns Hopkins University"},{"author_name":"Mauricio Santillana","author_inst":"Network Science Institute, Northeastern University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Wastewater Surveillance as an Event Detection System: Outbreak and Peak Detection of SARS-CoV-2 Across 281 U.S. Counties","rel_doi":"10.64898\/2026.05.14.26353186","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.05.14.26353186","rel_abs":"Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.","rel_num_authors":4,"rel_authors":[{"author_name":"Nicholas B Link","author_inst":"Network Science Institute, Northeastern University"},{"author_name":"Raul Garrido","author_inst":"Network Science Institute, Northeastern University; Physics Department, Northeastern University"},{"author_name":"Anjalika Nande","author_inst":"Nuffield Department of Primary Care Health Sciences, University of Oxford; Institute for Computational Medicine, Johns Hopkins University"},{"author_name":"Mauricio Santillana","author_inst":"Network Science Institute, Northeastern University"}],"rel_date":"2026-05-19","rel_site":"medrxiv"},{"rel_title":"Variant emergence, not vaccine deployment, drives episodic positive selection on the SARS-CoV-2 spike at provincial scale in Canada","rel_doi":"10.64898\/2026.05.16.725625","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.16.725625","rel_abs":"Mass immunization against SARS-CoV-2 created a heterogeneous landscape of antibody-mediated immune pressure, yet whether this pressure measurably altered episodic positive selection on spike remains unresolved. Using Canadian genomic surveillance data spanning the five major variants of concern (Alpha, Beta, Gamma, Delta, and Omicron), we inferred time-resolved phylogenies from spike-coding sequences and applied site- and branch-level episodic selection models to identify when and where adaptive change occurred. To evaluate whether vaccination intensity was associated with selection, we integrated these phylogenetic analyses with provincial vaccination time series using cross-correlation and lagged panel regression models that accounted for province and time effects, lineage prevalence, and sampling heterogeneity. Episodic positive selection was concentrated at a limited number of spike codons, especially within the N-terminal domain, receptor-binding domain, and furin cleavage region. However, these signals were dominated by substitutions associated with variant emergence, particularly during the Alpha-to-Delta transition, rather than by vaccination rollout. Whole-gene tests provided no evidence that vaccine intensity was associated with elevated episodic selection, and residualized vaccination trajectories did not predict selection at biologically plausible lags. Across provinces, the timing and distribution of selection events were inconsistent with a vaccine-driven escape model. Together, these results indicate that, at provincial resolution in Canada, episodic positive selection on SARS-CoV-2 spike was driven primarily by variant turnover rather than vaccine deployment. More broadly, this study provides a quantitative, VOC-resolved assessment of spike evolution in a structured epidemic and suggests that population-level vaccination intensity was not a detectable determinant of spike adaptation in the period examined.","rel_num_authors":4,"rel_authors":[{"author_name":"Marissa Tomas","author_inst":"University of Ottawa"},{"author_name":"Cheikh Pape Khary Ndongo","author_inst":"University of Ottawa"},{"author_name":"Matthieu Vilain","author_inst":"University of Ottawa"},{"author_name":"Stephane Aris-Brosou","author_inst":"University of Ottawa"}],"rel_date":"2026-05-19","rel_site":"biorxiv"},{"rel_title":"Variant emergence, not vaccine deployment, drives episodic positive selection on the SARS-CoV-2 spike at provincial scale in Canada","rel_doi":"10.64898\/2026.05.16.725625","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.16.725625","rel_abs":"Mass immunization against SARS-CoV-2 created a heterogeneous landscape of antibody-mediated immune pressure, yet whether this pressure measurably altered episodic positive selection on spike remains unresolved. Using Canadian genomic surveillance data spanning the five major variants of concern (Alpha, Beta, Gamma, Delta, and Omicron), we inferred time-resolved phylogenies from spike-coding sequences and applied site- and branch-level episodic selection models to identify when and where adaptive change occurred. To evaluate whether vaccination intensity was associated with selection, we integrated these phylogenetic analyses with provincial vaccination time series using cross-correlation and lagged panel regression models that accounted for province and time effects, lineage prevalence, and sampling heterogeneity. Episodic positive selection was concentrated at a limited number of spike codons, especially within the N-terminal domain, receptor-binding domain, and furin cleavage region. However, these signals were dominated by substitutions associated with variant emergence, particularly during the Alpha-to-Delta transition, rather than by vaccination rollout. Whole-gene tests provided no evidence that vaccine intensity was associated with elevated episodic selection, and residualized vaccination trajectories did not predict selection at biologically plausible lags. Across provinces, the timing and distribution of selection events were inconsistent with a vaccine-driven escape model. Together, these results indicate that, at provincial resolution in Canada, episodic positive selection on SARS-CoV-2 spike was driven primarily by variant turnover rather than vaccine deployment. More broadly, this study provides a quantitative, VOC-resolved assessment of spike evolution in a structured epidemic and suggests that population-level vaccination intensity was not a detectable determinant of spike adaptation in the period examined.","rel_num_authors":4,"rel_authors":[{"author_name":"Marissa Tomas","author_inst":"University of Ottawa"},{"author_name":"Cheikh Pape Khary Ndongo","author_inst":"University of Ottawa"},{"author_name":"Matthieu Vilain","author_inst":"University of Ottawa"},{"author_name":"Stephane Aris-Brosou","author_inst":"University of Ottawa"}],"rel_date":"2026-05-19","rel_site":"biorxiv"},{"rel_title":"Estimating the fraction of variance of crystallized intelligence explained by cortical surface area in early adolescence","rel_doi":"10.64898\/2026.05.16.725604","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.16.725604","rel_abs":"The relationship between cortical morphology and intelligence during adolescence has been widely studied, with existing literature reporting varying degrees of association across different modeling approaches. This study provides a comprehensive comparison of model performance in investigating the association between crystallized intelligence and cortical surface area using data from 11,351 subjects in the Adolescent Brain Cognitive Development (ABCD) study. We evaluate ten widely used models ranging from linear regression to graph convolutional networks across three covariate adjustment formulations: full (no adjustment), partial (age and sex adjusted), and total surface area (TSA) partial (age, sex, and TSA adjusted). Using bootstrap resampling with 50 iterations, we estimate the fraction of variance explained (FVE) for each model. Our results suggest that more complex models do not lead to higher FVE, with LASSO having the highest FVE of 15.9% (full formulation), Ridge at 10.5% (partial formulation), and Principal Component Regression (PCR) with 102 PCs at 2.5% (TSA partial formulation). Our results also reveal that the relationship between cortical surface area and crystallized intelligence is predominantly driven by global factors age, sex, and TSA, rather than by localized cortical surface area.","rel_num_authors":3,"rel_authors":[{"author_name":"Howon Ryu","author_inst":"University of California San Diego"},{"author_name":"Chun Chieh Fan","author_inst":"Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research"},{"author_name":"Armin Schwartzman","author_inst":"University of California San Diego"}],"rel_date":"2026-05-19","rel_site":"biorxiv"},{"rel_title":"B3GNT7 regulates mucin glycosylation and protects against colitis and infection","rel_doi":"10.64898\/2026.05.18.725942","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.05.18.725942","rel_abs":"Mucus covers and protects colonic epithelial cells. Mucus is mainly composed of heavily O-glycosylated proteins called mucins, and disruption of normal mucin glycosylation occurs in ulcerative colitis (UC). Mucin-2 (MUC2) is the major colonic mucin, and MUC2 O-glycans are often extended with sulfated polyLacNAc, also known as keratan sulfate (KS). The GlcNAc residues in KS are added by B3GNT family members. B3GNT7 is highly expressed in the colon, and B3GNT7 expression is dramatically reduced in UC. However, the function of B3GNT7 in colonic physiology is unexplored. Here we show that B3gnt7 is a key player in colonic physiology through its function in controlling the structure of mucus glycans. We found that B3GNT7 prefers to extend a sulfated acceptor substrate and is required for production of polyLacNAc-modified mucus in a human goblet cell model. In vivo, B3GNT7 regulates Muc2, Muc13, and Muc17 O-glycosylation. Intestinal B3GNT7 deficiency increases susceptibility to colitis and enteric infection in mice, showing that B3GNT7-dependent glycosylation confers protective properties to colonic mucus. Taken together, these results demonstrate that B3GNT7 has a function distinct from other B3GNT family members and is critical for maintaining colonic homeostasis.","rel_num_authors":13,"rel_authors":[{"author_name":"Mary W. N. Burns","author_inst":"UT Southwestern"},{"author_name":"Joann Chongsaritsinsuk","author_inst":"Yale University"},{"author_name":"Daniel C. Propheter","author_inst":"UT Southwestern"},{"author_name":"JIANYI YIN","author_inst":"UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER"},{"author_name":"Vivian Zuo","author_inst":"Yale University"},{"author_name":"Chin Huang","author_inst":"University of Georgia"},{"author_name":"Lan Peng","author_inst":"UT Southwestern"},{"author_name":"Kelly A. Ruhn","author_inst":"UT Southwestern"},{"author_name":"Kelley W. Moremen","author_inst":"University of Georgia"},{"author_name":"Ezra Burstein","author_inst":"University of Texas Southwestern Medical Center"},{"author_name":"Lora Hooper","author_inst":"University of Texas Southwestern Medical Center"},{"author_name":"Stacy A Malaker","author_inst":"Yale University"},{"author_name":"Jennifer J. Kohler","author_inst":"UT Southwestern"}],"rel_date":"2026-05-19","rel_site":"biorxiv"}]}