Publications

Refining sequence-to-expression modelling with chromatin accessibility
Orsolya Lapohos
Gregory Fonseca
Amin Emad
2025-04-20
bioRxiv (preprint)
doi.org
Cortical differences across psychiatric disorders and associated common and rare genetic variants
Kuldeep Kumar
Zhijie Liao
Jakub Kopal
Clara Moreau
Christopher R. K. Ching
Claudia Modenato
Will Snyder
Sayeh Kazem
Charles-Olivier Martin
C.O. Martin
Anne-Marie Bélanger
Valérie K. Fontaine
Khadije Jizi
Rune Boen
Guillaume Huguet
Zohra Saci
Leila Kushan
Ana I. Silva
Marianne B.M. van den Bree
David E.J. Linden … (see 16 more)
Michael J. Owen
Jeremy Hall
Sarah Lippé
Guillaume Dumas
Bogdan Draganski
Laura Almasy
Sophia I. Thomopoulos
Neda Jahanshad
Ida E. Sønderby
Ole A. Andreassen
David C. Glahn
Armin Raznahan
Carrie Bearden
Tomáš Paus
Paul M. Thompson
Sébastien Jacquemont
2025-04-18
medRxiv (preprint)
doi.org
Deep Learning Unlocks the True Potential of Organ Donation after Circulatory Death with Accurate Prediction of Time-to-Death
Xingzhi Sun
Edward De Brouwer
Chen Liu
Smita Krishnaswamy
Ramesh Batra
𝟏
Increasing the number of organ donations after circulatory death (DCD) has been identified as one of the most important ways of addressing t… (see more)he ongoing organ shortage. While recent technological advances in organ transplantation have increased their success rate, a substantial challenge in increasing the number of DCD donations resides in the uncertainty regarding the timing of cardiac death after terminal extubation, impacting the risk of prolonged ischemic organ injury, and negatively affecting post-transplant outcomes. In this study, we trained and externally validated an ODE-RNN model, which combines recurrent neural network with neural ordinary equations and excels in processing irregularly-sampled time series data. The model is designed to predict time-to-death following terminal extubation in the intensive care unit (ICU) using the last 24 hours of clinical observations. Our model was trained on a cohort of 3,238 patients from Yale New Haven Hospital, and validated on an external cohort of 1,908 patients from six hospitals across Connecticut. The model achieved accuracies of 95.3 {+/-} 1.0% and 95.4 {+/-} 0.7% for predicting whether death would occur in the first 30 and 60 minutes, respectively, with a calibration error of 0.024 {+/-} 0.009. Heart rate, respiratory rate, mean arterial blood pressure (MAP), oxygen saturation (SpO2), and Glasgow Coma Scale (GCS) scores were identified as the most important predictors. Surpassing existing clinical scores, our model sets the stage for reduced organ acquisition costs and improved post-transplant outcomes.
2025-04-18
Scientific Reports (published)
doi.org
Impact of Reducing Time Lived With Colostomies on Social Stigma Affecting Children With Anorectal Malformations in Southwestern Uganda.
Felix Oyania
Caroline Q. Stephens
Sarah Ullrich
Meera Kotagal
Amy M. Shui
Caleb Tuhumwire
Godfrey Zari Rukundo
Joseph Ngonzi
Ava Yap
Francis Bajunirwe
Dan Poenaru
Doruk Ozgediz
BACKGROUND The social stigma of families of children living with colostomies due to anorectal malformation (ARM) is significant in low-incom… (see more)e countries (LICs). Improved access to pediatric surgery has resulted in more 1-stage ARM procedures in Southwestern Uganda, avoiding colostomy creation, but the impact on social stigma experienced by families is unknown. We hypothesized that this change would decrease the social stigma experienced by families. METHODS A single-center mixed retrospective and prospective cohort study with combined qualitative data of families of children with ARM who underwent corrective surgery compared the stigma experienced by those with colostomies to those without. The Kilifi Stigma Scale of Epilepsy (KSSE) was used to assess social stigma. Multivariable regression analysis assessed differences in the stigma experienced, controlling for age at diagnosis, rurality, distance traveled, sex, and parental education. Subgroup analysis assessed the impact of colostomy duration on stigma, stratified over parental education. RESULTS Patient/family dyads with 238 ARM were included; 177 (74%) received a colostomy. Most patients were male (51%), lived in rural areas (71%), and had parents with primary school education (65%). For those without a colostomy, the median KSSE was 0 (Q1-Q3 0-0), compared to 11 (Q1-Q3 3-20) for colostomy. On multivariable analysis, after controlling for age at diagnosis, rurality, distance traveled, sex, and parental education attainment, families of patients with ARM who received a colostomy had a median KSSE score 7.8 points higher than those who did not receive a colostomy (coefficient 7.78, 95% 3.14-12.43, and p = 0.001). When the duration of colostomy (in years) was examined, the median KSSE score increased by 1.58 points for each additional year for a patient who had a colostomy (IRR 1.58, 95% CI: 0.76-2.40, and p  0.001). CONCLUSION Adopting a 1-stage ARM repair for the select types, which avoids colostomy creation, significantly reduces the exper
2025-04-18
World Journal of Surgery (published)
doi.org
Online HD-tRNS over the right temporoparietal junction modulates social inference but not motor coordination
Quentin Moreau
Vincent Chamberland
Lisane Moses
Gabriela Milanova
Guillaume Dumas
Social interactions are fundamental to human cognition, with the right temporoparietal junction (rTPJ) playing a key role in integrating mot… (see more)or coordination and social inference. While transcranial random noise stimulation (tRNS) is a promising technique for modulating cortical excitability in real time, its effect on dynamic social processes remains largely unexplored. This study applied high-definition tRNS (HD-tRNS) over the rTPJ during an interactive task to modulate motor coordination and social inference. Eighty neurotypical adults (49 female) were equally distributed across two experiments: Experiment 1, a block design with randomized active and sham stimulation blocks; or Experiment 2, a trial-by-trial design with intermixed stimulation protocols. Participants performed a coordination task with a covert virtual partner programmed to behave cooperatively or competitively. Kinematic data and self-reported attributions of humanness and cooperativeness were analyzed. The results showed that HD-tRNS over the rTPJ did not affect motor coordination or overall task performance in either experiment. However, in Experiment 1, active stimulation progressively reduced attributed humanness and cooperativeness toward the competitive virtual partner, suggesting enhanced detection of antagonistic intent. This gradual modulation of social inference was absent in Experiment 2, where frequent protocol switching likely disrupted the buildup of stimulation effects. Together, these findings highlight the rTPJ's causal role in self–other distinction, underscore the importance of stimulation protocol design in shaping social cognition, and support the exploration of targeted neuromodulation in clinical and developmental populations with atypical social cognition.
2025-04-18
eNeuro (published)
doi.org
DTractor enhances cell type deconvolution in spatial transcriptomics by integrating deep neural networks, transfer learning, and matrix factorization
Yong Jin Kweon
Chenyu Liu
Gregory Fonseca
Jun Ding
Spatial transcriptomics (ST) captures gene expression with spatial context but lacks single-cell resolution. Single-cell RNA sequencing (scR… (see more)NA-seq) offers high-resolution profiles without spatial information. Accurate spot-level decomposition requires effective integration of both. We present DTractor, a deep learning-based framework that improves cell-type deconvolution in ST data through spatial constraints and transfer learning. DTractor achieves dual utilization of scRNA-seq reference data by incorporating both a cell-type-specific gene expression matrix and learned latent embeddings into a unified matrix factorization model. This joint modeling enables accurate estimation of cell-type proportions and cell-type-resolved gene expression within each spatial spot, while preserving biological and spatial coherence. DTractor further applies spatial regularization to maintain local tissue structure. Across multiple ST platforms and tissue types, DTractor demonstrates improved decomposition accuracy, robustness, and interpretability compared to existing methods. The results from DTractor support downstream applications such as spatial domain analysis and the study of spatially organized cellular behaviors.
2025-04-17
bioRxiv (preprint)
doi.org
GeoLS: an Intensity-based, Geodesic Soft Labeling for Image Segmentation
Sukesh Adiga Vasudeva
Jose Dolz
Hervé Lombaert
Soft-label assignments have emerged as prominent strategies in training dense prediction problems, such as image segmentation. These approac… (see more)hes mitigate the limitations of hard labels, such as inter-class relationships in the data and spatial relationships between a given pixel and its neighbors. Nevertheless, most existing methods rely only on ground-truth masks and ignore the underlying image context associated with each label. For instance, image intensities convey information that could potentially clear ambiguities in the annotation. This paper, therefore, proposes a Geodesic Label Smoothing (GeoLS) approach that incorporates image intensity information within the soft labeling process. Specifically, we leverage the geodesic distance transform to capture the intensity variations between pixels. The generated maps geodesically modify the hard labels to obtain new intensity-based soft labels. The resulting geodesic soft labels better model spatial and class-wise relationships as they capture the variations of image gradients across classes and anatomy. The benefits of our intensity-based geodesic soft labels are assessed on three diverse sets of publicly accessible segmentation datasets. Our experimental results show that the proposed method consistently improves the segmentation accuracy compared to state-of-the-art soft-labeling techniques in terms of the Dice similarity and Hausdorff distance.
2025-04-17
Machine Learning for Biomedical Imaging (published)
doi.org
Multimodal population study reveals the neurobiological underpinnings of chronotype
Le Zhou
Karin Saltoun
Julie Carrier
Kai-Florian Storch
Robin I. M. Dunbar
Danilo Bzdok
2025-04-16
Nature Human Behaviour (unknown)
doi.org
Alcohol related hepatitis in intensive care units: clinical and biological spectrum and mortality risk factors: a multicenter retrospective study
Maxime Gasperment
Léa Duhaut
Nicolas Terzi
Côme Gerard
Luc Haudebourg
Alexandre Demoule
Mialy Randrianarisoa
Vincent Castelain
Sacha Sarfati
Fabienne Tamion
Charlene Le Moal
Christophe Guitton
Gabriel Preda
Arnaud Galbois
Thibault Vieille
Gaël Piton
Marika Rudler
Guillaume Dumas
Hafid AIT-OUFELLA
Background Alcohol related hepatitis is responsible for high morbidity and mortality, but little is known about the management of patients w… (see more)ith hepatitis specifically in intensive care units (ICU). Methods Retrospective study including patients with alcohol related hepatitis hospitalized in 9 French ICUs (2006–2017). Alcohol related hepatitis was defined histologically or by an association of clinical and biological criteria according to current guidelines. Results 187 patients (median age: 53 [43–60]; male: 69%) were included. A liver biopsy was performed in 51% of cases. Patients were admitted for impaired consciousness (71%), sepsis (64%), shock (44%), respiratory failure (37%). At admission, median SOFA and MELD scores were 10 [7–13] and 31 [26–40] respectively. 63% of patients received invasive mechanical ventilation, 62% vasopressors, and 36% renal replacement therapy. 66% of patients received corticosteroids, and liver transplantation was performed in 16 patients (8.5%). ICU and in-hospital mortality were 37% and 53% respectively. By multivariate analysis, ICU mortality was associated with SOFA score (without total bilirubin) (SHR 1.08 [1.02–1.14] per one-point increase), arterial lactate (SHR 1.08 [1.03–1.13] per 1 mmol/L) and MELD score (SHR 1.09 [1.04–1.14] per 1 point), while employment was associated with increased survival (HR 0.49 [0.28–0.86]). After propensity score weighting, the use of corticosteroids did not affect ICU mortality in the overall population but had a beneficial effect in the subgroup of patients with histological proof. Patient prognosis was also better in responders assessed by Lille score at day 7 (OR 6.67 [2.44–20.15], p  0.001). Conclusion Alcohol related hepatitis is a severe condition leading to high mortality in ICU patients. Severity of organ failure
2025-04-14
Annals of Intensive Care (published)
doi.org
Assessing Critical Thinking Skills in Data Literacy: A Digital Performance Assessment
Ying Cui
Xiaoxiao Liu
Fu Chen
Alina Lutsyk
Jaqueline P. Leighton
Maria Cutumisu
2025-04-14
Zeitschrift für Pädagogik (published)
doi.org
Brain Diffusion Transformer for Personalized Neuroscience and Psychiatry
Rongquan Zhai
Yechen Hu
Liping Zheng
Shitong Xiang
Chao Xie
Lei Peng
Tobias Banaschewski
Gareth J. Barker
Arun L.W. Bokde
Rüdiger Brühl
Sylvane Desrivières
Herta Flor
Hugh Garavan
Penny Gowland
Antoine Grigis
Andreas Heinz
Herve Lemaitre
Jean-Luc Martinot
Marie-Laure Paillère Martinot
Eric Artiges … (see 26 more)
Frauke Nees
Dimitri Papadopoulos Orfanos
Luise Poustka
Michael N. Smolka
Sarah Hohmann
Nathalie Holz
Nilakshi Vaidya
Robert Whelan
Zuo Zhang
Lauren Robinson
Jeanne Winterer
Sinead King
Yuning Zhang
Hedi Kebir
Ulrike Schmidt
Julia Sinclair
Argyris Stringaris
Gunter Schumann
Danilo Bzdok
Henrik Walter
Edmund T. Rolls
Barbara Sahakian
Trevor W. Robbins
Jianfeng Feng
Weikang Gong
Tianye Jia
Task-fMRI analyses typically focus on localized activation contrasts between stimuli, neglecting the brain’s dynamic hierarchy. We introdu… (see more)ce Brain Diffusion Transformer (Brain-DiT), a deep generative model capturing recurrent processing underlying individualized neurocognitive state transitions via functional networks. Without prior assumptions, Brain-DiT identifies canonical cognitive regions in the brain and reveals replicable subgroups with distinct neural circuits in large cohorts, offering critical clinical insights overlooked by traditional methods: individuals exhibiting negative emotion bias, linked to language-related regions, had a 12-fold higher likelihood of major depression, and those with maladaptive inhibition strategies, associated with overactive medial frontal regions, showed a 9-fold increased risk of alcohol abuse. By bridging cognitive theory and psychiatric applications, Brain-DiT provides a unified analytical paradigm, paving the way for operational personalized medicine in psychiatry.
2025-04-13
bioRxiv (preprint)
doi.org
IL1RAP is an immunotherapeutic target for normal karyotype triple-mutated acute myeloid leukemia
Arnaud Metois
Marie-Eve Bordeleau
Louis Theret
Azadeh Hajmirza
Ossama Moujaber
Jean-François Spinella
Jalila Chagraoui
Nadine Mayotte
Isabel Boivin
Éric Audemard
Léo Aubert
Véronique Lisi
Banafsheh Khakipoor
Azer Farah
Éric Bonneil
Alma Robert
Julie Lippens
Anna Moraitis
Francois Béliveau
Albert Feghaly … (see 10 more)
Geneviève Boucher
Richard Marcotte
Patrick Gendron
Pierre Thibault
Sébastien Lemieux
Guillaume Richard-Carpentier
Vincent-Philippe Lavallee
Josée Hébert
Philippe P. Roux
Guy Sauvageau
Surface antigens of potential clinical significance remain under-characterized in AML. The European Leukemia Network classifies normal karyo… (see more)type AML (NK-AML) mutated for NPM1 (NPM1c) as a distinct entity associated with favorable outcomes if not associated with FLT3-ITD mutation. A subset of NPM1c NK-AML shows additional mutations in 2 genes: FLT3 (FLT3-ITD) and DNMT3 A. These leukemias, also referred to as NK triple mutated AML (NKt-AML), are particularly difficult to eradicate with current treatment options. Therefore, novel therapies are necessary that use proteins specifically expressed at the surface. In order to identify surface antigens for immunotherapy in NKt-AML, an extensive multi-omic analysis was conducted on primary AML samples. Surface proteome enrichment was performed on 100 primary AML samples, twelve of which were NKt-AML. Transcriptome analysis was carried out on the 691 primary AML samples, and single-cell RNA sequencing was conducted on 23 primary AML samples. Herein, using multi-omics data from the Leucegene collection, we identify IL1RAP as a promising antigen for this AML subgroup. We demonstrate that IL1RAP is expressed at the surface of primitive AML cells reminiscent of leukemic stem cells in NKt-AML primary human AML specimens, while showing relatively low expression levels in normal bone marrow HSCs. Furthermore, results indicate that elevated IL1RAP expression associates with poor overall and relapse-free survival in the Leucegene cohort of AML patients and predicts nonresponse to hematopoietic stem cell transplantation. Finally, we show that IL1RAP protein is internalized following exposure to specific antibodies, suggesting that IL1RAP represents an interesting target for antibody–drug conjugate development in NKt-AML. IL1RAP exhibits preferential expression within NKt-AML, correlating with diminished overall survival rates and diminished responsiveness to hematopoietic stem cell transplantation. Moreover, internalization of IL1RAP presents a promising avenue for immunotherapeutic intervention. The online version contains supplementary material available at 10.1186/s40364-025-00769-z.
2025-04-13
Biomarker Research (published)
doi.org