bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reconsidering Silent Variant UnveilsSGCA’s Role in Atypical Cardiomyopathy
Authors: Horowitz-Cederboim Smadar , Hoffman-Lipschuetz Ronit , Durst Ronen , Harel Tamar , Shpitzen Shoshi , Shauer Ayelet , Zwas Donna R , Eilat Avital , Tomer Orr , Meiner Vardiella 
Published: February 2025

AbstractWe investigated an atypical form of limb-girdle muscular dystrophy type R3 (LGMDR3) associated with a homozygous synonymous variant inSGCAthat significantly expands the recognized clinical phenotype to include prominent cardiac involvement. While LGMDR3, caused by pathogenic variants inSGCA, typically presents as progressive muscle weakness with relatively limited cardiac manifestations, the individuals in our study developed substantial left ventricular dysfunction, arrhythmias, and even life-threatening ventricular tachyarrhythmias.Five consanguineous families, initially evaluated through exome sequencing, showed no conclusive results until a focused genotype-phenotype correlation reanalysis pinpointed a single homozygous synonymousSGCAvariant. Despite its location distant from canonical splice sites, this variant disrupted normal mRNA splicing, leading to aberrant transcripts and, presumably, a nonfunctional or structurally altered α-sarcoglycan protein. Cardiac assessments, including echocardiography, Holter monitoring, and cardiac magnetic resonance imaging, revealed a spectrum of findings from mild asymptomatic dysfunction to severe dilated cardiomyopathy and malignant arrhythmias requiring implantable cardioverter-defibrillators.This case broadens current understanding of LGMDR3 and its molecular underpinnings, ultimately guiding more personalized management strategies for affected individuals. It illustrates that thorough and ongoing variant interpretation is crucial, particularly in consanguineous populations where seemingly benign alterations may confer significant phenotypic consequences. By integrating carefully curated genomic data with clinical insights, clinicians can better identify patients at risk, tailor surveillance protocols, and implement timely interventions. In doing so, this discovery not only refines our appreciation of the intricate interplay between genetic variants and their phenotypic manifestations, but also underscores the importance of precision medicine approaches in the evolving landscape of inherited cardiomyopathies.
Variants inBSN, encoding the presynaptic protein Bassoon, result in a novel neurodevelopmental disorder with a broad phenotypic range
Authors: Guzman Stacy G , Ruggiero Sarah M , Ganesan Shiva , Ellis Colin A , Harrison Alicia G , Sullivan Katie R , Stark Zornitza , Brown Natasha J , Kana Sajel L , Tuttle Anabelle , Tenorio Jair , Lapunzina Pablo , Nevado Julián , McDonald Marie T , Jensen Courtney , Wheeler Patricia G , Stange Lila , Morrison Jennifer , Keren Boris , Heide Solveig , Keating Meg W , Butler Kameryn M , Lyons Mike A , Jain Shailly , Yeganeh Mehdi , Thompson Michelle L , Schroeder Molly , Nguyen Hoanh , Granadillo Jorge , Johnston Kari M , Murali Chaya N , Bosanko Katie , Burrow T Andrew ,   CHOP Birth Defects Biorepository,   Penn Medicine Biobank, Morgan Syreeta , Watson Deborah J , Hakonarson Hakon , Helbig Ingo 
Published: February 2025

AbstractDisease-causing variants in synaptic function genes are a common cause of neurodevelopmental disorders and epilepsy. Here, we describe 14 individuals withde novodisruptive variants inBSN, which encodes the presynaptic protein Bassoon. To expand the phenotypic spectrum, we identified 15 additional individuals with protein-truncating variants (PTVs) from large biobanks. Clinical features were standardized using the Human Phenotype Ontology (HPO) across all 29 individuals, which revealed common clinical characteristics including epilepsy (13/29 45%), febrile seizures (7/29 25%), generalized tonic-clonic seizures (5/29 17%), and focal onset seizures (3/29 10%). Behavioral phenotypes were present in almost half of all individuals (14/29 48%), which comprised ADHD (7/29 25%) and autistic behavior (5/29 17%). Additional common features included developmental delay (11/29 38%), obesity (10/29 34%), and delayed speech (8/29 28%). In adults withBSNPTVs, milder features were common, suggesting phenotypic variability including a range of individuals without obvious neurodevelopmental features (7/29 24%). To detect gene-specific signatures, we performed association analysis in a cohort of 14,895 individuals with neurodevelopmental disorders (NDDs). A total of 66 clinical features were associated withBSN, including febrile seizures (p=1.26e-06) and behavioral disinhibition (p = 3.39e-17). Furthermore, individuals carryingBSNvariants were phenotypically more similar than expected by chance (p=0.00014), exceeding phenotypic relatedness in 179/256 NDD-related conditions. In summary, integrating information derived from community-based gene matching and large data repositories through computational phenotyping approaches, we identifyBSNvariants as the cause of a new class of synaptic disorder with a broad phenotypic range across the age spectrum.
FedWeight: Mitigating Covariate Shift of Federated Learning on Electronic Health Records Data through Patients Re-weighting
Authors: Zhu He , Li Na , Li Xiaoxiao , Liu Dianbo , Buckeridge David , Li Yue 
Published: February 2025

AbstractFederated Learning (FL) has emerged as a promising approach for research on real-world medical data distributed across different organizations, as it allows analysis of distributed data while preserving patient privacy. However, one of the prominent challenges in FL is covariate shift, where data distributions differ significantly across different clinical sites, like hospitals and outpatient clinics. These differences in demographics, clinical practices, and data collection processes may lead to significant performance degradation of the shared model when deployed for a target population. In this study, we propose a Federatively Weighted (FedWeight) framework to mitigate the effect of covariate shift on Federated Learning. Leveraging the data distribution estimated by density estimator models, we re-weight the patients from the source clinical sites, making the trained model aligned with the data distribution of the target site, thus mitigating the covariate shift between source and target sites. To make our approach also applicable to unsupervised learning, we integrate Fed-Weight into a novel federated embedded topic model (ETM), namely FedWeight-ETM. We evaluated FedWeight in cross-site FL within the eICU dataset and also cross-dataset FL between eICU and MIMIC-III data. Compared with the baseline, FedWeight-corrected FL models demonstrate superior performance for predicting patient mortality, ventilator use, sepsis diagnosis, and length of stay in the intensive care unit (ICU). Moreover, FedWeight outper-forms FedAvg in identifying important features relevant to the clinical outcomes. Leveraging Shapley Additive Explanations (SHAP), the FedWeight-corrected classifiers reveal subtle yet significant associations between drugs, lab tests, and patient outcomes. Using FedWeight-ETM, we identified known disease topics involving renal or heart failure predictive of future mortality at the ICU readmission. Together, FedWeight provides a robust FL framework to address the challenge of covariate shift from clinical silos in predicting critical patient out-comes and providing meaningful clinical features.
Brucellaproline racemase protein A targets Tpl2 to promote IL-10 secretion for establishment of chronic infection
Authors: Zhang Huan , Wang Yuanzhi , Wang Yueli , Hou Huilin , Wang Yaqian , Deng Xiaoyu , Xu Zhenyu , Xia Xujin , Xu Mingguo , Wang Zhen , Wang Yong , Zhang Changsuo , Zhumanov Kait , Sheng Jinliang , Zhang Hui , Ma Zhongchen , Yi Jihai , Chen Chuangfu 
Published: February 2025

AbstractIL-10, an anti-inflammatory cytokine, plays a crucial role in limiting immune responses to pathogens, preventing host damage. However, the mechanisms underlyingBrucella-mediated IL- 10 production remain incompletely understood. In this study, we demonstrate that the proline racemase protein A (PrpA) ofBrucella melitensisM5-90 induces macrophages to secrete IL-10 by activating the Tpl2-ERK signaling pathway, thereby promoting chronic infection. Moreover,Tpl2deletion impairs macrophage bactericidal ability, accompanied by reduced TNF-α and IL-1β but unaffected IL-10 levels. Additionally, Trp309, Glu103, and Glu129 of PrpA participate in interaction with Tpl2, but these residues do not influence PrpA-mediated IL-10 production in macrophages.PrpAdeletion enhances IFN-γ levels, specific anti-BrucellaIgG, and CD4+ and CD8+ T cell numbers in mice. Furthermore, theBrucella melitensisM5-90prpAmutant provides higher protection than the parental strain against virulentBrucella melitensisM28 infection in mice. Our findings suggest thatBrucellaPrpA promotes IL-10 secretion by macrophages through Tpl2 activation for bacterial survival and persistent infection, making theBrucella melitensisM5-90prpAmutant a promising vaccine for enhanced protection.Author SummaryIL-10, an anti-inflammatory cytokine, is exploited byBrucellafor survival. We identifiedBrucellaPrpA as a potent IL-10 inducer, activating the Tpl2-ERK signaling pathway.Tpl2deletion increasedBrucellasurvival in macrophages, accompanied by reduced TNF-α and IL-1β but unaffected IL-10 secretion. Residues (Trp309, Glu103, and Glu129) of PrpA were crucial for interaction with Tpl2, yet did not impact PrpA-mediated IL-10 production. TheB. melitensisM5-90prpAmutant induced higher anti-BrucellaIgG, IFN-γ, and CD4+ and CD8+ T cell numbers in mice, providing better protection thanB. melitensisM5-90. These findings unveil PrpA’s role in IL-10 production and highlight the potential of theB. melitensisM5-90prpAmutant as a promising vaccine for further evaluation.
Complex Human Hair Bearing Skin Organoids as Model for Herpes Simplex Virus 1 Infection in the Skin
Authors: Wyler Emanuel , Albertini Silvia , Friedel Caroline C. , Manukyan Artür , Huang Jiabin , Krasemann Susanne , Plumbom Izabela , Altmüller Janine , Conrad Thomas , Radbruch Helena , Hafezi Wali , Hansen Arne , Grundhoff Adam , Landthaler Markus , Fischer Nicole , Czech-Sioli Manja 
Published: February 2025

AbstractFor Herpes Simplex Virus 1 (HSV-1) the skin is the primary site of infection. After the primary lytic infection, the virus enters the peripheral nervous system where it establishes latency. Spontaneous reactivation from the latently infected neurons leads to the typical HSV-1-induced diseases like cold sores. Modelling HSV-1-induced skin pathologies is challenging due to the variety of different cell types and structures in the skin and human-specific responses to the infection. Nevertheless, studies using monolayer cell lines, raft cultures,ex vivoskin and mouse models provided an immense contribution to our understanding of HSV-1 infection in the skin. However, the contribution of many skin-specific structures, especially hair follicles, to primary infection and reactivation remains unclear. In this study, we used complex human hair bearing skin organoids that were derived from induced pluripotent stem cell as a model for HSV-1 infection. We performed microscopy, bulk and spatial transcriptomics with single cell resolution to gain new insights into the cell-type specific viral life cycle and host responses. We show a restricted viral infection in keratinocytes of the epidermis and specific cell types of hair follicles. We show a cell type specific induction of interferon-stimulated genes and the TNF pathway. We can follow paracrine signaling through the tissue, showing that TNF response genes are upregulated in adjacent cells. Taken together, the skin organoids in combination with novel spatial transcriptomics techniques provide a physiologically highly relevant model system for HSV-1 infection in the skin.
Age-Dependent Patterns of GutBifidobacteriumMicrobiome Diversity across child Cohorts in a Multi-Ethnic population, Western China
Authors: Huang Jian , Chu Yuxin , Zhixuan Liang , Zhang Huimin , Zhao Quanhao , Tian Fengwei , Ni Yongqing 
Published: February 2025

ABSTRACTHigh-throughput sequencing has provided unprecedented opportunities to elucidate the role of human gut microbiota. However, current studies have primarily focused on infant and adult cohorts, leaving biomarkers associated with the development of transitional children unclear, particularly in revealing geographic, multi-ethnic group underrepresented. Here, we analyzed fecal samples from 776 infants and children aged 0 to 15 years with amplicon sequencing of the 16S rRNA andgroELgene, representing multi-ethnic groups from different residential locations in the Yining region of Xinjiang. First, we systematically characterized the gut microbiota Spectrum of children in the Ili region. As age increases, the diversity and functional composition of the microbiota become richer and more stable, withBifidobacteriumconsistently dominating the community. Utilizing Bayesian regression models, we identified a cluster of microbiota strongly associated with growth and development in children, which phylogenetically corresponds toBifidobacterium breve. Finally, we included another similar study in the species-level ofBifidobacterium, and metrics of the age-related effect sizes showed heterogeneity across ethnic groups (Uyghur vs Han: βDeming= 4.40 and Kazakh vs Han: βDeming= 4.33). In conclusion, this study provides novel insights into the developmental trajectories of the gut microbiome in children and its relationship with health.IMPORTANCEThe intestinal microbial markers associated with the development of geographically diverse, multi-ethnic children, particularly those represented by Bifidobacterium species, have been elucidated in this study. Through the application of Bayesian regression models, we identified a microbiome profile closely linked to childhood growth and development, specifically phylogenetically aligned withBifidobacterium breve. When incorporating a comparable study conducted at the species level of anotherBifidobacterium, it was observed that age-related effect sizes varied among different ethnic groups, offering novel insights into the developmental trajectory of children’s gut microbiota and its implications for health.
Spatially distinct cellular and molecular landscapes define prognosis in triple negative breast cancer
Authors: Mukund Kavitha , Veraksa Darya , Frankhouser David , Yang Lixin , Tomsic Jerneja , Pillai Raju , Atti Srijan , Mesrizadeh Zahra , Schmolze Daniel , Wu Xiao-Cheng , LeBlanc Mary-Anne , Miele Lucio , Ochoa Augusto , Seewaldt Victoria , Subramaniam Shankar 
Published: February 2025

ABSTRACTBackgroundTriple-negative breast cancer is a prevalent breast cancer subtype with the lowest 5-year survival. Several factors contribute to its treatment response, but the inherent molecular and cellular tumor heterogeneity are increasingly acknowledged as crucial determinants.MethodsSpatial transcriptomic profiling was performed on FFPE tissues from a retrospective, treatment-naive group of women with differential prognoses (17 with >15 years survival-good prognosis (GPx) and 15 with <3 years survival-poor prognosis (PPx)) using GeoMX®Digital Spatial Profiler. Regions of interest were segmented on pan-cytokeratin and analyzed for tumor and stromal components, probed using GeoMx human whole transcriptome atlas (WTA) panel. Data quality control, normalization, and differential analysis was performed in R using GeomxTools and linear mixed models. Additional analyses including cell-type deconvolution, spatial entropy, functional enrichment, TF-target / ligand-receptor analysis and convolution neural networks were employed to identify significant gene signatures contributing to differential prognosis.ResultsHere we report on the spatial and molecular heterogeneity underlying differential prognosis. We observe that the state of the epithelia and its microenvironment (TME) are transcriptionally distinct between the two groups. Invasive epithelia in GPx show a significant increase in immune transcripts with the TME exhibiting increased immune cell presence (via IF), while in PPx they are more metabolically and translationally active, with the TME being more mesenchymal/fibrotic. Specifically, pre-cancerous epithelia in PPx display a prescience of aggressiveness as evidenced by increased EMT-signaling. We identify distinct epithelial gene signatures for PPx and GPx, that can, with high accuracy, classify samples at the time of diagnosis and likely inform therapy.ConclusionsTo the best of our knowledge, this is the first study to leverage spatial transcriptomics for an in-depth delineation of the cellular and molecular underpinnings of differential prognosis in TNBC. Our study highlights the potential of spatial transcriptomics to not only uncover the molecular drivers of differential prognosis in TNBC but also to pave the way for precision diagnostics and tailored therapeutic strategies, transforming the clinical landscape for this aggressive breast cancer subtype.
Cryo-EM ligand building using generative AI and molecular dynamics
Authors: Haloi Nandan , Howard Rebecca J. , Lindahl Erik 
Published: February 2025

AbstractResolving protein-ligand interactions in atomic detail is key to understanding how small molecules regulate macromolecular function. Although recent break-throughs in cryogenic electron microscopy (cryo-EM) have enabled high-quality reconstruction of numerous complex biomolecules, the resolution of bound ligands is often relatively poor. Furthermore, automated methods for building and refining molecular models into cryo-EM maps have largely focused on proteins and may not be optimized for the diverse properties of small-molecule ligands. Here, we present an approach that integrates generative artificial intelligence (AI) with cryo-EM density-guided simulations to fit ligands into experimental maps. Using three inputs: 1) a protein amino acid sequence, 2) a ligand specification, and 3) an experimental cryo-EM map, we validated our approach on a set of biomedically relevant protein-ligand complexes including kinases, GPCRs, and solute transporters, none of which were present in the AI training data. In cases for which generative AI was not sufficient to predict experimental poses outright, integration of flexible fitting into molecular dynamics simulations improved ligand model-to-map cross-correlation relative to the deposited structure from 40–71% to 82–95%. This work offers a straightforward template for integrating generative AI and density-guided simulations to automate model building in cryo-EM maps of ligand-protein complexes, with potential applications for characterization and design of novel modulators and drugs.
Chimeric infective particles expand species boundaries in phage inducible chromosomal island mobilization
Authors: He Lingchen , Patkowski Jonasz B. , Miguel-Romero Laura , Aylett Christopher H S , Fillol-Salom Alfred , Costa Tiago R. D. , Penadés José R 
Published: February 2025

SUMMARYSome mobile genetic elements spread among unrelated bacterial species through unknown mechanisms. Recently, we discovered that identical capsid-forming phage-inducible chromosomal islands (cf-PICIs), a new family of phage satellites, are present across multiple species and genera, raising questions about their widespread dissemination. Here we have identified and characterized a new biological entity enabling this transfer. Unlike other satellites, cf-PICIs produce their own capsids and package their DNA, relying solely on phage tails for transfer. Remarkably, cf-PICIs release non-infective, tail-less capsids containing their DNA into the environment. These subcellular entities then interact with phage tails from various species, forming chimeric particles that inject DNA into different bacterial species depending on the tail present. Additionally, we elucidated the structure of the tail-less cf-PICIs and the mechanism behind their unique capsid formation. Our findings illuminate novel mechanisms used by satellites to spread in nature, contributing to bacterial evolution and the emergence of new pathogens.
Functional Dynamics Reveal the Response of the Crabapple (Malussp.) Phyllosphere Microbiome toGymnosporangium yamadaeInfection
Authors: Xu Qianran , Zhang Yonghua , Tao Siqi 
Published: February 2025

AbstractThe plant microbiome is crucial for maintaining plant health under disease stress. While considerable research has focused on belowground systems, the phyllosphere microbiome remains underexplored, particularly regarding its functional responses to pathogen infection. In this study, we investigated the phyllosphere microbiome dynamics of crabapple (Malus‘Kelsey’) infected byGymnosporangium yamadaeusing metatranscriptomic sequencing across six stages of rust disease progression. Our analysis revealed a general increase in the diversity of fungi, bacteria and viruses in infected leaves. Notably, fungal diversity negatively correlated with bacterial diversity, reflecting competitive interactions during disease development. Microbial taxa in diseased leaves exhibited heightened expression activity compared to healthy leaves, with fungi progressively dominating the microbial community. Functional co-occurrence networks of the phyllosphere microbiome in infected leaves were more complex than in healthy leaves, suggesting adaptive reorganization in response to pathogen invasion. Differentially expressed genes at each stage were significantly enriched in carbohydrate metabolism pathways and gene regulation-related functions, enabling functional adaptations to rust diseases. Random forest modeling identified key microbial transcripts associated with pathogen abundance, including beneficial microbes likeSaitozyma podzolica, which secretes glucan-degrading enzymes, andMortierella elongata, involved in sterol biosynthesis and plant resistance. Conversely,Alternaria alternataemerged as a major pathobiome contributor, secreting enzymes that degrade plant cell wall components (e.g., pectin, cellulose, lignin, and xylan), and engaging in MAPK signaling pathways critical for pathogenesis. Our findings underscore the vital role of the phyllosphere microbiome in mediating plant-pathogen interactions and shaping disease progression, providing a foundation for microbiome-based strategies to enhance plant resilience.ImportanceOur findings reveal the dynamic shifts in the expression patterns and adaptive functional strategies of crabapple phyllosphere microbiome in response to theGymnosporangium yamadaeinfection. We identified several key microbes that may play vital roles in pathogenesis and speculated on their roles and functions in plant-pathogen interactions. In conclusion, our study highlights the potential of the phyllosphere microbiome in regulating plant health.