Biology subjects

Xu, T.

Publications and source records attributed to Xu, T..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Human cortex organizes dynamic co-fluctuations along sensation-association axis

The human brain dynamically organizes its activity through coordinated fluctuations, whose spatiotemporal interactions form the foundation of functional networks. While large-scale co-fluctuations are well-studied, the principles governing their amplitude-dependent transitions--particularly across high, intermediate, and low-amplitude regimes--remain unknown. We introduce a co-fluctuation score to quantify how instantaneous functional interactions reorganize with global amplitude dynamics. Using resting-state fMRI data, we identified amplitude-dependent co-fluctuation transitions between functional systems hierarchically aligned with the sensorimotor-association (SA) axis: sensorimotor networks dominated high-amplitude co-fluctuations, associative systems prevailed during intermediate amplitudes, and limbic system preferentially engaged in low-amplitude states. This hierarchy underwent developmental refinement from childhood to adulthood and adaptively reconfigured under external stimuli. Replicated across four independent samples including 7T fMRI, these findings establish the SA axis as infrastructure for amplitude-dependent transitions of co-fluctuation states. Our framework bridges transient coordination and stable functional architecture, demonstrating how brain networks balance external processing (high-amplitude states) with internal cognition/emotion (mid-to-low amplitude states) through amplitude-stratified interactions.

neuroscience↗

bioRxiv2025

Statistically valid explainable black-box machine learning: applications in sex classification across species using brain imaging

Sex classification using neuroimaging data has the potential to revolutionize personalized diagnostics by revealing subtle structural brain differences that underlie sex-specific disease risks. Despite the promise of machine learning, traditional methods often fall short in providing both high classification accuracy and interpretable, statistically validated feature importance scores for high-dimensional imaging data. This gap is particularly evident when conventional techniques such as random forests, LIME, and SHAP are applied, as they struggle with complex feature interactions and managing noise in large datasets. We address this challenge by developing an integrated framework that combines Oblique Random Forests (ORFs) with a novel, permutation-based feature importance testing algorithm. ORFs extend traditional random forests by employing oblique decision boundaries through linear combinations of features, thereby capturing intricate interactions inherent in neuroimaging data. Our feature importance testing method, NEOFIT, rigorously quantifies the significance of each feature by generating null distributions and corrected p-values. We first validate our approach using simulated datasets, establishing its robustness and scalability under controlled conditions. We then apply our method to classify sex from both voxel-wise structural MRI and cortical thickness data in humans and macaques, facilitating direct cross-species comparisons. ORFs achieves AUC > 0.80 on human data, and > 0.70 on macaque data, while NEOFIT identifies statistically significant features aligned with sex-dimorphic neuroanatomy. Our results demonstrate that the proposed framework not only enhances classification performance but also provides clear, interpretable insights into the neuroanatomical features that distinguish sexes. These methodological advancements pave the way for improved diagnostic tools and contribute to a deeper understanding of the evolutionary basis of sex differences in brain structure.

neuroscience↗

bioRxiv2025

Population-level structural variant characterization from pangenome graph

Population-level structural variant (SV) profiling is crucial in the era of pangenomes. However, identifying SVs from genome assemblies and pangenome graphs remains a significant challenge. Here we present Swave, a sequence-to-image, deep-learning based method that accurately resolves both simple and complex SVs, along with their population characteristics, from assembly-derived pangenome graphs. Swave introduces projection waves to summarize the dotplot images that capture mapping patterns between reference and SV-indicating alleles in pangenome. These images are analyzed by a recurrent neural network to distinguishes true SV signals from background noise introduced by genomic repeats. Swave demonstrates superior performance in both SV type classification and genotyping compared to existing methods. When applied to a healthy cohort (n=334) and a rare-disease cohort (n=574), Swave reveals complex and polymorphic SV patterns across human populations and identifies potentially pathogenic SVs. These advancements will facilitate the creation of comprehensive population-level SV catalogs, deepening our understanding of SVs in genetic diversity and disease associations.

bioinformatics↗

bioRxiv2025

Mitochondrial Genome Variants and Nuclear Mitochondrial DNA Segments in 7331 Individuals from NyuWa and 1KGP

Dysfunctional mitochondria are implicated in various diseases, while little is known about comprehensive characterization of mitochondrial DNA (mtDNA) in Chinese population. Here, we conducted a systematic analysis of mtDNA from 7331 samples, comprising 4129 Chinese samples (NyuWa) and 3202 samples from the 1000 Genomes Project (1KGP). We identified 7216 distinct high-quality mtDNA variants and classified them into 22 macrohaplogroups, and detected 1466 distinct nuclear mitochondrial DNA segments (NUMTs), with 88 mtDNA variants and 642 NUMTs being specific to NyuWa. The genome-wide association analyses revealed that 12 mtDNA variants were significantly correlated with 199 nuclear DNA variants. Our findings revealed that all individuals in both NyuWa and 1KGP harbored common NUMTs, and one-fifth possessed ultra-rare NUMTs, which tended to insert into nuclear gene regions. Compared to 1KGP, significant enrichment of nuclear breakpoints in long interspersed nuclear elements (LINEs) was observed for rare NUMTs in NyuWa. Overall, this study represents the first comprehensive profiling the landscape of Chinese NUMTs and offers the most extensive resource of Chinese mtDNA variants and NUMTs based on high-depth WGS to date, providing valuable reference resources for genetic research on mtDNA-related diseases.

genomics↗

bioRxiv2025

Phosphoproteomics Maps Calcineurin-NFAT-DSCR1.4 Signaling as Druggable Axis in Gαq-R183Q-Driven Capillary Malformations

Vascular malformations are congenital lesions caused by somatic and germline mutations that disrupt developmental signaling pathways. Capillary malformations (CMs) typically present as port-wine stains in the skin and can also affect ocular and cerebral tissues in Sturge Weber Syndrome (SWS), leading to aesthetic, ophthalmic, and neurological complications. CMs are caused by a somatic mutation in the GNAQ gene in endothelial cells, leading to a p.R183Q substitution in the Gq protein. The underlying mechanisms of Gq-R183Q-driven CMs formation remain unclear. To address this, we generated CRISPR/Cas9-engineered human dermal microvascular endothelial cells lacking endogenous Gq, whilst expressing the Gq-R183Q mutant instead. The Gq-R183Q mutation strongly impaired endothelial cell migration and angiogenic sprouting capacity compared to wild-type controls. Next, using SILAC-based quantitative proteomics, we investigated the Gq-R183Q-induced changes in the endothelial phosphoproteome. These analyses revealed prominent activation of the calcineurin-NFAT signaling pathway in Gq-R183Q-expressing endothelial cells, leading to dephosphorylation of NFAT1 and NFAT2 and the selective expression of their transcriptional target DSCR1.4. Immunofluorescence of patient-derived skin biopsies confirmed deregulation of NFAT1/2 and the expression of DSRC1 in endothelial cells, validating their potential importance in CMs. We further demonstrate that pharmacological inhibition of calcineurin with tacrolimus (FK506) could partially restore NFAT signaling in Gq-R183Q endothelial cells. Intriguingly, the genetic depletion of the NFAT target DSCR1 in Gq-R183Q cells fully restored calcineurin/NFAT signaling to normal levels, enabling proper endothelial migration and sprouting. In summary, we uncovered a calcineurin-NFAT-DSCR1.4 signal transduction axis that is driven by Gq-R183Q and established its importance for endothelial angiogenic properties. These findings highlight the calcineurin/NFAT signaling axis as a promising therapeutic target to restore endothelial function in CMs.

cell biology↗

bioRxiv2025

TIP-seq: A Single-cell Multiomics Approach for Simultaneous Transcriptome and Intracellular Protein Profiling

Single-cell multiomics technologies have significantly advanced our understanding of cellular heterogeneity; however, the concurrent profiling of mRNA transcripts and target proteins continues to pose a substantial challenge. To bridge the gap between single-cell sequencing and proteomic methods, we developed an innovative single-cell multiomics methodology, termed TIP-seq, which facilitates the simultaneous profiling of the transcriptome and intracellular proteins without prior cell manipulation. In TIP-seq, microfluidic technology is leveraged to integrate oligonucleotide-labeled antibodies with hydrogel beads, allowing for the capture of mRNAs and proteins from individual cells within droplets, thereby enabling high-throughput and precise dual-omics data acquisition. When applied to lung cell lines and non-small cell lung cancer (NSCLC) tissues, TIP-seq analysis revealed notable cellular heterogeneity and molecular dynamics, emphasizing the distinct immune cell interactions within NSCLC tissues. Key immune checkpoint interactions in NSCLC, such as SPP1-CD44, NECTIN2-TIGIT, and NECTIN2-CTLA4, along with functional alterations in tumor-associated dendritic cells (DCs) and T cells, were identified via TIP-seq, underscoring their pivotal roles in mediating immune suppression within the tumor microenvironment. Collectively, TIP-seq represents a powerful methodology for identifying novel therapeutic targets and biomarkers, thereby holding significant potential for the advancement of precision medicine in the treatment of lung cancer and other complex diseases.

biochemistry↗

bioRxiv2025

How Bacterial Vesicles Trigger Hearing Loss: The Role of Pyroptosis in Cochlear Damage

Withdrawal StatementThe authors have withdrawn this manuscript because [After submitting my article, I discovered some important missing data that is crucial for supporting my viewpoint and research findings. Although I tried to supplement this data through other means, I was unable to complete it before the deadline. Therefore, I believe the best approach is to withdraw the article so that I can further refine and present my research findings in a complete manner.]. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

immunology↗

bioRxiv2025

Arcuate Fasciculus: Evolutionary Convergence in Marmosets and Humans

The marmoset is a highly vocal platyrrhine monkey that shares key anatomical and functional features with humans, offering insights into the evolution of brain connectivity. Although similarities in vocalization features with humans have been reported, it remains unclear whether marmosets possess an arcuate fasciculus (af) homolog. This study delineated white matter tracts in marmosets, establishing homologies with those observed in other primates, including macaques, chimpanzees, and humans. The presence of an af homolog in marmosets was confirmed by tracer and ultra-high-resolution diffusion magnetic resonance imaging datasets. We compared cortical connectivity patterns across these species and found the af in marmosets terminates in the ventral frontal cortex, with greater similarity to humans than macaques. Furthermore, we linked af connectivity with vocalization-related brain activation in both marmosets and humans. Collectively, our findings suggest that a dorsal pathway, which emerged early in marmoset evolution, has evolved convergently with humans, despite their distant phylogenetic kinship.

neuroscience↗

bioRxiv2025

Precon_all: A species-agnostic automated pipeline for non-human cortical surface reconstruction

Cortical surface reconstruction has changed how we study brain morphology and geometry. However, extending these methods to non-human species has been limited by the lack of standardized pipelines, anatomical templates, and variability in imaging protocols. To address these challenges, we present Precon_all, an open-source, species-agnostic pipeline that automates cortical surface reconstruction for non-human neuroimaging. It runs reliably across a wide range of anatomical structures and imaging conditions and has been successfully applied to datasets from primates, carnivores, and artiodactyls. Its modular framework mirrors human neuroimaging workflows, supports manual quality control, and produces outputs compatible with FreeSurfer and Connectome Workbench. In doing so, it substantially reduces technical barriers to non-human neuroimaging. As data-sharing initiatives continue to expand access to non-human imaging datasets, Precon_all provides a scalable and standardized solution that supports the broader adoption of surface-based methods for studying cortical evolution through comparative neuroscience.

neuroscience↗

bioRxiv2025

Three cortical streams for somatosensory information processing

AbstractThe somatosensory cortex processes information hierarchically, transforming sensory input into appropriate responses. This hierarchy, in turn, provides a fundamental principle for the organization of anatomical and functional properties across the somatosensory cortex. While the local somatosensory hierarchy has been studied, a comprehensive model that fully illustrates somatosensory information transmission in fine detail remains lacking. In this study, we examine multimodal connectivity patterns of the entire macaque somatosensory cortex by integrating the information from receptor covariance (RC) and structural (SC) or functional connectivity (FC). Our findings not only reveal the hierarchical relationships but also propose a model of somatosensory processing streams. In this model, area 3bl serves as the initial cortical stage for somatosensory signals, projecting to areas 3al, 1, and 2. From there, somatosensory signals follow three major pathways: ventrally to the SII complex, medially to the medial SI and TSA, and posteriorly to somatosensory association areas in the parietal lobe. Further analysis shows that RC is not only closely linked to SC and FC but in addition displays unique characteristics that likely relate to the hierarchical processing across sensory modalities. This study deepens our understanding of brain connectivity patterns across different modalities and links the structural, chemoarchitectonic, and functional organization of the macaque somatosensory cortex.

neuroscience↗

bioRxiv2025

Stress Granule Formation Drives ZBP1-dependent Necroptosis in Non-obstructive Azoospermia and Aging testes

Male infertility and age-related reproductive decline remain major unmet medical challenges, with limited understanding of the underlying mechanisms. Here, we identify a stress granule-driven necroptosis pathway involving ZBP1 and RIPK3 as a central driver of non-obstructive azoospermia (NOA), a severe form of male infertility marked by loss of spermatogenesis. We show that heat stress or environmental insults activate eIF2 kinases, inducing stress granules that recruit ZBP1 and RIPK3 to form a signaling complex. This leads to RIPK3 activation, MLKL phosphorylation, and necroptotic death of spermatogonia and Sertoli cells. Genetic ablation of Zbp1 or Ripk3 protects mice from heat-induced testicular atrophy, highlighting their essential role in testicular cell death. Notably, this same necroptosis pathway is also activated in aged human testes, suggesting a shared mechanism driving both male infertility and age-related testicular degeneration.

molecular biology↗

bioRxiv2025

Deciphering complex interactions between LTR retrotransposons and three Papaver species using LTR_Stream

Long terminal repeat retrotransposons (LTR-RTs), a major type of class I transposable elements (TEs), are the most abundant repeat element in plants. The study of the interactions between LTR-RTs and the host genome relies on high-resolution characterization of LTR-RTs. However, for non-model species, this remains a challenge. To address this, we developed LTR_Stream for sub-lineage clustering of LTR-RTs in specific or closely related species, providing higher precision than current database-based lineage-level clustering. Using LTR_Stream, we analyzed Retand LTR-RTs in three Papaver species. Our findings show that high-resolution clustering reveals complex interactions between LTR-RTs and the host genome. For instance, we found autonomous Retand elements could spread among the ancestors of different subgenomes, like retroviruses pandemics, enriching genetic diversity. Additionally, we identified that specific truncated fragments containing transcription factors motifs such as TCP and bZIP may contribute to generation of novel TAD-like boundaries. Notably, our pre- and post-allopolyploidization comparisons show that these effects diminished after allopolyploidization, suggesting that allopolyploidization may be one of the mechanisms by which Papaver species cope with LTR-RTs. We demonstrated the potential application of LTR_Stream and provided a reference case for studying the interactions between LTR-RTs and the host genome in non-model plant species.

bioinformatics↗

bioRxiv2025

MouseGPT: A Large-scale Vision-Language Model for Mouse Behavior Analysis

Analyzing animal behavior is crucial in advancing neuroscience, yet quantifying and deciphering its intricate dynamics remains a significant challenge. Traditional machine vision approaches, despite their ability to detect spontaneous behaviors, fall short due to limited interpretability and reliance on manual labeling, which restricts the exploration of the full behavioral spectrum. Here, we introduce MouseGPT, a Vision-Language Model (VLM) that integrates visual cues with natural language to revolutionize mouse behavior analysis. Built upon our first-of-its-kind dataset--incorporating pose dynamics and open-vocabulary behavioral annotations across over 42 million frames of diverse psychiatric conditions--MouseGPT provides a novel, context-rich method for comprehensive behavior interpretation. Our holistic analysis framework enables detailed behavior profiling, clustering, and novel behavior discovery, offering deep insights without the need for labor-intensive manual annotation. Evaluations reveal that MouseGPT surpasses existing models in precision, adaptability, and descriptive richness, positioning it as a transformative tool for ethology and for unraveling complex behavioral dynamics in animal models.

animal behavior and cognition↗

bioRxiv2025

Mapping affinity and allostery in human IgG antibody Fc region-Fc γ receptor interactions

IgG antibodies, required for a functional immune system, recognize antigens and neutralize pathogens using their Fab regions, while signaling to the immune system by binding to host Fc {gamma} receptors (Fc{gamma}Rs) through their Fc regions. These Fc{gamma}R interactions initiate and modulate antibody-mediated effector functions that are essential for host immunity, therapeutic monoclonal antibody effectiveness and IgG-mediated pathologies. Fc{gamma}Rs include both activating and inhibitory receptors and the relative binding affinities of the IgG Fc region to Fc{gamma}Rs that generate opposing signals is a key determinant of the immune response. Substantial research effort has been devoted to understanding and manipulating Fc{gamma}R interactions to decipher their fundamental biological activities and to develop therapeutic monoclonal antibodies with tailored effector functions. However, a common Fc-Fc{gamma}R binding interface, the high sequence identity of Fc{gamma}Rs, and the inherent conformational dynamics of the IgG Fc region, have prohibited a full understanding of these interactions, even when employing state-of-the-art biophysical and biological methods. Here, we used site-saturation libraries of the human IgG1 Fc region to determine the effective affinities of more than 98% of all possible single-site amino acid substitutions in the Fc to all human Fc{gamma}Rs, as well as the most common Fc{gamma}R polymorphisms. We provide a comprehensive analysis of Fc amino acid variations that determine Fc stability, orthosteric control of Fc{gamma}R binding, and short- and long-range allosteric control of Fc{gamma}R binding. We also predict the relative activating versus inhibitory effector function capacity of nearly every possible single-site Fc mutation.

biochemistry↗

bioRxiv2025

Respiratory Airway Secretory Cells act as Immune Sentinels in Human Distal Airways

Pulmonary immunity in the human distal respiratory airways is essential for lung function but remains poorly explored, mainly due to limited physiologically relevant models. Here, we develop distal lung organoids containing respiratory airway secretory (RAS) cells, a recently identified epithelial population unique to the distal airways of humans and large mammals, using human pluripotent stem cells (hPSCs). Lineage tracing identified RAS cells as descendants of SOX9brightNKX2-1bright progenitors. Single-cell transcriptomics elucidated that RAS cells exhibited a distinct immune-competent phenotype with enriched genes associated with viral host entry and pattern recognition receptor signaling. Functionally, RAS cells infected by respiratory syncytial virus (RSV) exhibited enhanced antiviral activity marked by upregulation of interferon-stimulated genes (ISGs) and complement component 3 (C3). In contrast, bacterial flagellin or Pseudomonas aeruginosa (PAO1) triggered a TLR5-driven immune response in RAS cells, inducing complement system activation, a response suppressed by selective TLR5 inhibition. Notably, in chronic obstructive pulmonary disease (COPD), RAS cells displayed dysregulated immune activation, characterized by elevated expression of adaptive immune mediators. Together, our findings identify RAS cells as previously unrecognized sensors and effectors of mucosal immunity in the human distal airways and reveal their roles in viral infection, bacterial stimulation, and chronic inflammatory lung disease, providing potential therapeutic targets for respiratory diseases.

cell biology↗

bioRxiv2025

Genetic association between posterior parietal cortex and intelligence

The identification of intelligence-associated loci raises questions for functional association of brain regions and for different intelligence concepts of either a general capability or discrete abilities. By generating single-nucleus transcriptomic atlas of mouse posterior parietal cortex (PPC), which is implicated in quantification behavior, we find that human intelligence-associated gene homologs are significantly enriched in certain specific neurons within the PPC. We also find 73% of the human intelligence gene homologs are highly enriched in PPC. In addition to PPC, several regions at different locations, not cortex next to PPC, are also significantly associated with intelligence genes. The separate locations of these cortex regions and their regional-specific expressed intelligence genes raise the possibility for discrete intelligence capabilities. Animal behavior analysis reveals that mutations for two top intelligence-associated genes with specific expression in either PPC or entorhinal cortex (ENT) affect quantification or learning and memory, respectively. Finally, five patients with PPC resection in the left hemisphere also display quantification defects, but not other cognitive abilities. Together, our studies provide the first genetic and functional evidence for the involvement of PPC in intelligence. Our data also support the model of multiple intelligence over a general capability for intelligence.

genetics↗

bioRxiv2025

Sub-second Fluctuation between Top-Down and Bottom-Up Modes Distinguishes Diverse Human Brain States

Information continuously flows between regions of the human brain, exhibiting distinct patterns that dynamically shift across states of consciousness, cognitive modes, and neuropsychiatric conditions. In this study, we introduce Relative Phase Analysis (RPA), a method that leverages phase-lead/lag relationships to reveal the real-time dynamics of dominant directional patterns and their rapid transitions. We demonstrate that the human brain switches on a sub-second timescale between a top-down mode-where anterior regions drive posterior activity-and a bottom-up mode, characterized by reverse directionality. These dynamics are most pronounced during full consciousness and gradually become less distinct as awareness diminishes. Furthermore, we find from simultaneous EEG-fMRI recordings that the top-down mode is expressed when higher-order cognitive networks are more active while the bottom-up mode is expressed when sensory systems are more active. Moreover, comparisons of an attention deficit hyperactivity disorder (ADHD) inattentive cohort with typically developing individuals reveal distinct imbalances in these transition dynamics, highlighting the potential of RPA as a diagnostic biomarker. Complementing our empirical findings, a coupled-oscillator model of the structural brain network recapitulates these emergent patterns, suggesting that such directional modes and transitions may arise naturally from inter-regional neural interactions. Altogether, this study provides a framework for understanding whole-brain dynamics in real-time and identifies sub-second fluctuations in top-down versus bottom-up directionality as a fundamental mechanism underlying human information processing.

neuroscience↗

bioRxiv2025

Biological subtyping of autism via cross-species fMRI

It is frequently assumed that the phenotypic heterogeneity in autism spectrum disorder reflects underlying pathobiological variation. However, direct evidence in support of this hypothesis is lacking. Here, we leverage cross-species functional neuroimaging to examine whether variability in brain functional connectivity reflects distinct biological mechanisms. We find that fMRI connectivity alterations in 20 distinct mouse models of autism (n=549 individual mice) can be clustered into two prominent hypo- and hyperconnectivity subtypes. We show that these connectivity profiles are linked to distinct signaling pathways, with hypoconnectivity being associated with synaptic dysfunction, and hyperconnectivity reflecting transcriptional and immune-related alterations. Extending these findings to humans, we identify analogous hypo- and hyperconnectivity subtypes in a large, multicenter resting state fMRI dataset of n=940 autistic and n=1036 neurotypical individuals. Remarkably, hypo- and hyperconnectivity autism subtypes are replicable across independent cohorts (accounting for 25.1% of all autism data), exhibit distinct functional network architecture, are behaviorally dissociable, and recapitulate synaptic and immune mechanisms identified in corresponding mouse subtypes. Our cross-species investigation, thus, decodes the heterogeneity of fMRI connectivity in autism into distinct pathway-specific etiologies, offering a new empirical framework for targeted subtyping of autism.

neuroscience↗