Biology subjects

Xian, J.

Publications and source records attributed to Xian, J..

11 recordsLinked to original sources

bioRxiv2026

OmicOS: A Comprehensive Omics Ecosystem Infrastructure and Agent System for the AI Era

Biology has accumulated a vast ecosystem of omics methods, but much of this ecosystem remains built for expert humans rather than scientific agents. Methods are scattered across Python packages, R/Bioconductor and CRAN workflows, command-line tools, incompatible data containers and implicit object states, making even routine analyses difficult for an AI system to choose, execute and verify reliably. Here we introduce OmicOS, a comprehensive omics ecosystem infrastructure and agent system that turns OmicVerse V2, an open-source omics community, into an executable foundation for agentic biology. OmicVerse V2 provides the community substrate: scalable AnnDataOOM-compatible rust backends, agent-friendly Python algorithms for single-cell, spatial, bulk and multi-omics analysis, interfaces to single-cell foundation models, and Python-native reconstructions of historically R-centred Bioconductor/CRAN-style workflows. OmicOS makes this substrate actionable by registering analytical functions as state-aware capability contracts, allowing agents to inspect live data objects, select valid methods, execute controlled workflows and record provenance. The result is not a fixed pipeline, but a programmable omics environment in which agents compose real analyses from verified community methods rather than inventing tools. Across external and purpose-built benchmarks, OmicOS ranked first among the evaluated systems, reaching 81.2% on BiomniBench. Adding OmicVerse to a minimal agent improved task completion by up to 34.2 percentage points with qwen-3.6-35b, and controlled ablations showed that the gains came from registry-grounded execution rather than from larger models, documentation retrieval or unrestricted tool exposure. The same infrastructure scaled to atlas-sized data, reproduced R-centred workflows in Python and converted external pathology software into agent-usable skills. In a discovery task starting from a whole-body spatial map and the term "Alzheimers disease", OmicOS composed a non-canonical workflow that integrated spatial expression, genetic association, eQTL and colocalization evidence to nominate a colon epithelial risk axis centred on PICALM, CD2AP and CR1. Together, OmicVerse and OmicOS define an open foundation for AI-era omics, showing how a community of biological methods can be transformed into a reliable, extensible and agent-operable system for discovery. HighlightO_LIOmicVerse 2.0 consolidates 694 methods spanning 11 omics domains into agent-callable high-level APIs. C_LIO_LIRebuildR automatically reconstructs and evolves R/Bioconductor methods as Python-native implementations under output-equivalence gates. C_LIO_LIOmicOS establishes a state-of-the-art omics agent harness, ranking first on general omics benchmarks across models and substantially improving the analytical capability of local open-source models. C_LIO_LICompositional use of ecosystem modules nominates a colon epithelial axis associated with Alzheimers disease risk. C_LIO_LIExternal algorithm packages supporting automatic iterative evolution can be integrated into the OmicOS ecosystem. C_LI

bioinformatics↗

bioRxiv2025

PI-FC: Pre-training Individual-specific Functional Connectome through State-invariant Contrastive Learning

Functional MRI enables non-invasive mapping of brain connectivity, yet its clinical translation remains hindered by uncontrolled state-dependent variability that obscures individual-specific signatures during routine scanning. Here we introduce PI-FC -- a deep learning framework leveraging state-invariant contrastive learning to extract stable individual brain signatures across diverse arousal levels, cognitive states, and temporal scales spanning tens of seconds to hours. PI-FC achieves equivalent phenotypic prediction accuracy using substantially reduced scanning time, and eliminates state-dependent effects varying task demands and brain states. Trained on 36,119 subjects across 8 independent datasets, our model demonstrates superior cross-site generalization and outperforms traditional functional connectome (FC) in predicting neuropsychiatric conditions including schizophrenia, autism, depression, and anxiety. Furthermore, PI-FC enables zero-shot inference of brain age, biological sex, and cognitive ability without site-specific retraining. Overall, PI-FC represents a robust, clinically scalable framework that overcomes fundamental barriers to real-world deployment of precision functional neuroimaging.

neuroscience↗

bioRxiv2025

Population-specific brain charts reveal Chinese-Western differences in neurodevelopmental trajectories

Human brain charts provide unprecedented opportunities for decoding neurodevelopmental milestones and establishing clinical benchmarks for precision brain medicine 1-7. However, current lifespan brain charts are primarily derived from European and North American cohorts, with Asian populations severely underrepresented. Here, we present the first population-specific brain charts for China, developed through the Chinese Lifespan Brain Mapping Consortium (Phase I) using neuroimaging data from 43,037 participants (aged 0-100 years) across 384 sites nationwide. We establish the lifespan normative trajectories for 296 structural brain phenotypes, encompassing global, subcortical, and cortical measures. Cross-population comparisons with Western brain charts (based on data from 56,339 participants aged 0-100 years) reveal distinct neurodevelopmental patterns in the Chinese population, including prolonged cortical and subcortical maturation, accelerated cerebellar growth, and earlier development of sensorimotor regions relative to paralimbic regions. Crucially, these Chinese-specific charts outperform Western-derived models in predicting healthy brain phenotypes and detecting pathological deviations in Chinese clinical cohorts. These findings highlight the urgent need for diverse, population-representative brain charts to advance equitable precision neuroscience and improve clinical validity across populations.

neuroscience↗

bioRxiv2025

TransBrain: A computational framework for translating brain-wide phenotypes between humans and mice

Despite remarkable advances in whole-brain imaging technologies, the lack of quantitative approaches to bridge rodent preclinical and human studies remains a critical challenge. Here we present TransBrain, a computational framework enabling bidirectional translation of brain-wide phenotypes between humans and mice. TransBrain improves human-mouse homology mapping accuracy through: (1) a novel detached region-specific deep neural network trained on integrated multi-modal human transcriptomics to improve cortical correspondence (89.5% improvement over the original transcriptome), which revealed two evolutionarily conserved gradients explaining >50% of cortical organizational variance, and (2) random walk-based graph representation learning to construct a unified cross-species latent space incorporating anatomical hierarchies and structural connectivity. We demonstrated TransBrains utility through three cross-species applications: quantitative assessment of resting-state brain organizational features, inferring human cognitive functions from mouse optogenetic circuits, and translating molecular insights from mouse models to individual-level mechanisms in autism. TransBrain enables quantitative cross-species comparison and mechanistic investigation of both normal and pathological brain functions.

neuroscience↗

bioRxiv2024

Identification of Stress-induced miRNA of Microbial flora, networking, expression with chronic rhinosinusitis (CRS)

All age groups are affected by one of the most prevalent chronic medical disorders globally: chronic rhinosinusitis (CRS). Its estimated incidence is 10.9% in Europe, 13% in China, and 12.3% in the United States. For many years, the 16S rRNA gene has been the backbone of sequence-based bacterial study. Still, it is only recently that the possibility of high-throughput sequencing the entire gene has been feasible. A unique gene regulation mechanism known as "RNA silencing" limits the transcript level by either starting specific RNA degradation or blocking translation. RNA interference (RNAi) is commonly induced by viruses or exogenously produced small interfering RNAs. Small RNAs like these have been utilized in biomedical research to specifically silence genes. The purpose of a short hairpin RNA is to create interference by inserting an artificial RNA molecule with a hairpin or loop-like structure into a specially designed siRNA. Every stage of life, including cell development, metabolism, the cell cycle, and signal transmission, depends on gene regulatory networks. Total fifteen mRNAs of 16SrRNA gene examined, siRNA regions is unique and isolated through 3 to 5 position nucleotide. Networking of both genes lies varieties of path in human being, so early to utilized siRNA technique to silence the effect of 16SrRNA gene in CRS illness. The gene encoding 16S rRNA has around ten target sites that siRNAs can attach to. The siRNAs are made to be complementary sequences to each of the target sites. Verify the 16S rRNA gene expression in CRS illness and other types across the body. Since a cystic fibrosis transmembrane conductance regulator (CFTR) mutation causes CRS illness, we isolated a mutant form of CFTR with an accession ID of 1XMJ and 16S rRNA protein quotes in 8SR6. Examine the two proteins interaction (1xmj, 8sr6) describe the inhibition of CRS illness through new way. Utilizing in-vitro exploratory approaches, both this computational study of siRNA and protein-protein interaction may be employed further to verify efficacy and appropriateness.

bioinformatics↗

bioRxiv2024

Longevity or Well-being? A Dual-Dimension Structure of Neuroticism

The development of personality traits is often viewed as evolutionarily adaptive. Current neuroticism research, however, predominantly highlights its negative health impacts, neglecting its potential evolutionary advantages. We propose that neuroticisms inter-individual variability can be structured into two distinct geometric dimensions. One, named the Emotional Reactivity-Instability/Distress Spectrum (ERIS), correlates strongly with longevity and is associated with chronic diseases and risk-averse lifestyle. This dimension is underpinned by evolutionarily conserved subcortical brain regions and genes. The other, resembling the overall neuroticism score, is primarily linked to mental and stress-related disorders, as well as life satisfaction. It involves higher-order emotional brain regions and is genetically enriched in human-accelerated regions. Collectively, these dimensions represent a dual-strategy personality framework that optimizes survival and well-being, with the former being evolutionarily conservative and the latter potentially a unique human adaptation.

neuroscience↗

bioRxiv2024

Mapping Individual Differences in the Topological Landscape of Naturalistic Brain Dynamics

Psychiatry seeks to unravel brain dysfunction and individual differences in real-world contexts. Naturalistic stimuli, like movie watching, are increasingly recognized for eliciting complex, context-dependent neural activity with high ecological validity. Yet, current methods often rely on standard paradigms that average data across time, limiting the full potential of such stimuli. Here, we present STIM, a Topological Data Analysis-based framework designed to dynamically track how individuals integrate complex contexts in real time. Applied to large-sample fMRI data from movie watching, STIM constructs a robust low-dimensional dynamical landscape that reflects group consensus while probing individual variations at both global (spanning narratives) and local (within specific narratives) levels. At the global level, individual differences emerge along a center-periphery gradient in the dynamical landscape, which significantly predicts fluid intelligence, underscoring the importance of neural adaptability and diversity. At finer scales, local geometric features correlate with context-specific psychological traits beyond cognition. STIM also captures developmental changes in the dynamical landscape and reveals abnormalities in conditions such as autism. These findings demonstrate that STIM leverages the rich information from movie stimuli and fMRI recordings as neural probes to assess individual differences in cognition and mental health.

neuroscience↗

bioRxiv2024

Optimizing clinical interpretability of functional evidence in epilepsy-related ion channel variants

Variants in genes encoding the voltage-gated ion channels are among the most common monogenic causes of epilepsy and neurodevelopmental disorders. Functional effects of a variant are increasingly important for diagnosis and therapeutic decisions. To incorporate knowledge regarding functional consequences in formal clinical variant interpretation, we developed an approach for evaluating multiple functional measurements within the Bayesian framework of the modified ACMG/AMP guidelines. We analyzed 216 functional assessments of 191 variants in SCN1A (n=74), SCN2A (n=66), SCN3A (n=18), and SCN8A (n=33). Of 20 commonly measured biophysical parameters, the most frequent drivers of overall functional consequence were persistent current (f=0.54), voltage dependence of activation (f=0.51), and voltage dependence of fast inactivation (f=0.40) for gain-of-function and peak current (f=0.87) for loss-of-function. By comparing measurements of 23 benign variants, we determined thresholds by which published data on these four parameters confer Strong evidence of variant pathogenicity (likelihood ratio > 18.7) under the ACMG/AMP rubric. Similarly, we delineated evidence weights for the most common epilepsy-related potassium channel gene, KCNQ2, through reports of 80 pathogenic and 24 benign variants, accounting for heterozygous and homozygous experimental conditions. We collected the resulting categorization of functional data into FENICS, a biomedical ontology of 152 standardized terms for coherent annotation of electrophysiological results. Across 271 variants in SCN1A/2A/3A/8A and KCNQ2, 1,731 annotations are available in ClinVar, facilitating use of this evidence in variant classification. In summary, we introduce and apply an ACMG/AMP-calibrated framework for electrophysiological studies in epilepsy-related channelopathies to delineate the impact of functional evidence on clinical variant interpretation.

genetics↗

bioRxiv2024

Heterogeneous hybrid immunity against Omicron variant JN.1 at 11 months following breakthrough infection

A highly transmissible SARS-CoV-2 variant JN.1 is rapidly spreading throughout the nation, becoming the predominant strain in China and worldwide. However, the current immunity against the circulating JN.1 at population level has yet to be fully evaluated. We recruited representative cohorts with stratified age groups and diverse combinations of vaccination and/or infection in recent months, and promptly assessed humoral immunity for these subjects predominantly exhibiting hybrid immunity. We report that at 11 months following BA.5-wave breakthrough infection (BTI), these vaccinated individuals generally showed above-the-threshold yet low level of neutralizing activity against JN.1, with slightly greater potency observed in children and adolescents compared to adults and seniors. Meanwhile, XBB/EG.5-wave reinfection post-BTI significantly boosted the neutralizing antibodies against Omicron variants, including JN.1 in both adults (13.4-fold increase) and seniors (24.9-fold increase). To better understand respiratory mucosal protection against JN.1 over an extended period of months post-BTI, we profiled the humoral immunity in bronchoalveolar lavage samples obtained from vaccinated subjects with or without BTI, and revealed increased potency of neutralizing activity against the BA.5 and JN.1 variants in the respiratory mucosa through natural infection. Notably, at 11 months post-BTI, memory B cell responses against prototype and JN.1 were detectable in both blood and respiratory mucosa, displaying distinct memory features in the circulation and airway compartments. XBB/EG.5-wave reinfection drove the expansion of JN.1-specific B cells, along with the back-boosting of B cells responding to the ancestral viral strain, suggesting the involvement of immune imprinting. Together, this study indicates heterogeneous hybrid immunity over 11 months post-BTI, and underscores the vulnerability of individuals, particularly high-risk seniors, to JN.1 breakthrough infection. An additional booster with XBB-containing vaccine may greatly alleviate the onward transmission of immune-evasive SARS-CoV-2 variants.

immunology↗

bioRxiv2022

Creating a 'Timeline' of ductal carcinoma in situ to identify processes and biomarkers for progression towards invasive ductal carcinoma

Ductal carcinoma in situ (DCIS) is considered a non-invasive precursor to breast cancer, and although associated with an increased risk of developing invasive disease, many women with DCIS will never progress beyond their in situ diagnosis. The path from normal duct to invasive disease is not well understood, and efforts to do so are hampered by the substantial heterogeneity that exists between patients and even within patients. Using gene expression analysis, we have generated a Timeline of disease progression, utilising the variability within patients and combining >2,000 individually micro-dissected ductal lesions from 145 patients into one continuous trajectory. Using this Timeline we show there is a progressive loss in basal layer integrity, coupled with two epithelial to mesenchymal transitions (EMT), one early in the timeline and a second just prior to cells leaving the duct. We identify early processes and potential biomarkers, including CAMK2N1, MNX1, ADCY5, HOXC11 and ANKRD22, whose reduced expression is associated with the progression of DCIS to invasive breast cancer.

cancer biology↗

bioRxiv2019

Satellite Imaging of Global Urbanicity relate to Adolescent Brain Development and Behavior

Urbanicity, the impact of living in urban areas, is among the greatest environmental challenges for mental health. While urbanicity might be distinct in different sociocultural conditions and geographic locations, there are likely to exist common features shared in different areas of the globe. Understanding these common and specific relations of urbanicity with human brain and behavior will enable to assess the impact of urbanicity on mental disorders, especially in childhood and adolescence, where prevention and early interventions are likely to be most effective.\n\nWe constructed from satellite-based remote sensing data a factor for urbanicity that was highly correlated with population density ground data. This factor, UrbanSat was utilized in the Chinese CHIMGEN sample (N=831) and the longitudinal European IMAGEN cohort (N=810) to investigate if exposure to urbanicity during childhood and adolescence is associated with differences in brain structure and function in young adults, and if these changes are linked to behavior.\n\nUrbanicity was found negatively correlated with medial prefrontal cortex volume and positively correlated with cerebellar vermis volume in young adults from both China and Europe. We found an increased correlation of urbanicity with functional network connectivity within- and between- brain networks in Chinese compared to European participants. Urbanicity was highly correlated with a measure of perceiving a situation from the perspective of others, as well as symptoms of depression in both datasets. These correlations were mediated by the structural and functional brain changes observed. Susceptibility to urbanicity was greatest in two developmental windows during mid-childhood and adolescence.\n\nUsing innovative technology, we were able to probe the relationship between urban upbringing with brain change and behavior in different sociocultural conditions and geographic locations. Our findings help to identify shared and distinct determinants of adolescent brain development and mental health in different regions of the world, thus contributing to targeted prevention and early-intervention programs for young people in their unique environment. Our approach may be relevant for public health, policy and urban planning globally.

neuroscience↗