Biology subjects

Ju, W.

Publications and source records attributed to Ju, W..

9 recordsLinked to original sources

bioRxiv2026

Deciphering Spatial Cellular Organization through RNA-Anchored Multi-Omics Deconvolution

Spatial technologies that jointly profile RNA and additional molecular layers provide a comprehensive view of tissue organization, yet their limited resolution results in measurements that reflect mixtures of multiple cell types. While RNA-based deconvolution methods are well established, incorporating co-profiled non-transcriptomic modalities without compromising cell-type identifiability remains an open challenge, as reliable references are largely restricted to transcriptomic data. Here we present SMODER, an RNA-anchored framework for spatial multi-omics deconvolution that treats transcriptomes as the primary determinant of cell identity while incorporating complementary molecular modalities in a constrained manner. By adopting an asymmetric integration strategy, SMODER preserves RNA-driven cell-type resolution and enables robust estimation of cell-type compositions across spatial locations. Across simulations and diverse spatial multi-omics datasets spanning protein, chromatin accessibility and histone modification assays, SMODER consistently outperforms existing methods in both accuracy and spatial coherence. Beyond deconvolution, SMODER denoises multi-omic signals and enables cell-type-aware analysis of regulatory programs. Application to spatial CUT\&Tag--RNA-seq and {RNA--ATAC-seq} data reveals spatially resolved epigenetic repression and cis-regulatory relationships linked to gene expression.

bioinformatics↗

bioRxiv2026

scOLAR: Ontology-Anchored Open-Set Annotation of Single-Cell RNA-seq Data

Single-cell RNA sequencing profiles cellular heterogeneity at atlas scale, making automated annotation essential. However, target datasets often contain novel cell types missing from incomplete references. We present scOLAR, an ontology-guided open-set framework that learns prototypes over the Cell Ontology and uses both reference and target expression to annotate known classes while detecting unfamiliar populations. Guided by ontology hierarchies and decision-boundary regularization, scOLAR penalizes coarse-lineage misclassification and groups novel cells without requiring predefined cluster counts. Across benchmarks, scOLAR achieves a novelty-detection AUROC of 0.9726 and an average precision of 0.9871, enabling structured post-hoc lineage-level interpretation of populations absent from the reference.

bioinformatics↗

bioRxiv2025

Poldip2 deficiency attenuates disease severity in a mouse model of COVID-19

The lungs are the primary target of severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2), with the infection resulting in lung inflammation, pulmonary vascular leakage and diffuse alveolar damage. Polymerase delta-interacting protein-2 (Poldip2) mediates lung inflammation and vascular permeability after lipopolysaccharide-induced acute respiratory distress syndrome; however, its role in regulating lung permeability, vascular inflammation and tissue damage following SARS-CoV-2 infection is completely unknown. Here, we assessed the role of Poldip2 in inflammation, immune cell infiltration and lung tissue damage in response to SARS-CoV-2 infection. Our data shows that while deletion of Poldip2 does not affect the susceptibility to SARS- CoV-2 infection, mice heterozygous for Poldip2 exhibit reduced lung tissue damage, reduced cytokine and chemokine induction and decreased infiltration of myeloperoxidase (MPO)-positive neutrophils into inflamed lung tissue. These data reveal that Poldip2 depletion mitigates inflammation and immune cell infiltration following SARS-CoV-2 infection, highlighting the therapeutic potential of Poldip2 inhibition to attenuate severe lung injury.

pathology↗

bioRxiv2024

A Novel Role of Hyaluronan and its Membrane Receptors, CD44 and RHAMM in Obesity-Related Glomerulopathy

Obesity-related glomerulopathy (ORG) contributes to diabetic nephropathy and kidney cancer, leading to chronic/end-stage kidney disease. To date, treatments for ORG are limited because of incomplete understanding of the disease pathogenesis. Here, we identified a novel role for hyaluronan (HA) and its membrane receptors, CD44 and RHAMM in obesity-associated renal inflammation, fibrosis, tubular injury, and kidney dysfunction. Pharmacological and genetic ablation of HA, CD44 or RHAMM reversed these renal disorders induced by high fat diet feeding in mice in vivo. Increased HA content, and CD44 and RHAMM expression damaged the kidney via activation of TGF-{beta}1/Smad2/3, P38/JNK MAPK and ROCK/ERK pathways. We further established a link between renal insulin resistance and ECM remodelling using human kidney cells in vitro, shedding mechanistic insight into the role of HA, CD44 and RHAMM in the pathogenesis of ORG. Furthermore, in human kidney biopsies gene expression of CD44 and RHAMM was increased in chronic kidney disease and diabetic nephropathy, and their levels were correlated with markers of kidney (dys)function (GFR, serum creatinine, proteinuria). Our findings provide evidence for HA-CD44/RHAMM as a potential therapeutic target in ORG and consequent prevention of chronic kidney disease.

physiology↗

bioRxiv2024

AIBP controls amyloid beta induced TLR4 inflammarafts and mitochondrial dysfunction in microglia

Microglia-driven neuroinflammation plays an important role in the development of Alzheimers disease (AD). Microglia activation is accompanied by the formation and chronic maintenance of TLR4 inflammarafts, defined as enlarged and cholesterol-rich lipid rafts serving as an assembly platform for TLR4 dimers and complexes of other inflammatory receptors. The secreted apoA-I binding protein (APOA1BP or AIBP) binds TLR4 and selectively targets cholesterol depletion machinery to TLR4 inflammaraft expressing inflammatory, but not homeostatic microglia. Here we demonstrated that amyloid-beta (A{beta}) induced formation of TLR4 inflammarafts in microglia in vitro and in the brain of APP/PS1 mice. Mitochondria in Apoa1bp-/- APP/PS1 microglia were hyperbranched and cupped, which was accompanied by increased ROS and the dilated ER. The size and number of A{beta} plaques and neuronal cell death were significantly increased, and the animal survival was decreased in Apoa1bp-/- APP/PS1 compared to APP/PS1 female mice. These results suggest that AIBP exerts control of TLR4 inflammarafts and mitochondrial dynamics in microglia and plays a protective role in AD associated oxidative stress and neurodegeneration.

neuroscience↗

bioRxiv2023

Poisoning medical knowledge using large language models

Biomedical knowledge graphs constructed from scientific literature have been widely used to validate biological discoveries and generate new hypotheses. Recently, large language models (LLMs) have demonstrated a strong ability to generate human-like text data. While most of these text data have been useful, LLM might also be used to generate malicious content. Here, we investigate whether it is possible that a malicious actor can use LLM to generate a malicious paper that poisons scientific knowledge graphs and further affects downstream biological applications. As a proof-of-concept, we develop Scorpius, a conditional text generation model that generates a malicious paper abstract conditioned on a promoting drug and a target disease. The goal is to fool the knowledge graph constructed from a mixture of this malicious abstract and millions of real papers so that knowledge graph consumers will misidentify this promoting drug as relevant to the target disease. We evaluated Scorpius on a knowledge graph constructed from 3,818,528 papers and found that Scorpius can increase the relevance of 71.3% drug disease pairs from the top 1000 to the top 10 by only adding one malicious abstract. Moreover, the generation of Scorpius achieves better perplexity than ChatGPT, suggesting that such malicious abstracts cannot be efficiently detected by humans. Collectively, Scorpius demonstrates the possibility of poisoning scientific knowledge graphs and manipulating downstream applications using LLMs, indicating the importance of accountable and trustworthy scientific knowledge discovery in the era of LLM.

bioinformatics↗

bioRxiv2021

Physiological activation of the nephron central command drives endogenous kidney tissue regeneration

Tissue regeneration is limited in several organs including the kidney, contributing to the high prevalence of kidney disease globally. However, evolutionary and physiological adaptive responses and the presence of renal progenitor cells suggest existing remodeling capacity. This study uncovered a novel endogenous tissue remodeling mechanism in the kidney that is activated by the loss of body fluid and salt and involves a unique niche of chief cells called macula densa (MD) that control resident progenitor cells via secreted angiogenic, growth and extracellular matrix remodeling factors, cytokines and chemokines. Serial intravital imaging, MD Wnt mouse models and transcriptome analysis provide functional and molecular characterization of this newly identified MD program for kidney regeneration complemented with human and therapeutic translation. The concept that chief cells responding to organ-specific physiological inputs control local progenitors and direct them to remodel or repair tissues may be applicable to other organs and diverse tissue regenerative therapeutic strategies.

physiology↗

bioRxiv2020

Comparative proteomics analysis identifies L-FABP as a putative biomarker of graft injury during liver transplantation

BackgroundTo a large extent the success of liver transplantation depends on quality of allografts. The molecular basis of the susceptibility of different liver allografts to transplant injury remains undefined. MethodsTransplanted liver samples were collected and divided into three groups: the optimal graft (OG) group, early allograft dysfunction (EAD) group, and primary nonfunction (PNF) group. iTRAQ comparative quantitative proteomic analysis and multiple reaction monitoring (MRM) verification was performed. ResultsMore than 160 differentially expressed proteins were detected in the PNF group, compared to 54 and 36 proteins in the EAD and OG groups respectively. Liver-type fatty acid-binding protein (L-FABP) was found as differentially expressed in both cold preserved and reperfused liver. Serum L-FABP level in donors was higher in the PNF and EAD groups than in the OG group. A lower tissue expression of L-FABP was observed in the PNF groups than other groups after reperfusion, indicating incompetent liver donor quality. In mouse ischemia reperfusion injury (IRI) model, the serum levels and tissue expression of L-FABP corresponded to the ALT variation curve. ConclusionsSuboptimal donor livers are more sensitive to ischemia reperfusion injury. L-FABP might be an effective biomarker for evaluating donor quality in liver transplantation.

molecular biology↗

bioRxiv2018

Inflammatory and JAK-STAT Pathways as Shared Molecular Targets for ANCA-Associated Vasculitis and Nephrotic Syndrome

BackgroundGlomerular diseases of the kidney are presently differentiated, diagnosed and treated according to conventional clinical or structural features. While etiologically diverse, these diseases share common clinical features including but not limited to reduced glomerular filtration rate, increased serum creatinine and proteinuria suggesting shared pathogenic mechanisms across diseases. Renal biopsies from patients with nephrotic syndrome (NS) or ANCA-associated vasculitis (AAV) were evaluated for molecular signals cutting across conventional disease categories as candidates for therapeutic targets.\n\nMethodsRenal biopsies were obtained from patients with NS (minimal change disease, focal segmental glomerulosclerosis, or membranous nephropathy) (n=187) or AAV (granulomatosis with polyangiitis or microscopic polyangiitis) (n=80) from the Nephrotic Syndrome Study Network (NEPTUNE) and the European Renal cDNA Bank. Transcriptional profiles were assessed for shared disease mechanisms.\n\nResultsIn the discovery cohort, 10-25% transcripts were differentially regulated versus healthy controls in both NS and AAV, >500 transcripts were shared across diseases. The majority of shared transcripts (60-77%) were validated in independent samples. Therapeutically targetable networks were identified, including inflammatory JAK-STAT signaling. STAT1 eQTLs were identified and STAT1 expression associated with GFR-based outcome. A transcriptional STAT1 activity score was generated from STAT1-regulated target genes which correlated with CXCL10 (p<0.001), a JAK-STAT biomarker, predictors of CKD progression, interstitial fibrosis (r=0.41, p<0.001), and urinary EGF (r=-0.51, p<0.001).\n\nConclusionAAV and NS caused from histopathologically distinct disease categories share common intra-renal molecular pathways cutting across conventional disease classifications. This approach provides a starting point for de novo drug development, and repurposing efforts in rare kidney diseases.

systems biology↗