Biology subjects

Xu, D.

Publications and source records attributed to Xu, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

A natural soil-derived microbiota reshapes nitrogen form and plant mineral nutrition

Nitrogen form in soil has a major influence on plant growth and mineral nutrition, yet whether and how nitrogen form is controlled by microbiota in natural soils remains poorly understood. Here we show that, in a high-organic-matter soil from Danish nature, the native soil microbiota determines nitrogen form and thereby controls plant mineral nutrition. Eliminating the microbiota by sterilization disrupted nitrification, causing ammonium accumulation and loss of nitrate, which resulted in impaired growth and a pronounced reduction in shoot Mg and Ca associated with chlorosis. Reintroduction of a simplified soil-derived microbiota restored nitrification and re-established a balanced NO{square}{square}/NH{square}{square} regime, which rescued Mg and Ca accumulation, alleviated chlorosis, and promoted plant growth. Metagenomic analyses of bulk soil, rhizosphere, and root-associated communities revealed enrichment of nitrogen-cycling functions, including nitrification-related genes, supporting the capacity of the restored microbiota to modulate nitrogen form in soil and the rhizosphere. Moreover, this microbiota alleviated mineral deficiency symptoms in an organic agricultural soil. Together, our findings reveal a natural microbiota-dependent mechanism by which soil microbes determine nitrogen form and thereby regulate plant mineral nutrition, particularly Mg and Ca homeostasis.

plant biology↗

bioRxiv2026

DPLM: Dynamics-aware Protein Language Model via contrastive learning between sequence and molecular dynamics simulation trajectory

Protein dynamics play a critical role in protein function, yet such important information is missing in many protein language models (PLM). We introduce DPLM, a dynamics-aware protein language model that aligns sequence embeddings with molecular dynamics (MD) trajectory embeddings via contrastive learning. Using MD features encoded by a pretrained video model, DPLM learns sequence representations that correlate with residue-level flexibility and improve protein-level functional clustering compared to static sequence- and structure-based PLMs. Without task-specific training, DPLM outperforms ESM-based representations in zero-shot mutation-effect prediction on multiple deep mutational scanning datasets. When adapted with lightweight task-specific heads, DPLM further achieves top-tier performance on protein stability prediction and intrinsic disorder region identification, demon-strating that contrastive alignment with MD trajectories enables PLMs to capture biologically meaningful dynamic properties.

bioinformatics↗

bioRxiv2026

CMS: Achieving Uniform and High-Quality Sequencing across Challenging Non-canonical Genomic Regions

High-throughput sequencing is essential in modern biological research, yet low-complexity sequences remain challenging as they form structurally complex, non-canonical (non-B) DNA conformations that impede sequencing enzyme read-through. This leads to a long-standing trade-off: maximizing coverage introduces false positives (FP), while stringent filtering causes coverage loss and false negatives (FN). To address this, we developed CMS (Cross Mountains and Seas) on GeneMind sequencing platforms by optimizing its chemistry and enzymatic systems to traverse these secondary structures with high fidelity. Benchmarking across whole-genome (WGS) and whole-exome (WES) sequencing demonstrates that CMS addresses the trade-off by simultaneously enhancing both coverage uniformity and accuracy, notably achieving an approximately 100-fold reduction in low-coverage bins for WGS and a 70% reduction in FN insertions/deletions (INDELs) within complex non-B regions. Specifically, a synthetic G-quadruplex (G4) motif sequencing experiment demonstrates that CMS maintains a 1:1 strand ratio, effectively handling G4-induced biases where benchmarked platforms exhibit extensive depletion. These findings establish CMS as a reliable technology for the precise characterization of structural-challenging but functional-essential genome regions.

genomics↗

bioRxiv2026

CellPulse: A Foundation Model of Coordinated Gene Dynamics Simulating Viral Infectious Diseases

Understanding how cells respond to perturbations like viral infections requires models capturing coordinated gene dynamics. However, current gene expression foundation models are predominantly reliant on single-cell data and static gene expression, limiting their applicability in real clinical scenarios. We present CellPulse, a direction-aware foundation model trained on the Virus Stimulated Atlas (VISTA), a newly curated atlas of over 23 million bulk RNA-sequencing differential expression profiles from viral infections. CellPulse models the direction and magnitude of gene expression changes via a structured representation of differential expression and a direction-aware attention mechanism, enabling the learning of coherent regulatory programs. It shows powerful diagnosing capability by accurately classifying 31 distinct virus types across diverse clinical and laboratory samples, solely from host transcriptional signatures. Crucially, without prior knowledge injection, CellPulses interpretability reveals virus-associated host factors that mediate infection. Using a selection of host factors for in silico drug screening yielded numerous compounds with confirmed efficacies in wet-lab assays, while cell-based and animal experiments further verified the causal relationship between host targets and viral infections. Overall, CellPulse represents a generalizable foundation model for deciphering coordinated gene dynamics from bulk transcriptomics, bridging host response modeling with clinical relevance and therapeutic discovery for infectious diseases and beyond.

bioinformatics↗

bioRxiv2026

Repetition-controllable gain-managed nonlinear fiber amplifier enables ultrashort, multiphoton imaging with reduced photodamage

1.We report a repetition-controllable gain-managed nonlinear fiber amplifier (GMNA) that delivers near-infrared 50-fs pulses with pulse energies up to 150 nJ and a widely tunable repetition rate from 1-20 MHz, while maintaining stable pulse quality across the full range. Using this source, we demonstrate label-free multiphoton imaging--including metabolic autofluorescence (2PF/3PF), second/third-harmonic generation, and Simultaneous Label-free Autofluorescence Multiharmonic (SLAM) microscopy imaging--across live cells, human lung spheroids, and hard tissues. We further assess the impact of laser repetition rate on photodamage at fixed pulse energy, supported by preliminary measurements indicating lower damage at lower repetition rate. Collectively, the compact architecture and repetition-rate agility of the GMNA enable real-time optimization of imaging speed, depth, and sample safety for advanced biological microscopy.

biophysics↗

bioRxiv2026

SIMBA: an agentic AI platform for single-molecule multi-dimensional imaging

Advances in multi-dimensional imaging method and probe developments have brought super-resolution fluorescence microscopy into a functional era. They capture additional single-molecule fluorescence information concurrently with spatial localization, enabling simultaneous identification of molecular species and interrogation of nanoscale environments with rich, high-dimensional imaging information. However, the adoption of multi-dimensional imaging has been hindered by fragmented analysis workflows, complex parameter tuning, and limited integration of advanced computational methods. Here, we introduce an agentic single-molecule multi-dimensional bioimaging AI, referred to as SIMBA, an AI-driven platform that unifies single-molecule localization, spectral processing and deep learning-based denoising within a single agentic and interactive framework. SIMBA incorporates large language model-based agents capable of interpreting user intent, orchestrating analysis pipelines, and dynamically selecting computational tools for automated data processing. We demonstrate that SIMBA enables supports standard single-molecule localization workflow, functional mapping of nanoscale environmental heterogeneity through single-molecule spectral analysis and denoising using developed supervised learning methods. By integrating extensible tool architectures with human language-guided workflows, SIMBA establishes a new paradigm for intelligent microscopy analysis, lowering barriers to multi-dimensional imaging adoption while enabling scalable, reproducible, and adaptive analysis of complex imaging datasets.

bioengineering↗

bioRxiv2026

A Brain-wide Neuronal Spiking and Behavior Dataset for Working Memory-Specific Activation and Reactivation in Mice

AbstractHow do millisecond-scale neural activities mediate multi-second behaviors such as working memory? This dataset provides brain-wide, high-spatiotemporal-resolution single-unit spiking activity recorded from 40 head-fixed mice performing an olfactory delayed paired-association (ODPA) task, encompassing 33,028 neurons across 62 anatomically defined brain regions. Utilizing this dataset enables the extraction of millisecond-scale within- and cross-region spike couplings enriched among memory-content-selective neurons. These couplings may be used to identify higher-order, hierarchically structured activity motifs. Because these multi-neuron patterns are captured both during active task performance and spontaneous inter-trial intervals, this dataset provides a resource for studying replay-related activity and for testing hypotheses about circuit-level processes associated with perceptual working memory. The dataset supports broad investigations into cross-regional spike organization, functional coupling, and temporal coding in working memory circuits.

neuroscience↗

bioRxiv2026

The chitin receptor-interacting protein LIK1 regulates extracellular ATP signaling via interaction with P2K1 in Arabidopsis thaliana

Previously, the chitin receptor-interacting protein kinase LIK1 (LysM receptor kinase 1/CERK1-interacting kinase) was shown to play an important role in regulating chitin signaling and plant defense. A limited proteolysis proteomics study revealed several LIK1-derived peptides that showed differential abundance between ATP-treated and mock-treated Arabidopsis samples, suggesting a possible involvement of LIK1 in extracellular ATP (eATP) signaling. To explore this possibility, LIK1 mutants were obtained and examined for their response to ATP. The results showed that mutations in LIK1 significantly reduced the expression of eATP-responsive genes. In addition, LIK1 was found to interact with the eATP receptor P2K1 and to be phosphorylated by it. The LIK1 protein was localized to the plasma membrane and its gene expression appeared to be ubiquitous. Collectively, these findings indicate that LIK1 not only contributes to chitin signaling but also participates in eATP signaling, highlighting its potential role as a shared component in multiple signaling pathways to regulate plant responses to diverse internal and external cues.

plant biology↗

bioRxiv2026

CNS diseases cerebrospinal fluid single-cell atlas reveals immune characteristics of neuropsychiatric systemic lupus erythematosus

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a potentially severe complication of systemic lupus erythematosus (SLE), yet its pathogenesis remains largely elusive. By jointly probing the immune dynamics of subjects cerebrospinal fluid (CSF) and peripheral blood, we showed that both innate and adaptive immune responses jointly contribute to the pathogenesis of NPSLE. In particular, we found the remarkable enrichment of BAM-CCL3, a subtype of border-associated macrophages with strong recruitment capacity, implicating its potential role in central nervous system (CNS) inflammation. We also observed pronounced activation of memory B cells and CD4+ regulatory T cells in NPSLE CSF, along with the preferential blood-to-CSF migration and subsequent within-CSF clonal expansion of CD8+ effector memory T cells in NPSLE patients, suggesting a persistent CNS-localized adaptive immune dysregulation. Finally, we developed the single-cell CNS disease CSF-Blood Atlas (scCDCB), a comprehensive collection for CSF and peripheral blood of multiple CNS diseases, which is publicly available at (https://sccdcb.gao-lab.org) to serve as a reference for future research on CNS diseases.

genomics↗

bioRxiv2026

Utilizing raw rapeseed press cake in foods: A case study on sensory quality and profile of selected bitter compounds in snack bars

Todays canola quality rapeseed press cake (RPC) is a protein-rich co-product with potential as human food, but its application is limited due to antinutritional compounds and bitter taste. It remains, however, unknown how introduction of raw RPC to a food matrix affects sensory perception and which metabolites drive the sensation. Here, raw RPC from whole or dehulled seeds was introduced into snack bars at 0%, 7%, 14%, and 21%, and sensory responses were correlated to selected known RPC-derived bitter compounds. A trained panel evaluated 13 RPC-characteristic sensory attributes, and the bitter compounds sinapic acid, kaempferol 3-O-(2'''-O-sinapoyl-{beta}-sophoroside) (KSS), KSS-hexose, selected bitter glucosinolates, and goitrin were quantified using targeted LC-MS/MS. Most dose-dependent sensory responses increased up to 14% RPC and then plateaued, whereas astringent mouthfeel increased almost linearly across the full dose range. Dehulling intensified several odor- and flavor-related attributes but did not increase bitterness or protein content in the final product. Principal component analysis linked bitterness and astringency positively with KSS, KSS-hexose, and goitrin. Dose-over-threshold analysis further showed that goitrin, but not progoitrin, reached concentrations relevant for bitterness perception. Together, the results demonstrate that raw RPC contributes distinct dose-dependent sensory attributes and that metabolite transformations in the food matrix shape final sensory profiles. These findings provide a basis for developing RPC-containing foods and for breeding rapeseed lines with improved sensory characteristics. HIGHLIGHTSO_LIThis study presents the first sensory panel assessment of rapeseed press cake (RPC)-containing in food products (snack bars) made from whole and dehulled seeds. C_LIO_LI13 RPC-characteristic sensory attributes are identified. C_LIO_LISensory profiles of the tasted snack bars differed significantly, influenced by the dosage of RPC and by the dehulling treatment. Bitterness and astringency are positively correlated with the RPC dosage. C_LIO_LIGoitrin, kaempferol 3-O-(2'''-O-sinapoyl-{beta}-sophoroside) (KSS) and sinapic acid are RPC-derived bitter compounds that correlate with bitter taste of RPC-containing snack bars. C_LIO_LIApproximately 90% of glucosinolates introduced with the RPC are not detected in the snack bars, and goitrin levels in snack bars accounts for only [~]10% of introduced progoitrin. C_LIO_LIGoitrin is - for the first time - reported to contribute to the perceived bitterness of an RPC-containing food product. C_LI

plant biology↗

bioRxiv2026

Tempo and mode of gene evolution revealed by the Lenski long-term evolution experiment

The process of evolutionary change remains poorly understood. By analyzing genomic data from 12 populations in Lenskis long-term evolution experiment (LTEE) over 60,000 generations, we identified a clear sequence in gene adaptation: growth-related genes evolved early, while survival-related genes evolved later. Early-evolving genes exhibited higher rates of both nonsynonymous and synonymous substitutions. We also observed a general decline in gene evolutionary rates across LTEE populations, with additional data highlighting the role of fitness gains in determining evolutionary rates. These findings suggest that, in a relatively stable environment, the fitness gains from beneficial mutations decrease as adaptation progresses. This diminishing return on fitness gains may represent a key evolutionary rule, potentially contributing to evolutionary stasis and the prevalence of neutral evolution.

evolutionary biology↗

bioRxiv2026

Heat stress-induced condensation of G3BP1 in perinuclear P-bodies in C. elegans' germline

Stress granules (SGs) are essential subcellular assemblies that enable cells to adapt to environmental stress, and their dynamic assembly and disassembly are critical for maintaining cellular homeostasis and reproductive capacity. However, the function and regulation of stress granules in germline cells remain mysterious. In this study, we characterized the function of GTBP-1, the homolog of human G3BP1, in response to heat stress in Caenorhabditis elegans and elucidated its regulation in stress granule dynamics. gtbp-1 mutants exhibit pronounced temperature-dependent biodirectional reproductive characteristics. At lower temperatures, their brood size is higher than that of wild-type animals, whereas at 25 {degrees}C they are completely sterile. GTBP-1 is diffusely distributed at normal culturing temperatures but forms perinuclear stress granules upon heat shock in the germline. While the NTF2 domain is essential for germline stress granule formation, other domains, including the IDR, RRM and RGG, are required for the recovery phase after heat shock. GTBP-1 stress granules colocalize with the P-bodies, but not with other germ granules. The depletion of P-bodies prohibited the perinuclear GTBP-1 stress granule formation. A combination of forward genetic screening together with RNAi-based candidate screening identified the P body components, the RNA helicase LAF-1, the SUMO protein SMO-1, and the mTOR pathway effector RSKS-1(S6K) as key regulators of GTBP-1 germline stress granule formation. Together, this work revealed that germline stress granules may be subjected to multiple layers of regulations and GTBP-1 may safeguards reproductive homeostasis under temperature stress by coordinating germline stress granule condensation. Author SummaryReproduction is particularly vulnerable to environmental stress, yet germ cells must remain functional to ensure fertility. How germ cells protect themselves under stressful conditions is still not well understood. In this study, we used the nematode Caenorhabditis elegans to examine how germ cells respond to heat stress, focusing on GTBP-1, a conserved protein involved in stress granule formation. We found that GTBP-1 plays contrasting roles depending on temperature: under normal conditions it restrains reproduction, whereas under heat stress it becomes essential for maintaining fertility. When animals are exposed to elevated temperature, GTBP-1 rapidly forms granules around the nuclei of germ cells, these granules assemble at sites occupied by processing bodies, another type of RNA-containing structure, revealing a close spatial relationship between two stress-responsive compartments. We also found that this process is regulated by conserved factors involved in RNA regulation and nutrient-responsive signaling. Together, our findings show how germ cells reorganize RNA-protein assemblies to preserve reproductive capacity under stressful conditions.

genetics↗

bioRxiv2026

Contrastive Alignment of Expression and Copy Number Highlights Dosage-Insensitive Genes in Cancer

Copy number variations (CNVs) are a hallmark of cancer genomes, yet the relationship between CNV and gene expression is not strictly deterministic. Some genes maintain stable expression despite copy number changes through regulatory compensation. Identifying these dosage-insensitive genes is challenging, requiring methods that distinguish true regulatory escape from technical noise in heterogeneous single-cell data. Here, we present a contrastive learning framework that learns a shared latent space aligning single-cell RNA-seq expression profiles with inferred CNV patterns. Our key innovation is hard negative mining: explicitly training on cell pairs with similar CNV but divergent expression patterns, which represent potential dosage insensitivity. By combining InfoNCE loss with hard negative triplet loss, we learn embeddings where expression-CNV distance quantifies regulatory concordance. We apply this framework to 10 lung adenocarcinoma patients (80k cells) from the GSE131907 atlas, classifying cancer cells as "concordant" (expression follows CNV) or "discordant" (expression escapes CNV). Differential expression analysis between these groups reveals two gene categories: escape genes upregulated in discordant cells despite CNV status, and compensation genes downregulated in discordant cells. Pooled analysis across 40,775 cancer cells identifies significant escape genes including VSIG4, FCGR1A, TREM2, and MARCO, as well as compensation genes such as MALAT1, CCL5, and CD8A. These genes represent candidate therapeutic targets and biomarker hypotheses for CNV-independent tumor behavior. Our approach provides a generalizable frame-work for discovering regulatory escape mechanisms in cancer using standard single-cell RNA-seq data.

genomics↗

bioRxiv2026

LEMONmethyl-seq: Targeted long-read DNA methylation profiling reveals dynamics of CRISPR epigenome editing and endogenous DNA methylation patterns

BACKGROUNDDNA methylation is the most prevalent epigenetic modification in human cells and undergoes dynamic changes during cell differentiation, disease progression, and aging. Here, we introduce Locus-Enriched Mapping Of Nucleotide methylation (LEMONmethyl-seq): an optimized, cost-effective pipeline for single-nucleotide detection of DNA methylation using locus-specific amplification and long-read DNA sequencing. RESULTSWe apply LEMONmethyl-seq to profile DNA methylation of endogenous gene promoters across different cell types along with DNA methylation establishment and long-range propagation induced by CRISPR epigenome editing technologies. We profile dynamic changes in DNA methylation patterns on transposable element genomic loci during global epigenetic resetting in stem cells, and we identify site-specific enrichment of non-canonical CpH methylation on genomic sites in stem cells and cultured neurons. Lastly, we apply LEMONmethyl-seq to profile DNA methylation across the MGMT promoter, a clinical biomarker for glioblastoma. We identify additional differentially methylated sites correlated with chemotherapeutic sensitivity, which may be clinically relevant. CONCLUSIONSTogether, LEMONmethyl-seq serves as a cost-effective, long-read DNA methylation sequencing pipeline that advances methods for detecting DNA methylation patterns and dynamics in mammalian cells. We envision its broad use for studying chromatin pathways, diagnostics, and therapeutic applications.

molecular biology↗

bioRxiv2026

Metformin promotes broad neuroprotection and proteostatic resilience via rngo/DDI2 stabilisation

Alzheimers disease (AD) is one of the most common age-related causes of death, with limited effective disease-modifying treatments. Although metformin shows promise as a disease-modifying agent for AD, its molecular mechanism--specifically how it confers neuroprotection despite potentially increasing amyloid-beta (A{beta}) load--remains obscure. Here, we demonstrate that metformin functions as a pharmacological activator of the ubiquitin-binding protease rngo/DDI2. Through a genetic screen in Drosophila, we identified rngo/DDI2 as a potent suppressor of A{beta} toxicity. We provide in silico and genetic evidence that metformin interacts with the conserved D257 residue of the rngo/DDI2 RVP domain, inducing homodimerisation and subsequent protein stabilisation. This activation boosts proteasome activity in the presence of A{beta} preferentially clearing highly abundant proteins to preserve proteostasis. Crucially, this intervention is broadly effective; rngo/DDI2 upregulation robustly suppresses toxicity in models of TDP-43 and C9orf72-repeat expansion pathology, indicating a generalised mechanism of neuroprotection. Supported by human iPSC data and evidence of DDI2 depletion in AD patient brains, our results identify rngo/DDI2 as a conserved regulator of neuronal resilience. We propose that directly targeting DDI2 stabilisation represents a novel, broadly applicable therapeutic strategy to counteract proteotoxic stress across a broad spectrum of neurodegenerative diseases.

neuroscience↗

bioRxiv2026

PlantMDCS: A code-free, modular toolkit for rapid deployment of plant multi-omics databases

With the rapid accumulation of diverse omics datasets, achieving efficient management and integrative analysis of plant multi-omics data remains a major challenge. Conventional solutions rely on constructing web-based databases, which often demand substantial programming expertise and long-term financial support. To address these limitations, we developed the Plant Multi-omics Database Construction System (PlantMDCS)-a locally deployable, user-friendly, and collaborative platform that unifies database construction and downstream multi-omics analysis within a graphical environment. PlantMDCS adopts a decoupled front-end/back-end architecture. The back end serves as the core engine for data management and computation, and is responsible for the storage, preprocessing, integration, and hierarchical association of multi-omics data. Once initialized, the front end supports the complete research workflow, including data import, querying, integrative analysis and visualization. All operations can be performed without programming, while local resource usage is dominated by disk storage required for user-provided datasets rather than sustained computational overhead. Benchmarking across plant species ranging from Arabidopsis to hexaploid wheat demonstrated that database construction can be completed within minutes, independent of genome size or data complexity. PlantMDCS is designed for local deployment to ensure data security, while allowing multi-user collaboration within local networks and supporting controlled remote access for teams distributed across different regions. Overall, PlantMDCS offers a secure and sustainable framework that integrates data management and analysis within a unified system. This design shifts multi-omics research away from fragmented file-based processing toward persistent, database-driven exploration, thereby enhancing analytical efficiency and reproducibility.

bioinformatics↗

bioRxiv2026

Heparan sulfate promotes autoactivation of pro-Cathepsin K by destabilizing the propeptide-catalytic domain interaction

Pro-cathepsin-K (pro-CtsK) is the zymogen of cathepsin-K (CtsK), a collagenase that is essential for bone resorption. pro-CtsK is known to bind heparan sulfate (HS), but the biological significance of the interaction remains unclear. Here we report that HS accelerates the autoprocessing of pro-CtsK in a manner dependent on both sulfation pattern and oligosaccharide length. We discovered a previously unknown electrostatic interaction between the propeptide and the catalytic domain, which stabilizes the conformation of the propeptide and prevents it from intermolecular proteolytic activation. HS accelerates autoprocessing of pro-CtsK by disrupting this critical electrostatic interaction. Mechanistically, HS competes with two glutamic acids in the propeptide for binding to three basic residues on the catalytic domain, thereby substantially alters the conformation of the propeptide and making it more labile for autoprocessing. We further discovered that HS is highly enriched in secretory lysosomes of osteoclasts and might be directly involved in autoactivation of CtsK.

biochemistry↗

bioRxiv2025

Combined antagonism of Oncostatin M (OSM) and Interleukin 6 (IL-6) provides both anti-fibrotic and anti-inflammatory benefit in pulmonary fibrosis

Interstitial lung diseases (ILDs), including idiopathic pulmonary fibrosis (IPF) and systemic sclerosis-associated ILD (SSc-ILD), are irreversible fibrosing diseases with a mean survival time of less than 5 years for IPF. Poorly understood etiology and complex pathogenesis of these diseases have hampered the identification and development of effective therapeutics. Existing treatments can slow progressive fibrosis and lung function decline but do not stop it entirely, resulting in a minimal impact on patient survival. Thus, novel therapeutic interventions are needed. Tocilizumab, an anti-IL-6 receptor antibody, was recently approved by FDA for the treatment of SSc-ILD based on evidence demonstrating a reduction in the rate of lung function decline. In this study, we have characterized an IL-6-driven feed-forward myeloid axis contributing to lung inflammation providing a mechanistic hypothesis for tocilizumab. Concomitantly we have identified an oncostatin M (OSM) orchestrated lung injury response contributing to epithelial and endothelial cell disruption, myofibroblast activation and fibrosis. Despite dysregulated expression of IL11 in IPF, SSc-ILD, and murine models of fibrosis, we found no evidence for a pro-fibrotic role for IL-11 in vitro or in vivo. Instead, in pre-clinical models of IPF we demonstrate that antagonism of OSM alone, or to a greater degree in combination with IL-6, reduced lung fibrosis and inflammation. Translating these observations, we validated gp130:OSMR, rather than gp130:LIFR, as the dominant human receptor complex used by OSM, identifying OSMR as a potential therapeutic target to stall fibrosis.

immunology↗