Biology subjects

Cao, K.

Publications and source records attributed to Cao, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Chronic stress promotes sex-divergent Type 1, 2 and 17 responses in brain resident lymphocytes.

T helper cytokines such as IFN{gamma} and IL-17 are dysregulated in a subset of patients with depression and are associated with poor responses to treatment. Both IFN{gamma} and IL-17 have been shown to regulate neural circuits involved in behavioral changes implicated in depression. However, the cellular source and the regulatory mechanisms governing these cytokines in this context remain incompletely understood. We analyzed brain lymphocytes in response to unpredictable chronic mild stress (UCMS), a model of depression with strong face and construct validity. We confirmed that UCMS induced depressive-like behavior in both male and female mice. Interestingly, UCMS preferentially reduced regional synaptic density in female and neuron counts in male hippocampi. Using single cell RNAseq, we identified T helper cytokine signatures to be enriched in distinct lymphocyte lineages expressing tissue resident markers and are regulated by both sex and chronic stress. Female brain-resident {gamma}{delta}T cells are significantly enriched for type 2 and type 17 signatures and have higher expression of inflammasome genes such as Nlrp3 and Il1b whereas male {beta}T cells and NKT cells are enriched for type 1 signatures and have elevated Cxcr3 and Il27ra expression. Chronic stress amplified the sex differences and preferentially increased the type 1 response including IFN{gamma} production in males at both the transcriptome and protein level. Type 17 response (e.g. IL-17A and IL-17F production) is also increased in response to UCMS, however with sex-divergent polarization: IL-22 is decreased in female and increased in male brain lymphocytes. Mechanistically, we found that UCMS suppressed P4ha1 in male and Zfp36 in female brain tissue resident lymphocytes. P4HA1 was previously shown to restrict mitochondrial function and limit type 1 responses in CD8 T cells, whereas ZFP36 is a suppressor of inflammatory cytokine translation. Consistent with this finding, ex vivo CD3-dependent stimulation of brain immune cells showed stress-dependent increase in cytokine production with sex-specific effects. Our study provides the cellular and molecular framework for chronic stress-induced tissue resident lymphocyte dysregulation and its sex bias in the brain, with implications for depressive disorders marked by inflammation.

immunology↗

bioRxiv2026

Single-atom inhibition of oncogenic drivers through cysteine coordination

Small-molecule inhibitors rely on molecular recognition within suitable binding pockets, leaving many disease-associated proteins difficult to target. Here, we introduce the concept of a single-atom inhibitor in which gold (Au) engages critical cysteine residues of oncogenic drivers to suppress their activity. We used an AI-assisted few-shot learning approach to identify EGFR-targeting peptides for in vivo Au delivery and showed that the lead candidate, 10714, promoted Au accumulation in EGFR-expressing cells and tumors. In vivo, Au exploited its intrinsic affinity for cysteine to inhibit two structurally distinct oncogenic proteins, engaging Cys797 in EGFR T790M and the mutation-derived Cys12 in KRAS G12C adjacent to their respective nucleotide-binding pockets. Structural and computational analyses supported stabilization of inactive nucleotide-bound states, while mutation of these cysteine residues abrogated Au-mediated inhibition. 10714-Au consequently suppressed oncogenic signaling, reduced non-small-cell lung cancer cell viability, and inhibited tumor growth in EGFR- and KRAS-mutant xenograft models and patient-derived organoids. These findings establish proof of principle for single-atom inhibition across structurally distinct oncogenic drivers and suggest that localized atomic coordination could provide an alternative mode of target engagement to conventional pocket-dependent inhibition.

molecular biology↗

bioRxiv2026

A Microfluidic Platform for Spatiotemporal Dissection of Neurodegeneration Across Hierarchical Human Neural Circuits

Understanding how neurodegenerative diseases initiate and propagate through neural circuits remains a fundamental challenge in neuroscience. The earliest stages occur years before symptoms emerge, making them inaccessible to study in patients. Microfluidic platforms, where neurons communicate across chambers through microchannels accessible only to their axons, have opened new experimental avenues. However, existing models lack the complexity and precision needed to track how individual circuit components respond to focal pathological changes over time. Here we present a 33-chamber cortical network-on-chip integrating human iPSC-derived excitatory neurons, inhibitory neurons, and astrocytes in a six-layer feedforward architecture recapitulating the laminar structure of the neocortex. Amyloid-{beta} is applied globally, while progerin-induced accelerated ageing in a single chamber establishes a defined disease core. Continuous recordings using high-density microelectrode arrays reveal progressive, layer-dependent changes in firing dynamics and network topology. Machine-learning-based feature analysis identifies a multiparametric electrophysiological signature distinguishing healthy from disease-affected chambers, enabling studies of the earliest timepoint at which pathology becomes detectable. This establishes a scalable framework for mechanistic studies of neurodegeneration and identification of electrophysiological biomarkers of disease progression.

neuroscience↗

bioRxiv2026

Network-Level Characterization of Spontaneous Calcium Activity in an In-Vitro Alzheimer's Disease Model

The neurodegenerative disorder Alzheimers disease (AD) is widely known for biomarkers such as amyloid beta plaques and tauopathy, as well as functional differences in memory and cognitive ability. Despite this devastating functional impact, a large body of work only focuses on molecular biomarkers of AD. In this study, we investigate collective neural dynamics in vitro and assess how network-level properties differ between a well-established model of familial AD (FAD) and a newly developed in vitro accelerated model (acAD). The new model system reliably develops the key structural characteristics of AD in three weeks, but its calcium dynamics had not been characterized previously. Spontaneous network dynamics influences information processing as part of the internal network state. Here we measure this spontaneous activity of a network of hundreds of cells in each field of view. We find that the FAD model has a larger fraction of hyperactive cells, while the acAD model displays similar characteristics to healthy cells. Additionally, the FAD model has altered cooperation between cells, losing a proportion of highly correlated cellular activities, both for fast and slow coupling among cells. The acAD model is again consistent with healthy networks. Since the acAD model does not show the same spontaneous network dysfunction seen in FAD, it can enable measurements of changes in learning and memory associated with the plasticity, rather than the structure of the internal network state.

biophysics↗

bioRxiv2026

CPS: Mapping Physical Coordinates to High-Fidelity Spatial Transcriptomics via Privileged Multi-Scale Context Distillation

MotivationSpatial transcriptomics enables the dissection of tissue heterogeneity within native contexts, yet current platforms are inherently constrained by high sparsity and low signal-to-noise ratios that obscure fine-grained biological signals. Current efforts to recover these signals are limited by image registration dependencies or the inherent context-blindness of implicit neural representations. ResultsWe introduce the Cell Positioning System (CPS), a context-aware implicit neural representation framework designed to map physical coordinates to high-fidelity spatial transcriptomics via a privileged multi-scale context distillation strategy. CPS treats multi-scale tissue niches as privileged information, employing a teacher network equipped with a multi-scale niche attention mechanism to capture adaptive biological interactions during training. This structural knowledge is explicitly distilled into a student coordinate network, enabling the generation of context-aware expression landscapes solely from spatial coordinates during inference. Benchmarking on the DLPFC dataset demonstrates that CPS achieves state-of-the-art performance in spatial and gene expression imputation and denoising. Furthermore, CPS enables super-resolution to recover high-resolution mouse brain anatomical details and offers interpretability by identifying the scale effective size of biological interactions within human breast cancer tissues. Finally, the framework exhibits superior scalability for large-scale datasets with linear computational complexity. AvailabilitySoftware is available online at https://github.com/tju-zl/CPS.

bioinformatics↗

bioRxiv2026

A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions

The interaction between T cell receptors (TCRs), peptides, and human leukocyte antigens (HLAs) underlies antigen-specific T cell immunity. Despite substantial advances in peptide- HLA presentation prediction, accurate modeling of coupled TCR-peptide-HLA recognition remains underdeveloped, limiting applications such as TCR and neoepitope prioritization in cancer and antigen identification in autoimmunity. Here we present StriMap, a unified framework for predicting TCR-peptide-HLA interactions by integrating physicochemical, sequence-context, and structural features at recognition interfaces. StriMap achieves state-of-the-art performance with improved generalizability and enables applications in both cancer and autoimmunity. As a case study in ankylosing spondylitis (AS), we screened 13 million peptides derived from 43,241 bacterial proteins and identified candidate molecular mimics that were experimentally validated to activate T cells expressing an AS-associated TCR. Notably, a top validated peptide was enriched in patients with inflammatory bowel disease (IBD), suggesting potential shared microbial triggers between AS and IBD. Overall, StriMap provides a generalizable framework for rational immunotherapy design and for dissecting antigenic drivers of autoimmunity.

bioinformatics↗

bioRxiv2026

MLL3/4 methyltransferases regulate the differentiation of pluripotent stem cells via cellular respiration

Enhancer-regulating epigenetic modifiers play critical roles in normal physiological processes and human pathogenesis. The major enhancer regulator paralogs MLL3 and MLL4 (MLL3/4) belong to the lysine methyltransferase 2 (KMT2) family, which catalyzes the methylation of lysine 4 on histone H3 (H3K4me). MLL3/4 are required for enhancer activation and are essential for mammalian development and stem cell differentiation. Although recent studies have linked MLL3/4 with different metabolic pathways in the regulation of stem cell self-renewal and cancer cell growth, the mechanisms connecting enhancer function to metabolic control remain elusive. Here, using respiration flux assays, stable isotope tracing, transcriptomics, and stem cell biology techniques, we show that the loss of MLL3/4 impairs glycolysis and mitochondrial respiration in murine embryonic stem cells. Mechanistically, MLL3/4 deficiency suppresses the expression of the rate-limiting glycolytic enzyme hexokinase 2 (HK2) and compromises the function of the oxoglutarate dehydrogenase (OGDH) complex, thereby coordinately impairing central carbon metabolism. Remarkably, combined restoration of HK2 and OGDH rescues the metabolic defects caused by MLL3/4 loss and reinstates differentiation capacity. Taken together, our study identifies a direct link between enhancer-regulating epigenetic machineries and metabolic control of cell fate transition, providing a mechanistic framework for understanding how enhancer malfunction contributes to developmental abnormalities and human diseases.

developmental biology↗

bioRxiv2026

HDAC5-encoded Microprotein NISM Mediates Nucleolar Formation and Ribosomal RNA Synthesis

Ribosome biogenesis is the process by which ribosomal RNA (rRNA) and ribosomal proteins are synthesized, processed, and assembled into functional ribosomes. This process begins in the nucleolus, a multiphase liquid condensate. Here, we discover an arginine-rich disordered nucleolar microprotein encoded within the HDAC5 5'-UTR that we termed Nucleolar Integrity and Stress Microprotein (NISM). NISM overexpression leads to impaired rDNA transcription, triggering nucleolar stress, p53 activation, and suppressed proliferation. NISM knockout causes disruption of nucleolar structure and also induces p53 activation. Mechanistically, NISM interacts with the DExH-box RNA helicase DHX9 and regulates its activities related to pre-rRNA synthesis. Computational analyses and polymer physics-based mathematical modeling revealed that NISM coordinates nucleolar formation and pre-rRNA synthesis by enhancing the liquid-liquid phase separation of DHX9. This study establishes NISM as a regulator of nucleolar biology and deepens our understanding of how disordered microproteins can facilitate the formation of membraneless organelles.

molecular biology↗

bioRxiv2025

DNA-barcoded microneedle array patch enabling the profiling of in vivo spatiotemporal transcriptomics

Recent years have witnessed profound advances in spatial transcriptomics (ST). However, current ST strategies are limited to tissue sections, unable to directly profile spatiotemporal transcriptome landscapes of individual living animals. To overcome this limitation, we present acupuncture-extracted in vivo spatiotemporal transcriptomics (aivST). It is mainly based on engineering clinical-grade acupuncture gold microneedles as a spatial-barcoding array patch with high-performance DNA recognition interfaces. These interfaces first utilize nanoparticles surface deposition to increase the density of DNA probes. A freeze-thawing method is further developed to regulate interfaced DNA probes with laterally uniform distribution and vertically upright conformation, mainly by loose stretching and local concentration of these DNA probes. It increased mRNA capture with 250% and speeded up reaction (from 60 min to 15 min), compared to that without freeze-thawing surface engineering. Using this method, we explored in vivo spatiotemporal transcriptome dynamics during skin wound healing of individual mice. We found four distinct expression changes of transcripts, including continuous upregulation, continuous downregulation, initial upregulation then downregulation, and initial downregulation then upregulation. Our aivST method advances the field from sparse tissue section sampling toward in vivo measurements of biological stereotypy and variability in individual living animals.

genomics↗

bioRxiv2025

Generative Design of Cell Type-Specific RNA Splicing Elements for Programmable Gene Regulation

Programmable control of gene expression in specific cell types is essential for both basic discovery and therapeutic intervention, yet current strategies lack scalability across diverse cellular contexts. Here, we introduce SPICE (Splicing Proportions In Cell types), an integrated experimental and computational framework that harnesses alternative RNA splicing as a programmable modality for cell type-specific gene regulation. To power SPICE, we constructed a massively parallel reporter assay (MPRA) comprising 46,372 human-derived sequences and profiled exon skipping across 43 cell lines spanning 10 lineages, uncovering widespread cell type-specific exon skipping. Using this data, we trained deep learning models that both predict splicing in unseen contexts and generate synthetic sequences with programmed, cell type-specific splicing patterns. Leveraging these models, we further engineered sequences that selectively splice in cells harboring oncogenic splicing factor mutations, demonstrating translational potential. SPICE provides a generalizable strategy for dissecting splicing regulation and engineering alternative splicing as a gene expression regulatory layer for research and therapeutic applications. One Sentence SummaryWe introduce SPICE, an integrated framework that couples large-scale splicing assays with generative design to uncover regulatory principles and design programmable, cell-specific gene expression for research and therapeutic applications.

molecular biology↗

bioRxiv2025

ODC1 restricts meningeal B cell age-associated-like phenotype and function in multiple sclerosis: a human and experimental study

Meningeal inflammation, as a clinical feature of multiple sclerosis (MS), is associated with worse clinical disease outcomes. In both relapsing and secondary progressive MS and the experimental autoimmune encephalomyelitis (EAE) MS model, the meninges have been found to contain ectopic lymphoid follicles enriched with B cells. The metabolic requirement of meningeal B cell function in MS or EAE is not well elucidated. Using 7-Tesla MRI brain scans of MS patients and leptomeningeal enhancement (LME) as a marker, we found a correlation between meningeal inflammation and metabolites of the arginine/polyamine pathway, a finding recapitulated in the EAE model. Ornithine Decarboxylase (ODC1), the rate limiting enzyme for polyamine biosynthesis, as well as polyamine metabolism was diminished in the dura meningeal B cells from mice with MOG35-55 induced EAE mice as compared to naive controls. Pharmacological inhibition of ODC1 restricted meningeal T cells but promoted meningeal B cell proliferation. B cell-specific deletion of ODC1 resulted in expansion of B cells with age-associated B cell-like phenotype (CD11c+CD21/35-CD23-IgD-) and exacerbated disease in the MOG1-125 EAE model. Together, these findings demonstrate a divergent role of polyamines in regulating B and T cell responses in the meninges during autoimmunity. Significance StatementThis study identified the polyamine pathway to be associated with meningeal inflammation in multiple sclerosis, a clinical phenotype associated with worse disease outcomes and without targeted therapy. Using a mouse experimental model, we found that ODC1, the rate limiting enzyme of the polyamine biosynthesis pathway, was suppressed in meningeal B cells, restricted the development of age-associated B cells in the meninges and limited disease severity. This study elucidated a metabolic pathway regulating meningeal B cell function, informing its therapeutic applications in autoimmune diseases.

immunology↗

bioRxiv2025

Energy-Regularized Graph Learning for Multiscale Spatial Representation

Spatial omics map gene and protein expression in situ, demanding methods that recover cellular and tissue architecture from noisy, high-dimensional data. This need spans two scales: (i) subcellular, where high-resolution measurements must be grouped into coherent cells, and (ii) tissue-wide, where the goal is to recover spatial domains. Existing embedding approaches either ignore space or rely on static neighborhood graphs that over- or under-smooth local heterogeneity. We present Glimmer (Graph-Learned Inference of Multiscale Molecular Embedding for Spatial Representation), a unified framework that learns adaptive neighborhood graphs by minimizing Dirichlet energy under a log-barrier regularizer. Beginning from a k-nearest neighbor scaffold, Glimmer adaptively reweights edges to balance molecular similarity and spatial proximity, yielding interpretable, locally smoothed embeddings. These graphs enable segmentation-free reconstruction from transcript localizations or fine bins and support the discovery of tissue niches at large tissue scales. Across diverse datasets and modalities (Slide-tags, Slide-seq, MERFISH, Xenium, and CODEX), Glimmer surpasses kernel and graph neural network based methods in clustering accuracy and spatial conservation. At the subcellular level, Glimmer corrects transcript-to-cluster misassignments on lymph node slides, thereby improving gene specificity within biological clusters and addressing a key challenge in spatial transcriptomics. At the tissue-wide scale, Glimmer enables accurate region identification, as demonstrated in tonsil tissue by resolving germinal center subregions, which in turn facilitates niche-specific immune profiling. Glimmer thus offers a generalizable framework for spatial representation learning across scales and modalities, enabling comprehensive insights into tissue architecture and cellular ecosystems.

bioinformatics↗

bioRxiv2025

Off-target effects of PLX5622 revealed: mixing microglial function in anesthesia and addiction withdrawal

Microglia have gained increasing attention as important regulators in the brain. Acute microglial depletion using the colony-stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622, has become a popular approach to uncover microglial function. PLX5622 treatment has been recently shown to significantly promote anesthetic emergence. In characterizing underlying mechanisms, we found that PLX5622 treatment did not change the global neuronal activity during anesthesia, but robustly enhanced anesthetic metabolism. Moreover, PLX5622 dramatically induced the expression of hepatic enzymes that extensively modify xenobiotic and endobiotic metabolism. Blocking increased enzymatic activity significantly reduced the arousal-promoting effects of PLX5622 in anesthesia, irrespective of microglial elimination. In addition, we demonstrate that enhanced drug metabolism also contributed to PLX5622-induced attenuation in nicotine-withdrawal anxiety. By revealing previously unrecognized effects of PLX5622, our findings raise caution in interpreting data generated from PLX5622 treatment and bring forward the need for designing more specific CSF1R inhibitors.

neuroscience↗

bioRxiv2025

H3K79 methylation and H3K36 tri-methylation synergistically regulate gene expression in pluripotent stem cells

In metazoans, nucleosomes harboring H3K79 methylation (H3K79me) deposited by the histone methyltransferase DOT1L decorate actively transcribed genes. Although DOT1L is implicated in transcription regulation and pathogenesis of human diseases such as leukemia and neurological disorders, the role of H3K79me in these biological processes remains elusive. Here, we reveal a novel functional synergism between H3K79me and H3K36 tri-methylation (H3K36me3), another histone modification enriched at active genes, in regulating gene expression and neural cell fate transition. Simultaneous catalytic inactivation of DOT1L and the H3K36 methyltransferase SETD2 via gene editing leads to the global loss of H3K79me and H3K36me3, hyperactive transcription, and failures in neural differentiation. Interestingly, the loss of H3K79me and H3K36me3 causes increased transcription elongation, gained chromatin accessibility at a group of enhancers, and increased binding of TEAD4 transcription factor and its co-activator YAP1 at these enhancers. Furthermore, YAP-TEAD inhibition partially restores the expression levels of hyperactivated genes upon H3K79me/H3K36me3 loss. Taken together, our study demonstrates a synergistic role of H3K79me and H3K36me3 in regulating transcription and cell fate transition, unveils novel mechanisms underlying such synergism, and provides insight into designing therapies that target diseases driven by misregulation or mutations of DOT1L and/or SETD2.

genetics↗

bioRxiv2025

Sympathetic nociceptive afferent signaling drives the chronic structural and functional autonomic remodeling after myocardial infarction

After chronic myocardial infarction (MI), pathological autonomic remodeling, including vagal dysfunction and sympathoexcitation, predisposes to ventricular arrhythmias (VT/VF). However, what underlies this functional and structural remodeling remains unknown. We hypothesized that sympathetic nociceptive afferent signaling initiates and perpetuates these pathological autonomic changes. We employ cervicothoracic epidural resiniferatoxin (RTX) to ablate spinal nociceptive neurons in male pigs before MI, and assessed autonomic and electrophysiological function four-to-six weeks post-infarction. Compared to vehicle-treated infarcted animals, epidural RTX attenuates the loss of vagal tone and baroreflex sensitivity, reduces spinal cord inflammation, glial activation, and circulating stress and inflammatory markers, and stabilizes electrophysiological parameters, lowering VT/VF inducibility. In a separate cohort, acute C7-T1 nociceptive afferent ablation after chronic MI acutely restores vagal function and decreases VT/VF inducibility. This study demonstrates that cervicothoracic spinal nociceptive afferents significantly contribute to MI-induced autonomic remodeling and VT/VF, providing novel insight into the mechanisms underlying sympathovagal imbalance after MI.

physiology↗

bioRxiv2025

Detection of human unannotated microproteins by mass spectrometry-based proteomics: a community assessment

Thousands of short open reading frames (sORFs) are translated outside of annotated coding sequences. Recent studies have pioneered searching for sORF-encoded microproteins in mass spectrometry (MS)- based proteomics and peptidomics datasets. Here, we assessed literature-reported MS-based identifications of unannotated human proteins. We find that studies vary by three orders of magnitude in the number of unannotated proteins they report. Of nearly 10,000 reported sORF-encoded peptides, 96% were unique to a single study, and 12% mapped to annotated proteins or proteoforms. Manual curation of a benchmark dataset of 406 manually evaluated spectra from 204 sORF-encoded proteins revealed large variation in peptide-spectrum match (PSM) quality between studies, with immunopeptidomics studies generally reporting higher quality PSMs than conventional enzymatic digests of whole cell lysates. We estimate that 65% of predicted sORF-encoded protein detections in immunopeptidomics studies were supported by high-quality PSMs versus 7.8% in non-immunopeptidomics datasets. Our work stresses the need for standardized protocols and analysis workflows to guide future advancements in microprotein detection by MS towards uncovering how many human microproteins exist.

genomics↗

bioRxiv2025

scCausalVI disentangles single-cell perturbation responses with causality-aware generative model

Single-cell RNA sequencing provides detailed insights into cellular heterogeneity and responses to external stimuli. However, distinguishing inherent cellular variation from extrinsic effects induced by external stimuli remains a major analytical challenge. Here, we present scCausalVI, a causality-aware generative model designed to disentangle these sources of variation. scCausalVI decouples intrinsic cellular states from treatment effects through a deep structural causal network that explicitly models the causal mechanisms governing cell-state-specific responses to external perturbations while accounting for technical variations. Our model integrates structural causal modeling with cross-condition in silico prediction to infer gene expression profiles under hypothetical scenarios. Comprehensive benchmarking demonstrates that scCausalVI outperforms existing methods in disentangling causal relationships, quantifying treatment effects, generalizing to unseen cell types, and separating biological signals from technical variation in multi-source data integration. Applied to COVID-19 datasets, scCausalVI effectively identifies treatment-responsive populations and delineates molecular signatures of cellular susceptibility. Code availabilitySoftware is available at https://github.com/ShaokunAn/scCausalVI.

bioinformatics↗

bioRxiv2024

Osthole Suppresses Prostate Cancer Progression by Modulating PRLR and the JAK2/STAT3 Signaling Axis

Prostate cancer is a common malignancy in men with limited effective treatment options, highlighting the urgent need for novel therapeutic approaches. Osthole, a natural coumarin compound with antitumor properties, has demonstrated potential in targeting various cancers. This study investigates the therapeutic effects of Osthole in prostate cancer by focusing on its ability to target the Prolactin Receptor (PRLR) and modulate the JAK2/STAT3 signaling pathway. Using a combination of network pharmacology, in vitro assays, and in vivo experiments, we first employed network pharmacology to predict Ostholes potential targets, identifying 68 targets shared with prostate cancer, including AKT1, TNF, IL6, STAT3, and CTNNB1. We then confirmed these targets and assessed the effects of Osthole on cell proliferation, migration, and apoptosis using the Cell Counting Kit-8 (CCK-8) and transwell invasion assays. To further elucidate the molecular interactions and protein expression levels, we employed molecular docking and western blot analysis. Our findings revealed that Osthole significantly inhibited prostate cancer cell proliferation and migration in a dose-dependent manner and reduced tumor volume in in vivo assays. Western blot analysis also indicated that Osthole downregulated PRLR expression and decreased the phosphorylation of JAK2 and STAT3, suggesting the inhibition of the JAK2/STAT3 pathway. These results collectively highlight the therapeutic potential of Osthole in targeting prostate cancer cells through PRLR and modulating the JAK2/STAT3 pathway, warranting further clinical exploration.

cancer biology↗