Biology subjects

Shang, J.

Publications and source records attributed to Shang, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Bumetanide Strengthens Residual Brain Bladder Communication After Spinal Cord Injury

Neurogenic bladder is one of the most disabling consequences of spinal cord injury (SCI), yet it remains unclear whether residual brain bladder communication persists after injury and can be therapeutically strengthened. Here, we integrated analysis of a clinical SCI cohort with studies in a mouse model that recapitulates key features of human neurogenic bladder. SCI markedly impaired both descending and ascending limbs of the spinobulbospinal micturition reflex, reducing bladder responses evoked by stimulation of the pontine micturition center (PMC) and bladder filling-induced activation of the periaqueductal gray. Despite this marked functional impairment, pseudorabies virus tracing, optogenetics, and machine learning assisted three dimensional imaging revealed persistent bladder connected neurons within the spared thoracic interlesion region. Neurons within this region remained responsive to descending PMC input, identifying the interlesion network as a candidate substrate for residual brain bladder communication. Early continuous intrathecal bumetanide improved urinary storage and emptying, enhanced descending PMC to bladder and ascending bladder to brain signaling, and increased the functional engagement of bladder-connected thoracic neurons without increasing urine production. Bumetanide also increased transsynaptic labeling between the bladder and PMC, consistent with enhanced polysynaptic brain bladder connectivity. Together, these findings indicate that brain bladder communication is not completely lost after SCI and may be supported by a functionally compromised residual spinal network that remains amenable to therapeutic reinforcement. Targeting spared autonomic circuitry may therefore provide a strategy for improving bladder function after SCI.

neuroscience↗

bioRxiv2026

FXR-mediated recruitment of PPP1CB suppresses SMAD2/3 phosphorylation to mitigate pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease with limited treatment options and poorly understood molecular underpinnings. Dysregulated TGF-{beta}/SMAD signaling is a key driver of fibrotic remodeling, promoting persistent myofibroblast activation and excessive extracellular matrix deposition. Here we identify the Farnesoid X receptor (FXR), a bile acid activated nuclear receptor, as a previously unrecognized suppressor of pulmonary fibrosis. FXR expression is significantly reduced in lung tissues from patients with PF and in myofibroblasts derived from BLM-induced mouse models, correlating inversely with fibrosis severity. Genetic ablation of FXR exacerbates BLM-induced pulmonary fibrosis by promoting fibroblast hyperactivation and dysregulation of the TGF-{beta}/SMAD signaling pathway. Mechanistically, we identify PPP1CB as a previously unrecognized FXR-interacting protein in primary myofibroblasts derived from IPF patients. We further show that FXR both increases chromatin accessibility at the PPP1CB locus and assembles a functional complex with PPP1CB, which in turn promotes SMAD2/3 dephosphorylation and suppresses their nuclear translocation. Notably, the clinical-stage FXR agonist TERN101 exhibits potent therapeutic efficacy in a BLM-induced mouse pulmonary fibrosis model. These findings establish FXR as a critical antifibrotic regulator in lung tissue and suggest that pharmacological activation of FXR may offer a promising therapeutic strategy for IPF.

cell biology↗

bioRxiv2026

A novel AR molecular glue degrader via bivalent engagement of the N-terminal domain and RNF213-UBE2J2 complex

Targeted protein degradation enables the elimination of disease-relevant proteins through induced proximity between E3 ligases and substrates. Current androgen receptor (AR) therapies act via the ligand-binding domain (LBD) but fail against constitutively active LBD mutants or splice variants such as AR-V7. Here, we identify GZL626, a small-molecule degrader that induces proteasome-dependent degradation of both full-length AR and AR-V7. GZL626 suppresses AR transcriptional activity, inhibits proliferation of AR-positive prostate cancer cells, and blocks SARS-CoV-2 infection. Mechanistically, GZL626 binds the intrinsically disordered AR N-terminal domain (NTD) and promotes formation of a noncanonical RNF213-UBE2J2-AR ternary complex that drives AR ubiquitination and degradation. The AR DNA-binding domain (DBD) acts as a structural hub within this assembly. Distinct from PROTACs or classical molecular glues, GZL626 engages both AR and RNF213 bivalently, remodeling protein interactions to stabilize a functional E3-E2-substrate complex. These findings establish GZL626 as a first-in-class NTD degrader with potential to overcome resistance in advanced prostate cancer.

biophysics↗

bioRxiv2026

Mechanism of fatty acid uptake and inhibition in human FATP2

Fatty Acid Transport Protein 2 (FATP2) couples fatty acid uptake to intracellular activation and is associated with pathological lipid accumulation in cancer and nonalcoholic fatty liver disease. Here, we present cryo-electron microscopy structures of human FATP2 across its reaction cycle. Our structures suggest that FATP2 recruits fatty acids directly from the membrane interface through a hydrophobic tunnel. Catalysis involves a [~]130{degrees} rotation of the C-terminal domain, a transition trapped by the antihypertensive drugs isradipine and benidipine. Both drugs lock the enzyme in a thioester-forming state, but benidipine exhibits superior efficacy by extending a bulky moiety into the primary catalytic tunnel to sterically block substrate entry. Furthermore, we identify a product inhibition mechanism where excess acyl-CoA traps the enzyme, potentially limiting metabolic overload. These findings provide a structural framework for understanding vectorial fatty acid channeling and a scaffold for developing modulators of metabolic flux. HighlightsO_LICryo-EM structures of human FATP2 reveal a membrane-anchored lollipop topology C_LIO_LIEndogenous fatty acids within a hydrophobic tunnel delineate the fatty acid uptake pathway C_LIO_LIIsradipine and benidipine displace fatty acids to trap a non-productive conformation C_LIO_LIAcyl-CoA product inhibition may provide negative feedback via steric occlusion C_LI

biophysics↗

bioRxiv2026

First community challenge for automated virus taxonomy

The rapid rate of virus discovery renders manual curation by taxonomy experts increasingly impractical, creating a need for reliable software that can reproducibly assign viral contigs to taxa at all fifteen ranks of the virus taxonomy. We led an open community challenge for the computational taxonomic classification of viruses and assembled a dataset of virus sequences combining expert-curated and metagenomic sequences. Seventeen teams contributed a total of thirty-four automated, fully reproducible classification pipelines. Most tools correctly assigned viruses belonging to established species, genera, or families, but viruses that are unclassified at those lower ranks remain challenging. This study provides datasets, open-source software, novel approaches, and recommendations to benchmark computational taxonomic classification of viruses, and support organizing the many viruses discovered in big omics data.

microbiology↗

bioRxiv2026

VirProtRAG: Literature-grounded viral protein function annotation with retrieval-augmented generation

Viruses play indispensable roles in ecosystems and human health, yet deciphering their molecular functions remains challenging. Many viral protein annotations are incomplete or poorly characterized. Existing tools typically predict functional categories without linking to verifiable evidence, hindering the credibility of functional interpretation. Here, we present VirProtRAG, a viral protein function annotation framework that integrates information retrieval with evidence-grounded knowledge generation. It introduces three task-adapted components: a hybrid retrieval module combining keyword-based and semantic dense retrieval to maximize literature coverage, synonym-expanded and rank-aware retrieval with reciprocal rank fusion for improved search effectiveness, and literature quality and evidence-oriented re-ranking to enhance reliability and interpretability. Results show that hybrid retrieval strategy performed best, with quality and evidence features further enhancing re-ranking. Compared with direct LLM prompting without retrieved literature, it consistently improves generation performance, underscoring the critical role of external knowledge. Finally, we built a searchable database comprising all 17,484 reviewed Swiss-Prot viral proteins, supporting both sequence- and text-based queries. VirProtRAG introduced 32.53% non-overlapping function annotations beyond existing expert curation, and independently supported 56.34% of sequence-inferred function points with retrieved literature. Case studies further demonstrate its capability to augment and refine the characterization of previously unannotated or poorly understood viral proteins. Key MessagesO_LIVirProtRAG bridges large-scale biomedical literature and viral protein annotation, enabling traceable and biologically interpretable annotations grounded in verifiable publications. C_LIO_LIBy integrating hybrid sparse-dense retrieval, synonym expansion, and adaptive re-ranking using literature quality and evidence-type features, VirProtRAG substantially improves recall and ranking of biologically relevant publications, helping ground LLM outputs in traceable literature evidence. C_LIO_LILeveraging this framework, VirProtRAG automatically annotated all 17,484 reviewed Swiss-Prot viral proteins under the Virus taxonomic group and established an interactive, continuously expandable database. The resource may assist curators in rapid validation while supporting large-scale studies of viral evolution and host interactions. C_LI

bioinformatics↗

bioRxiv2026

Development of GS-441524 Derivatives as Potent SARS-CoV-2 Mac1 Inhibitors via a Direct-to-Biology Approach

Targeting viral macrodomains (Mac) has emerged as a promising strategy for antiviral drug development, especially after the outbreak of COVID-19 that claimed millions of lives worldwide. Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Mac1 inhibitors have been reported in the past few years. In the present work, we converted GS-441524 (IC50 of [~]10 M for SARS-CoV-2 Mac1) to KP-S54 (18c), a potent inhibitor of both SARS-CoV-2 Mac1 (IC50: 44 nM) and Middle East respiratory syndrome coronavirus (MERS-CoV) Mac1 (IC50: 91 nM) through an iterative direct-to-biology approach. This approach leverages efficient amide-coupling reaction and the mix-and-read fluorescence polarization (FP) assays where reaction mixtures could be screened directly without purification. Cocrystal structure of a selected derivative (12p) binding to SARS-CoV-2 Mac1 revealed the binding mode, which will guide future drug development against viral macrodomains.

pharmacology and toxicology↗

bioRxiv2025

Bacteroidetes promote hepatocellular carcinoma progression and resistance to immunotherapy

Background and AimsGrowing evidence highlight the critical role of the gut microbiome in tumorigenesis and response to immunotherapies. However, the impact of gut microbes on hepatocellular carcinoma (HCC) progression and response to immune-checkpoint blockade (ICB) remains unclear due to the lack of combined preclinical and clinical studies. Approach & ResultsWe performed 16S rRNA of cross-cohort stool samples from 10 HCC responders (R) and 40 non-responders (NR) to ICB at baseline and on-treatment time-points. We identified an enrichment of Bacteroidetes in NR. To study the role of the microbiome in the cancer immune response, we generated an immunogenic mouse model of HCC via hydrodynamic tail-vein injection (HDTVI) of DNA plasmids mimicking common HCC alterations and immunogenicity by expressing model antigens (MYC-lucOS;CTNNB1 tumors). We found that antibiotic (ABX)-induced dysbiosis promoted a pro-tumorigenic effect in the MYC-lucOS;CTNNB1 HCC model by the expansion of a specific Bacteroidetes, Parabacteroides distasonis. Colonization of mice carrying MYC-lucOS;CTNNB1 HCCs with Parabacteroides distasonis confirmed its pro-tumorigenic effect in vivo. Furthermore, we explored the effects of colonizing with microbiotas from patients and showed that microbiota from a NR donor enriched in Bacteroidetes promoted faster tumorigenesis than microbiota from a R donor with reduced Bacteroidetes. We isolated 6 Bacteroidetes species from the NR donor, cultured them, and used them as a cocktail to colonize mice; similarly, mice transplanted with this cocktail showed increased tumorigenesis and reduced survival. ConclusionsThis study identified Bacteroidetes enrichment as a potential biomarker of ICB resistance in HCC and, by using immunogenic mouse models, established that Bacteroidetes abundance influences tumor development.

cancer biology↗

bioRxiv2025

Targeting the host factor HGS-viral membrane protein interaction in coronavirus infection

While current antivirals primarily target viral proteins, host-directed strategies remain underexplored. Here, we performed a genome-wide CRISPRi screening to identify the host protein, Hepatocyte Growth Factor-Regulated Tyrosine Kinase Substrate (HGS), as essential for the pan-coronaviruses infection both in vitro and in vivo. Mechanistically, HGS directly interacts with the viral membrane (M) protein, facilitating its trafficking to the ER-Golgi intermediate compartment (ERGIC) for virion assembly. Conversely, HGS deficiency caused M retention in the ER, blocking assembly. Leveraging this interaction, we designed M-derived peptides and screened over 5,000 FDA-approved drugs, identifying riboflavin tetrabutyrate (RTB). Both the peptides and RTB bind HGS and disrupt its interaction with the M protein, leading to M retention in the ER and subsequent blockade of virion assembly. These agents demonstrated broad anti-pan-coronavirus activity in vitro and in vivo. Collectively, our findings establish HGS as a druggable host target and identify RTB as a promising broad-spectrum antiviral candidate.

microbiology↗

bioRxiv2025

in vivo Reprogramming of NG2 Glia Improves Bladder Function After Spinal Cord Injury

Neurogenic bladder is a debilitating consequence of spinal cord injury (SCI), with few treatment options that restore voluntary voiding. Here, we show that SOX2-mediated in vivo reprogramming of NG2 glia improves bladder function in a clinically relevant mouse model of contusive SCI. NG2 glia reprogramming induces adult neurogenesis, reduces glial scarring, and significantly improves urinary performance, as measured by voiding assays and conscious cystometry. Functional recovery correlates positively with neurogenesis and negatively with glial scarring. These findings demonstrate that SOX2-mediated glial reprogramming promotes autonomic repair and offers a regenerative strategy for neurogenic bladder after SCI.

neuroscience↗

bioRxiv2025

PlasRAG: comprehensive plasmid characterization and retrieval through sequence-text alignment

Plasmids play a pivotal role in the emergence of multidrug-resistant and pathogenic bacteria, posing significant clinical challenges. The integration of metagenomic sequencing with advanced bioinformatics tools surpasses traditional wet lab methods, leading to the discovery of millions of plasmids from diverse origins. However, the rapidly growing number of unannotated plasmids necessitates comprehensive characterization of their multi-faceted properties, such as risk indices and ecological contexts, to support various downstream applications. Achieving this goal is hindered by several challenges, including the limited availability of plasmid characterization tools, the inadequacies of alignment-based methods for novel plasmids, and inconsistencies in manual annotations across plasmid reference databases. To address these issues, we present PlasRAG, a novel tool that integrates two key modules: multi-faceted property characterization of query plasmids and plasmid DNA retrieval based on textual queries. At its core, PlasRAG employs a bidirectional multi-modal information retrieval model that aligns DNA sequences with textual data, effectively overcoming the limitations of traditional approaches. Specifically, within the characterization module, PlasRAG leverages the retrieval-augmented generation (RAG) framework and the Llama-3 large language model (LLM) to provide accurate and context-aware responses to user queries. Rigorous experiments demonstrate that PlasRAG delivers robust performance and enhanced analytical capabilities, underscoring the effectiveness of its architectural design. In particular, experiments on a real-world plasmid dataset curated from diverse human gut metagenomes suggest that plasmids with a broader host range and encoded ARGs tend to spread more extensively. The source code of PlasRAG is available via: https://github.com/Orin-beep/PlasRAG.

bioinformatics↗

bioRxiv2025

A systemically delivered AAV-CFTR gene therapy for cystic fibrosis

Cystic fibrosis (CF) is the most common monogenic lung disease and results from mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR). There have been over 2000 variants identified in patients that result in loss of function of the CFTR protein leading to systemic disease and respiratory failure in adolescence. While some variants encode proteins with residual activity that can be corrected or potentiated by CFTR modulators, at least 10% of CF individuals cannot tolerate the modulators or have nonsense mutations which fail to make any protein. For all people with CF, a mutation agnostic gene replacement strategy could provide a cure for CF lung disease. Here, we propose using a systemic route of administration to deliver a functional CFTR minigene cargo with a lung tropic AAV capsid. This would serve to reach multiple organs, most importantly the lung epithelium, and would provide a functional CFTR transgene that could be expressed in any cell type with a ubiquitous promoter. To achieve this, we generated the smallest CFTR minigene tested in an AAV delivery to date. We demonstrate its expression and function following transfection in cell-based assays and restoration of function in primary CF airway cells after viral delivery. Furthermore, we identify an AAV capsid that can transduce alveolar and airway epithelium with systemic delivery in non-human primates. These data provide tools for delivering a functional CFTR minigene that fits within the packaging capacity of an AAV and demonstrate lung transduction with an AAV following systemic delivery in a large animal model. This strategy first and foremost can reach target airway cells by circumventing the strong mucosal barrier in CF airways but may also provide a method by which to restore CFTR function in additional CF affected organs.

genetics↗

bioRxiv2025

Shifting the PPARγ conformational ensemble towards a transcriptionally repressive state improves covalent inhibitor efficacy

The nuclear receptor peroxisome proliferator-activated receptor gamma (PPAR{gamma}) regulates transcription in response to ligand binding at an orthosteric pocket within the ligand-binding domain (LBD). We previously showed that two covalent ligands, T0070907 and GW9662--extensively used as PPAR{gamma} inhibitors to assess off-target activity--weaken but do not completely block ligand binding via an allosteric mechanism associated with pharmacological inverse agonism (Shang et al., 2024). These covalent inhibitors shift the LBD towards a repressive conformation, where the activation function-2 (AF-2) helix 12 occupies the orthosteric pocket, competing with orthosteric ligand binding. Here, we provide additional support for this allosteric mechanism using two covalent inverse agonists, SR33065 and SR36708, which better stabilize the repressive LBD conformation and are more effective inhibitors of--but also do not completely inhibit--ligand cobinding. Furthermore, we show that ligand cobinding can occur with a previously reported PPAR{gamma} dual-site covalent inhibitor, SR16832, which appears to weaken ligand binding through a direct mechanism independent of the allosteric mechanism. These findings underscore the complex nature of the PPAR{gamma} LBD conformational ensemble and highlight the need to develop alternative methods for designing more effective covalent inhibitors.

biochemistry↗

bioRxiv2025

Single-cell RNA-seq reveals altered plasma cell subsets and decreased cytotoxicity of NK cells in patients with Kawasaki diseas

AimThe pathogenesis and therapeutic strategies of Kawasaki disease (KD) are worth further exploring. Using single-cell RNA sequencing (scRNA-seq), our study aimed to explore the landscape of peripheral blood mononuclear cells (PBMCs) in patients with KD. MethodsWe analyzed the scRNA-seq data of three patients with KD and three healthy controls from the GSE168732 dataset. Additionally, we explored the immune profiles and immune cell subtypes of patients with KD. ResultsSignificantly increased B cells and decreased NK cells were observed in the KD group compared with that in the control group. Furthermore, six B cell subsets were identified in the PBMCs of patients with KD. Particularly, plasma cells (CD9+ and S100A9+ B cell clusters) distinctly increased in the KD group. CD9+ B cell cluster was characterized by vascular endothelial growth factor (VEGF) signaling-associated marker genes and DEGs. Meanwhile the S100A9+ B cell cluster was characterized by platelet aggregation marker genes. As for NK cells, CD16+CD56dim NK cells were enriched in the KD group. Cytotoxicity-related activating receptors (KLRD1,KLRC3) and cytotoxicity-associated genes (PRF1, NKG7, GZMA, GZMH, GNLY) were downregulated in the KD group. ConclusionCD9+ and S100A9+ plasma cells may contribute to CALs in KD by upregulating VEGF and activating platelet. In addition, decreased cytotoxicity of NK cells mediated by KLRD1/KLRC3 receptor may play a vital role in the development of KD. Our results suggested that plasma cells and NK cells could be promising targets for the treatment of KD.

immunology↗

bioRxiv2025

Circulating extracellular vesicles from HIV-1 gp120-treated mice act as endogenous algogens, mediating and maintaining HIV-associated chronic pain

HIV-associated chronic pain (HIV-PAIN) remains prevalent in the post combined antiretroviral therapy era, affecting 30-60% of HIV patients worldwide. The underlying mechanism responsible for the development and maintenance of chronic pain remains unclear. gp120 is a causal factor of the HIV-PAIN and functions as an exogenous algogen. The pain experienced by human HIV-PAIN has been modeled in mice (referred to as mHIV-PAIN) using intrathecal (i.t.) injections of gp120. gp120 is a relatively short-term, static, exogenous algogen that is exhaustible in vivo. In authentic infection, HIV virions serve as the primary source of exogenous gp120, which initiates the early phase of clinical HIV-PAIN. Interestingly, while the source of replenishing gp120 decreases after antiretroviral therapy by suppressing viremia, the prevalence of chronic HIV-PAIN remains stable. To induce chronic pain in mice, gp120 needs to be repeatedly applied by the i.t. route. This raises a key question: Is an endogenous inexhaustible algogen responsible for maintaining the chronicity of HIV-PAIN? In the present study, we isolated circulating small extracellular vesicles (sEV) from mice using our mHIV-PAIN model that is i.t. injected with gp120. We refer to such sEV as gp120-sEV herein. We observed that gp120 is absent in gp120-sEV. Following transfusion of gp120-sEV intrathecally, naive recipient mice exhibit an extensive pain phenotype, including cold pain tested with we newly invented dry ice vapor cold test. RNA-sequence analysis suggests that gp120-sEVs induced expression of genes related to nociception and neuroinflammation pathways. These findings provide direct evidence that circulating sEV function as endogenous long-term "dynamic" algogens that enhance initial pain and extend the chronification of HIV-PAIN in mice, suggesting that chronic HIV-PAIN requires an exogenous algogen (gp120) paired with endogenous algogen (gp120-sEV), and that these components work synchronically to initiate and extend pain chronification. This double algogen concept provides a new insight into the pathogenesis of HIV-PAIN chronification. Our new mechanistic understanding will also assist in identifying new therapeutics to alleviate HIV-PAIN by targeting pathological gp120-sEV.

neuroscience↗

bioRxiv2024

Discovery of novel quinoline papain-like protease inhibitors for COVID-19 through topology constrained molecular generative model

The rapid emergence of drug-resistant SARS-CoV-2 variants poses a persistent challenge to current antiviral strategies. Mutations in key viral targets, including RNA-dependent RNA polymerase (RdRp), main protease (3CLpro), and papain-like protease (PLpro), have been shown to markedly reduce the efficacy of approved therapeutics, highlighting the urgent need for next-generation antivirals capable of overcoming resistance. Here, we report the discovery of a novel class of PLpro inhibitors through an AIDD strategy based on a topology-constrained molecular generative model (Tree-Invent) integrated with structure-guided optimization. Scaffold hopping from a previously reported lead enabled the identification of a quinoline-based chemical series with substantially improved metabolic stability and antiviral potency. Structure-guided optimization yielded compound GZNL-2016, which exhibited potent enzymatic inhibition of PLpro (IC50 = 10.5 nM), robust antiviral activity against multiple SARS-CoV-2 variants, including Omicron BA.5 and XBB.1, and favorable pharmacokinetic properties following oral administration. Notably, GZNL-2016 retained substantial inhibitory activity against the clinically relevant drug-resistant mutant PLpro E167K (IC50 = 480.2 nM; Ki = 439.3 nM), in contrast to previously reported inhibitors that exhibit markedly reduced potency. In a SARS-CoV-2 infection mouse model, oral administration of GZNL-2016 significantly reduced pulmonary viral titers, demonstrating in vivo antiviral efficacy. Collectively, this study establishes an AI-enabled strategy for rapid antiviral discovery and identifies GZNL-2016 as a promising lead compound to address the threat of coronavirus infections caused by drug-resistant mutant SARS-CoV-2 variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/611841v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@ecbd3eorg.highwire.dtl.DTLVardef@7c663corg.highwire.dtl.DTLVardef@11c0e37org.highwire.dtl.DTLVardef@e950f0_HPS_FORMAT_FIGEXP M_FIG C_FIG We leveraged an AI generative model to discover a novel PLpro inhibitor with excellent liver stability, low CYP, hERG inhibition and reasonable oral PK properties. At the same time, the compound 16 exhibits high efficacy for the resistance mutation E167K, which resulted in severe resistance to the previously reported inhibitor Jun12682 and PF-07957472.

microbiology↗

bioRxiv2024

Mechanisms of traditional Chinese medicine in modulating cardiac microvascular endothelial cells in various injury models: A comprehensive systematic review

BackgroundThe structural and functional failure of cardiac microvascular endothelial cells (CMECs) is a primary contributor to coronary microvascular dysfunction (CMD). Traditional Chinese medicine (TCM) has been identified as a potential therapeutic approach for preserving CMECs and mitigating CMD. ObjectiveThis systematic review aims to present the latest evidence on TCM intervention mechanisms in CMECs under diverse injury models. MethodsThis systematic review was performed following the parameters of the PRISMA statement (Preferred Reporting Items for Systematic Reviews and Meta-Analysis). A comprehensive literature search was conducted using PubMed, Embase, Web of Science, Scopus, China National Knowledge Infrastructure and China Biology Medicine disc. Reference lists of selected articles were reviewed to identify relevant studies. The search was not limited by year and was conducted solely in English. Eligible studies comprised publications describing in vitro studies that presented the latest evidence on TCM intervention mechanisms in CMECs under diverse injury models. ResultsA total of 63 papers were included in this study. According to the cell processing approach, 19 studies on ischemia or hypoxic injury models, 16 studies on Ischemia/reperfusion (I/R) or hypoxia/reoxygenation (H/R) injury models, 10 studies on inflammatory injury models, 5 studies on metabolic injury models, 3 studies on angiotensin II injury models, and 10 studies on other models. TCM exhibits structural and functional intervention capabilities in diverse damage conditions of CMECs. Its mechanism of action involves antioxidant, anti-apoptotic, anti-inflammatory effects, as well as regulation of energy metabolism through signaling pathways such as HIF-1/VEGF, PI3K/AKT, MAPK, and NF-{kappa}B. ConclusionsThe CCM and its constituents modulate CMECs through multiple signaling pathways in response to various injury models, thereby conferring protection on the coronary microcirculation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/611361v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@188068forg.highwire.dtl.DTLVardef@166c434org.highwire.dtl.DTLVardef@1db6c16org.highwire.dtl.DTLVardef@952182_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

PlasGO: enhancing GO-based function prediction for plasmid-encoded proteins based on genetic structure

Plasmid, as a mobile genetic element, plays a pivotal role in facilitating the transfer of traits, such as antimicrobial resistance, among the bacterial community. Annotating plasmid-encoded proteins with the widely used Gene Ontology (GO) vocabulary is a fundamental step in various tasks, including plasmid mobility classification. However, GO prediction for plasmid-encoded proteins faces two major challenges: the high diversity of functions and the limited availability of high-quality GO annotations. Thus, we introduce PlasGO, a tool that leverages a hierarchical architecture to predict GO terms for plasmid proteins. PlasGO utilizes a powerful protein language model to learn the local context within protein sentences and a BERT model to capture the global context within plasmid sentences. Additionally, PlasGO allows users to control the precision by incorporating a self-attention confidence weighting mechanism. We rigorously evaluated PlasGO and benchmarked it against six state-of-the-art tools in a series of experiments. The experimental results collectively demonstrate that PlasGO has achieved commendable performance. PlasGO significantly expanded the annotations of the plasmid-encoded protein database by assigning high-confidence GO terms to over 95% of previously unannotated proteins, showcasing impressive precision of 0.8229, 0.7941, and 0.8870 for the three GO categories, respectively, as measured on the novel protein test set.

bioinformatics↗