Search Results (3,440)

Rainbow trout (Oncorhynchus mykiss) is an important cold-water aquaculture species and a tractable salmonid model for functional genomics. Rapid advances in chromosome-level genome assemblies, genetic variation resources, regulatory annotations, tissue and cell models, controlled challenge systems, and genome-editing technologies have established an increasingly integrated framework for linking genomic variation with measurable phenotypes. Evidence from studies of mucosal immunity, disease-resistance genetics, and environmental stress responses indicates that these resources can improve candidate-gene prioritization and mechanistic interpretation across molecular, cellular, tissue, and whole-fish levels. However, differential gene expression, quantitative trait locus and genome-wide association signals, genomic predictions, and cell-type localization remain largely associative and rarely provide direct evidence of causality. Interpretation is further complicated by salmonid-specific whole-genome duplication, because retained paralogues may exhibit tissue-specific divergence, functional redundancy, and compensatory responses. Further progress will require the integration of pangenomics, regulatory annotation, single-cell and spatial analyses, and paralogue-aware functional perturbation in both cell-based and whole-fish systems. Such integration will strengthen causal inference, clarify genotype–phenotype relationships, and support disease-resistant breeding, healthy aquaculture, and environmental risk assessment. Full article

Grape white rot, a fungal disease caused by Coniella diplodiella, leads to the decay and abscission of leaves and fruits. This disease is recognized as one of the major fungal diseases affecting the grape industry, significantly impacting the quality and yield of grapes. In this study, a seed-derived Streptomyces strain with high biocontrol activity, designated YTU-S40, was isolated from the seeds of Cnidium monnieri (L.). Molecular phylogenetic identification revealed that this isolate belongs to Streptomyces pseudogriseolus. In vitro plate confrontation experiments demonstrated that YTU-S40 exhibited a robust inhibition rate of 76.2% against C. diplodiella. Furthermore, this strain exhibited relatively broad-spectrum antifungal activity, and genomic analysis predicted that its genome harbors 21 biosynthetic gene clusters responsible for secondary metabolite production. In vivo postharvest grape biocontrol assays verified that YTU-S40 significantly reduced the incidence of grape white rot from 94.4% to 1.9%. Untargeted metabolomic profiling suggested that YTU-S40 may produce bioactive antifungal compounds such as antimycins. Collectively, these findings suggest that YTU-S40 holds considerable promise for development as a biocontrol agent. Full article

Alzheimer’s disease (AD) has a complex pathogenesis, involving molecular and neuroimmune dysregulation, but the causal drivers linking transcriptomic changes to immune remodeling are not yet clear. In a discovery cohort, differential expression analysis was performed, and it was independently validated in two external cohorts. Key genes were prioritized via LASSO/logistic regression, functionally annotated, and causally linked to AD using two-sample MR. The neuroimmune landscape was mapped by ssGSEA, and top candidates were validated in vitro. RGS1 is a key node in neuroinflammation and cytoskeletal dynamics, which is prioritized by the algorithmic intersection. MR analysis suggested a potential causal association between genetically predicted RGS1 expression and AD risk. RGS1 was consistently upregulated in both discovery and validation cohorts (AUC: 0.61–0.67) and was confirmed in vitro. Immune deconvolution showed that AD-specific enrichment profiles occur, and RGS1 is strongly correlated with activated CD4+ T cells and pro-inflammatory chemokines. RGS1 is identified as a robust key gene that may contribute to immune microenvironment dysregulation in AD, and combining discovery-validation transcriptomics, causal inference, and experimental validation, we find that RGS1 is a potential immunomodulatory target. Full article

Hemodialysis (HD) is the most widely used renal replacement therapy for patients with end-stage renal disease (ESRD) and is frequently accompanied by long-term complications that impair quality of life, including metabolic and inflammatory disturbances. Growing evidence suggests that these complications may be linked to alterations in the gut microbiota; however, microbial composition and interaction patterns in HD patients remain incompletely characterized. In this exploratory, cross-sectional study, high throughput 16S rRNA gene sequencing was used to profile the fecal microbiota of patients undergoing hemodialysis and of healthy controls. The objective was to characterize associations between hemodialysis and gut microbial composition, ecological network organization, and predicted functional potential. Comparative analyses revealed significant differences in bacterial community structure and microbial networks in the HD cohort. Both gender and dialysis vintage were associated with variation in specific taxa, including increased detection of the Synergistetes phylum, particularly among male patients and those undergoing long-term HD. Associations were also observed between clinical and demographic factors and the relative abundance of several short-chain fatty acid-associated taxa, including members of the Lachnospiraceae and Ruminococcaceae families and the genus Bifidobacterium. Predicted functional potential (PICRUSt2) indicated distinct microbial metabolic profiles in HD patients compared with controls, particularly in pathways related to carbohydrate, nucleotide, and amino acid metabolism, with additional variation according to dialysis vintage. Overall, these findings provide an exploratory characterization of structural, compositional, and predicted functional alterations of the gut microbiota associated with hemodialysis. Although the modest cohort size precludes definitive conclusions, the results support the rationale for larger, longitudinal studies investigating microbiota-derived biomarkers and host–microbiome interactions in ESRD. Full article

Background/Objective: Cinnamaldehyde (CA) is a naturally occurring bioactive compound derived from the leaves, bark, roots, and flowers of the Chinese medicinal plant Cinnamomum cassia. It exhibits a broad spectrum of pharmacological properties, encompassing antioxidant, antibacterial, anti-diabetic, antifungal, and anticancer activities. Notably, it has shown potential therapeutic benefits in the management of type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD). Ochratoxin A (OTA), a common contaminant found in foods such as cereals, coffee, and raisins, is also present in traditional Chinese medicinal materials, including Astragalus and liquorice. T2DM and NAFLD share intertwined pathophysiological pathways, including insulin resistance, dyslipidaemia, chronic low-grade inflammation and oxidative stress, with insulin resistance serving as the common pathological hub for both conditions. Consequently, they frequently co-occur and exacerbate each other. OTA exerts dual-targeted toxicity to the pancreas and liver, which may synergistically drive the development of the comorbidity of T2DM and NAFLD. These two processes are mutually causal and together constitute the pathological basis of metabolic comorbidity. Methods: Network toxicology employs toxicological data, gene expression, and protein–protein interaction (PPI) networks to predict the targets of toxins, while network pharmacology, based on systems biology principles, reveals how drugs exert regulatory effects through multiple targets and pathways. In this study, we employed an integrated network toxicology and network pharmacology approach to jointly decipher the potential mechanisms by which CA intervenes in OTA-induced comorbid T2DM-NAFLD. First, a network toxicology approach was employed to preliminarily screen for core toxicological targets responsible for OTA’s pathogenicity. Subsequently, network pharmacology was used to identify potential targets of CA-mediated intervention in the disease. Finally, the common overlap among the CA intervention targets, OTA toxicity targets, and disease targets was defined as the final set of potential targets for CA-mediated intervention in OTA-induced T2DM-NAFLD comorbidity. A PPI network was constructed using the STRING database, and topological analysis was performed with Cytoscape. Core targets were selected using the median values of six parameters—betweenness centrality, closeness centrality, degree centrality, eigenvector centrality, LAC (local average connectivity) score, and network centrality—as cut-off thresholds, and the top 10 key genes were further identified using the cytoHubba plugin. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database, and the results were visualized on the CNSknowall platform. Lastly, molecular docking of the core targets was performed using the CB-DOCK2 platform to validate binding affinity. Results: Based on an integrated analysis of network toxicology, network pharmacology, and molecular docking, 10 key targets were systematically identified. These may serve as potential mediators of cinnamaldehyde in the treatment of OTA-induced T2DM-NAFLD comorbidity. Among these, six targets—albumin (ALB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), interleukin-6 (IL-6), tumor necrosis factor (TNF), actin beta (ACTB), and estrogen receptor 1 (ESR1)—possess crystal structures amenable to molecular docking. KEGG enrichment analysis revealed that CA and OTA jointly participate in key pathological processes such as the cancer pathway, the lipid and atherosclerosis pathway, the advanced glycation end-products–receptor for advanced glycation end-products (AGE-RAGE) signaling pathway, the phosphatidylinositol 3-kinase–protein kinase B (PI3K-Akt) signaling pathway, the TNF signaling pathway, and the interleukin-17 (IL-17) signaling pathway. OTA exacerbates inflammatory responses, impairs insulin signaling, promotes hepatic steatosis, and disrupts systemic metabolic homeostasis, ultimately contributing to T2DM-NAFLD comorbidity. Conversely, cinnamaldehyde counteracts these pathological processes through multiple mechanisms, including antioxidant and anti-inflammatory effects as well as regulation of glucose and lipid metabolism, thereby restoring metabolic homeostasis. Conclusions: This study has preliminarily identified the toxicological targets of OTA and the potential intervention targets of CA, offering new avenues for preventing and intervening in OTA-induced metabolic toxicity. Furthermore, it provides a theoretical basis for CA as a potential multi-target therapeutic agent and presents novel insights worthy of further investigation into the prevention of T2DM-NAFLD comorbidity. Full article

Background: Frontotemporal dementia (FTD) is a neurodegenerative disease that shares numerous clinical features with other forms of dementia. In this context, non-coding RNAs, specifically microRNAs (miRNAs), represent a promising tool for differential diagnosis. Since these miRNAs can be isolated from circulating extracellular vesicles (EVs) in peripheral blood, they provide a direct insight into FTD-specific molecular processes. Consequently, while EV-contained miRNAs hold potential as disease-specific biomarkers, investigating their relative target genes can help elucidate their precise functional roles. Aim: This work aimed to identify a specific miRNA signature to better characterize FTD pathology. Methods: Building on a previous Next-Generation Sequencing (NGS) analysis, three candidate miRNAs were selected for validation in both EVs and peripheral blood mononuclear cells (PBMCs) of FTD patients. Subsequently, the predicted target genes of two of these miRNAs were validated in PBMCs to assess their expression levels. Results: Our findings revealed that miR-365a-3p and miR-212 were significantly down-regulated in FTD. Conclusions: Together with their target genes, these miRNAs are involved in cell cycle and apoptotic pathways, suggesting a potential role in the pathological mechanisms of the disease. Full article

Objective: While advancements in radiotherapy and systemic agents have significantly improved survival rates in head and neck squamous cell carcinoma (HNSCC), managing long-term, treatment-induced toxicities remains a critical clinical challenge. This study aimed to develop a personalized, supervised machine learning-driven predictive model for multiple chronic toxicities by integrating clinical, dosimetric, and genetic data specifically evaluating the impact of the NBN gene rs1805794 (c.553G>C) polymorphism. Methods: This study enrolled 125 patients with HNSCC who received curative-intent radiotherapy and remained disease-free during follow-up with a median of 98 months. Comprehensive clinical and dosimetric data were collected, and chronic toxicities were recorded. Peripheral blood samples were analyzed for the NBN rs1805794 polymorphism using allele-specific PCR (AS-PCR). Following feature selection, four supervised machine learning classifiers were trained and evaluated to identify the optimal model for predicting multiple chronic toxicities. Results: The XGBoost algorithm emerged as the highest performing model. Baseline clinico-dosimetric predictors of multiple chronic toxicities included PTV70 volume, the addition of concurrent chemotherapy, advanced T and N stages, and continued smoking. Integrating the NBN rs1805794 genotype into the XGBoost architecture enhances its predictive capability. The final model accurately identified patients at high risk for multiple chronic toxicities, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, a sensitivity of 0.74, and a specificity of 0.79. Conclusions: Integrating clinical, dosimetric, and genetic data within a machine learning framework effectively predicts multiple chronic toxicities in HNSCC. This approach enabled early risk stratification, providing the potential for personalized therapy. Full article

Bisphenols (BPs) are widespread environmental endocrine disruptors, but their potential depression-related neurotoxicity has not been systematically assessed. Here, we combined machine learning (ML), network toxicology, molecular docking, and in vivo experiments to screen 26 bisphenols for depression-related neurotoxic risk. We first integrated bisphenol A (BPA)-related targets with depression-related genes to build a chemical-gene-phenotype-disease network and an adverse outcome pathway (AOP) framework. We then used nine ML algorithms to rank the predicted risk of the 26 bisphenols. Molecular docking showed that the predicted high-risk compounds had strong binding affinity for estrogen receptor 1 (ESR1). The AOP analysis further suggested the involvement of the ESR1–cAMP response element-binding protein 1 (CREB1)–glutamate ionotropic receptor N-methyl-D-aspartate type subunit 2B (GRIN2B) pathway. In vivo experiments showed that BPA exposure caused neuronal damage in the cornu ammonis 3 (CA3) region of the rat hippocampus and significantly reduced the messenger RNA (mRNA) expression of the corresponding genes Esr1, Creb1, and Grin2b in hippocampal tissue. Overall, this study screened and prioritized the model-predicted depression-related neurotoxic risk of 26 bisphenols, supports a role for the ESR1–CREB1–GRIN2B pathway in BPA-induced neurotoxicity, and provides mechanistic evidence for bisphenol risk assessment. Full article

Squamous cell carcinoma of the anal canal (SCAC) is a rare malignancy whose incidence has been steadily increasing worldwide. Persistent infection with high-risk human papillomavirus (HPV), particularly HPV16 and HPV18 genotypes, is the main etiological factor and plays a central role in tumor development. While combined chemoradiotherapy remains the standard treatment for localized disease and achieves high rates of tumor control, a considerable proportion of patients experience recurrence or present with advanced disease. For the latter, therapeutic options remain limited. Over the last decade, advances in genomic profiling have significantly expanded our understanding of SCAC biology. Recurrent alterations affecting the PI3K/AKT/mTOR pathway, especially PIK3CA mutations, have emerged as the most common molecular events, particularly in HPV-positive tumors. Additional alterations involve receptor tyrosine kinase signaling, chromatin remodeling genes, DNA damage response pathways, and components of the MAPK cascade. Moreover, HPV-positive and HPV-negative tumors display distinct molecular features with important prognostic implications. Immunotherapy has recently become an important component of treatment for advanced SCAC, although reliable predictive biomarkers are still lacking. This review summarizes the current evidence on the molecular landscape of SCAC, discusses emerging prognostic and predictive biomarkers, and highlights potential opportunities for the development of more personalized therapeutic strategies. Full article

Although Alternaria gansuense causes yellow stunt and root rot (YSRR)—a destructive disease of the leguminous forage Astragalus adsurgens in northern China—systematic investigations of this pathogen at the protein level remain scarce. In this study, we establish an optimized proteomic workflow for A. gansuense by comparing two protein extraction methods. Using data-independent acquisition (DIA) mass spectrometry with a DIA-NN search against the Alternaria protein database, we construct the first comprehensive proteome reference map of A. gansuense, then perform functional annotation via Gene Ontology, KOG, KEGG, InterPro domain, and subcellular localization analyses. A total of 5052 proteins were identified from vegetative mycelia, and the proteome was found to be predominantly composed of proteins involved in primary metabolism, signal transduction, secondary metabolism, and stress responses. Notably, a set of putative pathogenicity-associated proteins, including two-component regulators (SSK1p), protein kinases, cytochrome P450 enzymes, and ABC transporters, was identified. These proteins are homologs of well-characterized virulence factors in other pathogenic fungi, suggesting a potential coordinated signaling—metabolism—defense network that may contribute to fungal virulence. Subcellular localization further shows that cytoplasmic and nuclear proteins together account for over 50% of the annotated proteome. This study presents the first comprehensive proteomic reference map for A. gansuense, providing a valuable resource for functional genomics. Subsequent experimental validation of the bioinformatically predicted candidate molecular targets presented here may help to dissect the pathogenic mechanisms of YSRR and enable the development of novel disease management strategies. Full article

Background/Objectives: N6-methyladenosine (m6A) RNA modification is a major epitranscriptomic regulator of mRNA stability and translation. Genetic variants in the m6A pathway may influence gastric cancer progression, but their prognostic significance after curative gastrectomy remains uncertain. Methods: This retrospective study included 226 patients with gastric adenocarcinoma who underwent curative gastrectomy. Single nucleotide polymorphisms in five m6A-related genes (METTL3, METTL14, FTO, ALKBH5, and YTHDF1) were genotyped. Overall survival (OS) and disease-free survival (DFS) were analyzed using Kaplan–Meier and log-rank tests. Multivariable Cox regression was performed after adjustment for age, sex, tumor stage, lymph node status, and adjuvant therapy. Results: During a median follow-up of 38 months, 78 patients (34.5%) died and 92 (40.7%) experienced recurrence. High-risk m6A genotypes were associated with significantly poorer survival. The 5-year OS was 68.2% in the low-risk group versus 41.5% in the high-risk group (p < 0.001), while 5-year DFS was 61.4% versus 36.8% (p < 0.001). High-risk genotypes independently predicted worse OS (HR 1.87, 95% CI 1.28–2.74; p = 0.001) and DFS (HR 1.94, 95% CI 1.36–2.78; p < 0.001). Patients with the highest genetic risk scores had the poorest outcomes, particularly those with stage III–IV disease. Conclusion: Genetic variants in the m6A RNA modification pathway are independently associated with poorer survival after curative gastrectomy and may serve as prognostic biomarkers for risk stratification and personalized management in gastric cancer. Full article

This comprehensive literature review delves into the multifaceted roles of RNA-binding motif protein 3 (RBM3) in cellular processes, disease pathogenesis, and therapeutic potential. RBM3 has been implicated in shaping cell morphology, synaptic protection in neurodegenerative conditions, and regulating gene expression through binding to specific RNA sequences. In cancer, RBM3 exhibits contrasting effects, influencing cell proliferation, tumorigenic potential, and RNA splicing. Clinical studies suggest RBM3 as a predictive biomarker in chemotherapy response for muscle-invasive bladder cancer. Despite promising therapeutic implications in neuroprotection and cancer, challenges persist in understanding the regulatory mechanisms and clinical behavior of RBM3. Further research is warranted to elucidate the molecular mechanisms underlying RBM3’s diverse functions and its significance as a potential target for personalized medicine in cancer therapy. This review underscores the pivotal role of RBPs, particularly RBM3, in disease progression and highlights the need for continued investigation to harness their therapeutic potential effectively. This review evaluates evidence available through December 2025, with particular emphasis on studies published between 2010 and 2025. Full article

Background: Mechanosensitive ion channels PIEZO1 and PIEZO2 are key mediators of mechanotransduction, which converts physical forces into cellular signals involved in proprioception, touch, vascular function, and other physiological processes. Mutations in human PIEZO proteins are linked to various diseases, such as hereditary xerocytosis, lymphatic dysplasia, and proprioceptive dysfunction. However, the role of intrinsic disorder in the regulation of these proteins and their susceptibility for disease-associated mutations remains unclear. Methods: We analyzed canonical human PIEZO1 and PIEZO2 protein sequences using machine learning, neural network, and energy-based disorder predictors, together with the prediction of disorder-mediated binding regions, phase separation propensity, interaction networks, evolutionary conservation, clinically annotated human variants, and peptide structural modeling. Results: Both proteins showed moderate intrinsic disorder, with PIEZO2 having slightly greater disorder propensity and higher predicted phase separation potential. Intrinsically disordered regions frequently overlapped binding-prone segments and post-translational modification sites, supporting regulatory functions. Evolutionary comparisons showed strong conservation of PIEZO proteins, while selected disordered regions retained disorder propensity despite greater sequence variability. Disease-causing variants mainly affected the ordered regions of both proteins, whereas disordered regions contained proportionally more benign variants and relatively few pathogenic mutations. The modeling of mutations within disordered hotspots showed altered local conformational tendencies, indicating that some disease variants may disrupt dynamic interaction interfaces rather than global structure. Interaction network analysis linked both proteins to enriched mechanotransduction, ion transport, and cytoskeletal pathways. Conclusions: Overall, our findings identify intrinsic disorder as an underappreciated feature of PIEZO channel biology and provide a framework for interpreting PIEZO-associated channelopathies. PIEZO proteins also perfectly illustrate the proteoform concept, where one gene yields a highly diverse kit of mechanosensitive molecular tools. While humans only have two primary PIEZO genes (PIEZO1 and PIEZO2), the body generates a vast array of functional variations. Full article

Background: Ankylosing Spondylitis (AS) and inflammatory bowel disease (IBD) exhibit substantial pathophysiological overlap, including dysregulated innate immunity, barrier dysfunction, and Th17-mediated inflammation. However, whether Na⁺ overload-related genes (NRGs) exhibit shared transcriptional alterations in IBD and AS remains unclear. This study aimed to characterize the expression patterns of NRGs across IBD and AS and to identify candidate genes associated with both diseases. Methods: Differential expression analysis was performed to identify differentially expressed NRGs (DE-NRGs) in diseased tissues relative to normal tissues. Shared DE-NRGs between IBD and AS were screened and defined as common differentially expressed NRGs (Co-DE-NRGs). We then analyzed the correlations of these Co-DE-NRGs and explored their relationships with immune cell infiltration in target tissues. Four machine learning algorithms were applied to screen key NRGs associated with both IBD and AS. Potential therapeutic agents targeting these core biomarkers were predicted using drug–gene interaction databases, and molecular docking was conducted for further validation. Results: A total of 32 shared Co-DE-NRGs were identified for IBD and AS, with nine key regulatory NRGs recognized: CALR, CD63, CYBA, DYSF, HYOU1, IL1B, JAK1, MMP9, and STAT3. Exploratory MR analysis identified disease-specific associations between genetically predicted expression of NRGs and CD, UC, and AS. Genetically predicted STAT3 expression showed positive associations with CD and UC but an inverse association with AS and therefore did not represent a consistent risk factor across the three diseases. Furthermore, transcriptome-based drug-response analysis identified four candidate agents shared between AS and at least one IBD dataset: ciclosporin, BCL-LZH-4, BRD-K79669418, and CID-5951923. Exploratory molecular docking generated STAT3 binding poses for BCL-LZH-4 and CID-5951923, with DOCK Grid Scores of −35.321896 and −28.361128, respectively. CID-5951923 was selected for representative visualization of its predicted interaction with STAT3. Single-cell RNA-sequencing analysis identified tissue- and cell-type-specific STAT3 mRNA expression patterns in the analyzed IBD colonic and AS peripheral-blood datasets, with monocytes representing a major cell population exhibiting detected STAT3 expression in the AS dataset. Conclusions: These findings identify shared NRG-related transcriptional alterations in IBD and AS, with STAT3 emerging as a candidate gene associated with both diseases. Further experimental studies are required to determine whether these alterations reflect the involvement of NECSO and to evaluate their potential diagnostic or therapeutic relevance. Full article

Parkinson’s disease (PD) is a multisystem disorder in which gastrointestinal dysfunction often precedes motor symptoms, yet the molecular links between peripheral stress and central neurodegeneration remain unclear. We investigated whether genes commonly dysregulated in PD and a classic model of intestinal inflammation (IBD) might reveal conserved stress-responsive molecules relevant to brain pathology. Shared gene signatures between PD and inflammatory bowel disease (IBD) were identified from peripheral blood transcriptomes using weighted gene co-expression network analysis (WGCNA). Hub genes were prioritized via protein–protein interaction (PPI) analysis and evaluated for expression consistency in independent brain tissue transcriptomic datasets. Single-cell RNA sequencing (scRNA-seq) of the PD substantia nigra was used to define the cellular context of the key hub gene, and CellChat analysis assessed intercellular communication changes. Immunofluorescence validation was performed in an MPTP-induced PD mouse model. We identified 79 shared genes and 6 hub genes, among which only HSP90AA1 showed consistent upregulation across independent PD transcriptomic validation datasets. Functional enrichment highlighted inflammation-related pathways. Because peripheral immune infiltration showed only minor changes, we further investigated the cellular context of HSP90AA1 within the PD brain. ScRNA-seq analysis of the PD substantia nigra demonstrated that HSP90AA1 was expressed across multiple cell populations. Integration with transcriptional regulatory analysis identified TP53 as a potential upstream regulator, and the strongest TP53–HSP90AA1 co-expression and cellular colocalization signals were observed in astrocytes, prompting further astrocyte-focused investigation. CellChat analysis revealed altered intercellular communication patterns in PD substantia nigra, including changes in synapse-associated ligand–receptor interaction signatures, particularly involving NCAM-related pathways. In the MPTP-induced PD mouse model, immunofluorescence identified astrocytic HSP90α upregulation, and increased nuclear p53 signal in astrocytes, accompanied by dopaminergic neuron loss. Conclusion: Astrocytic upregulation of HSP90AA1 is associated with altered synapse-related intercellular communication patterns in the PD substantia nigra, potentially involving a predicted TP53 associated regulatory component. These findings, validated in an MPTP mouse model, identify HSP90AA1 as a candidate stress-responsive hub linking peripheral inflammatory states with astrocyte-associated molecular alterations in PD, providing a framework for further experimental investigation. Full article