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Biology subjects

Hayat, K.

Publications and source records attributed to Hayat, K..

2 recordsLinked to original sources

Loss of connexin 43 in cartilage causes mitochondrial dysfunction and accelerates post-traumatic osteoarthritis progression

Osteoarthritis (OA) is a major cause of chronic pain and disability worldwide, characterized by progressive degeneration of cartilage and subchondral bone. Post-traumatic OA (PTOA) develops in as many as 25-50% of individuals following major joint injury, making it a leading cause of OA in younger and otherwise healthy populations.1,2 Connexin 43 (Cx43), a gap junction protein involved in intercellular communication and cellular stress responses, has been linked to OA; however, its role in the progression of PTOA remains unclear. Here, we examined how cartilage-specific loss of Cx43 influences PTOA and chondrocyte metabolic function. Using a murine model of conditional Cx43 deletion in cartilage, we demonstrate that male knockout mice exhibited severe cartilage surface damage and matrix loss, whereas female knockout mice showed cartilage thinning accompanied by reduced chondrocyte hypertrophy, decreased subchondral bone density, and increased osteophyte formation. Thus, loss of Cx43 disrupts cartilage integrity and osteochondral remodeling in a sex-specific manner, predisposing joints to maladaptive bone changes and cartilage degeneration. Complementary mechanistic studies in human articular chondrocytes revealed that Cx43 deficiency impairs mitochondrial respiration, reduces spare respiratory capacity, and lowers ATP production, consistent with compromised cellular bioenergetics. Together, these findings identify Cx43 as an important coordinator of metabolic and structural responses to joint injury. These results position Cx43 as a context-dependent regulator of joint homeostasis and suggest that maintenance of Cx43 expression may support cartilage resilience following injury.

cell biology↗

From Metabolism to Malignancy: Profiling Diabetes-Related Genes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) and diabetes mellitus both affect the liver, a key metabolic organ. This study uses bioinformatics to explore genetic links between Type 1 Diabetes (T1D) and HCC prognosis. Eleven HCC gene expression datasets from GEO and one TCGA-LIHC dataset were analyzed. Gene Set Enrichment Analysis (GSEA) identified up- and downregulated genes after data normalization in R. Four datasets (GSE64041, GSE78737, GSE107170, TCGA) revealed increased expression of T1D-related genes. Ten genes, including HLA-DOB and HLA-DPB1, were consistently upregulated. Statistical analysis (Kruskal-Wallis and Mann-Whitney U tests) showed these two genes were significantly associated with tumor grade and T-stage, with p-values ranging from 0.008 to 0.019. Co-expression analysis with 96 literature-curated T1D genes identified 23 related genes. Survival analysis using Kaplan-Meier curves highlighted five genes (IL7R, CD69, CCR5, RUNX3, PRF1), with CD69 showing strong associations with T-stage and disease-free survival. PRF1, RUNX3, and CCR5 were also linked to survival outcomes. Seven diabetes-related GEO datasets were used for validation. GSEA showed T1D gene enrichment in two datasets (GSE228267, GSE232310), with HLA-DOB significantly expressed in GSE228267 (p = 0.004). These findings suggest that HLA-DOB, HLA-DPB1, and three other T1D-related genes may serve as potential biomarkers for understanding the genetic connection between T1D and HCC. Though computational, this study lays the groundwork for future experimental validation.

bioinformatics↗