Causal Relationships between Homocysteine and the Polycystic Ovary Syndrome: A Mendelian Randomization Analysis.

Background: Polycystic ovary syndrome (PCOS) is an endocrine disease attributed to multiple genetic variants and environmental factors. We aimed to find the causal association of homocysteine (Hcy) with PCOS. Methods: A two-sample Mendelian randomization (MR) analysis was performed. We selected 14 single-nucleotide polymorphisms (SNPs) as instrumental variables to predict the risk of PCOS from genome-wide association studies (GWAS). The summary statistics of PCOS were obtained from 3 large genome-wide association studies in the European population, involving 4,138 cases and 20,129 controls, 3,609 cases and 229,788 controls, 994 cases and 165,817 controls, separately. Results: The IVM analyses revealed that plasma Hcy levels were not causally associated with the risk of PCOS in the meta-analysis (combined effect = 1.032, 95% confidence interval (CI): 0.885-1.203, p=0.688). Conclusions: There was no sufficient evidence to support the causal association of the Hcy with the risk of PCOS.

Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value.

BACKGROUND: Ovarian cancer (OC) is a severe gynecological malignancy with significant diagnostic and therapeutic challenges. The discovery of reliable cancer biomarkers can be used to adjust diagnosis and improve patient care. However, serous OC lacks effective biomarkers. We aimed to identify novel biomarkers for OC and their pathogenic causes. METHODS: The present study used the differentially expressed genes (DEGs) obtained from the "Limma" package and WGCNA modules for intersection analysis to obtain DEGs in OC. Three hub genes were identified-claudin 3 (CLDN3), interferon regulatory factor 6 (IRF6), and prostasin (PRSS8)-by searching for hub genes through the PPI network and verifying them in GSE14407, GSE18520, GSE66957, and TCGA + GTEx databases. The correlation between IRF6 and the prognosis of OC patients was further confirmed in Kaplan-Miller Plotter. RT-qPCR and IHC confirmed the RNA and protein levels of IRF6 in the OC samples. The effect of IRF6 on OC was explored using transwell invasion and scratch wound assays. Finally, we constructed a ceRNA network of hub genes and used bioinformatics tools to predict drug sensitivity. RESULTS: The joint analysis results of TCGA, GTEx, and GEO databases indicated that IRF6 RNA and protein levels were significantly upregulated in serous OC and were associated with OS and PFS. Cell function experiments revealed that IRF6 knockdown inhibited SKOV3 cell proliferation, migration and invasion. CONCLUSION: IRF6 is closely correlated with OC development and progression and could be considered a novel biomarker and therapeutic target for OC patients.

CNKSR2 expression is correlated with immune infiltrates in Cervical Cancer as a favorable prognostic factor.

Connector enhancer of kinase suppressor of Ras 2 (CNKSR2) is a scaffold protein that mediates mitogen-activated protein kinase pathways. However, the molecular function of CNKSR2 in cervical squamous cell carcinoma (CESC) remains unknown. This study aimed to characterize the role of CNKSR2 in patients with CESC. Immunohistochemistry revealed that the expression of CNKSR2 in CESCs is relatively low compared with that in normal cells. We also explored the gene expression profile of high- and low-CNKSR2 expression in patients with cervical cancer. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the expression of CNKSR2 was upregulated in synapse assembly, which was coordinately regulated using the cAMP signaling pathway and calcium signaling pathway. The correlation between CNKSR2 and cancer immune cell infiltration was investigated via single-sample gene set enrichment analysis (ssGSEA). High CNKSR2 expression was associated with better overall survival (OS) and disease-free survival (DFS). Interestingly, high CNKSR2 expression was a good predictor of the survival outcome in cervical cancer patients. Additionally, CNKSR2 expression was strongly correlated with diverse immune cells in CESCs, including NK cells and T cells. These findings suggest that CNKSR2 is correlated with prognosis and immune infiltration, laying the foundation for future studies on the functional role of CNKSR2 in CESC.

Comprehensive analysis of hub genes associated with cisplatin-resistance in ovarian cancer and screening of therapeutic drugs through bioinformatics and experimental validation.

BACKGROUND: To identify key genes associated with cisplatin resistance in ovarian cancer, a comprehensive analysis was conducted on three datasets from the GEO database and through experimental validation. METHODS: Gene expression profiles were retrieved from the GEO database. DEGs were identified by comparing gene expression profiles between cisplatin-sensitive and resistant ovarian cancer cell lines. The identified genes were further subjected to GO, KEGG, and PPI network analysis. Potential inhibitors of key genes were identified through methods such as LibDock nuclear molecular docking. In vitro assays and RT-qPCR were performed to assess the expression levels of key genes in ovarian cancer cell lines. The sensitivity of cells to chemotherapy and proliferation of key gene knockout cells were evaluated through CCK8 and Clonogenic assays. RESULTS: Results showed that 12 genes influenced the chemosensitivity of the ovarian cancer cell line SKOV3, and 9 genes were associated with the prognosis and survival outcomes of ovarian cancer patients. RT-qPCR results revealed NDRG1, CYBRD1, MT2A, CNIH3, DPYSL3, and CARMIL1 were upregulated, whereas ERBB4, ANK3, B2M, LRRTM4, EYA4, and SLIT2 were downregulated in cisplatin-resistant cell lines. NDRG1, CYBRD1, and DPYSL3 knock-down significantly inhibited the proliferation of cisplatin-resistant cell line SKOV3. Finally, photofrin, a small-molecule compound targeting CYBRD1, was identified. CONCLUSION: This study reveals changes in the expression level of some genes associated with cisplatin-resistant ovarian cancer. In addition, a new small molecule compound was identified for the treatment of cisplatin-resistant ovarian cancer.

Transformation of Natural Resin Resina Draconis to 3D Functionalized Fibrous Scaffolds for Efficient Chronic Wound Healing.

Chronic wound healing is a major challenge in clinical practice. Secondary dressing damage and antibiotic resistance are the main obstacles for traditional wound dressings. Resina draconis (RD), a natural resin traditionally used in powder form for wound care, is now considered unsuitable due to the lack of gas permeability and moist environment required for wound healing. Here, RD is incorporated in situ by constructing a 3D coiled fibrous scaffold with polycaprolactone/polyethylene oxide. Due to the high porosity of 3D scaffold, the RD-3D dressings have a favorable swelling capacity, providing permeability and moisture for wound repair. Meanwhile, the transformation of RD powder into 3D dressings fully demonstrates capabilities of RD in rapid hemostasis, bactericidal, and inflammation-regulating activities. In vivo evaluations using pressure ulcer and infected wound models confirm the high efficacy of RD-3D dressing in early wound healing, particularly beneficial in the infected wound model compared to recombinant bovine FGF-basic. Further biological analysis shows that resveratrol, loureirin A, and loureirin B, as potentially bioactive components of RD, individually contribute to different aspects of wound healing. Collectively, RD-3D integrated dressings represent a simple, cost-effective, and safe approach to wound healing, providing an alternative therapy for translating medical dressings from bench to bedside.

Application and discoveries of metabolomics and proteomics in the study of female infertility.

Introduction: Female infertility is defined as the absence of clinical pregnancy after 12 months of regular unprotected sexual intercourse. Methods: This study employed metabolomics and proteomics approaches to investigate the relationship between metabolites and proteins and female infertility. The study used metabolomics and proteomics data from the UK Biobank to identify metabolites and proteins linked to infertility. Results: The results showed that GRAM domain-containing protein 1C and metabolites fibrinogen cleavage peptides ADpSGEGDFXAEGGGVR and 3-Hydroxybutyrate had a positive correlation with infertility, whereas proteins such as Interleukin-3 receptor subunit alpha, Thrombospondin type-1 domain-containing protein 1, Intestinal-type alkaline phosphatase, and platelet and endothelial cell adhesion molecule 1 exhibited a negative correlation. These findings provide new clues and targets for infertility diagnosis and treatment. However, further research is required to validate these results and gain a deeper understanding of the specific roles of these metabolites and proteins in infertility pathogenesis. Discussion: In conclusion, metabolomics and proteomics techniques have significant application value in the study of infertility, allowing for a better understanding of the biological mechanisms underlying infertility and providing new insights and strategies for its diagnosis and treatment. These research findings provide a crucial biological mechanistic basis for early infertility screening, prevention, and treatment.