Biomarkers of ocular allergy and dry eye disease

Molecular insights into ulcerative colitis and orbital inflammation

Ulcerative colitis (UC) is an increasingly prevalent inflammatory condition affecting the intestinal mucosa, while nonspecific orbital inflammation (NSOI) is a common non-neoplastic orbital disorder. Exploring the molecular interplay between UC and NSOI may help physicians make earlier diagnoses and enhance treatment approaches. We analyzed gene expression datasets (GSE58331, GSE105149, GSE206285, and GSE179285) for UC and NSOI from the GEO database. Using WGCNA and differential expression analysis, we identified genes commonly altered in both diseases. GO enrichment, PPI networks, and transcription factor prediction were performed using Cytoscape plugins (cytoHubba and iRegulon). Machine learning techniques were employed to assess transcription factor activity and evaluate potential therapeutic targets among the hub genes. We conducted an association analysis using the TwoSampleMR package in R to explore potential causal relationships between NSOI and UC. A total of 85 intersecting genes between NSOI and UC were identified, and enrichment analyses revealed their roles in immune and inflammatory processes. Key biomarkers, including CXCL10, CXCR4, CXCL9, CD27, SELL, MMP9, CD79A, CD3E, GZMK, and CCL19, were highlighted, linking them to processes such as leukocyte migration, viral response, and monocyte differentiation. STAT1 was identified as a shared transcription factor influencing both diseases. Machine learning algorithms identified eight potential genes for diagnostic and therapeutic use, with CXCL10 emerging as a key player in the pathogenesis of NSOI and UC. CXCL10 likely regulates CXCR4, LCK, CCR7, and other genes involved in pathways such as cytokine-cytokine receptor interactions, HIV-1 infection, and Epstein-Barr virus infection. This study offers insights into the co-pathogenic mechanisms of UC and NSOI, providing a foundation for further mechanistic research and therapeutic development.

The role of MUC16 in tumor biology and tumor immunology in ovarian cancer

In this study, the influence of glycoproteomic changes, specifically MUC16, on NK cell-mediated immunotherapy response in ovarian cancer is explored. Analysis of glycoprotein data from the CPTAC database identified significant upregulation of MUC16 in ovarian cancer tissues, associated with tumor invasiveness and immune evasion. Experimental findings showed that MUC16 knockdown increased NK cell cytotoxicity, decreased invasiveness, and boosted NK cell activation, while MUC16 overexpression resulted in the opposite effects. In vivo experiments demonstrated that MUC16 knockdown suppressed tumor growth, enhanced NK cell infiltration, and bolstered NK cell activation, underscoring the potential of MUC16 as a target for novel immunotherapy approaches in ovarian cancer treatment.

Evaluation of Ocular Surface Parameters and Systemic Inflammatory Biomarkers in Hazelnut Harvesters

AIM

To assess the relationship between systemic inflammation markers and ocular surface parameters in hazelnut harvesters.

MATERIAL AND METHOD

This prospective study included 30 patients presenting with moderate ocular surface diseases during the hazelnut harvesting season. A detailed ophthalmological examination was performed during the harvesting season and the first month after the end of treatment (control). Schirmer test, tear break-up time (TBUT), and ocular surface disease index (OSDI) scores were determined. In complete blood count analysis, in addition to the evaluation of inflammatory cells, the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) were calculated.

RESULTS

Eosinophil percentage had a high level of negative correlation with the TBUT and Schirmer values and a high level of positive correlation with the OSDI score during the hazelnut picking season (r = -0.727, r = -0.735, r = 0.750, respectively). During the hazelnut harvesting season, the NLR and SII parameters had a moderate level of negative correlation with the TBUT (r = -0.29 and r = -0.276) and Schirmer (r = -0.33 and r = -0.298) values and a moderate level of positive correlation with the OSDI score (r = 0.389 and r = 0.264).

CONCLUSION

In hazelnut harvesters, ocular allergy and inflammation may be associated with systemic biomarkers.