Shahid Beheshti University

Patients with multiple sclerosis (MS) face a heightened risk of developing chronic obstructive pulmonary disease (COPD). Despite this widely reported association, the pathogenic contributors and processes that may favor the development of COPD in MS patients have yet to be identified. Recent studies have suggested peripheral blood leukocytes as a potential link between COPD and autoimmune disorders. Therefore, this study aimed to unveil shared molecular signatures between MS and COPD using blood transcriptomes. To this end, gene expression datasets obtained from MS and COPD blood specimens were retrieved from the Gene Expression Omnibus (GEO) database. By integrating datasets belonging to each disorder, differentially expressed genes (DEGs) were determined for each disease. Then, the protein-protein interaction (PPI) network was constructed for shared DEGs between MS and COPD. Subsequently, the network was analyzed to identify hub genes and key regulatory miRNAs. The integrated data for MS encompassed 51 samples (28 from MS patients and 23 from controls), and the integrated data for COPD included 450 samples (275 from COPD patients and 175 from controls). A total of 246 genes were found to exhibit identical directions of expression in both MS and COPD. By applying a high confidence threshold (0.7), a PPI network with 74 nodes was constructed. TP53, H4C6, SNRPE, and RPS11 were identified as hub genes according to the degree measure. In addition, 8 miRNAs were identified as key regulators, each interacting with 6 mRNAs. Among these miRNAs, miR-218-5p and miR-142-5p have been previously reported to contribute to the pathogenesis of these diseases, and here they were identified as key regulators of the shared PPI network, suggesting a potential epigenetic link between MS and COPD. In conclusion, the results highlighted the potential role of peripheral blood leucocytes as a bridge between MS and COPD. These findings broaden our understanding of pathogenic contributors linking MS and COPD. While this transcriptomics study identified multiple key players, such as TP53, miR-218-5p, and miR-142-5p, the assessment of their therapeutic efficacy demands further experimental studies.

Bacteria play a crucial role in human health and disease pathogenesis. In recent years, the therapeutic potential of probiotics has gained increasing attention, with studies suggesting their application in treating various diseases, including cancer. We evaluated clinical data supporting the use of oral and topical probiotics for skin malignancies by conducting a literature search in PubMed and Google Scholar. Although limited, clinical trials investigating probiotics in cancer prevention and treatment have shown promising results, particularly in controlling tumor progression and enhancing therapeutic outcomes. Emerging research suggests that probiotics may contribute to skin cancer prevention by modulating the gut and skin microbiomes, enhancing immune responses, exerting antioxidant and anti-inflammatory effects, and inducing apoptosis. Given their antiproliferative and pro-apoptotic effects on carcinoma cells, probiotic-based therapies may serve as potential cancer-preventive agents and adjunctive treatments during conventional therapies. Key findings from our review highlight the ability of probiotics to influence cancer progression through immune regulation, apoptosis induction, and modulation of inflammatory pathways. However, further well-designed clinical trials are needed to validate these findings and establish probiotics as a viable therapeutic approach in oncology.

In X-ray inspection systems employing dual-energy capabilities, material discrimination primarily centers on three methodologies based on curves: the α curve, the R curve, and the H - L curve.Despite extensive research in this field, there remains ambiguity regarding the comparative effectiveness of these methods under different conditions.This study aims to evaluate the accuracy of material discrimination using a standard cargo inspection system for four wedge-shaped materials.Multiple experiments were conducted, where exptl. data were mapped onto the coordinate system for all three discrimination methods, and discrimination curves were generated using cubic interpolation.Regular residual anal. and statistical tests, including ANOVA and Tukey HSD, were performed to evaluate the effectiveness of the R, α, and H - L methods.No statistically significant differences in the performance of these methods were found.Unlike some previous studies where one method was favored over another, no inherent superiority of any particular method was observed in this research.Addnl., combining these methods yields no significant gains in accuracy or efficiency, and their simultaneous use is not recommended due to increased computational costs.The anal. of sample thickness effects revealed higher success rates for thicker samples, though no method outperformed the others across thickness ranges.These findings suggest that the choice of method should be guided by practical considerations rather than assumptions of inherent superiority.