Relationship between clonal evolution and drug resistance in bladder cancer: A genomic research review.

Bladder cancer stands as a prevalent global malignancy, exhibiting notable sex-based variations in both incidence and prognosis. Despite substantial strides in therapeutic approaches, the formidable challenge of drug resistance persists. The genomic landscape of bladder cancer, characterized by intricate clonal heterogeneity, emerges as a pivotal determinant in fostering this resistance. Clonal evolution, encapsulating the dynamic transformations within subpopulations of tumor cells over time, is implicated in the emergence of drug-resistant traits. Within this review, we illuminate contemporary insights into the role of clonal evolution in bladder cancer, elucidating its influence as a driver in tumor initiation, disease progression, and the formidable obstacle of therapy resistance.

Inflammatory cytokines mediating the effect of oral lichen planus on oral cavity cancer risk: a univariable and multivariable mendelian randomization study.

BACKGROUND: While observational studies and experimental data suggest a link between oral lichen planus (OLP) and oral cavity cancer (OCC), the causal relationship and the role of inflammatory cytokines remain unclear. METHODS: This study employed a univariable and multivariable Mendelian Randomization (MR) analysis to investigate the causal relationship between OLP and the risk of OCC. Additionally, the potential role of inflammatory cytokines in modulating this association was explored. Instrumental variables were derived from genetic variants associated with OLP (n = 377,277) identified in Finngen R9 datasets, with 41 inflammatory cytokines as potential mediators, and OCC (n = 4,151) as the outcome variable. Analytical methods including Inverse Variance Weighted (IVW), Weighted Median, MR-Egger, and MR-PRESSO were utilized to assess the causal links among OLP, inflammatory cytokines, and OCC risk. Multivariable MR (MVMR) was then applied to quantify the mediating effects of these cytokines in the relationship between OLP and increased OCC risk. RESULTS: MR analysis provided strong evidence of a causal relationship between OLP (OR = 1.417, 95% CI = 1.167-1.721, p < 0.001) and the risk of OCC. Furthermore, two inflammatory cytokines significantly influenced by OLP, IL-13 (OR = 1.088, 95% CI: 1.007-1.175, P = 0.032) and IL-9 (OR = 1.085, 95% CI: 1.005-1.171, P = 0.037), were identified. Subsequent analysis revealed a significant causal association only between IL-13 (OR = 1.408, 95% CI: 1.147-1.727, P = 0.001) and higher OCC risk, establishing it as a potential mediator. Further, MVMR analysis indicated that IL-13 (OR = 1.437, 95% CI = 1.139-1.815, P = 0.002) mediated the relationship between OLP and OCC, accounting for 8.13% of the mediation. CONCLUSION: This study not only elucidates the potential causal relationship between OLP and the risk of OCC but also highlights the pivotal mediating role of IL-13 in this association.

Efficacy and safety of topical clobetasol propionate in comparison with alternative treatments in oral lichen planus: an updated systematic review and meta-analysis.

Background: Oral lichen planus (OLP) is a relatively common chronic T cell-mediated disease characterized by pain and inflammation. Clobetasol propionate (CLO) is the first-line drug in the treatment of OLP. The meta-analysis aimed to evaluate the efficacy and safety of CLO for treating patients with OLP. Methods: PubMed, Embase and Web of Science were systematically searched from the database inception date up to August 2023. There were no restrictions on language or date of publication. The outcomes of our interest were as follows: improvement of clinical signs and/or symptoms, total lesion size, relapse and adverse events. Results: A total of 17 RCTs evaluating the effects of CLO were included in this study. The results revealed no significant difference in the clinical score (WMD = 0.14, 95% CI: -0.39, 0.66; p = 0.609) and pain score (WMD = 0.17, 95% CI: -0.44, 0.79; p = 0.582) between CLO and other treatments. However, clinical resolution (RR = 1.61, 95% CI: 1.17, 2.22; p = 0.003) and symptoms improvement (RR = 1.80, 95% CI: 1.17, 2.77; p = 0.008) were significantly different between CLO and other treatments. Moreover, there was a significant reduction in the total lesion size with CLO treatment (WMD = -0.58, 95% CI: -1.03, -0.13; p = 0.011). In addition, CLO showed no statistical incidence of adverse events (RR = 1.46, 95% CI: 0.86, 2.50; p = 0.161) and relapse (RR = 1.56, 95% CI: 0.66, 3.71; p = 0.314) than other therapies. Conclusion: This systematic review and meta-analysis of 17 randomized clinical trials supported the long-term application of CLO as an effective regimen in OLP patients.

Oral Microbiota Linking Associations of Dietary Factors with Recurrent Oral Ulcer.

Recurrent oral ulcer (ROU) is a prevalent and painful oral disorder with implications beyond physical symptoms, impacting quality of life and necessitating comprehensive management. Understanding the interplays between dietary factors, oral microbiota, and ROU is crucial for developing targeted interventions to improve oral and systemic health. Dietary behaviors and plant-based diet indices including the healthful plant-based diet index (hPDI) were measured based on a validated food frequency questionnaire. Saliva microbial features were profiled using 16S rRNA gene amplicon sequencing. In this cross-sectional study of 579 community-based participants (aged 22-74 years, 66.5% females), 337 participants had ROU. Participants in the highest tertile of hPDI exhibited a 43% lower prevalence of ROU (odds ratio [OR] = 0.57, 95%CI: 0.34-0.94), compared to the lowest tertile, independent of demographics, lifestyle, and major chronic diseases. Participants with ROU tended to have lower oral bacterial richness (Observed ASVs, p < 0.05) and distinct bacterial structure compared to those without ROU (PERMANOVA, p = 0.02). The relative abundances of 16 bacterial genera were associated with ROU (p-FDR < 0.20). Of these, Olsenella, TM7x, and unclassified Muribaculaceae were identified as potential mediators in the association between hPDI and ROU (all p-mediations < 0.05). This study provides evidence of the intricate interplays among dietary factors, oral microbiota, and ROU, offering insights that may inform preventive and therapeutic strategies targeting diets and oral microbiomes.

Research on the anti-oxidant and anti-aging effects of Polygonatum kingianum saponins in Caenorhabditis elegans.

Oxidative stress and its impact on aging are critical areas of research. Natural anti-oxidants, such as saponins found in Polygonatum sibiricum, hold promise as potential clinical interventions against aging. In this study, we utilized the nematode model organism, Caenorhabditis elegans, to investigate the pharmacological effects of Polygonatum sibiricum saponins (PKS) on antioxidation and anti-aging. The results demonstrated a significant anti-aging biological activity associated with PKS. Through experiments involving lifespan and stress, lipofuscin, q-PCR, and ROS measurement, we found that PKS effectively mitigated aging-related processes. Furthermore, the mechanism underlying these anti-aging effects was linked to the SKN-1 signaling pathway. PKS increased the nuclear localization of the SKN-1 transcription factor, leading to the up-regulation of downstream anti-oxidant genes, such as gst-4 and sod-3, and a substantial reduction in intracellular ROS levels within the nematode. In conclusion, our study sheds light on the anti-oxidant and anti-aging properties of PKS in C. elegans. This research not only contributes to understanding the biological mechanisms involved but also highlights the potential therapeutic applications of these natural compounds in combating aging-related processes.

SLPA-Net: A Real-Time Recognition Network for Intelligent Stomata Localization and Phenotypic Analysis.

Plant stomatal phenotype traits play an important role in improving crop water use efficiency, stress resistance and yield. However, at present, the acquisition of phenotype traits mainly relies on manual measurement, which is time-consuming and laborious. In order to obtain high-throughput stomatal phenotype traits, we proposed a real-time recognition network SLPA-Net for stomata localization and phenotypic analysis. After locating and identifying stomatal density data, ellipse fitting is used to automatically obtain phenotype data such as apertures. Aiming at the problems of small stomata and high similarity to background, we introduced ECANet to improve the accuracy of stoma and aperture location. In order to effectively alleviate the unbalance problem in bounding box regression, we replaced the Loss function with a more effective Focal EIoU Loss. The experimental results show that SLPA-Net has excellent performance in the migration generalization and robustness of stomata and apertures detection and identification, as well as the correlation between stomata phenotype data obtained and artificial data.