Atherosclerotic cardiovascular disease and its complications are a high-incidence disease worldwide. Numerous studies have shown that blood flow shear has a huge impact on the function of vascular endothelial cells, and it plays an important role in gene regulation of pro-inflammatory, pro-thrombotic, pro-oxidative stress, and cell permeability. Many important endothelial cell mechanosensitive genes have been discovered, including KLK10, CCN gene family, NRP2, YAP, TAZ, HIF-1α, NF-κB, FOS, JUN, TFEB, KLF2/KLF4, NRF2, and ID1. Some of them have been intensively studied, whereas the relevant regulatory mechanism of other genes remains unclear. Focusing on these mechanosensitive genes will provide new strategies for therapeutic intervention in atherosclerotic vascular disease. Thus, this article reviews the mechanosensitive genes affecting vascular endothelial cells, including classical pathways and some newly screened genes, and summarizes the latest research progress on their roles in the pathogenesis of atherosclerosis to reveal effective therapeutic targets of drugs and provide new insights for anti-atherosclerosis.
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In recent years, cardiovascular health problems are becoming more and more serious. At the same time, mechanical stimulation closely relates to cardiovascular health. In this context, Piezo1, which is very sensitive to mechanical stimulation, has attracted our attention. Here, we review the critical significance of Piezo1 in mechanical stimulation of endothelial cells, NO production, lipid metabolism, DNA damage protection, the development of new blood vessels and maturation, narrowing of blood vessels, blood pressure regulation, vascular permeability, insulin sensitivity, and maintenance of red blood cell function. Besides, Piezo1 may participate in the occurrence and development of atherosclerosis, diabetes, hypertension, and other cardiovascular diseases. It is worth noting that Piezo1 has dual effects on maintaining cardiovascular health. On the one hand, the function of Piezo1 is necessary to maintain cardiovascular health; on the other hand, under some extreme mechanical stimulation, the overexpression of Piezo1 may bring adverse factors such as inflammation. Therefore, this review discusses the Janus-faced role of Piezo1 in maintaining cardiovascular health and puts forward new ideas to provide references for gene therapy or nanoagents targeting Piezo1.
Most patients with advanced non‐small cell lung cancer (NSCLC) have a poor prognosis. Predicting overall survival using clinical data would benefit cancer patients by allowing providers to design an optimum treatment plan. We compared the performance of nomograms with machine‐learning models at predicting the overall survival of NSCLC patients. This comparison benefits the development and selection of models during the clinical decision‐making process for NSCLC patients.
Multiple machine‐learning models were used in a retrospective cohort of 6586 patients. First, we modeled and validated a nomogram to predict the overall survival of NSCLC patients. Subsequently, five machine‐learning models (logistic regression, random forest, XGBoost, decision tree, and light gradient boosting machine) were used to predict survival status. Next, we evaluated the performance of the models. Finally, the machine‐learning model with the highest accuracy was chosen for comparison with the nomogram at predicting survival status by observing a novel performance measure: time‐dependent prediction accuracy.
Among the five machine‐learning models, the accuracy of random forest model outperformed the others. Compared with the nomogram for time‐dependent prediction accuracy with a follow‐up time ranging from 12 to 60 months, the prediction accuracies of both the nomogram and machine‐learning models changed as time varied. The nomogram reached a maximum prediction accuracy of 0.85 in the 60th month, and the random forest algorithm reached a maximum prediction accuracy of 0.74 in the 13th month.
Overall, the nomogram provided more reliable prognostic assessments of NSCLC patients than machine‐learning models over our observation period. Although machine‐learning methods have been widely adopted for predicting clinical prognoses in recent studies, the conventional nomogram was competitive. In real clinical applications, a comprehensive model that combines these two methods may demonstrate superior capabilities.
Genetic compensation is a remarkable biological concept to explain the genetic robustness in an organism to maintain its fitness and viability if there is a disruption occurred in the genetic variation by mutation. However, the underlying mechanism in genetic compensation remain unsolvable. The initial concept of genetic compensation has been studied in model organisms when there was a discrepancy between knockout-mediated and knockdown-mediated phenotypes. In the zebrafish model, several studies have reported that zebrafish mutants did not exhibit severe phenotype as shown in zebrafish morphants for the same genes. This phenomenon in zebrafish mutants but not morphants is due to the response of genetic compensation. In 2019, two amazing works partially uncovered genetic compensation could be triggered by the upregulation of compensating genes through regulating NMD and/or PTC-bearing mRNA in collaboration with epigenetic machinery in mutant zebrafish. In this review, we would like to update the recent advances and future perspectives of genetic compensation studies, which including the hypothesis of time-dependent involvement and addressing the discrepancy between knockout-mediated and knockdown-mediated to study gene function in the zebrafish model. At last, the study of genetic compensation could be a potential therapeutic strategy to treat human genetic disorder related diseases.
It is increasingly aware that gut microbiota is closely associated with atherosclerosis. However, which and how specific gut bacteria regulate the progression of atherosclerosis is still poorly understood. In this study, modified linear discriminant analysis was performed in comparing the gut microbiota structures of atherosclerotic and non-atherosclerotic mice, and Desulfovibrio desulfuricans (D. desulfuricans) was found to be associated with atherosclerosis. D. desulfuricans-treated Apoe−/− mice showed significantly aggravated atherosclerosis. The proatherogenic effect of D. desulfuricans was attributed to its ability to increase intestinal permeability and subsequent raise in the transit of lipopolysaccharide (LPS) from the intestine to the bloodstream. Excessive LPS in the blood can elicit local and systemic inflammation and activate Toll-like receptor 4 (TLR4)/nuclear factor-κB (NF-κB) signaling of endothelial cells. TAK-242, a specific inhibitor of TLR4, can ameliorate the development of D. desulfuricans-induced atherosclerosis by blocking the LPS-induced activation of TLR4/NF-κB signaling.