Potential mechanisms for the effects of far-infrared on the cardiovascular system:a review

Far-infrared (FIR) is a form of thermal radiation, which may have beneficial effects on cardiovascular health. Clinical studies suggest that FIR irradiation may have therapeutic effects in heart failure, myocardial ischaemia and may improve flow and survival of arteriovenous fistula. Animal studies have suggested a wide range of potential mechanisms involving endothelial nitric oxide synthase and nitric oxide bioavailability, oxidative stress, heat shock proteins and endothelial precursor cells. However, the exact cellular and molecular mechanism of FIR on the cardiovascular system remains elusive. The purpose of this review is to discuss the current literature, focusing on mechanistic studies involving the cardiovascular system, and with a view to highlighting areas for future investigation.<br/

Predicting a Rationale Weighted Criterion for Admission to Higher Education Institutions

Undergraduate selection, especially for medical degree programs, is a challenging and controversial matter for both national and international institutions. The importance of this paper lies in trying to identify the process of selecting prospective students for medical studies in Saudi Arabia. The currently applied admission criteria are the weighted average score (WAS) of the three pre-university attainments, the general secondary school (GSS), the general aptitude test (GAT), and the scientific achievement test (SAT). There is a different weightage assigned to WAS throughout the national medical institutions. It raises concern about the scientific rationale behind the differences. The present research correlates longitudinal school and university data of medical graduates using a robust methodology of multinomial logistic regression in an attempt to find statistically significant ratios of WAS. A quantitative critique of the admission process was conducted for relatively large 440 graduates of the six-year medicine program, enrolled in five academic years. Several scenarios of admission criteria have been investigated for their significant association and prediction of the academic and clinical performance of medical students. The findings suggest several choices of WAS according to the decision of educational policymakers. The future implications that may influence forthcoming decisions regarding selection criteria are humbly offered. Keywords: Admission test, entrance exam, medical study, logistic regression, Qiyas tests, Saudi Arabia

Identification and Validation of Pathogenic Genes in Sepsis and Associated Diseases by Integrated Bioinformatics Approach

Sepsis is a clinical syndrome with high mortality and morbidity rates. In sepsis, the abrupt release of cytokines by the innate immune system may cause multiorgan failure, leading to septic shock and associated complications. In the presence of a number of systemic disorders, such as sepsis, infections, diabetes, and systemic lupus erythematosus (SLE), cardiorenal syndrome (CRS) type 5 is defined by concomitant cardiac and renal dysfunctions Thus, our study suggests that certain mRNAs and unexplored pathways may pave a way to unravel critical therapeutic targets in three debilitating and interrelated illnesses, namely, sepsis, SLE, and CRS. Sepsis, SLE, and CRS are closely interrelated complex diseases likely sharing an overlapping pathogenesis caused by erroneous gene network activities. We sought to identify the shared gene networks and the key genes for sepsis, SLE, and CRS by completing an integrative analysis. Initially, 868 DEGs were identified in 16 GSE datasets. Based on degree centrality, 27 hub genes were revealed. The gProfiler webtool was used to perform functional annotations and enriched molecular pathway analyses. Finally, core hub genes (EGR1, MMP9, and CD44) were validated using RT-PCR analysis. Our comprehensive multiplex network approach to hub gene discovery is effective, as evidenced by the findings. This work provides a novel research path for a new research direction in multi-omics biological data analysis