Atherosclerosis is an immunoinflammatory disease caused by lipids which is an important factor in causing coronary heart disease and stroke. Medical researchers around the world are working on more effective ways to diagnose and treat it. This article will introduce a method of machine learning algorithm to screen biomarkers and perform pan-cancer analysis for reference. First, we downloaded the GEO dataset containing information on atherosclerotic patients for differential gene screening. At the same time, we also used TCGA and GTEx databases for pan-carcinogenic analysis of differential genes. Then, we performed WGCNA analysis. The selected module genes were crossed with the differential genes to obtain 122 key genes. Four machine learning algorithms, XGBoost, RandomForest, SVM-REF and GLM, were used to calculate the critical genes and get the junction of the results to obtain 4 hub genes (SLAMF8, TLR2, VAMP8 and VSIG4). Next, we build a diagnostic model and assess the capabilities of this model.At the same time, the ROC curves of the four genes also suggest that their role in the development of atherosclerosis is critical. Next, we performed gene correlation analysis, immune infiltration analysis and RT-PCR verification of the four core genes, and finally screened out TLR2 for pan-carcinoma. Through analysis, we can find that the expression of TLR2 in patients with a variety of tumors is different from that of normal people, and it is strongly associated with the proportion of prognosis of patients with diverse cancers. The results suggest that TLR2 may be a target for intervention in the development of diseases such as atherosclerosis and tumors.
In the case of acute myocardial infarction, after coronary angioplasty, thrombolytic therapy and cardiac arrest and rebound surgery, the ischemic myocardium of patients may suffer from blood reperfusion injury. However, this is an inevitable complication of treatment, mainly manifested in arrhythmia, myocardial stunning, heart failure and so on, and even death in severe cases. The main mechanisms of myocardial ischemia-reperfusion injury include inflammatory response, autophagy, apoptosis, oxidative stress response, calcium overload, mitochondrial dysfunction and so on. What makes me curious is the calcium overload mechanism, which is the main inducement of reperfusion injury, and can act with other inducing mechanisms to further aggravate reperfusion injury. It is an important cause of myocardial injury and provides a new idea for myocardial protection. This paper comprehensively discusses calcium overload from the perspective of the mechanism of ischemia-reperfusion injury.
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