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ObjectiveTo investigate the potential pharmacological mechanism of Xinmaikang tablets in the treatment of atherosclerosis cardiovascular disease by using network pharmacology and cell experimental validation. MethodThe components of Xinmaikang tablets were searched by BATMAN-TCM database and the active ingredients and potential targets were screened. The atherosclerosis related disease targets were searched in GeneCards and online mendelian inheritance in man（OMIM） disease databases. The therapeutic targets were obtained by mapping the intersection of the tablets and disease targets. Therapeutic targets were uploaded to STRING database to construct protein-protein interaction（PPI） network. Cytoscape software was used to create a "drug-active component-therapeutic target" network map， and a network topology algorithm was used to screen key action targets. David software was used for gene ontology（GO） and Kyoto encyclopedia of genes and genomes（KEGG） function enrichment analysis. The key targets of drug therapy were validated by in vitro cell assay. ResultA total of 19 active ingredients， 132 potential targets and 4703 atherosclerotic disease-related target genes of Xinmaikang tablets were retrieved and screened， and 84 intersection targets were obtained. 3 key therapeutic targets of Xinmaikang tablets in the treatment of atherosclerotic diseases were screened， including Calmodulin 1（CALM1）， voltage-dependent L-type calcium channel subunit alpha-1C（CACNA1C） and Phosphatidylinositol 4，5-bisphosphate 3-kinase catalytic subunit alpha isoform（PIK3CA）. A total of 313 biological processes， 89 molecular functions and 53 cell components were obtained by GO enrichment. A total of 40 pathways were obtained from KEGG functional enrichment， including purine metabolism， renin secretion， CGMP/PKG signaling pathway and so on. In vitro cell experiment results verified that Xinmaikang tablets can up-regulate the expression of CALM1 and CACNA1C， down-regulate the expression of PIK3CA， so as to inhibit the activity of inflammatory response， and play a therapeutic role in atherosclerotic diseases. ConclusionXinmaikang tablets may treat atherosclerosis cardiovascular disease through betulin， methyleugenol and other compounds， through purine metabolism， renin secretion， cGMP/PKG signaling pathway and other pathways， which acts on CALM1， CACNA1C， PIK3CA and other targets.
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@#Fine particulate matter (PM2.5) not only directly damages lung tissue, but also can be absorbed into blood through alveolar capillaries, which is toxic to the cardiovascular system. PM2.5 can affect lipid metabolism, endothelial function, coagulation and thrombosis through oxidative stress, inflammatory reaction, autonomic nervous dysfunction and immune regulation abnormality, so that it promote arteriosclerosis, plaque instability, and increase the morbidity and mortality of cardiovascular disease. We reviewed the effects and mechanisms of PM2.5 on arteriosclerosis, in order to provide the evidence for the studies into prevention of cardiovascular diseases caused by air pollution.
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Objectives: Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality. The American College of Cardiology/American Heart Association (ACC/AHA) atherosclerotic cardiovascular disease (ASCVD) risk estimator is a recently developed online calculator tool for primary prevention. Family physicians, as first-line soldiers, have close contact with local community patients making preventive care management an integral part of their routine work. Therefore, we would like to assess primary health care providers’ knowledge, attitude and barriers for using ASCVD risk estimator in a family health care facility. Methods: This was a quantitative, cross-sectional, single-center study which took place at a tertiary health care facility between December 2018 and January 2019. An English-paper-based self-administered questionnaire was distributed to all primary health care physicians (n=172). Results: Most of the participants were using a different type of cardiovascular risk score calculator 128 (97.7%). Among these scores, ASCVD risk assessment calculator was the highest frequently used calculator 67 (51.1%) and Framingham risk score 43 (32.8%). Study participant preferred to use mobile application 102 (77.9%) as a technical method of risk score calculation. ASCVD knowledge was significantly related to participants’ clinical attitude (r=0.3, p-value=0.003) however, they have moderate knowledge about ASCVD risk calculator (61.7%), and only 37.3% have a positive attitude towards it. Conclusion: Health promotion implementation needs using powerful primary prevention of cardiovascular risk calculators. Therefore, enhancing family physician knowledge and eliminate obstacles will gradually improve their attitude towards disease prediction and prevention.