Age-dependent Changes in Skeletal Muscle Mass and Visceral Fat Area in a Chinese Population.

OBJECTIVE: The present study was conducted to demonstrate the age-dependent changes in skeletal muscle mass and visceral fat area in a population of Chinese adults aged 30-92 years old. METHODS: A total of 6669 healthy Chinese men and 4494 healthy Chinese women aged 30-92 years old were assessed for their skeletal muscle mass and visceral fat area. RESULTS: The results showed age-dependent decreases in the total skeletal muscle mass indexes in both men and women aged 40-92 years old as well as age-dependent increases in the visceral fat area in men aged 30-92 years old and in women aged 30-80 years old. Multivariate regression models showed that the total skeletal muscle mass index was positively associated with the body mass index and negatively associated with the age and visceral fat area in both sexes. CONCLUSION: The loss of skeletal muscle mass becomes obvious at approximately 50 years of age, and the visceral fat area commences to increase at approximately 40 years of age in this Chinese population.

Assessment of pulmonary infectious disease treatment with Mongolian medicine formulae based on data mining, network pharmacology and molecular docking.

Objective: Pulmonary infectious diseases (PID) include viral pneumonia (VP) and pulmonary tuberculosis (PT). Mongolian medicine (MM) is an effective treatment option in China, however, the core group medicines (CGMs) in the treatment of PID and their underlying therapeutic mechanisms remain unclear. In this study, through the method of data mining, the CGMs of MM for the treatment of PID were excavated, and the possible mechanism of action of the CGMs in the treatment of PID was explored by using network pharmacology. Methods: First, 89 MM formulae for the treatment of pulmonary infectious diseases collected from Gan Lu Si Bu, Meng Yi Jin Kui, People's Republic of China Ministry of Health Drug Standards (Mongolian Medicine Volume), Standard of Mongolian Medicine Preparations in Inner Mongolia (2007 Edition), and Standard of Mongolian Medicine Preparations in Inner Mongolia (2014 Edition). The CGMs of MM for PID were excavated through association rule analysis and cluster analysis. Then, the active ingredients and potential targets of the CGMs were obtained from TCMSP, TCMIP, BATMAN-TCM databases. PID targets information was collected from OMIM, GeneCards, and DrugBank databases. The possible targets of CGMs treatment for PID were obtained by intersection. The PPI network was constructed through the STRING database, and the topology analysis of the network was performed. Through the enrichment analysis of the intersection targets by R language, the main action pathways and related target proteins of CGMs in the treatment of PID were screened out. The results were verified by molecular docking. Results: A total of 89 formulae were included, involving 164 MM herbs. The efficacy of the drugs was mainly cough-suppressing and panting-calming herbs, and heat-clearing herbs. The nature and flavor were mainly bitter and cold. The CGMs of MM to treatment of PID was excavated as the classic famous formula Sanzi Decoction (Toosendan Fructus-Chebulae Fructus-Gardeniae Fructus). A total of 28 candidate components and 237 predicted targets of CGMs were collected, and 61 common targets with PID were obtained, including key compounds such as quercetin, kaempferol, ß-sitosterol and stigmastero and key targets such as VEGFA, IL6, TP53, AKT1. KEGG enrichment analysis yielded AGE-RAGE signaling pathways, IL-17 signaling pathways, and TNF signaling pathways. Molecular docking results showed that the key targets were well matched with the potential active ingredients of CGMs. Conclusion: This study found that MM commonly used cough-suppressing and panting-calming herbs in combination with heat-clearing herbs to treat PID, and the CGMs for the treatment of PID is "Toosendan Fructus-Chebulae Fructus-Gardeniae Fructus". CGMs mainly play a role in the treatment of PID by acting on VEGFA, IL6, TP53, AKT1 and other targets, regulating AGE-RAGE signaling pathways, IL-17 signaling pathways, and TNF signaling pathways.