Depression status of elderly patients with metabolic syndrome in three provinces of China / 中华流行病学杂志

Objective: To understand the depression status and its influencing factors in elderly patients with MS in China and to explore the correlation between various components of elderly MS and depression. Methods: This study is based on the "Prevention and Intervention of Key Diseases in Elderly" project. We used a multi-stage stratified cluster random sampling method to complete 16 199 elderly aged 60 years and above in 16 counties (districts) in Liaoning, Henan, and Guangdong Provinces in 2019, excluding 1 001 missing variables. Finally, 15 198 valid samples were included for analysis. The respondents' MS disease was obtained through questionnaires and physical examinations, and the respondents' depression status within the past half month was assessed using the PHQ-9 Depression Screening Scale. The correlation between elderly MS and its components and depression and its influencing factors were analyzed by logistic regression. Results: A total of 15 198 elderly aged 60 years and above were included in this study, with the prevalence of MS at 10.84% and the detection rate of depressive symptoms in MS patients at 25.49%. The detection rates of depressive symptoms in patients with 0, 1, 2, 3, and 4 MS abnormal group scores were 14.56%, 15.17%, 18.01%, 25.21%, and 26.65%, respectively. The number of abnormal components of MS was positively correlated with the detection rate of depressive symptoms, and the difference between groups was statistically significant (P<0.05). The risk of depression symptoms in patients with MS, overweight/obesity, hypertension, diabetes, and dyslipidemia was 1.73 times (OR=1.73, 95%CI:1.51-1.97), 1.13 times (OR=1.13, 95%CI:1.03-1.24), 1.25 times (OR=1.25, 95%CI:1.14-1.38), 1.41 times (OR=1.41, 95%CI:1.24-1.60), 1.81 times (OR=1.81,95%CI:1.61-2.04), respectively, more than those without the disease. Multivariate logistic regression analysis showed that the detection rate of depressive symptoms in patients with sleep disorders was higher than that with normal sleep (OR=4.89, 95%CI: 3.79-6.32). The detection rate of depressive symptoms in patients with cognitive dysfunction was 2.12 times higher than that in the average population (OR=2.12, 95%CI: 1.56-2.89). The detection rate of depressive symptoms in patients with impaired instrumental activities of daily living (IADL) was 2.31 times (OR=2.31, 95%CI: 1.64-3.26) higher than that in the average population. Tea drinking (OR=0.73, 95%CI: 0.54-0.98) and physical exercise (OR=0.67, 95%CI: 0.49-0.90) seemed to be protective factors for depression in elderly MS patients (P<0.05). Conclusions: Older patients with MS and its component abnormalities have a higher risk of depression than the average population. Sleep disorders, cognitive impairment, and IADL impairment are important influencing factors for depression in elderly MS patients, while tea drinking and physical exercise may help to reduce the risk of the disease.

Predictive study on properties of traditional Chinese medicine components based on pharmacological effects / 中国中药杂志

<p><b>OBJECTIVE</b>To study the relationship between pharmacological effects and properties of traditional Chinese medicine by the decision tree algorithm.</p><p><b>METHOD</b>Based on of pharmacological effects of traditional Chinese medicine, the decision tree algorithm was applied in the study on the relationship between pharmacological effects and properties of traditional Chinese medicines. A model was established with the decision tree algorithm for the purpose of predicting the properties of traditional Chinese medicine components.</p><p><b>RESULT</b>The established model was reliable and stable, and could be used to predict the properties of traditional Chinese medicine components.</p><p><b>CONCLUSION</b>The prediction for the properties of traditional Chinese medicine components with a decision tree model could reflect the theoretical connotation of the properties of traditional Chinese medicine components to some extent and provide a new method for studying the properties of traditional Chinese medicine components.</p>

Study on self-similarity relationship between decoction pieces property and component property / 中国中药杂志

<p><b>OBJECTIVE</b>To predict part of medicinal properties of traditional Chinese medicine components and traditional Chinese medicine decoction pieces by using the traditional Chinese medicinal property data prediction platform, in order to establish the relationship between properties of traditional Chinese medicine components and traditional Chinese medicine decoction pieces.</p><p><b>METHOD</b>The properties of traditional Chinese medicine components were predicted by using the medicinal property data prediction platform based on the pharmacological effects of the components.</p><p><b>RESULT</b>The total sum of identical or similar results of the prediction for the properties of traditional Chinese medicine components and traditional Chinese medicine decoction pieces accounted for over 75%.</p><p><b>CONCLUSION</b>The self-similarity exists between properties of traditional Chinese medicine components and traditional Chinese medicine decoction pieces, which reflects the inheritance, additivity and emergence among different properties of traditional Chinese medicines.</p>