Construction of a clinical prediction model for the impact of acupuncture on pregnancy outcomes in poor ovarian response (POR) patients based on a patient registry research platform / 中国针灸

OBJECTIVES@#To construct a clinical prediction model for the impact of acupuncture on pregnancy outcomes in poor ovarian response (POR) patients, providing insights and methods for predicting pregnancy outcomes in POR patients undergoing acupuncture treatment.@*METHODS@#Clinical data of 268 POR patients (2 cases were eliminated) primarily treated with "thirteen needle acupuncture for Tiaojing Cuyun (regulating menstruation and promoting pregnancy)" was collected from the international patient registry platform of acupuncture moxibustion (IPRPAM) from September 19, 2017 to April 30, 2023, involving 24 clinical centers including Acupuncture-Moxibustion Hospital of China Academy of Chinese Medical Sciences. LASSO and univariate Cox regression were used to screen factors influencing pregnancy outcomes, and a multivariate Cox regression model was established based on the screening results. The best model was selected using the Akaike information criterion (AIC), and a nomogram for clinical pregnancy prediction was constructed. The prediction model was evaluated using receiver operating characteristic (ROC) curves and calibration curves, and internal validation was performed using the Bootstrap method.@*RESULTS@#(1) Age, level of anti-Müllerian hormone (AMH), and total treatment numbers of acupuncture were independent predictors of pregnancy outcomes in POR patients receiving acupuncture (P<0.05). (2) The AIC value of the best subset-Cox multivariate model (560.6) was the smallest, indicating it as the optimal model. (3) The areas under curve (AUCs) of the clinical prediction model after 6, 12, 24, and 36 months treatment were 0.627, 0.719, 0.770, and 0.766, respectively, and in the validation group, they were 0.620, 0.704, 0.759, and 0.765, indicating good discrimination and repeatability of the prediction model. (4) The calibration curve showed that the prediction curve of the clinical prediction model was close to the ideal model's prediction curve, indicating good calibration of the prediction model.@*CONCLUSIONS@#The clinical prediction model for the impact of acupuncture on pregnancy outcomes in POR patients based on the IPRPAM platform has good clinical application value and provides insights into predicting pregnancy outcomes in POR patients undergoing acupuncture treatment.

Screening of traditional Chinese medicine-derived snail control drug targets based on network pharmacology / 中国血吸虫病防治杂志

Objective To screen the targets of traditional Chinese medicine-derived potential plant molluscicides based on network pharmacology and explore the mechanisms of molluscicidal actions. Methods The traditional Chinese medicines with molluscicidal actions were screened based on retrospective literature reviews, and their molluscicidal efficiency was summarized. The active ingredients and potential targets of traditional Chinese medicines were captured from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Unified Protein Database and literature mining using network pharmacology. The drug-active ingredient-target network was created using the software Cytoscape 3.7.2, and the key targets were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis using the Metascape software. Results A total of 27 types of snail control drugs derived from traditional Chinese medicines were screened from publications and classified into 14 categories. Network pharmacology identified 190 active ingredients, and the active ingredients with a high degree in the drug-active ingredient-target network included quercetin, linoleyl acetate, luteolin, beta-carotene, (24S)-ethylcholesta-5,22,25-trans-3beta-ol, fumarine and arctiin, with 181 corresponding potential targets screened. KEGG pathway enrichment analysis revealed that these targets were mainly located in 16 pathways, including the neuroactive ligand-receptor interactions, regulation of adipocyte lipolysis and adrenergic signal in myocardial cells. Conclusions This study preliminarily demonstrates the multi-ingredient, multi-target and multi-pathway mechanisms of action of 27 molluscicides. The screened key ingredient may provide the basis for isolation, purification and pharmacological studies of molluscicides, and the screened key targets and key pathways may facilitate the illustration of mechanisms of actions of traditional Chinese medicine-derived molluscicides and development of novel green molluscicides.