Clinical efficacy of low-dose aspirin combined with calcium in preventing preeclampsia: A systematic review and meta-analysis.

OBJECTIVE: This systematic review and meta-analysis aimed to evaluate the clinical effectiveness of low-dose aspirin combined with calcium supplements for the prevention of preeclampsia. METHODS: China National Knowledge Infrastructure, VIP, Wanfang, PubMed, EMBASE, and Cochrane Library databases were searched from inception until December 2022. Randomized controlled trials investigating the preventive use of aspirin in combination with calcium supplementation for preeclampsia in high-risk pregnant women were included. The quality of the literature was evaluated, and a meta-analysis was conducted using RevMan 5.3 software to analyze the clinical efficacy of low-dose aspirin combined with calcium supplementation in preventing preeclampsia. RESULTS: Seven randomized controlled trials were included in this meta-analysis, and compared with the control group, the experimental group had lower incidence rates of preeclampsia with gestational hypertension (odds ratios [OR]: 0.17, 95% confidence interval [CI]: 0.11-0.28), preeclampsia (OR: 0.20, 95% CI: 0.10-0.37), gestational hypertension (OR: 0.15, 95% CI: 0.07-0.31), preterm birth (OR: 0.26, 95% CI: 0.16-0.44), postpartum hemorrhage (OR: 0.15, 95% CI: 0.08-0.27), and fetal growth restriction (OR: 0.16, 95% CI: 0.08-0.33). CONCLUSION: Compared with aspirin alone, low-dose aspirin combined with calcium supplementation was more effective in preventing preeclampsia, reduced the risk of preterm birth and postpartum hemorrhage, and promoted fetal growth. This intervention has clinical value and should be considered for high-risk pregnant women.

Exploring the active components and potential mechanisms of Rosa roxburghii Tratt in treating type 2 diabetes mellitus based on UPLC-Q-exactive Orbitrap/MS and network pharmacology.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a global disease with growing prevalence that is difficult to cure. Rosa roxburghii Tratt is an edible and medicinal plant, and modern pharmacological studies have shown that it has potential anti-diabetic activity. This is the first study to explore the active components and potential mechanisms of Rosa roxburghii Tratt fruit for treating T2DM based on UPLC-Q-Exactive Orbitrap/MS and network pharmacology. METHODS: The active components of Rosa roxburghii Tratt fruit were obtained from UPLC-Q-Exactive Orbitrap/MS analysis and retrieval in the SciFinder, PubMed, Web of Science, and CNKI databases. The potential targets of the active components were obtained from the SwissTargetPrediction and PharmMapper databases. The disease targets for T2DM were obtained from GeneCards, OMIM, TTD, DisGENent, and GEO databases. The intersection of the two datasets was used to obtain the potential targets of Rosa roxburghii Tratt fruit against T2DM. The target protein interaction network was constructed using the String database and Cytoscape software. The R software ClusterProfiler package was used for target enrichment analysis and the Cytoscape CytoNCA plug-in was used to screen core targets. Molecular docking and result visualization were performed using PyMOL and Autodock Vina software. RESULTS: We obtained 20 bioactive ingredients, including alphitolic acid, quercetin, and ellagic acid, as well as 13 core targets, such as AKT1, TNF, SRC, and VEGFA. All bioactive ingredients in Rosa roxburghii Tratt fruit were active against T2DM-related therapeutic targets. Rosa roxburghii Tratt fruit may play a therapeutic role in T2DM by regulating the PI3K/AKT, RAS, AGE-RAGE, and other signaling pathways. CONCLUSIONS: This study explored the active components and potential mechanisms of Rosa roxburghii Tratt fruit in the treatment of T2DM, laying the foundation for a further experimental study based on pharmacodynamic substances and their mechanisms of action.

The safety of Chinese medicine: A systematic review of endogenous substances and exogenous residues.

BACKGROUND: Safety and toxicity have become major challenges in the internationalization of Chinese medicine. Inspite of its wide application, security problems of Chinese medicine still occur from time to time, raising widespread concerns about its safety. Most of the studies either only partially discussed the intrinsic toxicities or extrinsic harmful residues in Chinese medicine, or briefly described detoxification and attenuation methods. It is necessary to systematically discuss Chinese medicine's extrinsic and intrinsic toxic components and corresponding toxicity detoxification or detection methods as a whole. PURPOSE: This review comprehensively summarizes various toxic components in Chinese medicine from intrinsic and extrinsic. Then the corresponding methods for detoxification or detection of toxicity are highlighted. It is expected to provide a reference for safeguards for developing and using Chinese medicine. METHODS: A literature search was conducted in the databases, including PubMed, Web of Science,Wan-fang database, and the China National Knowledge Infrastructure (CNKI). Keywords used were safety, toxicity, intrinsic toxicities, extrinsic harmful residues, alkaloids, terpene and macrolides, saponins, toxic proteins, toxic crystals, minerals, heavy metals, pesticides, mycotoxins, sulfur dioxide, detoxification, detection, processing (Paozhi), compatibility (Peiwu), Chinese medicine, etc., and combinations of these keywords. All selected articles were from 2006 to 2022, and each was assessed critically for our exclusion criteria. Studies describe the classification of toxic components of Chinese medicine, the toxic effects and mechanisms of Chinese medicine, and the corresponding methods for detoxification or detection of toxicity. RESULTS: The toxic components of Chinese medicines can be classified as intrinsic toxicities and extrinsic harmful residues. Firstly, we summarized the intrinsic toxicities of Chinese medicine, the adverse effects and toxicity mechanisms caused by these components. Next, we focused on the detoxification or attenuation methods for intrinsic toxicities of Chinese medicine. The other main part discussed the latest progress in analytical strategies for exogenous hazardous substances, including heavy metals, pesticides, and mycotoxins. Beyond reviewing mainstream instrumental methods, we also introduced the emerging biochip, biosensor and immuno-based techniques. CONCLUSION: In this review, we provide an overall assessment of the recent progress in endogenous toxins and exogenous hazardous substances concerning Chinese medicine, which is expected to render deeper insights into the safety of Chinese medicine.

Clinical Application of a Multiparameter-Based Nomogram Model in Predicting Preeclampsia.

Based on single-center data, the related predictive factors of preeclampsia (PE) were investigated, and a nomogram prediction model was established and validated. A retrospective collection of 93 PE patients admitted to our hospital from January 2019 to January 2021 were included in the PE group. In addition, non-PE pregnant women were selected for physical examination during the same period for matching, and 170 normal pregnant women who met the matching conditions were found as the normal pregnancy group. Clinical data of the selected candidates were collected. The risk factors of PE were screened by logistic regression analysis, and the lipopograph prediction model was constructed and verified. Logistic analysis results showed that age (OR = 3.069, 95% CI = 1.233-7.638), prepregnancy BMI (OR = 2.896, 95% CI = 1.193-7.029), vitamin E deficiency (OR = 2.803, 95% CI = 1.134-6.928), 25-(OH)D (OR = 0.944, 95% CI = 0.903∼9.988), PLGF (OR = 0.887, 95% CI = 0.851∼0.924), PAPP-A (OR = 1.240, 95% CI = 1.131∼1.360), and PI (OR = 6.376, 95% CI = 1.163∼34.967) were the independent risk factors for PE prediction (P < 0.05). The ROC curve showed that the AUC of the model for predicting the risk of PE was 0.957 (95% CI: 0.935-0.979), and the specificity and sensitivity were 0.912 and 0.892, respectively. H-L goodness of the fit test showed that there was no statistical significance in the deviation between the actual observed value and the predicted value of the risk in the line graph model (χ 2 = 7.001, P=0.536). The bootstrap test was used for internal verification, and the original data were repeatedly sampled 1000 times. The average absolute error of the calibration curve is 0.014, and the fitting degree between the calibration curve and the ideal curve is good. Age, prepregnancy BMI, lack of vitamin E, 25-(OH)D, PLGF, PAPP-A, and PI are independent risk factors for predicting PE. The establishment of a nomogram prediction model based on the above parameters can help identify PE high-risk groups in the early clinical stage and provide a reference for individualized clinical diagnosis and treatment.

[Studies on tea plants (Camellia sinensis) germplasms using EST-SSR marker].

Forty two tea varieties were analyzed by using 16 SSR primer sets derived from tea ESTs in this study, and 13 of the primer sets produced clear bands and 10 of them showed polymorphism, accounting for 76.9%. The PIC (polymorphism information content) for each polymorphic primer set varied from 0.522 to 0.866, with a average about 0.73. Totally 84 Genotypes and 74 alleles were detected in all materials by 10 polymorphic markers, with the range from 4 to 12 and from 3 to 10 for each polymorphic primer set, respectively. The genetic distance among 42 tea varieties varied from 0.074 to 0.667, averagely 0.363, suggesting that the materials used in the experiment possess a broad genetic variation. Based on the similarity coefficient about 0.55, all the tea varieties tested could be classified into 3 groups and most of them were in first group. The results of this study proved that the EST-SSR marker is very effective in evaluation of tea germplasms.