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Correlation Analysis and Intervention Study on Disturbance of Lipid Metabolism and Diabetic Peripheral Neuropathy.
Wang, W, Li, X, Ren, Y
Computational and mathematical methods in medicine. 2022;:2579692
Abstract
OBJECTIVE To explore the significance and clinical value of dynamic monitoring of lipid metabolism indexes in patients with diabetic peridiabetic lesions. METHODS A total of 192 patients with type 2 diabetes (T2DM) treated in our hospital from October 2019 to July 2021 were divided into two groups according to whether they were complicated with peripheral neuropathy (DPN). The patients in the observation group were randomly assigned into group A (n = 45) and group B (n = 45) according to the method of random number table. The patients were assigned into control group (n = 102) and observation group (n = 90), and the patients in the observation group were randomly divided into two groups (n = 45). All the patients in the three groups were given routine hypoglycemic treatment, and group B was observed to dynamically monitor the indexes of lipid metabolism and regulate blood lipids on the basis of routine hypoglycemic treatment. The indexes of lipid metabolism, including total cholesterol (TC), triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C)/low-density lipoprotein cholesterol (LDL-C), were detected before treatment. The receiver operating curve (ROC) was applied to elucidate the efficacy of TC, TG, and HDL-C and LDL-C in predicting peripheral neuropathy (DPN) in patients with T2DM. The indexes of lipid metabolism and neurological function of patients were determined after the treatment. The difference was considered to be statistically significant (P < 0.05). RESULTS In contrast to the control, the serum levels of TG, TC, and LDL-C in the observation group were significantly higher, with HDL-C significantly lower. ROC curve analysis indicated that the area under the curve (AUC) of serum TG level to predict peripheral neuropathy in patients with T2DM was 0.753 (95% CI = 0.604 - 0.901, P = 0.007). When the Youden index reached the maximum (0.677), with corresponding sensitivity and specificity 77.18% and 82.58%, respectively, and the critical value was 2.31 mmol/L, the AUC of serum TC level for predicting peripheral neuropathy in patients with T2DM was 0.851 (95% CI = 0.735 ~ 0.967P < 0.001); when the Youden index reaches its maximum (0.750), with the sensitivity and specificity 84.44% and 92.06%, respectively, and the critical value is 4.52 mmol/L, the AUC of predicting peripheral neuropathy in patients with T2DM by serum LDL-C level was 0.799 (95% CI = 0.52 ~ 0.946, P = 0.001); when the Youden index reaches its maximum (0.706), with sensitivity and specificity 80.58% and 87.24%, respectively, and the critical value is 3.36 mmol/L, the AUC of serum HDL-C level for predicting DPN in patients with T2DM was 0.727 (95% CI = 0.568 ~ 0.886P = 0.014). When the Youden index reached the maximum (0.640), the sensitivity and specificity were 74.56% and 83.25%, respectively, the critical value is 1.51 mmol/L. The AUC in predicting DPN in patients with T2DM was 0.919 (95% CI = 0.839 ~ 0.978P < 0.001); when the Jordan index reached the maximum (0.786), the sensitivity and specificity were 91.75% and 95.82%, respectively. Compared with group A, the levels of serum TG, TC, and LDL-C in group B decreased significantly, while the level of HDL-C increased (P < 0.05). The motor nerve conduction velocity and sensory nerve conduction velocity of median nerve and peroneal nerve in group B were higher than those in group A (P < 0.05). CONCLUSION Diabetic patients with severe lipid metabolic disorders have a higher risk of DPN. Combined detection of lipid metabolism indexes such as TC, TG, and HDL-C and LDL-C is effective in predicting diabetic patients with DPN. In clinic, through dynamic monitoring of lipid metabolism indexes, we can actively regulate the level of blood lipids in patients with T2DM, which can delay the occurrence and development of DPN to a certain extent, as well as improving the prognosis of patients with diabetes.
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Discussion on Protein Metabolism and Requirement of Aerobics Athletes during Training Based on Multisensor Data Fusion.
Gong, H, Chen, S, Yu, S, Liu, D, Li, X, Shan, Z, Kong, F, Yan, Z, Han, F
Journal of healthcare engineering. 2022;:6169150
Abstract
Competitive aerobics has emerged as a highly competitive sport beyond its own physical limit. Modern competitive aerobics competition is very fierce; athletes cannot only rely on a specific competitive skill to achieve good results. Protein is the physical basis of life activity. The life activity of human body is closely related to protein, and protein is closely related to human exercise ability. This article aims to study protein metabolism and demand of aerobics athletes during training based on multisensor data fusion. A total of 26 female aerobics athletes were randomly divided into two groups: exercise group and exercise + nutrition group. According to the characteristics of human motion, a comprehensive measurement acquisition sensor system for collecting human motion information is designed and implemented, and the system is used to monitor the subject's protein condition in real time. The subjects took protein nutrient solution before breakfast every day. The dynamic recognition algorithm designed in this paper also has shortcomings, and the monitoring protein method based on gait and other signs is not completely correct. The experiment lasted for 7 weeks. The results showed that the level of serum transferrin receptor decreased significantly in the quiet + nutrition group for 4 weeks, which was significantly different from that at 0 and 3 weeks in the same group (P < 0.01) and was significantly different from that in the same group at 7 weeks (P < 0.05). In the exercise group, the level of serum transferrin receptor increased significantly at 5 weeks, compared with the same group at 0 and 3 weeks (P < 0.05).
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Two Myricetin-Derived Flavonols from Morella rubra Leaves as Potent α-Glucosidase Inhibitors and Structure-Activity Relationship Study by Computational Chemistry.
Liu, Y, Wang, R, Ren, C, Pan, Y, Li, J, Zhao, X, Xu, C, Chen, K, Li, X, Gao, Z
Oxidative medicine and cellular longevity. 2022;:9012943
Abstract
Diabetes mellitus (DM) is a chronic disease characterized by hyperglycemia, and oxidative stress is an important cause and therapeutic target of DM. Phytochemicals such as flavonols are important natural antioxidants that can be used for prevention and treatment of DM. In the present study, six flavonols were precisely prepared and structurally elucidated from Morella rubra leaves, which were screened based on antioxidant assays and α-glucosidase inhibitory activities of different plant tissues. Myricetin-3-O-(2″-O-galloyl)-α-L-rhamnoside (2) and myricetin-3-O-(4″-O-galloyl)-α-L-rhamnoside (3) showed excellent α-glucosidase inhibitory effects with IC50 values of 1.32 and 1.77 μM, respectively, which were hundredfold higher than those of positive control acarbose. Molecular docking simulation illustrated that the presence of galloyl group altered the binding orientation of flavonols, where it occupied the opening of the cavity pocket of α-glucosidase along with Pi-anion interaction with Glu304 and Pi-Pi stacked with His279. Pi-conjugations generated between galloyl moiety and key residues at the active site of α-glucosidase reinforced the flavonol-enzyme binding, which might explain the greatly increased activity of compounds 2 and 3. In addition, 26 flavonols were evaluated for systematic analysis of structure-activity relationship (SAR) between flavonols and α-glucosidase inhibitory activity. By using their pIC50 (-log IC50) values, three-dimensional quantitative SAR (3D-QSAR) models were developed via comparative molecular field analysis (CoMFA) and comparative similarity index analysis (CoMSIA), both of which were validated to possess high accuracy and predictive power as indicated by the reasonable cross-validated coefficient (q 2) and non-cross-validated coefficient (r 2) values. Through analyzing 3D contour maps of both CoMFA and CoMSIA models, QSAR results were in agreement with in vitro experimental data. Therefore, such results showed that the galloyl group in compounds 2 and 3 is crucial for interacting with key residues of α-glucosidase and the established 3D-QSAR models could provide valuable information for the prediction of flavonols with great antidiabetic potential.
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Association between Rosacea and Cardiovascular Diseases and Related Risk Factors: A Systematic Review and Meta-Analysis.
Li, Y, Guo, L, Hao, D, Li, X, Wang, Y, Jiang, X
BioMed research international. 2020;:7015249
Abstract
BACKGROUND Rosacea is a common inflammatory skin disorder. Several studies, but not all, have suggested a high prevalence of cardiovascular diseases (CVDs) in rosacea patients. This study is aimed at investigating the association between rosacea and CVDs and related risk factors. METHODS We performed a literature search through PubMed, Embase, and Web of Science databases, from their respective inception to December 21, 2019. Two reviewers independently screened the articles, extracted data, and performed analysis, following the PRISMA guidelines. Odds ratios (OR) or standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for outcomes. The included studies' quality was evaluated using the Newcastle Ottawa Scale (NOS). RESULTS The final meta-analysis included ten studies. The pooled analysis found no association between rosacea prevalence and the incidence of CVDs (OR 0.97; 95% CI 0.86-1.10). Rosacea was found to be significantly associated with several risk factors for CVDs (OR 1.17; 95% CI 1.05-1.31), including hypertension (OR 1.17; 95% CI 1.02-1.35), dyslipidemia (OR 1.34; 95% CI 1.00-1.79), and metabolic syndrome (OR 1.72; 95% CI 1.09-2.72). However, no association was found between rosacea and diabetes mellitus (OR 0.98; 95% CI 0.82-1.16). Among the biological parameters, a significant association was found between rosacea and total cholesterol (SMD = 0.40; 95% CI = -0.00, 0.81; p < 0.05), low-density lipoprotein cholesterol (SMD = 0.28; 95% CI = 0.01, 0.56; p < 0.05), and C-reactive protein (CRP) (SMD = 0.25; 95% CI = 0.10, 0.41; p < 0.05). We found no association between rosacea and high-density lipoprotein cholesterol (SMD = 0.00; 95% CI = -0.18, 0.18; p = 0.968) or triglycerides (SMD = 0.10; 95% CI = -0.04, 0.24; p = 0.171). CONCLUSIONS Although no significant association was found between rosacea and CVDs, rosacea was found to be associated with several of related risk factors. Patients with rosacea should pay more attention to identifiable CVD risk factors, especially those related to inflammatory and metabolic disorders.