Effects of Resveratrol on the Mechanisms of Antioxidants and Estrogen in Alzheimer’s Disease

Objective. To observe the effects of resveratrol (Res) on the antioxidative function and estrogen level in an Alzheimer’s disease (AD) mouse model. Methods. First, we examined the effects of Res on an AD mice model. SAMP8 mice were selected as the model, and normal-aging SAMR1 mice were used as the control group. The model mice were randomly divided into three groups: a model group, high-dose Res group (40mg/kg, intraperitoneal (ip)), and low-dose Res group (20mg/kg, ip). After receiving medication for 15 days, the mice were subjected to the water maze test to assess their spatial discrimination. The spectrophotometric method was used to detect the activity of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) as well as the malondialdehyde (MDA) content. Quantitative PCR (q-PCR) was used to detect SOD, GSH-Px, CAT, and heme oxygenase-1 (HO-1) mRNA level changes. Western blot analysis detected HO-1 and Nrf2 protein expression. Second, we researched the effect of Res on the estrogen level in the SAMP8 model mice. The model mice were randomly divided into four groups: a model group, estrogen replacement group (0.28 mg/kg, intramuscular (im), estradiol benzoate), high-dose Res group (5 mg/kg, im), and low-dose Res group (2.5 mg/kg, im). The mice were injected, once every three days, for 5 weeks. Q-PCR was used to detect brain tissue mRNA expression changes. Western blot analysis detected ERα, ERβ, and ChAT protein expression. An enzyme-linked immunosorbent assay (ELISA) kit was used to detect the expression of E2 and amyloid β protein (Aβ) in brain tissue. Results. Compared with the control treatment, Res could improve the spatial abilities of the mice to a certain extent and also increase the expression of SOD, GSH-Px, CAT, and HO-1 at the mRNA level (P<0.05). In addition, enhanced SOD, GSH-Px, and CAT activities and HO-1 protein levels and decreased MDA content (P<0.05) were detected in the brain tissue of the Res-treated mice. The cytoplasmic Nrf2 content in the Res-treated mice was also decreased while the nuclear Nrf2 content and the nuclear translation rate of Nrf2 were increased (P<0.05). Res could decrease the expression of ERβ in the brain tissue at the mRNA and protein levels and the expression of Aβ in the brain tissue at the protein level. Res could also increase the mRNA and protein expression of ERα and ChAT and the protein expression of estradiol in the brain tissue. Conclusion. Res can increase the antioxidant capacity of AD models through the Nrf2/HO-1 signaling pathway. In addition, Res can enhance estrogen levels in an AD model. These findings provide a new idea for the treatment of AD

Additional file 1 of Prevalence of S. aureus and/or MRSA in hospitalized patients with diabetic foot and establishment of LAMP methods for rapid detection of the SCCmec gene

Additional file 1: Supplement Table. LAMP primers used in this study

Application of back propagation neural network model optimized by particle swarm algorithm in predicting the risk of hypertension

Abstract The structure of a back propagation neural network was optimized by a particle swarm optimization (PSO) algorithm, and a back propagation neural network model based on a PSO algorithm was constructed. By comparison with a general back propagation neural network and logistic regression, the fitting performance and prediction performance of the PSO algorithm is discussed. Furthermore, based on the back propagation neural network optimized by the PSO algorithm, the risk factors related to hypertension were further explored through the mean influence value algorithm to construct a risk prediction model. In the evaluation of the fitting effect, the root mean square error and coefficient of determination of the back propagation neural network based on the PSO algorithm were 0.09 and 0.29, respectively. In the comparison of prediction performance, the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of the back propagation neural network based on PSO algorithm were 85.38%, 43.90%, 96.66%, and 0.86, respectively. The results showed that the backpropagation neural network optimized by PSO had the best fitting effect and prediction performance. Meanwhile, the mean impact value algorithm could screen out the risk factors related to hypertension and build a disease prediction model, which can provide clues for exploring the pathogenesis of hypertension and preventing hypertension

Role of remnant cholesterol in the relationship between physical activity and diabetes mellitus: an intermediary analysis

ObjectiveThe purpose of this investigation was to evaluate the potential link between physical activity (PA) and the heightened susceptibility to diabetes mellitus (DM), by examining whether remnant cholesterol (RC) might act as a mediator in this correlation.MethodsThe research utilized data from the National Health and Nutrition Examination Survey, spanning from 2005 to 2018. Various statistical analyses were conducted for continuous and categorical variables, including the t-test, ANOVA, and χ2 test. Logistic regression was employed to analyze the association between PA and DM across three distinct models. Mediation analysis was also conducted to assess the potential mediation effects of RC.ResultsThe study encompassed a total of 9,149 participants, and it was observed that individuals with DM exhibited lower levels of PA. Furthermore, PA levels were found to be associated with all participant characteristics except poverty income ratio, fasting blood glucose, and HOMA-IR (p &lt; 0.05). After adjusting for covariates (Model 3), individuals with high PA levels demonstrated a decreased likelihood of developing DM compared to those in the low PA group (OR: 0.73, 95%CI: 0.54–0.99). A significant dose–response relationship was identified (p &lt; 0.05). No interaction between PA and RC in relation to DM risk was detected, and RC was found to serve as a mediator in the connection between PA and DM. After considering covariates, the mediating effect of RC between PA and DM weakens.DiscussionOur findings suggest that higher levels of PA are linked to a reduced risk of DM in U.S. adults, with RC likely playing a mediating role

Table_1_Association between systemic immune-inflammatory index and diabetes mellitus: mediation analysis involving obesity indicators in the NHANES.DOCX

BackgroundInflammation and obesity have been widely recognized to play a key role in Diabetes mellitus (DM), and there exists a complex interplay between them. We aimed to clarify the relationship between inflammation and DM, as well as the mediating role of obesity in the relationship.MethodsBased on the National Health and Nutrition Examination Survey (NHANES) 2005–2018. Univariate analyses of continuous and categorical variables were performed using t-test, linear regression, and χ2 test, respectively. Logistic regression was used to analyze the relationship between Systemic Immune-Inflammatory Index (SII) or natural logarithm (Ln)-SII and DM in three different models. Mediation analysis was used to determine whether four obesity indicators, including body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI) and lipid accumulation product index (LAP), mediated the relationship between SII and DM.ResultsA total of 9,301 participants were included, and the levels of SII and obesity indicators (BMI, WC, LAP, and VAI) were higher in individuals with DM (p ConclusionOur findings suggest that increased SII levels were associated with a higher risk of DM, and BMI and WC played a critical mediating role in the relationship between SII and DM.</p