MicroRNAs (miRNAs) are important post-transcriptional regulators during adipocyte adipogenesis. MiR-206-3p, a tissue-specific miRNA, is absent in white adipocytes. In this study, we examined the roles of mmu-miR-206-3p in the adipogenic differentiation of 3T3-L1 preadipocytes. The miR-206-3p expression has shown an apparent decreasing trend after induction, and sustained low expression throughout the differentiation of 3T3-L1 cells. miR-206-3p blocked the adipogenic differentiation of 3T3-L1 cells by attenuating c-Met expression; the inhibition effect of miR-206 to the adipogenic differentiation can be counteracted by restoring c-Met expression. In addition, miR-206-3p decreased the phosphorylation of Akt, which is the downstream effector of c-Met in the PI3K/Akt signaling pathway. These data indicate that miR-206-3p inhibits adipocyte adipogenesis through silencing c-Met and subsequently inactivating the PI3K/Akt signaling pathway.

Folic acid (FA) is an antioxidant that can reduce reactive oxygen species generation and can blunt cardiac dysfunction during ischemia. We hypothesized that FA supplementation prevents cardiac fibrosis and cardiac dysfunction induced by obesity. Six-week-old C57BL6/J mice were fed a high-fat diet (HFD), normal diet (ND), or an HFD supplemented with folic acid (FAD) for 14 weeks. Cardiac function was measured using a transthoracic echocardiographic exam. Phenotypic analysis included measurements of body and heart weight, blood glucose and tissue homocysteine (Hcy) content, and heart oxidative stress status. HFD consumption elevated fasting blood glucose levels and caused obesity and heart enlargement. FA supplementation in HFD-fed mice resulted in reduced fasting blood glucose, heart weight, and heart tissue Hcy content. We also observed a significant cardiac systolic dysfunction when mice were subjected to HFD feeding as indicated by a reduction in the left ventricular ejection fraction and fractional shortening. However, FAD treatment improved cardiac function. FA supplementation protected against cardiac fibrosis induced by HFD. In addition, HFD increased malondialdehyde concentration of the heart tissue and reduced the levels of antioxidant enzyme, glutathione, and catalase. HFD consumption induced myocardial oxidant stress with amelioration by FA treatment. FA supplementation significantly lowers blood glucose levels and heart tissue Hcy content and reverses cardiac dysfunction induced by HFD in mice. These functional improvements of the heart may be mediated by the alleviation of oxidative stress and myocardial fibrosis.

Background: Serum uric acid (SUA) is associated with many cardiovascular risk factors, such as metabolic syndrome (MetS) and subclinical atherosclerosis. However, the relationship of SUA with carotid atherosclerosis remains controversial. We aimed to investigate whether elevated SUA levels are associated with a high risk of carotid atherosclerosis and MetS in patients with type 2 diabetes mellitus (T2DM).Methods: This cross-sectional study was performed with a sample of 1,947 hospitalized patients with T2DM. Carotid intima-media thickness and carotid artery plaques were measured via Doppler ultrasound.Results: Uric acid levels were negatively associated with HbA1C, eGFR, and HDL-C (all P < 0.001) and positively associated with WBC, BMI, ACR, creatinine, total cholesterol, triglycerides, LDL-C, systolic blood pressure, and diastolic blood pressure (all P < 0.001). After adjusting for multiple potential confounders, the risks were substantially higher for MetS in the highest quartile of SUA levels (odds ratio: 2.91, 95% confidence interval: 1.54–5.51, P = 0.003 for trend) than in the lowest quartile of SUA levels. Furthermore, a significant increase was observed in the prevalence of overweight/obesity, hypertension, and dyslipidemia across the SUA quartiles independent of confounders. However, no significant association was found between SUA quartile with the presence of carotid atherosclerosis.Conclusions: In patients with T2DM, SUA levels were closely associated with MetS and its components but not with carotid atherosclerosis.

Mortality of dermatomyositis patients positive with anti-melanoma differentiation-related gene 5 antibody (anti-MDA5-DM) is alarming, especially during the first several months. Infection is an important cause of early death. As there are no reports regarding the effect of prophylactic use of the compound sulfamethoxazole (SMZ Co) on anti-MDA5-DM patients, we conducted this study to evaluate the efficacy of SMZ Co in reducing the incidence of pneumocystis jirovecii pneumonia (PJP). Consecutive patients with newly onset anti-MDA5-DM from June 2018 to October 2021 in our center were retrospectively reviewed for over 12 months. They were divided into two groups: SMZ Co and non-SMZ Co groups based on the initial use of prophylactic SMZ Co. Mortality and incidence of severe infection within 12 months were compared between two groups. . Compared with the non-SMZ Co group (n = 93), the SMZ Co group (n = 121) had lower mortality (18.8% vs 51.1%; p＜ 0.001), and lower incidence of PJP (6.8% vs 15.2%; p= 0.040) and fatal infection (16.1% vs 3.3%; p= 0.001) during the first 12 months from diagnosis. After adjusting for age, gender, disease duration, peripheral blood lymphocyte count, anti-MDA5-Ab titers, GGO scores, and treatments, an inverse association was revealed between the prophylactic use of SMZ Co and incidence of PJP (adjusted OR : 0.299; 95% CI, 0.102–0.878, p= 0.028). Prophylactic use of SMZ Co is an effective and safe way to improve the prognosis of anti-MDA5-DM patients by preventing the incidence of PJP.

Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to develop a machine learning model that can accurately predict diabetic macroangiopathy in Chinese patients. A retrospective cross-sectional analytical study was conducted on 1566 hospitalized patients with T2DM. Feature selection was performed using recursive feature elimination (RFE) within the mlr3 framework. Model performance was benchmarked using 29 machine learning (ML) models, with the ranger model selected for its superior performance. Hyperparameters were optimized through grid search and 5-fold cross-validation. Model interpretability was enhanced using SHAP values and PDPs. An external validation set of 106 patients was used to test the model. Key predictive variables identified included the duration of T2DM, age, fibrinogen, and serum urea nitrogen. The predictive model for macroangiopathy was established and showed good discrimination performance with an accuracy of 0.716 and an AUC of 0.777 in the training set. Validation on the external dataset confirmed its robustness with an AUC of 0.745. This study establish an approach based on machine learning algorithm in features selection and the development of prediction tools for diabetic macroangiopathy.