This study aimed to evaluate the role of the triglyceride (triacylglycerol) glucose (TyG) index in predicting and mediating the development of cardiovascular disease (CVD). This cohort study included 6078 participants aged over 60 years who participated in a routine health check-up programme from 2011 to 2017. The competing risk model, cox regression model and multimediator analyses were performed. TyG was calculated as ln [fasting triglyceride (mg/dl) × fasting plasma glucose (mg/dl)/2]. During a median 6 years of follow-up, 705 (21.01/1000 person-years) CVD events occurred. In fully adjusted analyses, quartiles 3 and 4 versus quartile 1 of TyG index (adjusted subhazard ratios [SHRs] 1.33 [95% CI: 1.05–1.68] and 1.72 [1.37–2.16]) were associated with an increased risk of CVD events. The continuous time-dependent TyG remained significant in predicting CVD events (adjusted hazard ratios [HR] 1.43 [1.24–1.63]). The adverse estimated effects of body mass index (BMI) or resting heart rate (RHR) on CVD mediated through the joint effect of the baseline and follow-up TyG index. In addition, an effect mediated only through the follow-up TyG existed ( P < 0.05). Thus, it is necessary to routinely measure the TyG. The TyG index might be useful for predicting CVD events in clinical practice.

Background Previous studies have evaluated the association of multimorbidity with higher mortality, but epidemiologic data on the association between the disease clusters and all-cause mortality risk are rare. We aimed to examine the relationship between multimorbidity (number/ cluster) and all-cause mortality in Chinese older adults. Methods We conducted a population-based study of 50,100 Chinese participants. Multiple logistic regression analysis was used to estimate the impact of long-term conditions (LTCs) on all-cause mortality. Results The prevalence of multimorbidity was 31.35% and all-cause mortality was 8.01% (50,100 participants). In adjusted models, the odds ratios (ORs) and 95% confidence intervals (CIs) of all-cause mortality risk for those with 1, 2, and ≥ 3 LTCs compared with those with no LTCs was 1.45 (1.32–1.59), 1.72 (1.55–1.90), and 2.15 (1.85–2.50), respectively (Ptrend < 0.001). In the LTCs ≥2 category, the cluster of chronic diseases that included hypertension, diabetes, CHD, COPD, and stroke had the greatest impact on mortality. In the stratified model by age and sex, absolute all-cause mortality was higher among the ≥75 age group with an increasing number of LTCs. However, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those < 75 years. Conclusions The risk of all-cause mortality is increased with the number of multimorbidity among Chinese older adults, particularly disease clusters.

Asthma is a chronic inflammatory disease of the airways that involves multiple cells, including inflammatory cells, structural cells, and cellular components. Glucocorticoids and beta-receptor agonists are still the first choices for asthma treatment. However, the asthma symptoms may still be poorly controlled in some patients after an optimal treatment. Mesenchymal stem cells (MSCs) are characterized by the potential for multi-directional differentiation and can exert immunomodulatory and anti-inflammatory effects. Its role in treating asthma has increasingly been recognized in recent years. In this review article, we sought to summarize the recent advances in the therapeutic effects of MSCs on several types of asthma and explain the relevant mechanisms. Articles on asthma treatment with MSCs as of January 2020 were searched in PubMed, Google Scholar, and Web of Science databases. It was found that MSCs have therapeutic effects on allergic asthma, non-allergic asthma and occupational asthma; gene-modified or pretreated MSCs improves the therapeutic effects of MSCs in asthma; MSC-derived conditioned medium or extracellular vesicles possess the considerable curative effect as MSC on asthma; and MSCs exert their therapeutic effects on asthma by restoring Th1/Th2 balance, reversing Th17/Tregs imbalance, inhibiting DC maturation, and promoting the switch of M1 to M2 and repairing epithelial injury. Thus, MSCs may be a promising treatment for asthma.

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Background: The tumor microenvironment (TME) and immune checkpoint inhibitors have been shown to promote active immune responses through different mechanisms. We attempted to identify the important prognostic genes and prognostic characteristics related to TME in prostate cancer (PCa). Methods: The gene transcriptome profiles and clinical information of PCa patients were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated by the ESTIMATE algorithm. We evaluated the prognostic value of the risk score (RS) model based on univariate Cox analysis and least absolute shrinkage and selection operation (LASSO) Cox regression analysis and established a nomogram to predict disease-free survival (DFS) in PCa patients. The GSE70768 dataset was utilized for external validation. Twenty-two subsets of tumor-infiltrating immune cells were analyzed using the CIBERSORT algorithm. Results: In this study, the patients with higher immune/stromal scores were associated with a worse DFS, higher Gleason score, and higher pathological T stage. Based on the immune and stromal scores, 515 differentially expressed genes (DEGs) were identified. The univariate Cox and LASSO Cox regression models were employed to select 18 DEGs from 515 DEGs and construct an RS model. The DFS of the high-RS group was significantly lower than that of the low-RS group (P<0.001). The AUCs for the 1-year, 3-year and 5-year DFS rates in the RS model were 0.890, 0.877 and 0.841, respectively. A nomogram of DFS was established based on the RS and Gleason score, and the AUCs for the 1-year, 3-year and 5-year DFS rates in the nomogram were 0.907, 0.893, and 0.872, respectively. These results were further validated in the GSE70768 dataset. In addition, the proportion of Tregs was determined to be higher in high-RS patients (P<0.05), and the expression levels of five immune checkpoints (CTLA-4, PD-1, LAG-3, TIM-3 and TIGIT) were observed to be higher in high-RS patients (P<0.05). Conclusions: Our study established and validated an 18-gene prognostic signature model associated with TME, which might serve as a prognosis stratification tool to predict DFS in PCa patients after radical prostatectomy.