Diabetes is a chronic disease, and it could affect both health and quality of life (QOL). A lot of studies have reported some predictors of QOL of type 2 diabetes patients. While their results were not completely consistent. So the aim of our study was finding out the related factors (including characteristics related to the disease, life styles and mental health factors) of QOL of type 2 diabetes patients. We searched Cochrane library, EmBase, PubMed and CNKI databases for published studies that evaluated the related factors of QOL of type 2 diabetes patients by using a proper statistic method and had effect sizes (OR or β) and 95% confidence intervals from January 1st 2000 to May 31st 2016. Any study types were acceptable, and we excluded the reviews, letters, editorials and pooled analyses. The data were analyzed using STATA software (Version 12.0; Stata Corporation). Effect sizes and 95% confidence intervals were calculated to evaluate the relationship between these factors and QOL. Eighteen studies were included into our systematic review and meta-analysis, totaling 57,109 type 2 diabetes patients. Do more physical exercises (The pooled ORs ranged from 0.635 to 0.825 for different scales, less than 1.00), glucose check more frequently [pooled OR (95%CI): 0.175 (0.041, 0.756)] were associated with a better QOL. Presence of complications (The pooled ORs ranged from 1.462 to 3.038 for different scales, more than 1.00), presence of hypertension [pooled OR (95%CI): 1.389 (1.173, 1644)], longer duration of diabetes [pooled OR (95%CI): 1.865 (1.088, 3.197)], diet with more red meat [pooled OR (95%CI): 2.085 (1.063, 4.089)] and depression (The pooled ORs ranged from 3.003 to 11.473 for different scales, higher than 1.00) were associated with a worse QOL. The results of this study show that physical exercise, glucose check frequently, complications, hypertension, duration of diabetes, diet with more red meat, and depression were associated with the QOL of type 2 diabetes patients.

Background: Non-alcoholic fatty liver disease (NAFLD) has become a serious disease affecting people's health in the world. This article studies the causal relationship between NAFLD and serum uric acid (SUA) levels. Methods: During the 4 years of follow-up in a fixed cohort that was established in 2014, 2,832 follow-up subjects without NAFLD were finally included in this study. The study population was divided into four groups according to baseline SUA levels. Cox hazard regression model and Kaplan–Meier survival curves analysis were used to predict risk factors of NAFLD. The receiver operating characteristic curve analyses were used to determine SUA cutoffs for predicting NAFLD. Results: The cumulative prevalence rates of NAFLD were 33.97% (962/2,832), 38.93% (758/1,947) in males and 23.05% (204/885) in females. The results showed that males had a higher incidence of NAFLD (χ² = 68.412, P = 0.000). The Cox regression analysis disclosed that the hazard ratios of NAFLD [95% confidence interval (CI)] were 1.431 (95% CI, 1.123~1.823), 1.610 (95% CI, 1.262–2.054), and 1.666 (95% CI, 1.287–2.157) across the second to the fourth quartile of SUA adjusted for other confounders. The SUA cutoffs, sensitivity, specificity, and area under the curve (AUC) (95% CI) were ≥288.5 μmol/L, 75.5, 46.5%, 0.637(0.616–0.658), respectively, for total; ≥319.5 μmol/L, 65.8%, 48.4%, 0.590 (0.564–0.615), respectively, for males; and ≥287.5 μmol/L, 51.0%, 75.6%, 0.662 (0.619–0.704), respectively, for females. Kaplan–Meier survival curves revealed that individuals with higher SUA level had an increased risk of NAFLD in comparison to lower SUA level (P = 0.000). Conclusion: Serum uric acid is positively correlated with NAFLD, and elevated SUA level can be used as an independent predictor for NAFLD.

Since chronic hyperglycemia-related damage to small blood vessels results in complications, patients with longer durations of type 2 diabetes mellitus (T2DM) are more likely to develop microvascular complications, such as retinopathy, neuropathy and nephropathy, which are very harmful to the health of humans. Therefore, this study aimed to assess the prevalence of diabetes-related microvascular complications and to explore their risk factors in patients with T2DM in Tianjin, China. This observational, cross-sectional study was conducted at 8 hospitals in urban and suburban regions of Tianjin, China. The information collected from the subjects mainly included demographic characteristics, anthropometric measurements and clinical information. Univariate and multivariate logistic regression was used to identify the possible risk factors for microvascular complications (retinopathy, neuropathy and nephropathy). A total of 4,490 patients with T2DM from 8 hospitals in Tianjin, China were selected from November 2015 to January 2016. Of the study subjects, 2,270 (50.6%) were males. The median age was 64.0±13.0 years. The percentage of patients with T2DM who had at least one microvascular complication was 34.5%. The prevalence rates of neuropathy, retinopathy, and nephropathy were 23.5%, 17.4%, and 10.8%, respectively. The results of the multivariate logistic regression showed that the duration of diabetes, insulin use, and the presence of hypertension and dyslipidemia were the main risk factors for developing microvascular complications of T2DM. The incidence of diabetes complications in Tianjin is high. Increasing the control of risk factors can reduce the occurrence of complications to reduce the disease burden and improve the quality of life of patients.

P-glycoprotein (P-gp) is a major factor in multidrug resistance (MDR) which is a serious obstacle in chemotherapy. P-gp has also been implicated in causing apoptosis of tumor cells, which was shown to be another important mechanism of MDR recently. To study the influence of P-gp in tumor cell apoptosis, K562/A cells (P-gp+) and K562/S cells (P-gp−) were subjected to doxorubicin (Dox), serum withdrawal, or independent co-incubation with multiple P-gp inhibitors, including valspodar (PSC833), verapamil (Ver) and H108 to induce apoptosis. Apoptosis was simultaneously detected by apoptotic rate, cell cycle by flow cytometry and cysteine aspartic acid-specific protease 3 (caspase 3) activity by immunoassay. Cytotoxicity and apoptosis induced by PSC833 were evaluated through an MTT method and apoptosis rate, and cell cycle combined with caspase 3 activity, respectively. The results show that K562/A cells are more resistant to apoptosis and cell cycle arrest than K562/S cells after treatment with Dox or serum deprivation. The apoptosis of K562/A cells increased after co-incubation with each of the inhibitors of P-gp. P-gp inhibitors also enhanced cell cycle arrest in K562/A cell. PSC833 most strikingly decreased viability and led to apoptosis and S phase arrest of cell cycle in K562/A cells. Our study demonstrates that P-gp inhibits the apoptosis of tumor cells in addition to participating in the efflux of intracellular chemotherapy drugs. The results of the caspase 3 activity assay also suggest that the role of P-gp in apoptosis avoidance is caspase-related.

Background: Blood glucose control is closely related to type 2 diabetes mellitus (T2DM) prognosis. This multicenter study aimed to investigate blood glucose control among patients with insulin-treated T2DM in North China and explore the application value of combining an elastic network (EN) with a machine-learning algorithm to predict glycemic control.Methods: Basic information, biochemical indices, and diabetes-related data were collected via questionnaire from 2787 consecutive participants recruited from 27 centers in six cities between January 2016 and December 2017. An EN regression was used to address variable collinearity. Then, three common machine learning algorithms (random forest [RF], support vector machine [SVM], and back propagation artificial neural network [BP-ANN]) were used to simulate and predict blood glucose status. Additionally, a stepwise logistic regression was performed to compare the machine learning models.Results: The well-controlled blood glucose rate was 45.82% in North China. The multivariable analysis found that hypertension history, atherosclerotic cardiovascular disease history, exercise, and total cholesterol were protective factors in glycosylated hemoglobin (HbA1c) control, while central adiposity, family history, T2DM duration, complications, insulin dose, blood pressure, and hypertension were risk factors for elevated HbA1c. Before the dimensional reduction in the EN, the areas under the curve of RF, SVM, and BP were 0.73, 0.61, and 0.70, respectively, while these figures increased to 0.75, 0.72, and 0.72, respectively, after dimensional reduction. Moreover, the EN and machine learning models had higher sensitivity and accuracy than the logistic regression models (the sensitivity and accuracy of logistic were 0.52 and 0.56; RF: 0.79, 0.70; SVM: 0.84, 0.73; BP-ANN: 0.78, 0.73, respectively).Conclusions: More than half of T2DM patients in North China had poor glycemic control and were at a higher risk of developing diabetic complications. The EN and machine learning algorithms are alternative choices, in addition to the traditional logistic model, for building predictive models of blood glucose control in patients with T2DM.