Omega-3 polyunsaturated fatty acids (PUFAs) can play important roles in maintaining mental health and resistance to stress, and omega-3 PUFAs supplementation can display beneficial effects on both the prevention and treatment of depressive disorders. Although the underlying mechanisms are still unclear, accumulated evidence indicates that omega-3 PUFAs can exhibit pleiotropic effects on the neural structure and function. Thus, they play fundamental roles in brain activities involved in the mood regulation. Since depressive symptoms have been assumed to be of central origin, this review aims to summarize the recently published studies to identify the potential neurobiological mechanisms underlying the anti-depressant effects of omega-3 PUFAs. These include that of (1) anti-neuroinflammatory; (2) hypothalamus-pituitary-adrenal (HPA) axis; (3) anti-oxidative stress; (4) anti-neurodegeneration; (5) neuroplasticity and synaptic plasticity; and (6) modulation of neurotransmitter systems. Despite many lines of evidence have hinted that these mechanisms may co-exist and work in concert to produce anti-depressive effects, the potentially multiple sites of action of omega-3 PUFAs need to be fully established. We also discussed the limitations of current studies and suggest future directions for preclinical and translational research in this field.

BACKGROUND Glycated albumin (GA), the non-enzymatic glycation product of albumin in plasma, became a glycemic marker in the beginning of the 21st century. The assay is not affected by hemoglobin levels and reflects the glycemic status over a shorter period as compared to HbA1c measurements. Thus, GA may contributes as an intermediate glucose index in the current diabetes mellitus (DM) diagnostic system. AIM To search and summarize the available data on glycated albumin measurements required for the diagnosis of diabetes mellitus. METHODS Databases, including PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL), among others, were systematically searched. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was applied for the assessment of quality, and the bivariate model was used to pool the sensitivity and specificity. The hierarchical summary receiver operator characteristic curves (HSROC) model was utilized to estimate the summary receiver operating characteristics curve (SROC). Sensitivity analysis was performed to investigate the association of the study design and patient characteristics with the test accuracy and meta-regression to find the source of heterogeneity. RESULTS Three studies regarding gestational diabetes mellitus (GDM) and a meta-analysis of 16 non-GDM studies, comprising a total sample size of 12876, were included in the work. Results reveal that the average cut-off values of GA reported for the diagnosis of GDM diagnosis was much lower than those for non-GDM. For non-GDM cases, diagnosing DM with a circulating GA cut-off of 14.0% had a sensitivity of 0.766 (95%CI: 0.539, 0.901), specificity of 0.687 (95%CI: 0.364, 0.894), and area under the curve of 0.80 (95%CI: 0.76, 0.83) for the SROC. The estimated SROC at different GA cut-off values for non-GDM exhibited that the average location parameter lambda of 16 non-GDM studies was 2.354 (95%CI: 2.002, 2.707), and the scale parameter beta was -0.163 (95%CI: -0.614, 0.288). These non-GDM studies with various thresholds had substantial heterogeneity, which may be attributed to the type of DM, age, and body mass index as possible sources. CONCLUSION Glycated albumin in non-DM exhibits a moderate diagnostic accuracy. Further research on the diagnostic accuracy of GA for GDM and combinational measurements of GA and other assays is suggested.

Objective Secretagogin, a Ca2+ binding protein, is one of the most abundant proteins in pancreatic β-cells and is critical for maintaining the structural integrity and signaling competence of β-cells. This study seeks to assess the concentrations of plasma secretagogin in participants with prediabetes (pre-DM) and newly diagnosed type 2 diabetes (T2DM) and to explore its relationship to parameters of glucose and lipid metabolism, first-phase insulin secretion, insulin resistance and pancreatic β-cell function. Materials and Methods A total of 126 eligible subjects were divided into three groups: a normal glucose tolerance (NGT, n=45), a pre-DM (n=30), and a T2DM (n=51) group. An intravenous glucose tolerance test (IVGTT) was performed, and clinical and biochemical parameters were measured for all subjects. Results Plasma secretagogin levels were significantly higher in both pre-DM and T2DM patients compared with NGT subjects and were highest in the T2DM group. Correlation analysis showed that plasma secretagogin levels were positively correlated with fasting plasma glucose, postchallenge plasma glucose (2hPG), HbA1c and body mass index (BMI) but were not correlated with waist-hip ratio, blood pressure, lipid profiles, fasting serum insulin, homeostasis model assessment for insulin resistance, homeostasis model assessment for β-cell function and first-phase insulin secretion indicators. Multiple logistic regression analysis revealed that 2hPG and BMI were independent predictors for elevation of plasma secretagogin concentrations. Conclusions Increased circulating secretagogin might be a molecular predictor for early diagnosis of diabetes. Further studies are needed to confirm this finding and explore the role of secretagogin in obesity.

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Background: Among patients with diabetes who had been hospitalized, 30% had twice or more hospitalisations rate, accounting for more than 50% of total hospitalizations and hospitalization expense. The purpose of our study was to to find available strategies to reduce the readmission rate of diabetics in rural areas.Methods: This retrospective single-center study used the data from Yongchuan Hospital of Chongqing Medical University. The t-test and the chi-square test or Fisher's exact test were used to compare continuous and categorical variables, respectively. We used the Spearman correlation coefficient to examine the relationship between variables. Multiple linear regression was performed to analyze the influencing factors of hospitalisation time, and dummy variables were set for categorical independent variables. Results: There were a total of 1721 readmissions during a five-year period; among them, 829 were females and 892 males. The readmission rate of diabetic patients in the endocrinology department was 32.40%. The age, times of hospitalisation, and duration of all subjects were 64.67 ± 13.82, 2.69 ± 1.41 and 10.60 ± 6.78, respectively. Among all the diabetic patients, type 2 diabetes accounted for 98.55% (n = 1696). Most of the patients were readmitted due to poor glycemic control, infection, edema, dizziness, and weakness, accounting for approximately 56%. During the 5-year period, the majority of readmitted diabetic patients were hospitalized twice. Times of hospitalisation was weakly positively correlated with age (Rho = 0.206, P≤0.001), diabetic duration (Rho = 0.248, P ≤ 0.001) and hospitalisation expenses (Rho = 0.008, P = 0.035) by Spearman correlation analysis. Age, duration of diabetes, systolic blood pressure (SBP), diastolic blood pressure (DBP) and alanine aminotransferase (ALT) were the main factors affecting times of hospitalisation in diabetes patients (all P < 0.05). Compared with current smokers, non-smokers and cessation smokers had high hospitalisations rate (all P for trend < 0.05). When taking diabetic foot infection as a reference, edema was more accountable than diabetic foot infection for hospitalisation times, which was statistically significant (P for trend = 0.048).Conclusion: Age, duration of diabetes and hospitalisation costs were positively correlated with times of hospitalisation. Age, duration of diabetes, blood pressure, ALT, smoking status and edema are the influencing factors of hospitalisation times. The most common causes of hospitalisation for diabetics are poor glycemic control, infection, edema, dizziness, and weakness. Controlling these factors may be key to developing rational health strategies for rural diabetics.