BACKGROUND Diabetes significantly heightens risks of COVID-19 infection, and vaccine hesitancy remains high due to safety concerns. MATERIAL AND METHODS This study assessed the effects of inactivated COVID-19 vaccine in 548 diabetic patients from Tianjin, China, categorized by vaccination status: unvaccinated (n=94), primary immunization (n=117), and booster immunization (n=337). A total of 22 clinical values were assessed prior to vaccination, 3 months after vaccination, and 12 months after vaccination. Variables with a normal distribution were compared across groups using one-way ANOVA, while non-normally distributed variables were compared using the Kruskal-Wallis test and chi-square tests for categorical data. Linear mixed-effects models were used to evaluate the effects of time and vaccine type on these clinical values, with random intercepts to account for within-subject variability and interaction terms for detailed group comparisons over time. RESULTS Baseline results showed no major differences across groups, including fasting glucose, HbA1c, granulocytes, hemoglobin, platelets, renal function markers such as uric acid, creatinine, and eGFR. Booster vaccination significantly reduced FPG (Estimate=-0.123, p<0.001) and HbA1c (Estimate=-0.049, p<0.01), with primary vaccination also reducing FPG (Estimate=-0.118, p<0.001) and HbA1c (Estimate=-0.040, p<0.05). However, creatinine decreased and bilirubin levels rose in vaccinated groups but remained within the normal physiological range. Other indicators showed no significant changes. CONCLUSIONS In conclusion, COVID-19 inactivated vaccine can provide metabolic benefits for diabetic patients.

BACKGROUND We designed this study to develop and validate a prevalence model for latent autoimmune diabetes in adults (LADA) among people initially diagnosed with type 2 diabetes mellitus (T2DM). MATERIAL AND METHODS The study recruited 930 patients aged ≥18 years who were diagnosed with T2DM within the past year. Demographic information, medical history, and clinical biochemistry records were collected. Logistic regression was used to develop a regression model to distinguish LADA from T2DM. Predictors of LADA were identified in a subgroup of patients (n=632) by univariate logistic regression analysis. From this we developed a prediction model using multivariate logistic regression analysis and tested its sensitivity and specificity among the remaining patients (n=298). RESULTS Among 930 recruited patients, 880 had T2DM (96.4%) and 50 had LADA (5.4%). Compared to T2DM patients, LADA patients had fewer surviving b cells and reduced insulin production. We identified age, ketosis, history of tobacco smoking, 1-hour plasma glucose (1hPG-AUC), and 2-hour C-peptide (2hCP-AUC) as the main predictive factors for LADA (P<0.05). Based on this, we developed a multivariable logistic regression model: Y=-8.249-0.035(X1)+1.755(X2)+1.008(X3)+0.321(X4)-0.126(X5), where Y is diabetes status (0=T2DM, 1=LADA), X1 is age, X2 is ketosis (1=no, 2=yes), X3 is history of tobacco smoking (1=no, 2=yes), X4 is 1hPG-AUC, and X5 is 2hCP-AUC. The model has high sensitivity (78.57%) and selectivity (67.96%). CONCLUSIONS This model can be applied to people newly diagnosed with T2DM. When Y ≥0.0472, total autoantibody screening is recommended to assess LADA.

To assess the prevalence of diabetes-associated autoantibodies in Chinese patients recently diagnosed with adult-onset diabetes and to evaluate the potential role of the autoantibody markers for characterization of disease phenotype in the patient population. The study included 1273 recent-onset adult patients with phenotypic type 2 diabetes mellitus (T2DM). Serum samples were tested using the 3-Screen ICA™ ELISA (3-Screen) designed for combined measurement of GADAb and/or IA-2Ab and/or ZnT8Ab. 3-Screen positive samples were then tested for individual diabetes-associated and other organ-specific autoantibodies. Clinical characteristics of patients positive and negative in 3-Screen were analysed. Forty-four (3.5%) of the T2DM patients were positive in 3-Screen, and 38 (86%) of these were also positive for at least one of GADAb, IA-2Ab and ZnT8Ab in assays for the individual autoantibodies. 3-Screen positive patients had lower BMI, higher HbA1c, lower fasting insulin levels and lower fasting C-peptide levels compared to 3-Screen negative patients. Analysis using a homeostatic model assessment (HOMA2) indicated that HOMA2-β-cell function was significantly lower for the forty-four 3-Screen positive patients compared to 3-Screen negative patients. Twenty (45%) 3-Screen positive patients were also positive for at least one thyroid autoantibody. The 3-Screen ELISA has been used successfully for the first time in China to detect diabetes autoantibodies in patients with phenotypic T2DM. 3-Screen positive patients presented with poorer β cell function.

INTRODUCTION:The effect of comorbid cardiometabolic diseases (CMDs), including diabetes, heart diseases, and stroke, on dementia remains unclear.METHODS:A cohort of 2648 dementia-free adults aged ≥60 years was followed up for 12 years. An active lifestyle was defined in accordance with the engagement in leisure activities and/or a social network. Cox models were used in data analysis.RESULTS:The multiadjusted hazard ratio (HR, 95% confidence interval) of dementia was 1.41 (1.07-1.86) for one, 2.38 (1.58-3.59) for two, and 4.76 (2.04-11.13) for three CMDs. In joint exposure analysis, the HR of dementia was 3.36 (2.14-5.30) for participants with CMDs plus an inactive lifestyle and 1.32 (0.95-1.84) for those with CMDs plus an active lifestyle (reference: no CMDs plus active lifestyle). An active lifestyle delayed dementia onset by 3.50 years in people with CMDs.DISCUSSION:CMDs, especially when comorbid, are associated with increased dementia risk; however, leisure activities and social integration mitigate this risk.

Introduction/Background: Although some studies have explored the association of adiposity and life habits (such as smoking) with osteoporosis and osteopenia among type 2 diabetes mellitus (T2DM) patients, the association between diabetic clinical characteristics (especially hypoglycemic drug use) and osteoporosis/ osteopenia remains unclear. This study aimed to investigate the relationship of clinical characteristics with osteoporosis and osteopenia among T2DM patients by sex. Methods: A total of 1222 T2DM patients aged >= 50 were included in the present study. Information on demographic, anthropometric and clinical characteristics was collected from medical records. Bone mineral density was assessed by dual-energy X-ray absorptiometry densitometer. Multiple adjusted logistic regression analyses were performed to estimate the odds ratio (OR) and 95% confidence interval (CI) of osteoporosis and osteopenia related to clinical characteristics. Results: Of all participants, the prevalence of osteoporosis and osteopenia was 9.2% and 41.3%, respectively, and they were higher in females (14.7% and 48.5%) than in males (2.8% and 33%). After adjustment for potential confounders, the results showed that overweight (OR = 0.59; 95 % CI, 0.42-0.81) and obesity (OR = 0.35; 95% CI, 0.24-0.50) were related to decreased odds of osteoporosis and osteopenia in both male and female T2DM patients, poor glycemic control (OR = 1.63; 95% CI, 1.08-2.47) was associated with increased odds of osteoporosis and osteopenia in males, and metformin treatment (OR = 0.65; 95% CI, 0.43-0.99) was associated with decreased odds of osteoporosis and osteopenia in females. Conclusions: Better glycemic management and rational choice of antidiabetic medication might be promising to prevent osteoporosis in T2DM patients. Further longitudinal studies are warranted to explore the association between antidiabetic treatment and osteoporosis.

This meta-analysis was performed to evaluate the effect of cognitive behavioural therapy (CBT) in improving the depression symptoms of patients with diabetes. Literature search was conducted in PubMed and Embase up to October 2016 without the initial date. The pooled SMD (standard mean difference) and its 95% confidence interval (CI) were calculated by Revman 5.3. Subgroup analyses were performed by type of diabetes and evaluation criteria of depression. A total of five randomized control trials involving 834 patients with diabetes mellitus (including 417 patients in CBT group and 417 patients in control group) were included in this meta-analysis. The pooled estimates indicated significant improvement of depression by CBT compared with routine approaches in overall outcomes (SMD =-0.33, 95% CI =-0.46 to -0.21, P<0.00001), post-intervention outcomes (SMD =-0.43, 95% CI =-0.73 to -0.12, P=0.006) and outcomes after 12 months intervention (SMD =-0.38, 95% CI = -0.54 to -0.23, P<0.0001). Subgroup analyses showed that the results were not influenced by the type of diabetes. However, the effect of CBT on improving the depression symptoms disappeared when only using CES-D (Centre for Epidemiological Studies scale for Depression) to evaluate depression.

Background: Cell-derived microvesicles (MVs) are vesicles released from activated or apoptotic cells. However, the levels of MVs in myocardial infarction have been found inconsistent in researches. Objective: To assess the association between MVs and myocardial infarction by conducting a meta-analysis. Methods: A systematic literature search on PubMed, Embase, Cochran, Google Scholar electronic database was conducted. Comparison of the MVs levels between myocardial infarction patients and healthy persons were included in our study. Standard Mean Difference (SMD) and 95% confidence interval (CI) in groups were calculated and meta-analyzed. Results: 11 studies with a total of 436 participants were included. Compared with the health persons, AMVs [SMD = 3.65, 95% CI (1.03, 6.27)], PMVs [SMD = 2.88, 95% CI (1.82, 3.93),] and EMVs [SMD = 2.73, 95% CI (1.13, 4.34)], levels were higher in patients with myocardial infarction. However, LMVs levels [SMD = 0.73, 95% CI (-0.57, 2.03)] were not changed significantly in patients with myocardial infarction. Conclusions: AMVs, PMVs and EMVs might be potential biomarkers for myocardial infarction.

Statins may decrease chronic kidney diseases (CKDs) risk, but their underlying molecular mechanisms are not completely understood. Recent studies indicate Endothelial-to-mesenchymal transition (EndMT) plays an important role contributing to renal interstitial fibrosis. In the present study, we first investigated whether lovastatin could ameliorate renal fibrosis via suppression of EndMT and its possible mechanism. In vitro experiments, lovastatin significantly ameliorated microalbuminuria and pathologic changes in diabetic rats. Double labeling immunofluorescence showed lovastatin could inhibit EndMT in glomeruli. Furthermore, lovastatin could inhibit oxidative stress and down-regulate TGF-β1-Smad signaling. Consistent alterations were observed in vivo that lovastatin substantially suppressed EndMT and TGF-β1 signaling induced by high glucose in glomerular endothelial cells (GEnCs). These data indicated that lovastatin could ameliorate EndMT in glomeruli in diabetic nephropathy, the mechanism of which might be at least partly through suppression of oxidative stress and TGF-β1/Smad signaling pathway.

Currently, cerebral infarction (CI) is the leading cause of disability and the second leading cause of mortality in China, seriously affecting patient quality of life. Ischemia (IS) is considered to be the early stage of CI. The present study aims to investigate the variation of intestinal microbial communities in patients with CI and IS using high throughput sequencing technology, and then analyze the results to identify a novel potential pathogenic mechanism of CI and IS. In total, 8 patients with CI, 2 patients with IS and 10 healthy volunteers as a control were selected. Throughput sequencing technology was used to analyze the character and microbial population of the gut. The abundance of Escherichia, Bacteroides, Megamonas, Parabacteroides, Akkermansia, Prevotella, Faecalibacterium, Dialister, Bifidobacterium and Ruminococcus was the significant difference in the intestinal microbial communities of the CI and IS patients compared with the healthy group. It was also observed that CI and IS were closely associated with internal glucose metabolism. The intestinal gut disturbance of CI patients may be one of the causes inducing CI by glucose metabolism and maybe considered as a potential method to predict the disease.

Cerebral infarction has currently become No. 1 disabling disease and No. 2 fatal disease in China, seriously affecting patient’s quality of life. Cerebral infarction is considered to be closely related to carbohydrate metabolism in the body while human intestines are the main organ for the digestion of food. This study was designed to observe changes in the composition of intestinal flora in phylum level and carbohydrate metabolism using high-throughput sequencing technology in patients with cerebral infarction, followed by analysis of the corresponding characteristics, in order to explore the potential new mechanism of pathogenesis involved in cerebral infarction. 10 fecal samples from patients with cerebral infarction and 10 samples from healthy volunteers as control were selected to determine the abundance of intestinal flora in phylum level using sequencing technology for characteristic analysis. When compared with healthy group, the flora composition in phylum level was low similarity (P<0.05), Firmicutes and Proteobacteria in CI patients were significantlyincreased while Actinobacteria, Bacteriodetes, Cyanobacteria and Verrucomicrobiasignificantly decreased (P<0.05) in patients with cerebral infarction (P<0.05). The level of ApoE and glucose in CI patients significantly was increased (P<0.05). There was an altered intestinal guts feature in cerebral infarction patients and it may be the potential relationship between metabolism of ApoE and glucose and cerebral

Diabetes can increase the risk of cancers at several sites, but the association between diabetes and lung cancer remains unclear. We aimed to provide the quantitative estimates for the association between diabetes or antidiabetic treatment and lung cancer risk in the present meta‐analysis.

OBJECTIVETo investigate the effects of Helicobacter pylori (Hp) on blood glucose fluctuation in type 2 diabetic mellitus.METHODS130 type 2 diabetic patients were selected, 72 patients with Hp infection and 58 without Hp infection. Relevant clinical data: blood pressure, body mass index, cholesterol, triglyceride, low density lipoprotein cholesterol, high density lipoprotein cholesterol, glycosylated hemoglobin, insulin resistance index, liver function, and renal function were collected. The data of blood glucose levels at 7 time points, 6 - 7 am, 9 - 10 am, 11 - 12 am, 14 - 15 pm, 17 - 18 pm, 19 - 20 pm, and 22 - 23 pm in 3 days, totally 21 data, were collected. And input into the OTDMS data analysis software to evaluate the blood glucose fluctuation indexes: standard deviation of mean blood glucose (SDBG), mean amplitude of glycemic excursions (MAGE), large amplitude of glycemic excursions (LAGE).RESULTSThere were no significant differences in age, course of disease, blood pressure, body mass index, cholesterol, triglyceride, low density lipoprotein cholesterol, glycosylated hemoglobin, and insulin resistance index between these 2 groups (all P > 0.05). The levels of MBG, SDBG, MAGE, LAGE, (mmol/L: 9.0 +/- 1.1 vs 7.6 +/- 0.5, 3.3 +/- 1.1 vs 1.7 +/- 0.5, 6.7 +/- 4.5 vs 3.0 +/- 1.1, 8.6 +/- 3.8 vs 4.2 +/- 1.5, all P < 0.05) and incidence of hypoglycemia [16.6% (12/72) vs 5.1% (3/58), P < 0.05] were all higher in the Hp positive group than in the Hp negative group.CONCLUSIONHp infection has a significant effect on the daily blood glucose level and blood glucose fluctuation in the patients with type 2 diabetes.