The ALDH2 gene rs671 polymorphism is associated with cardiometabolic risk factors in East Asian population: an updated meta-analysis.

Introduction: Acetaldehyde dehydrogenase 2 (ALDH2) had reported as a prominent role in the development of cardiometabolic diseases among Asians. Our study aims to investigate the relationship between ALDH2 polymorphism and cardiometabolic risk factors in East Asian population. Method: We searched databases of PubMed, Web of Science, and Embase updated to Oct 30th, 2023. We extracted data of BMI, Hypertension, SBP, DBP, T2DM, FBG, PPG, HbA1c, TG, TC, LDL-C and HDL-C. Result: In total, 46 studies were finally included in our meta-analysis, containing, 54068 GG and, 36820 GA/AA participants. All outcomes related to blood pressure revealed significant results (hypertension OR=0.83 [0.80, 0.86]; SBP MD=-1.48 [-1.82, -1.14]; DBP MD=-1.09 [-1.58, -0.61]). FBG showed a significant difference (MD=-0.10 [-0.13, -0.07]), and the lipid resulted significantly in some outcomes (TG MD=-0.07 [-0.09, -0.04]; LDL-C MD=-0.04 [-0.05, -0.02]). As for subgroups analysis, we found that in populations without severe cardiac-cerebral vascular diseases (CCVDs), GG demonstrated a significantly higher incidence of T2DM (T2DM OR=0.88 [0.79, 0.97]), while the trend was totally opposite in population with severe CCVDs (T2DM OR=1.29 [1.00, 1.66]) with significant subgroup differences. Conclusion: Our updated meta-analysis demonstrated that ALDH2 rs671 GG populations had significantly higher levels of BMI, blood pressure, FBG, TG, LDL-C and higher risk of hypertension than GA/AA populations. Besides, to the best of our knowledge, we first report GG had a higher risk of T2DM in population without severe CCVDs, and GA/AA had a higher risk of T2DM in population with severe CCVDs.Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023389242.

Association between sex hormones and gout: An analysis of the UK Biobank cohort.

OBJECTIVES: To investigate the associations between sex hormones and gout. METHODS: A total of 448,836 individuals free of gout at baseline were included from the UK Biobank. Cox regression models were used to estimate hazard ratios (HRs) for gout. Besides, we investigated the causal relationship between bioavailable testosterone (BAT) and gout using mendelian randomization (MR). RESULTS: There were differential effects in different testosterone active states in gout. One-unit higher log-transformed total testosterone (TT) was associated with a 52 % [95 % CI, 0.39-0.58] lower risk of gout in males. In contrast, free testosterone (FT) and BAT were associated with a 74 % [95 % CI, 1.38-2.20] and a 78 % [95 % CI, 1.41-2.25] higher risk of gout in males respectively. For MR, the weighted median [OR, 1.70; 95 % CI, 1.14-2.56;] and inverse variance-weighted [OR, 1.25; 95 % CI, 0.96-1.62; P = 0.09] method revealed significant and approximately significant positive effect of genetic liability to BAT levels on the risk of gout respectively. CONCLUSIONS: Sex hormones were potentially associated with gout. Notably, we were the first to explore different testosterone states on gout and found that FT and BAT may increase the risk of gout in males, which is opposite to TT. And the former are active states of androgens, may be more accurately reflect the association between androgens and gout.

Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China.

Objective: Insulin plays a central role in the regulation of energy and glucose homeostasis, and insulin resistance (IR) is widely considered as the "common soil" of a cluster of cardiometabolic disorders. Assessment of insulin sensitivity is very important in preventing and treating IR-related disease. This study aims to develop and validate machine learning (ML)-augmented algorithms for insulin sensitivity assessment in the community and primary care settings. Methods: We analyzed the data of 9358 participants over 40 years old who participated in the population-based cohort of the Hubei center of the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals). Three non-ensemble algorithms and four ensemble algorithms were used to develop the models with 70 non-laboratory variables for the community and 87 (70 non-laboratory and 17 laboratory) variables for the primary care settings to screen the classifier of the state-of-the-art. The models with the best performance were further streamlined using top-ranked 5, 8, 10, 13, 15, and 20 features. Performances of these ML models were evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPR), and the Brier score. The Shapley additive explanation (SHAP) analysis was employed to evaluate the importance of features and interpret the models. Results: The LightGBM models developed for the community (AUROC 0.794, AUPR 0.575, Brier score 0.145) and primary care settings (AUROC 0.867, AUPR 0.705, Brier score 0.119) achieved higher performance than the models constructed by the other six algorithms. The streamlined LightGBM models for the community (AUROC 0.791, AUPR 0.563, Brier score 0.146) and primary care settings (AUROC 0.863, AUPR 0.692, Brier score 0.124) using the 20 top-ranked variables also showed excellent performance. SHAP analysis indicated that the top-ranked features included fasting plasma glucose (FPG), waist circumference (WC), body mass index (BMI), triglycerides (TG), gender, waist-to-height ratio (WHtR), the number of daughters born, resting pulse rate (RPR), etc. Conclusion: The ML models using the LightGBM algorithm are efficient to predict insulin sensitivity in the community and primary care settings accurately and might potentially become an efficient and practical tool for insulin sensitivity assessment in these settings.

Cold-stored mulberry leaves affect antioxidant system and silk proteins of silkworm (Bombyx mori) larva.

BACKGROUND: Cold storage has been widely used to maintain the quality of vegetables, but whether eating cold-stored vegetables affects health remains unknown. RESULTS: This study used silkworms as an animal model to evaluate the effects of nutrient changes in cold-stored mulberry leaves (CSML) on health. Compared with fresh mulberry leaves (FML), CSML contained lower vitamin C, soluble sugars and proteins, and higher H2 O2 , suggesting decreased antioxidant ability and nutrition. The CSML did not obviously affect larval survival rate, body weight or dry matter rate, cocoon shape, weight and size, or final rates of cluster and cocooning relative to the FML, suggesting CSML did not alter overall growth and development. However, the CSML increased the initial rates of cluster and cocooning and upregulated BmRpd3, suggesting CSML shortened larval lifespan and enhanced senescence. CSML upregulated BmNOX4, downregulated BmCAT, BmSOD and BmGSH-Px and increased H2 O2 in silkworms, suggesting CSML caused oxidative stress. CSML upregulated ecdysone biosynthesis and inactivation genes and elevated ecdysone concentration in silkworms, suggesting that CSML affected hormone homeostasis. CSML upregulated apoptosis-related genes, downregulated sericin and silk fibroin genes and decreased sericin content rate in silkworms, suggesting oxidative stress and protein deficiency. CONCLUSION: Cold storage reduced nutrition and antioxidant capability of mulberry leaves. CSML did not influence growth and development of silkworm larva, but affected health by causing oxidative stress and reducing protein synthesis. The findings show that the ingredient changes in CSML had negative effects on health of silkworms. © 2023 Society of Chemical Industry.

Preharvest Application of Sodium Nitroprusside Alleviates Yellowing of Chinese Flowering Cabbage via Modulating Chlorophyll Metabolism and Suppressing ROS Accumulation.

Chinese flowering cabbage is prone to senescence and yellowing after harvest, leading to a huge postharvest loss. Nitric oxide (NO) is a multifunctional plant growth regulator, but the effect of preharvest application of NO on the storage quality of Chinese flowering cabbage remains unclear. Preharvest application of 50 mg L-1 sodium nitroprusside (SNP, a NO donor) to the roots obviously reduced leaf yellowing in Chinese flowering cabbage during storage. Proteomic analysis reveals 198 differentially expressed proteins (DEPs) in SNP-treated plants compared to the control. The main DEPs were significantly enriched in chlorophyll metabolisms, phenylpropanoid synthesis, and antioxidant pathways. SNP treatment enhanced chlorophyll biosynthesis and suppressed chlorophyll-degradation-related proteins and genes. It also modulated flavonoid-biosynthesis-related genes, and 21 significantly regulated flavonoids were identified in SNP-treated plants. The enhanced antioxidant capacity in SNP-treated plants was able to decrease chlorophyll catabolism by inhibiting peroxidase-mediated chlorophyll bleaching. Collectively, preharvest SNP treatment modulated chlorophyll metabolism and preserved chlorophyll content in leaves during storage. Moreover, SNP treatment enhanced flavonoid synthesis, suppressed reactive oxygen species accumulation, and delayed the senescence process, thereby maintaining leaf greening in Chinese flowering cabbage. These findings highlight the role of exogenous NO in alleviating yellowing of leafy vegetables.

Clinical and prognostic significance of long non-coding RNA CRNDE expression in severe pneumonia and its correlation with inflammatory factor levels.

OBJECTIVE: To investigate the clinical and prognostic significance of long non-coding RNA (lncRNA) CRNDE expression in severe pneumonia and its correlation with the levels of inflammatory factors. METHODS: In this retrospective study, 86 patients with severe pneumonia were selected as the observation group (OG), and 70 patients with non-severe pneumonia were selected as the control group (CG). The expression of lncRNA CRNDE was measured by real-time fluorescence quantitative reverse transcription polymerase chain reaction. The relationship between lncRNA CRNDE expression and clinical characteristics and prognosis of patients was analyzed. The correlation between lncRNA CRNDE expression and the levels of inflammatory factors related to severe pneumonia was also analyzed. RESULTS: Relative expression of lncRNA CRNDE in OG was significantly higher than that in CG (P<0.05). The receiver operator characteristic (ROC) curve analysis revealed that lncRNA CRNDE expression could be used for the detection of severe pneumonia. The expression of lncRNA CRNDE was not related to gender, age, or smoking history (all P>0.05), but related to the pneumonia severity index (PSI) score, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and procalcitonin (PCT), C-reactive protein (CRP), and D-dimer (DD) expression (P<0.05). Spearman correlation analysis revealed that lncRNA CRNDE expression was positively correlated with the expressions of PCT, CRP, and DD (r=0.908, 0.898, and 0.951, respectively, P<0.001). CONCLUSIONS: lncRNA CRNDE is highly expressed in the serum of patients with severe pneumonia and is an independent risk factor for the poor prognosis of these patients. The expression of lncRNA CRNDE is also positively correlated with the levels of inflammatory factors in such patients, which can be used for the clinical detection of severe pneumonia.

Preharvest application of selenite enhances the quality of Chinese flowering cabbage during storage via regulating the ascorbate-glutathione cycle and phenylpropanoid metabolisms.

Chinese flowering cabbage (Brassica campestris L. ssp. chinensis var. utilis Tsen et Lee) is a candidate of selenium (Se) accumulator, but it is not clear whether and how preharvest Se treatment affects its quality after harvest. Here, we showed that preharvest application of 100 µmol/L selenite to roots enhanced storage quality of Chinese flowering cabbage. It increased antioxidant capacity and reduced weight loss, leaf yellowing, and protein degradation after harvest. Furthermore, it increased the activities of antioxidant enzymes such as POD, CAT, GSH-Px, and GR, as well as contents of AsA, GSH, phenolics, and flavonoids during storage. Metabolome analysis revealed that phenolic acids including p-Coumaric acid, caffeic acid, and ferulic acid; flavonoids such as naringenin, eriodictyol, apigenin, quercetin, kaempferol, and their derivatives were notably increased by preharvest selenite treatment. Consistently, the total antioxidant capacity, evaluated by DPPH, ABTS, and FRAP methods, were all markedly enhanced in selenite-treated cabbage compared to the control. Transcriptomics analysis showed that the DEGs induced by selenite were significantly enriched in AsA-GSH metabolisms and phenylpropanoids biosynthesis pathways. Moreover, preharvest selenite treatment significantly up-regulated the expressions of BrGST, BrGSH-Px, BrAPX, BrASO, BrC4H, BrCOMT, BrCHS, and BrFLS during storage. These results suggest that preharvest selenite treatment enhanced quality of cabbage not only by increasing Se biological accumulation, but also through regulating AsA-GSH cycle and increasing phenolics and flavonoids synthesis after harvest. This study provides a novel insight into the effects of preharvest Se treatment on quality of Chinese flowering cabbage during storage.

Preharvest Hydrogen Peroxide Treatment Delays Leaf Senescence of Chinese Flowering Cabbage During Storage by Reducing Water Loss and Activating Antioxidant Defense System.

Leaf yellowing, an indicator of senescence, reduces commercial value of Chinese flowering cabbage after harvest. Hydrogen peroxide (H2O2) plays a dual role in mediating plant stress responses, but it is not clear whether and how it affects leaf senescence when exogenously stimulating the plants before harvest. Here, we found that preharvest application with low concentrations of H2O2 to root delays leaf senescence. Around 10 mM H2O2 reduced leaf yellowing rate by 8.2 and 26.4% relative to the control following 4 and 8 days storage, respectively. The H2O2-treated cabbages showed higher chlorophyll and lower relative expression of senescence-associated gene (SAG) BrSAG12 than the control. Proteomic analysis revealed 118 and 204 differentially expressed proteins (DEPs) in H2O2-treated plants at 4 and 8 days of storage, respectively. The main DEPs are involved in chlorophyll degradation and synthesis, water deprivation, antioxidant activity, and protections on chloroplast membranes. Decline of water loss in H2O2-treated cabbages was coincide with increase of proline contents and modulation of leaf stomatal aperture. Alleviation of oxidative stress was indicated by suppression of respiratory burst oxidase homolog and upregulation of reactive oxygen species (ROS) scavenging-related genes. These results were also supported by the alleviation of lipid peroxidation and the protections on cell integrity and photochemical efficiency in H2O2-treated group. Collectively, preharvest H2O2 treatment alleviates water loss and activates antioxidant defense system, protects chloroplast membrane from oxidative damage, and ultimately delays leaf senescence during storage. This study provides novel insights into the roles of H2O2 for regulating leaf senescence of Chinese flowering cabbage.

Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study.

Background: There is an increasing trend of Metabolic syndrome (MetS) prevalence, which has been considered as an important contributor for cardiovascular disease (CVD), cancers and diabetes. However, there is often a long asymptomatic phase of MetS, resulting in not diagnosed and intervened so timely as needed. It would be very helpful to explore tools to predict the probability of suffering from MetS in daily life or routinely clinical practice. Objective: To develop models that predict individuals' probability of suffering from MetS timely with high efficacy in general population. Methods: The present study enrolled 8964 individuals aged 40-75 years without severe diseases, which was a part of the REACTION study from October 2011 to February 2012. We developed three prediction models for different scenarios in hospital (Model 1, 2) or at home (Model 3) based on LightGBM (LGBM) technique and corresponding logistic regression (LR) models were also constructed for comparison. Model 1 included variables of laboratory tests, lifestyles and anthropometric measurements while model 2 was built with components of MetS excluded based on model 1, and model 3 was constructed with blood biochemical indexes removed based on model 2. Additionally, we also investigated the strength of association between the predictive factors and MetS, as well as that between the predictors and each component of MetS. Results: In this study, 2714 (30.3%) participants suffer from MetS accordingly. The performances of the LGBM models in predicting the probability of suffering from MetS produced good results and were presented as follows: model 1 had an area under the curve (AUC) value of 0.993 while model 2 indicated an AUC value of 0.885. Model 3 had an AUC value of 0.859, which is close to that of model 2. The AUC values of LR model 1 and 2 for the scenario in hospital and model 3 at home were 0.938, 0.839 and 0.820 respectively, which seemed lower than that of their corresponding machine learning models, respectively. In both LGBM and logistic models, gender, height and resting pulse rate (RPR) were predictors for MetS. Women had higher risk of MetS than men (OR 8.84, CI: 6.70-11.66), and each 1-cm increase in height indicated 3.8% higher risk of suffering from MetS in people over 58 years, whereas each 1- Beat Per Minute (bpm) increase in RPR showed 1.0% higher risk in individuals younger than 62 years. Conclusion: The present study showed that the prediction models developed by machine learning demonstrated effective in evaluating the probability of suffering from MetS, and presented prominent predicting efficacies and accuracies. Additionally, we found that women showed a higher risk of MetS than men, and height in individuals over 58 years was important factor in predicting the probability of suffering from MetS while RPR was of vital importance in people aged 40-62 years.

Nonomuraea nitratireducens Qu et al. 2020 is a later heterotypic synonym of Nonomuraea phyllanthi Klykleung et al. 2020.

Nonomuraea nitratireducens WYY166T was compared with Nonomuraea phyllanthi PA1-10T to examine the taxonomic relationship between the two type strains. The 16S rRNA gene sequence of N. nitratireducens WYY166T had high similarity (99.9 %) to that of N. phyllanthi PA1-10T. The results of phylogenetic analyses based on 16S rRNA gene sequences indicated that the two strains formed a tight cluster within the genus Nonomuraea. Draft genomic comparison between the two strains revealed an average nucleotide identity of 99.3 % and a digital DNA-DNA hybridization estimate of 94.4±1.8 %, strongly indicating that the two strains represented a single species. In addition, neither strain displayed any striking difference in metabolic, physiological or chemotaxonomic features. Therefore, we propose Nonomuraea nitratireducens as a later heterotypic synonym of Nonomuraea phyllanthi.

Integrative Analyses of Genes Associated with Hashimoto's Thyroiditis.

OBJECTIVE: Hashimoto's thyroiditis, also known as chronic lymphocytic thyroiditis, is a common autoimmune thyroiditis, which mostly occurs in young and middle-aged women. It can be manifested as hyperthyroidism in the early stage; hypothyroidism may appear with the progression of the disease. Studies have shown that multiple factors such as heredity, environment, and autoimmunity are involved in the pathogenesis, but the specific mechanism is not clear. In our study, we tried to find key genes and potential molecular mechanisms of Hashimoto's thyroiditis to provide new ideas for the therapeutic targets of Hashimoto's thyroiditis. METHOD: GSE138198 and GSE54958 were downloaded from the GEO database, and two datasets were combined for analysis. The combined data were normalized to identify the differentially expressed genes (DEGs), and GO and KEGG enrichment analyses were performed. Protein-protein interaction (PPI) networks and hub genes between DEGs were identified. We also used the miRWalk database to identify regulatory miRNAs associated with expressions of DEGs. RESULT: We identified 182 DEGs (160 upregulated and 22 downregulated) between Hashimoto's disease patients and the healthy control group. GO analysis showed that DEGs were mostly concentrated in detection of chemical stimulus involved in sensory perception, intermediate filament cytoskeleton, and olfactory receptor activity. KEGG pathway analysis showed that DEGs were mainly related to olfactory transduction. Some members of the KRTAP family and HTR5A, KNG1, DRD3, HTR1D, TAS2R16, INSL5, TAS2R42, and GRM7 are the most important hub genes in the PPI network. In addition, we recognized that OTUD4, LLPH, and ECHDC1 were the most important hub genes in the miRNA-target gene network. CONCLUSION: In this study, a series of bioinformatics analyses of DEGs were performed to identify the key genes and pathways associated with Hashimoto's thyroiditis. These genes and pathways provide a more detailed understanding of the pathogenesis of Hashimoto's disease and provide new ideas for the therapeutic targets of Hashimoto's thyroiditis.

Short-Term Changes in Metabolically Healthy Overweight/Obesity Status Impact the Susceptibility to Type 2 Diabetes in Chinese Adults.

PURPOSE: Changes in transition from metabolically healthy overweight/obesity (MHO) to metabolically unhealthy overweight/obesity (MUO) are associated with the risk for cardiometabolic complications. This study aims to investigate the effects of short-term dynamic changes in body mass index (BMI) and metabolic status on the risk of type 2 diabetes (T2D) and to identify biological predictors for the MHO-to-MUO transition. PATIENTS AND METHODS: A total of 4604 subjects from the REACTION study were included for a 3-year follow-up. Subjects were categorized based on their BMI and metabolic syndrome status. Overweight/obesity was defined as BMI ≥ 24 kg/m2. Metabolically healthy was defined as having two or fewer of the metabolic syndrome components proposed by the Chinese Diabetes Society. Thus, subjects were divided into four groups: metabolically healthy normal weight (MHNW), MHO, metabolically unhealthy normal weight (MUNW), and MUO. RESULTS: Compared with MHNW, MHO was not predisposed to an increased risk for T2D (OR 1.08, 95% CI 0.64-1.83, P = 0.762). However, a 3-year transition probability of 20.6% was identified for subjects who shifted from MHO to MUO; this conversion increased the risk of T2D by 3-fold (OR 3.04, 95% CI 1.21-7.68, P = 0.018). The fatty liver index independently predicted the MHO-to-MUO transition with an OR 3.14 (95% CI 1.56-7.46, P = 0.002) when comparing the fourth quartile to the first quartile. CONCLUSION: This study reveals that metabolic changes affect the short-term susceptibility to T2D in the overweight/obese Chinese population, and the fatty liver index is an efficient clinical parameter for identifying those with a metabolic deterioration risk.

Identification of Inflammation-Related Biomarker Pro-ADM for Male Patients With Gout by Comprehensive Analysis.

Objective: Gout is a local inflammatory disease caused by the deposition of monosodium urate (MSU) crystals in joints or adjacent tissues. When some gout occurs without hyperuricemia, or its clinical symptoms and signs are not typical, the diagnosis of gout will be delayed, so there is an urgent need to find a new biomarker to predict and diagnose of gout flare. Our research attempts to find the key genes and potential molecular mechanisms of gout through bioinformatics analysis, and collected general data and blood biochemical samples of patients with gout and healthy, then analyzed and compared the expression of factors regulated by key genes. Method: GSE160170 were downloaded from GEO database for analysis. The data were normalized to identify the differentially expressed genes (DEGs), then GO and KEGG enrichment analysis were applied. Protein-protein interaction (PPI) networks and hub genes between DEGs were identified. Then collect general information and blood samples from male patients with acute gout, hyperuricemia and healthy. ELISA method was used to detect pro-ADM levels of different groups, and the data was input into SPSS statistical software for analysis. Result: We identified 266 DEGs (179 up-regulated and 87 down-regulated) between gout patients and healthy controls. GO analysis results show that DEGs are mostly enriched in inflammatory response, growth factor activity, cytokine activity, chemokine activity, S100 protein binding and CXCR chemokine receptor binding. KEGG pathway analysis showed that DEGs are mainly related to Chemokine signaling pathway and Cytokine-cytokine receptor interaction. ADM, CXCR1, CXCR6, CXCL3, CCL3, CCL18, CCL3L3, CCL4L1, CD69, CD83, AREG, EREG, B7RP1, HBEGF, NAMPT and S100B are the most important hub genes in the PPI network. We found that the expression of pro-ADM in the gout group and hyperuricemia group was higher than that in the healthy group, and the difference was statistically significant. Conclusion: In this study, a series of bioinformatics analyses were performed on DEGs to identify key genes and pathways related to gout. Through clinical verification, we found that pro-ADM can be used as an inflammation-related biomarker for acute attacks of gout, providing new ideas for the diagnosis and treatment of gout.

Effects of soluble fiber supplementation on glycemic control in adults with type 2 diabetes mellitus: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND & AIMS: Soluble dietary fiber is prompted as an important part of reducing blood glucose, ameliorating insulin resistance and controlling body weight. Thus, we performed this systematic review and meta-analysis of randomized controlled trials (RCTs) to quantify and synthesize the effects of soluble fiber supplementation on glycemic control and BMI modification in adults with type 2 diabetes. METHODS: We searched MEDLINE, Embase, Web of Science, ClinicalTrials.gov, and Cochrane databases until February 13, 2020 to identify RCTs that detected the effects of soluble fiber supplementation on glycemic control in adults with type 2 diabetes. A random-effects model with the generic inverse variance method was used to analyze the pooled data. The meta-regression and subgroup analyses were conducted to identify the variables that influenced the pooled results. The robust error meta-regression model was used to conduct the dose-response test. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was undertaken to evaluate the overall quality of the evidence. RESULTS: A total of 29 RCTs (33 comparisons) involving 1517 participants were identified in this meta-analysis. Results showed that supplemental soluble dietary fiber significantly reduced glycosylated hemoglobin (HbA1c, MD -0.63%, 95% CI [-0.90, -0.37]; P < 0.00001), fasting plasma glucose (FPG, MD -0.89 mmol/L, 95% CI [-1.28, -0.51]; P < 0.00001), fasting insulin (SMD -0.48, 95% CI [-0.80, -0.17]; P = 0.003), homeostatic model assessment of insulin resistance (HOMA-IR, SMD -0.58, 95% CI [-0.86, -0.29], P < 0.0001), fructosamine (SMD -1.03, 95% CI [-1.51, -0.55]; P < 0.0001), 2-h postprandial plasma glucose (SMD -0.74, 95% CI [-1.00, -0.48]; P < 0.00001), and BMI (SMD -0.31, 95% CI [-0.61, -0.00], P = 0.05) compared with control diets in patients with type 2 diabetes. Specifically, dose-response meta-analyses presented that a daily dosage of 7.6-8.3 g was recommended. CONCLUSION: Intake of soluble fiber supplementation is effective in improving glycemic control and BMI level in type 2 diabetes and is also a convenient way to help individuals meet standard dietary fiber needs. But due to the evidence of substantial heterogeneity in most pooled estimates, further long-term and high-quality RCTs are needed.

Risk Factors for Poor Outcomes of Diabetes Patients With COVID-19: A Single-Center, Retrospective Study in Early Outbreak in China.

Background: Diabetes has been found to increase severity and mortality under the current pandemic of coronavirus disease of 2019 (COVID-19). Up to date, the clinical characteristics of diabetes patients with COVID-19 and the risk factors for poor clinical outcomes are not clearly understood. Methods: The study was retrospectively carried out on enrolled diabetes patients with laboratory confirmed COVID-19 infection from a designated medical center for COVID-19 from January 25th, 2020 to February 14th, 2020 in Wuhan, China. The medical record was collected and reviewed. Univariate and multivariate analyses were performed to assess the risk factors associated with the severe events which were defined as a composite endpoint of admission to intensive care unit, the use of mechanical ventilation, or death. Results: A total of 52 diabetes patients with COVID-19 were finally included in the study. 21 (40.4%) patients had developed severe events in 27.50 (IQR 12.25-35.75) days follow-up, 15 (28.8%) patients experienced life-threatening complications and 8 patients died with a recorded mortality rate of 15.4%. Only 13 patients (41.9%) were in optimal glycemic control with HbA1c value of <7.0%. In addition to general clinical characteristics of COVID-19, the severe events diabetes patients showed higher counts of white blood cells and neutrophil, lower lymphocytes (40, 76.9%), high levels of hs-CRP, erythrocyte sedimentation rate (ESR) and procalcitonin (PCT) as compared to the non-severe diabetes patients. Mild higher level of cardiac troponin I (cTNI) (32.0 pg/ml; IQR 16.80-55.00) and D-dimer (1.70 µg/L, IQR 0.70-2.40) were found in diabetes patients with severe events as compared to the non-severe patients (cTNI:20.00 pg/ml, IQR5.38-30.00, p = 0.019; D-dimer: 0.70 µg/L, IQR 0.30-2.40, p = 0.037). After adjusting age and sex, increased level of cTNI was found to significantly associate with the incidence of severe events (HR: 1.007; 95% CI: 1.000-1.013; p = 0.048), Furthermore, using of α-glucosidase inhibitors was found to be the potential protectant for severe events (HR: 0.227; 95% CI: 0.057-0.904; p = 0.035). Conclusion: Diabetes patients with COVID-19 showed poor clinical outcomes. Vigorous monitoring of cTNI should be recommended for the diabetes patients with COVID-19. Usage of α-glucosidase inhibitors could be a potential protectant for the diabetes patients with COVID-19.

Protein Arginine Methyltransferase 4 Regulates Adipose Tissue Lipolysis in Type 1 Diabetic Mice.

PURPOSE: Hypertriglyceridemia is considered to be driven by increased lipolysis in type 1 diabetes mellitus (T1DM). However, information regarding the transcriptional circuitry that governs lipolysis remains incomplete in T1DM. Protein arginine methyltransferase 4 (PRMT4), a transcriptional coactivation factor, promotes autophagy and may play an important role in lipolysis. We wonder whether activated lipolysis in T1DM is regulated by PRMT4. MATERIALS AND METHODS: Recombinant adeno-associated virus was adopted to overexpress PRMT4 in adipose tissue of mice. Streptozotocin (150 mg/kg) was injected intraperitoneally into mice to induce T1DM. Plasma insulin, triglycerides, free fatty acids (FFAs) levels were determined using commercial assay kits. Differentiated adipocytes were applied to verify the regulation of PRMT4 on lipolysis. RESULTS: Elevated serum triglycerides and FFAs were observed in PRMT4-overexpressed T1DM mice. We also observed that PRMT4 over-expression induced the decrease of fat pads weights and adipocyte sizes. Moreover, expression levels of lipolysis-related molecules, including ATGL, HSL, and MAGL, and HSL phosphorylation levels were increased in PRMT4-overexpressed mice when compared to those of control mice. In vitro, PRMT4 promoted FFAs release and activated HSL phosphorylation, whereas PRMT4 knockdown inhibited these processes. CONCLUSION: PRMT4 promotes lipolysis and increases serum triglyceride in T1DM.

Optimization of a Technique to Standardize the Rodent Roux-En-Y Gastric Bypass Model and Troubleshooting of Postoperative Failures.

BACKGROUND: Rodent models are required in studies on the mechanism of Roux-en-Y gastric bypass (RYGB). However, the construction of the model is hard, and there are various causes of death after surgery in rats. METHODS: RYGB models with procedures containing a series of anatomic landmark were established in rats. Optimized procedures during surgery, possible complications after surgery, and corresponding solutions were studied. RESULTS: With the introduction of perioperative nursing and optimized surgery procedures, less time-consuming surgeries were performed and higher survival rates were achieved. Trouble-shooting data based on death time points are listed and discussed for various causes of failure. CONCLUSIONS: This study provides practical suggestions for investigators to perform RYGB surgery on rats. The troubleshooting suggestions will help operators to efficiently identify problems in their procedures.

Alcohol consumption and diabetes risk in a Chinese population: a Mendelian randomization analysis.

AIM: To assess the causality between alcohol intake, diabetes risk and related traits. DESIGN: Mendelian randomization (MR) study. Subgroup analysis, standard instrumental variable analysis and local average treatment effect (LATE) methods were applied to assess linear and non-linear causality. SETTING: China. PARTICIPANTS: A total of 4536 participants, including 721 diabetes cases. FINDINGS: Carriage of an ALDH2 rs671 A allele reduced alcohol consumption by 44.63% [95% confidence interval (CI) = -49.44%, -39.37%]. In males, additional carriage of an A allele was significantly connected to decreased diabetes risk for the overall population [odds ratio (OR) = 0.716, 95% CI = 0.567-0.904, P = 0.005] or moderate drinkers (OR = 0.564, 95% CI = 0.355-0.894, P = 0.015). In instrumental variable (IV) analysis, increasing alcohol consumption by 1.7-fold was associated with an incidence-rate ratio of 1.32 (95% CI = 1.06-1.67, P = 0.014) for diabetes risk, and elevated alcohol intake was causally connected to natural log-transformed fasting, 2-hour post-load plasma glucose (ß = 0.036, 95% CI = 0.018-0.054; ß = 0.072, 95% CI = 0.035-0.108) and insulin resistance [homeostatic model assessment for IR (HOMA-IR] (ß = 0.104, 95% CI = 0.039-0.169), but was not associated with beta-cell function (HOMA-beta). In addition, the LATE method did not identify significant U-shaped causality between alcohol consumption and diabetes-related traits. In females, the effects of alcohol intake on all the outcomes were non-significant. CONCLUSION: Among men in China, higher alcohol intake appears to be causally associated with increased diabetes risk and worsened related traits, even for moderate drinkers. This study found no significant U-shaped causality between alcohol consumption and diabetes-related traits.

Not performing an OGTT results in underdiagnosis, inadequate risk assessment and probable cost increases of (pre)diabetes in Han Chinese over 40 years: a population-based prospective cohort study.

OBJECTIVE: To explore the influence by not performing an oral glucose tolerance test (OGTT) in Han Chinese over 40 years. DESIGN: Overall, 6682 participants were included in the prospective cohort study and were followed up for 3 years. METHODS: Fasting plasma glucose (FPG), 2-h post-load plasma glucose (2h-PG), FPG and 2h-PG (OGTT), and HbA1c testing using World Health Organization (WHO) or American Diabetes Association (ADA) criteria were employed for strategy analysis. RESULTS: The prevalence of diabetes is 12.4% (95% CI: 11.6-13.3), while the prevalence of prediabetes is 34.1% (95% CI: 32.9-35.3) and 56.5% (95% CI: 55.2-57.8) using WHO and ADA criteria, respectively. 2h-PG determined more diabetes individuals than FPG and HbA1c. The testing cost per true positive case of OGTT is close to FPG and less than 2h-PG or HbA1c. FPG, 2h-PG and HbA1c strategies would increase costs from complications for false-positive (FP) or false-negative (FN) results compared with OGTT. Moreover, the least individuals identified as normal by OGTT at baseline developed (pre)diabetes, and the most prediabetes individuals identified by HbA1c or FPG using ADA criteria developed diabetes. CONCLUSIONS: The prevalence of isolated impaired glucose tolerance and isolated 2-h post-load diabetes were high, and the majority of individuals with (pre)diabetes were undetected in Chinese Han population. Not performing an OGTT results in underdiagnosis, inadequate developing risk assessment and probable cost increases of (pre)diabetes in Han Chinese over 40 years and great consideration should be given to OGTT in detecting (pre)diabetes in this population. Further population-based prospective cohort study of longer-term effects is necessary to investigate the risk assessment and cost of (pre)diabetes.

Intestinal Glucose Absorption Was Reduced by Vertical Sleeve Gastrectomy via Decreased Gastric Leptin Secretion.

BACKGROUND: The unique effects of gastric resection after vertical sleeve gastrectomy (VSG) on type 2 diabetes mellitus remain unclear. This work aimed to investigate the effects of VSG on gastric leptin expression and intestinal glucose absorption in high-fat diet-induced obesity. METHODS: Male C57BL/6J mice were fed a high-fat diet (HFD) to induce obesity. HFD mice were randomized into VSG and sham-operation groups, and the relevant parameters were measured at 8 weeks postoperation. RESULTS: Higher gastric leptin expression and increased intestinal glucose transport were observed in the HFD mice. Furthermore, VSG reduced gastric leptin expression and the intestinal absorption of alimentary glucose. Both exogenous leptin replenishment during the oral glucose tolerance test (OGTT) and the addition of leptin into the everted isolated jejunum loops in vitro restored the glucose transport capacity in VSG-operated mice, and this effect was abolished when the glucose transporter GLUT2 was blocked with phloretin. Moreover, phloretin almost completely suppressed glucose transport in the HFD mice. Intestinal immunohistochemistry in the obese mice showed increased GLUT2 and diminished sodium glucose co-transporter 1 (SGLT-1) in the apical membrane of enterocytes. Decreased GLUT2 and enhanced SGLT1 were observed following VSG. VSG also reduced the phosphorylation status of protein kinase C isoenzyme ß II (PKCß II) in the jejunum, which was stimulated by the combination of leptin and glucose. CONCLUSION: Our data demonstrated that the decreased secretion of gastric leptin in VSG results in a decrease in intestinal glucose absorption via modulation of GLUT2 translocation.