Li Zhang, Zhaoxiang Wang, Fengyan Tang, Menghuan Wu, Ying Pan, Song Bai, Bing Lu, Shao Zhong, Ying Xie
{"title":"Identification of Senescence-Associated Biomarkers in Diabetic Glomerulopathy Using Integrated Bioinformatics Analysis","authors":"Li Zhang, Zhaoxiang Wang, Fengyan Tang, Menghuan Wu, Ying Pan, Song Bai, Bing Lu, Shao Zhong, Ying Xie","doi":"10.1155/2024/5560922","DOIUrl":"https://doi.org/10.1155/2024/5560922","url":null,"abstract":"<i>Background</i>. Cellular senescence is thought to play a significant role in the onset and development of diabetic nephropathy. The goal of this study was to explore potential biomarkers associated with diabetic glomerulopathy from the perspective of senescence. <i>Methods</i>. Datasets about human glomerular biopsy samples related to diabetic nephropathy were systematically obtained from the Gene Expression Omnibus database. Hub senescence-associated genes were investigated by differential gene analysis and Least Absolute Shrinkage and Selection Operator analysis. Cluster analysis was employed to identify senescence molecular subtypes. A single-cell dataset was used to validate the above findings and further evaluate the senescence environment. The relationship between these genes and the glomerular filtration rate was explored based on the Nephroseq database. These gene expressions have also been explored in various kidney diseases. <i>Results</i>. Twelve representative senescence-associated genes (VEGFA, IQGAP2, JUN, PLAT, ETS2, ANG, MMP14, VEGFC, SERPINE2, CXCR2, PTGES, and EGF) were finally identified. Biological changes in immune inflammatory response, cell cycle regulation, metabolic regulation, and immune microenvironment have been observed across different molecular subtypes. The above results were also validated based on single-cell analysis. Additionally, we also identified several significantly altered cell communication pathways, including COLLAGEN, PTN, LAMININ, SPP1, and VEGF. Finally, almost all these genes could well predict the occurrence of diabetic glomerulopathy based on receiver operating characteristic analysis and are associated with the glomerular filtration rate. These genes are differently expressed in various kidney diseases. <i>Conclusion</i>. The present study identified potential senescence-associated biomarkers and further explored the heterogeneity of diabetic glomerulopathy that might provide new insights into the diagnosis, assessment, management, and personalized treatment of DN.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"74 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139555031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Taichi Ochi, Stijn de Vos, Daan Touw, Petra Denig, Talitha Feenstra, Eelko Hak
{"title":"Tailoring Type II Diabetes Treatment: Investigating the Effect of 5-HTT Polymorphisms on HbA1c Levels after Metformin Initiation","authors":"Taichi Ochi, Stijn de Vos, Daan Touw, Petra Denig, Talitha Feenstra, Eelko Hak","doi":"10.1155/2024/7922486","DOIUrl":"https://doi.org/10.1155/2024/7922486","url":null,"abstract":"<i>Aims</i>. To investigate the effect of serotonin transporter (5-HTT) polymorphisms on change in HbA1c levels six months after metformin initiation in type 2 diabetes patients. <i>Materials and Methods</i>. Participants of PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALidation of biomarkers) within the GIANTT (Groningen Initiative to ANalyse Type 2 Diabetes Treatment) cohort who initiated metformin were genotyped for combined 5-HTTLPR/rs25531 (L<svg height=\"10.1524pt\" style=\"vertical-align:-0.04990005pt\" version=\"1.1\" viewbox=\"-0.0498162 -10.1025 6.17869 10.1524\" width=\"6.17869pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.0091,0,0,-0.0091,0,-5.741)\"></path></g></svg>L<svg height=\"10.1524pt\" style=\"vertical-align:-0.04990005pt\" version=\"1.1\" viewbox=\"-0.0498162 -10.1025 6.17869 10.1524\" width=\"6.17869pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.0091,0,0,-0.0091,0,-5.741)\"><use xlink:href=\"#g50-43\"></use></g></svg>, L<svg height=\"10.1524pt\" style=\"vertical-align:-0.04990005pt\" version=\"1.1\" viewbox=\"-0.0498162 -10.1025 6.17869 10.1524\" width=\"6.17869pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.0091,0,0,-0.0091,0,-5.741)\"><use xlink:href=\"#g50-43\"></use></g></svg>S<svg height=\"10.1524pt\" style=\"vertical-align:-0.04990005pt\" version=\"1.1\" viewbox=\"-0.0498162 -10.1025 6.17869 10.1524\" width=\"6.17869pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.0091,0,0,-0.0091,0,-5.741)\"><use xlink:href=\"#g50-43\"></use></g></svg>, and S<svg height=\"10.1524pt\" style=\"vertical-align:-0.04990005pt\" version=\"1.1\" viewbox=\"-0.0498162 -10.1025 6.17869 10.1524\" width=\"6.17869pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.0091,0,0,-0.0091,0,-5.741)\"><use xlink:href=\"#g50-43\"></use></g></svg>S<svg height=\"10.1524pt\" style=\"vertical-align:-0.04990005pt\" version=\"1.1\" viewbox=\"-0.0498162 -10.1025 6.17869 10.1524\" width=\"6.17869pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.0091,0,0,-0.0091,0,-5.741)\"><use xlink:href=\"#g50-43\"></use></g></svg>) and 5-HTT VNTR (STin 2.12, 12/-, and 10/-) polymorphisms, respectively. Multiple linear regression was applied to determine the change in HbA1c level from baseline date to six months across 5-HTTLPR/VNTR genotype groups, adjusted for baseline HbA1c, age, gender, triglyceride level, low-density lipoprotein level, and serum creatinine. <i>Results</i>. 157 participants were included, of which 56.2% were male. The average age was <span><svg height=\"8.69875pt\" style=\"vertical-align:-0.3499298pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.34882 32.222 8.69875\" width=\"32.222pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matr","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"86 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139515897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unveiling the Hidden Burden: Estimating All-Cause Mortality Risk in Older Individuals with Type 2 Diabetes","authors":"Dikang Pan, Hui Wang, Sensen Wu, Jingyu Wang, Yachan Ning, Jianming Guo, Cong Wang, Yongquan Gu","doi":"10.1155/2024/1741878","DOIUrl":"https://doi.org/10.1155/2024/1741878","url":null,"abstract":"<i>Background</i>. The mortality rate among older persons with diabetes has been steadily increasing, resulting in significant health and economic burdens on both society and individuals. The objective of this study is to develop and validate a predictive nomogram for estimating the 5-year all-cause mortality risk in older persons with T2D (T2D). <i>Methods</i>. We obtained data from the National Health and Nutrition Survey (NHANES). A random 7 : 3 split was made between the training and validation sets. By linking the national mortality index up until December 31, 2019, we ensured a minimum of 5 years of follow-up to assess all-cause mortality. A nomogram was developed in the training cohort using a logistic regression model as well as a least absolute shrinkage and selection operator (LASSO) regression model for predicting the 5-year risk of all-cause mortality. Finally, the prediction performance of the nomogram is evaluated using several validation methods. <i>Results</i>. We constructed a comprehensive prediction model based on the results of multivariate analysis and LASSO binomial regression. These models were then validated using data from the validation cohort. The final model includes four independent predictors: age, gender, estimated glomerular filtration rate, and white blood cell count. The C-index values for the training and validation cohorts were 0.748 and 0.762, respectively. The calibration curve demonstrates satisfactory consistency between the two cohorts. <i>Conclusions</i>. The newly developed nomogram proves to be a valuable tool in accurately predicting the 5-year all-cause mortality risk among older persons with diabetes, providing crucial information for tailored interventions.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"26 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139509692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Huaju Xiaoji Formula Regulates ERS-lncMGC/miRNA to Enhance the Renal Function of Hypertensive Diabetic Mice with Nephropathy","authors":"Zeng Zhang, Xiaodong Fu, Fengzhu Zhou, Duanchun Zhang, Yanqiu Xu, Zhaohua Fan, Shimei Wen, Yanting Shao, Zheng Yao, Yanming He","doi":"10.1155/2024/6942156","DOIUrl":"https://doi.org/10.1155/2024/6942156","url":null,"abstract":"<i>Background</i>. Better therapeutic drugs are required for treating hypertensive diabetic nephropathy. In our previous study, the Huaju Xiaoji (HJXJ) formula promoted the renal function of patients with diabetes and hypertensive nephropathy. In this study, we investigated the therapeutic effect and regulation mechanism of HJXJ in hypertensive diabetic mice with nephropathy. <i>Methods</i>. We constructed a mouse hypertensive diabetic nephropathy (HDN) model by treating mice with streptozotocin (STZ) and nomega-nitro-L-arginine methyl ester (LNAME). We also constructed a human glomerular mesangial cell (HGMC) model that was induced by high doses of sugar (30 mmol/mL) and TGF<i>β</i>1 (5 ng/mL). Pathological changes were evaluated by hematoxylin and eosin (H&E) staining, periodic acid Schiff (PAS) staining, and Masson staining. The fibrosis-related molecules (TGF<i>β</i>1, fibronectin, laminin, COL I, COL IV, <i>α</i>-SMA, and p-smad2/3) were detected by enzyme-linked immunosorbent assay (ELISA). The mRNA levels and protein expression of endoplasmic reticulum stress, fibrosis molecules, and their downstream molecules were assessed using qPCR and Western blotting assays. <i>Results</i>. Administering HJXJ promoted the renal function of HDN mice. HJXJ reduced the expression of ER stress makers (CHOP and GRP78) and lncMGC, miR379, miR494, miR495, miR377, CUGBP2, CPEB4, EDEM3, and ATF3 in HDN mice and model HGMCs. The positive control drugs (dapagliflozin and valsartan) also showed similar effects after treatment with HJXJ. Additionally, in model HGMCs, the overexpression of <i>CHOP</i> or <i>lncMGC</i> decreased the effects of HJXJ-M on the level of fibrosis molecules and downstream target molecules. <i>Conclusion</i>. In this study, we showed that the HJXJ formula may regulate ERS-lncMGC/miRNA to enhance renal function in hypertensive diabetic mice with nephropathy. This study may act as a reference for further investigating whether combining HJXJ with other drugs can enhance its therapeutic effect. The findings of this study might provide new insights into the clinical treatment of hypertensive diabetic nephropathy with HJXJ.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"1 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139509793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jing-Mei Yin, Yang Li, Jun-Tang Xue, Guo-Wei Zong, Zhong-Ze Fang, Lang Zou
{"title":"Explainable Machine Learning-Based Prediction Model for Diabetic Nephropathy","authors":"Jing-Mei Yin, Yang Li, Jun-Tang Xue, Guo-Wei Zong, Zhong-Ze Fang, Lang Zou","doi":"10.1155/2024/8857453","DOIUrl":"https://doi.org/10.1155/2024/8857453","url":null,"abstract":"The aim of this study is to analyze the effect of serum metabolites on diabetic nephropathy (DN) and predict the prevalence of DN through a machine learning approach. The dataset consists of 548 patients from April 2018 to April 2019 in the Second Affiliated Hospital of Dalian Medical University (SAHDMU). We select the optimal 38 features through a least absolute shrinkage and selection operator (LASSO) regression model and a 10-fold cross-validation. We compare four machine learning algorithms, including extreme gradient boosting (XGB), random forest, decision tree, and logistic regression, by AUC-ROC curves, decision curves, and calibration curves. We quantify feature importance and interaction effects in the optimal predictive model by Shapley additive explanation (SHAP) method. The XGB model has the best performance to screen for DN with the highest AUC value of 0.966. The XGB model also gains more clinical net benefits than others, and the fitting degree is better. In addition, there are significant interactions between serum metabolites and duration of diabetes. We develop a predictive model by XGB algorithm to screen for DN. C2, C5DC, Tyr, Ser, Met, C24, C4DC, and Cys have great contribution in the model and can possibly be biomarkers for DN.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"14 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139509797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Glucose Fluctuation Inhibits Nrf2 Signaling Pathway in Hippocampal Tissues and Exacerbates Cognitive Impairment in Streptozotocin-Induced Diabetic Rats","authors":"Haiyan Chi, Yujing Sun, Peng Lin, Junyu Zhou, Jinbiao Zhang, Yachao Yang, Yun Qiao, Deshan Liu","doi":"10.1155/2024/5584761","DOIUrl":"https://doi.org/10.1155/2024/5584761","url":null,"abstract":"<i>Background</i>. This research investigated whether glucose fluctuation (GF) can exacerbate cognitive impairment in streptozotocin-induced diabetic rats and explored the related mechanism. <i>Methods</i>. After 4 weeks of feeding with diets containing high fats plus sugar, the rat model of diabetes mellitus (DM) was established by intraperitoneal injection of streptozotocin (STZ). Then, GF was triggered by means of alternating satiety and starvation for 24 h. The weight, blood glucose level, and water intake of the rats were recorded. The Morris water maze (MWM) test was carried out to appraise the cognitive function at the end of week 12. Moreover, the morphological structure of hippocampal neurons was viewed through HE and Nissl staining, and transmission electron microscopy (TEM) was performed for ultrastructure observation. The protein expression levels of Nrf2, HO-1, NQO-1, Bax, Bcl-2, and Caspase-3 in the hippocampal tissues of rats were measured <i>via</i> Western blotting, and the mRNA expressions of Nrf2, HO-1, and NQO-1 were examined using qRT-PCR. Finally, Western blotting and immunohistochemistry were conducted to detect BDNF levels. <i>Results</i>. It was manifested that GF not only aggravated the impairment of spatial memory in rats with STZ-induced type 2 DM but also stimulated the loss, shrinkage, and apoptosis of hippocampal neurons. Regarding the expressions in murine hippocampal tissues, GF depressed Nrf2, HO-1, NQO-1, Bcl-2, and BDNF but boosted Caspase-3 and Bax. <i>Conclusions</i>. GF aggravates cognitive impairment by inhibiting the Nrf2 signaling pathway and inducing oxidative stress and apoptosis in the hippocampal tissues.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"52 4 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139499099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giovanni Sartore, Eugenio Ragazzi, Elena Deppieri, Annunziata Lapolla
{"title":"Is eGFR Slope a Novel Predictor of Chronic Complications of Type 2 Diabetes Mellitus? A Systematic Review and Meta-Analysis","authors":"Giovanni Sartore, Eugenio Ragazzi, Elena Deppieri, Annunziata Lapolla","doi":"10.1155/2024/8859678","DOIUrl":"https://doi.org/10.1155/2024/8859678","url":null,"abstract":"<i>Background</i>. Diabetic kidney disease affects approximately 40% of patients with type 2 diabetes mellitus (T2DM) and is associated with an increased risk of end-stage kidney disease (ESKD) and cardiovascular (CV) events, as well as increased mortality. Among the indicators of decline in renal function, the eGFR slope is acquiring an increasing clinical interest. The aim of this study was to evaluate, through a systematic review of the literature and meta-analysis of the collected data, the association between the decline of the eGFR slope, chronic complications, and mortality of T2DM patients, in order to understand whether or not the eGFR slope can be defined as a predictive indicator of complications in T2DM. <i>Methods</i>. The review and meta-analysis were conducted according to PRISMA guidelines considering published studies on patients with T2DM. A scientific literature search was carried out on PubMed from January 2003 to April 2023 with subsequent selection of scientific papers according to the inclusion criteria. <i>Results</i>. Fifteen studies were selected for meta-analysis. Risk analysis as hazard ratio (HR) indicated a significant association between all events considered (all-cause mortality, CV events, ESKD, and microvascular events) for patients with steeper eGFR slope decline than subjects with stable eGFR. Calculated HRs (with 95% CI) were as follows: for all-cause mortality, 2.31 (1.70-3.15); for CV events, 1.73 (1.43-2.08); for ESKD, 1.54 (1.45-1.64); and for microvascular events, 2.07 (1.57-2.73). Overall HR was 1.82 (1.72-1.92). <i>Conclusions</i>. An association between rapid eGFR decline and chronic diabetes complications was demonstrated, suggesting that eGFR slope variability significantly impacts the course of T2DM and that eGFR slope should be considered as a predictor for chronic complications in patients with T2DM. According to the obtained results, the therapeutic management of the patient with diabetes should not focus exclusively on glycaemic control, and particular attention should be paid to preserve renal function.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"11 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139483281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Huihui Zhang, Jun Lu, Jie Gao, Wenjun Sha, Xinhua Cai, Mai Re Yan Mu Rouzi, Yuanying Xu, Wenjun Tang, Tao Lei
{"title":"Association of Monocyte-to-HDL Cholesterol Ratio with Endothelial Dysfunction in Patients with Type 2 Diabetes","authors":"Huihui Zhang, Jun Lu, Jie Gao, Wenjun Sha, Xinhua Cai, Mai Re Yan Mu Rouzi, Yuanying Xu, Wenjun Tang, Tao Lei","doi":"10.1155/2024/5287580","DOIUrl":"https://doi.org/10.1155/2024/5287580","url":null,"abstract":"<i>Aims</i>. To explore the relationship between monocyte-to-HDL cholesterol ratio (MHR) and endothelial function in patients with type 2 diabetes (T2DM). <i>Methods</i>. 243 patients diagnosed with T2DM were enrolled in this cross-sectional study. Patients were divided into two groups by flow-mediated dilation (FMD) quintile as nonendothelial dysfunction (<span><svg height=\"9.64479pt\" style=\"vertical-align:-1.11981pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.52498 39.383 9.64479\" width=\"39.383pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,6.877,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,18.46,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,31.752,0)\"></path></g></svg><span></span><span><svg height=\"9.64479pt\" style=\"vertical-align:-1.11981pt\" version=\"1.1\" viewbox=\"42.9651838 -8.52498 25.495 9.64479\" width=\"25.495pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,43.015,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,49.255,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,52.219,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,58.459,0)\"></path></g></svg>)</span></span> and endothelial dysfunction (<span><svg height=\"9.16198pt\" style=\"vertical-align:-0.6370001pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.52498 39.383 9.16198\" width=\"39.383pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"><use xlink:href=\"#g190-71\"></use></g><g transform=\"matrix(.013,0,0,-0.013,6.877,0)\"><use xlink:href=\"#g190-78\"></use></g><g transform=\"matrix(.013,0,0,-0.013,18.46,0)\"><use xlink:href=\"#g190-69\"></use></g><g transform=\"matrix(.013,0,0,-0.013,31.752,0)\"></path></g></svg><span></span><span><svg height=\"9.16198pt\" style=\"vertical-align:-0.6370001pt\" version=\"1.1\" viewbox=\"42.9651838 -8.52498 25.495 9.16198\" width=\"25.495pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,43.015,0)\"><use xlink:href=\"#g113-55\"></use></g><g transform=\"matrix(.013,0,0,-0.013,49.255,0)\"><use xlink:href=\"#g113-47\"></use></g><g transform=\"matrix(.013,0,0,-0.013,52.219,0)\"><use xlink:href=\"#g113-53\"></use></g><g transform=\"matrix(.013,0,0,-0.013,58.459,0)\"><use xlink:href=\"#g121-35\"></use></g></svg>).</span></span> The relationship between MHR and FMD was analyzed using Spearman’s correlation, partial correlation, and multiple logistic regression analysis. ROC curve was fitted to evaluate the ability of MHR to predict endothelial dysfunction. <i>Results</i>. Endothelial dysfunction was present in 193 (79%) patients. Patients with endothelial dysfunction had higher MHR (<span><svg height=\"11.7782pt\" style=\"vertical-align:-3.42938pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.34882 18.973 11.7782\" width=\"18.973pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"18 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139421334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pathology of Ketoacidosis in Emergency of Diabetic Ketoacidosis and Alcoholic Ketoacidosis: A Retrospective Study","authors":"Katsumasa Koyama, Takatoshi Anno, Yukiko Kimura, Fumiko Kawasaki, Kohei Kaku, Koichi Tomoda, Hideaki Kaneto","doi":"10.1155/2024/8889415","DOIUrl":"https://doi.org/10.1155/2024/8889415","url":null,"abstract":"This study is aimed at examining which factors are useful for the diagnosis and distinction of ketoacidosis. We recruited 21 diabetic ketoacidosis (DKA) and alcoholic ketoacidosis (AKA) patients hospitalized in Kawasaki Medical School General Medical Center from April 2015 to March 2021. Almost all patients in this study were brought to the emergency room in a coma and hospitalized. All patients underwent blood gas aspiration and laboratory tests. We evaluated the difference in diagnosis markers in emergencies between DKA and alcoholic ketoacidosis AKA. Compared to AKA patients, DKA patients had statistically higher values of serum acetoacetic acid and lower values of serum lactate, arterial blood pH, and base excess. In contrast, total ketone bodies, <i>β</i>-hydroxybutyric acid, and <i>β</i>-hydroxybutyric acid/acetoacetic acid ratio in serum did not differ between the two patient groups. It was shown that evaluation of each pathology such as low body weight, diabetes, liver dysfunction, and dehydration was important. It is important to perform differential diagnosis for taking medical histories such as insulin deficiency, alcohol abuse, or starvation as the etiology in Japanese subjects with DKA or AKA. Moreover, it is important to precisely comprehend the pathology of dehydration and alcoholic metabolism which would lead to appropriate treatment for DKA and AKA.","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"120 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139396783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hae Jin Kim, Jung Hyun Noh, Min Kyong Moon, Sung Hee Choi, Seung-Hyun Ko, Eun-Jung Rhee, Kyu Yeon Hur, In-Kyung Jeong
{"title":"A Multicenter, Randomized, Open-Label Study to Compare the Effects of Gemigliptin Add-on or Escalation of Metformin Dose on Glycemic Control and Safety in Patients with Inadequately Controlled Type 2 Diabetes Mellitus Treated with Metformin and SGLT-2 Inhibitors (SO GOOD Study)","authors":"Hae Jin Kim, Jung Hyun Noh, Min Kyong Moon, Sung Hee Choi, Seung-Hyun Ko, Eun-Jung Rhee, Kyu Yeon Hur, In-Kyung Jeong","doi":"10.1155/2024/8915591","DOIUrl":"https://doi.org/10.1155/2024/8915591","url":null,"abstract":"<i>Background</i>. We aimed to compare efficacy and safety between gemigliptin add-on and escalation of the metformin dose in patients with inadequately controlled type 2 diabetes mellitus (T2DM) despite treatment with metformin and SGLT2 inhibitors. <i>Methods</i>. This study was a multicenter, randomized, open-label, active-controlled, parallel-group comparative study. Patients with T2DM uncontrolled on metformin and SGLT2 inhibitors were randomized to receive gemigliptin 50 mg as an add-on (GEM group, <span><svg height=\"8.55521pt\" style=\"vertical-align:-0.2063904pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.34882 17.789 8.55521\" width=\"17.789pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,10.158,0)\"></path></g></svg><span></span><span><svg height=\"8.55521pt\" style=\"vertical-align:-0.2063904pt\" version=\"1.1\" viewbox=\"21.3711838 -8.34882 12.679 8.55521\" width=\"12.679pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,21.421,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,27.661,0)\"></path></g></svg>)</span></span> or escalation of the metformin dose (500 mg, MET group, <span><svg height=\"8.55521pt\" style=\"vertical-align:-0.2063904pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.34882 17.789 8.55521\" width=\"17.789pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"><use xlink:href=\"#g113-111\"></use></g><g transform=\"matrix(.013,0,0,-0.013,10.158,0)\"><use xlink:href=\"#g117-34\"></use></g></svg><span></span><span><svg height=\"8.55521pt\" style=\"vertical-align:-0.2063904pt\" version=\"1.1\" viewbox=\"21.3711838 -8.34882 12.679 8.55521\" width=\"12.679pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,21.421,0)\"><use xlink:href=\"#g113-52\"></use></g><g transform=\"matrix(.013,0,0,-0.013,27.661,0)\"></path></g></svg>)</span></span> for 24 weeks. The primary endpoint was the change in glycosylated hemoglobin (HbA1c) from baseline to week 24. <i>Results</i>. At weeks 12 and 24, the reduction in HbA1c levels was significantly greater in the GEM group than in the MET group (GEM vs. <span><svg height=\"9.2207pt\" style=\"vertical-align:-0.4673605pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.75334 38.3 9.2207\" width=\"38.3pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,11.583,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,18.915,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,30.669,0)\"><use xlink:href=\"#g117-34\"></use></g></svg><span></span><svg height=\"9.2207pt\" style=\"vertical-align:-0.4673605pt\" version=\"1.1\" viewbox=\"41.8821838 -8.75334 49.68 9.2207\" width=\"49.68pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www","PeriodicalId":15576,"journal":{"name":"Journal of Diabetes Research","volume":"51 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139104610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}