Journal of Diabetes Research最新文献

Diabetic foot infections (DFIs) represent a significant and prevalent complication of diabetes, contributing to considerable morbidity, mortality, and healthcare costs globally. These infections, ranging from mild monomicrobial cases to severe polymicrobial infections, often require hospitalization and can result in limb amputation. The microbial etiology of DFIs is diverse, with common pathogens including Staphylococcus aureus (S. aureus), Escherichia coli, Pseudomonas aeruginosa, and various anaerobes. The pathogenic mechanisms of DFIs are complex, involving peripheral neuropathy, vascular insufficiency, and immune dysfunction, all exacerbated by a hyperglycemic state. Despite advances in treatment, the increasing prevalence of antimicrobial resistance, particularly among methicillin-resistant S. aureus (MRSA) strains, presents a major challenge to managing these infections effectively. This review systematically examines the pathogenesis, diagnostic techniques, microbial profiles, and treatment strategies for DFIs, with an emphasis on antibiotic resistance and new therapeutic approaches. Furthermore, the article highlights the need for a multidisciplinary approach, including early diagnosis, appropriate antibiotic therapy, advanced wound care, and patient education to mitigate the risk of severe complications. Given the rising global burden of diabetes, improved management of DFIs remains critical for reducing the incidence of amputations and minimizing the economic burden on healthcare systems.

Background: Hyperbaric oxygen treatment (HBOT) is clinically used to improve oxygen supply to hypoperfused tissues under certain conditions. HBOT can decrease the incidence of autoimmune diabetes in nonobese diabetic mice by reducing apoptosis and increasing β-cell proliferation. HBOT ameliorates glucose tolerance in Type 2 diabetes (T2D) mellitus patients, but the underlying mechanism needs further investigation. Methods: We used a diet-induced T2D mouse model and a genetic mouse model (ob/ob mice) to evaluate the effects of HBOT on serum glucose levels in mice. The body weights and blood glucose levels of the mice were measured weekly. An oral glucose tolerance test (OGTT) was performed 12 weeks after the start of the experiment. All the mice were euthanized, and the serum and liver tissues were collected to test the total cholesterol, triglycerides, alanine aminotransferase, aspartate aminotransferase, malondialdehyde, and antioxidant enzymes. Results: Our results demonstrated that HBOT can delay/attenuate the onset of diet-associated T2D in wild-type mice. However, HBOT had no significant effects on blood glucose or T2D incidence in ob/ob mice. Furthermore, we found that HBOT improved glucose tolerance and liver steatosis in diet-induced T2D model mice but not in ob/ob mice. Our results indicated that the effects of HBOT on T2D were dependent at least partly on the presence of leptin. Conclusion: Our study offers a rationale for using serum leptin as a predictor of clinical outcomes of HBOT and elucidates possible reasons why many patients may experience HBOT failure.

Background: Diabetes mellitus (DM) is a growing global health issue, with diabetic retinopathy (DR) being a significant complication causing vision loss. Whether the Controlling Nutritional Status (CONUT) score is predictive of DR has yet to be understood. Objective: This study is aimed at exploring the relationship between CONUT scores and DR using national health data. Methods: Data from adults aged ≥ 20 years diagnosed with DM were extracted from the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2016 and analyzed retrospectively. DR was identified based on participants' self-reported physician diagnosis. The CONUT score was calculated from serum albumin, lymphocyte count, and cholesterol levels, obtained from the NHANES lab profiles. Logistic regression analysis was used to determine the relationship between CONUT scores and the presence of DR. All data were analyzed in 2024. Results: Data from 3494 NHANES participants (representing 17,619,250 people in the United States after weighting) were analyzed. After adjusting for relevant confounders, multivariable analysis revealed that each one-point increase in CONUT score was significantly associated with increased odds of DR by 11% (adjusted odds ratio [aOR] = 1.11, confidence interval: 1.02-1.22). Stratified analyses revealed significant associations between CONUT score and DR among patients with a DM duration of ≥ 10 years (aOR = 1.14, 95% CI: 1.03-1.26) and those younger than 60 years (continuous: aOR = 1.19, 95% CI: 1.03-1.37; high vs. low: aOR = 1.57, 95% CI: 1.05-2.35). Conclusions: Poor nutritional status, indicated by higher CONUT scores, is associated with an increased likelihood of DR in adults with DM. The relationship was particularly evident among those with a DM duration of ≥ 10 years and younger than 60 years. These findings highlight the potential of CONUT score assessments as part of comprehensive diabetes care.

Background: Type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) are highly prevalent in Kazakhstan, with metformin as the first-line therapy. However, individual variability in treatment response and adverse effects necessitates pharmacogenetic evaluation. This study is aimed at assessing the clinical and biochemical efficacy of metformin in Kazakh patients with MetS, T2DM, or both and at identifying pharmacogenetic markers associated with treatment response and tolerability. Methods: A prospective cohort of 206 Kazakh patients (MetS: n = 44, MetS + T2DM: n = 123, T2DM: n = 39) was enrolled. Clinical, anthropometric, and biochemical parameters were measured at baseline and 3 months after metformin therapy. Ten SNPs previously implicated in metformin pharmacogenetics were genotyped. Associations with treatment efficacy (HbA1c reduction and glycemic goal achievement) and dyspeptic side effects were analyzed using ANOVA, logistic regression, and chi-square tests. Results: Metformin significantly improved weight, blood pressure, glucose, and lipid profiles across all groups. The SNPs rs2289669 (SLC47A1) and rs3792269 (CAPN10) were significantly associated with greater HbA1c reduction, glycemic goal achievement, and risk of dyspepsia. The rs11212617 variant showed a modest association with treatment efficacy. Conclusions: Metformin is effective across diverse metabolic phenotypes in the Kazakh population, with genetic variation contributing to interindividual differences in efficacy and tolerability. Pharmacogenetic profiling may improve personalized diabetes care.

Introduction: This study is aimed at examining the associations of alcohol consumption and cigarette smoking with insulin secretion and resistance and the effect modification by body mass index (BMI) in middle-aged men without a history of diabetes in rural Vietnam. Materials and Methods: The study included data from 1102 men without diabetes, aged between 40 and 60 years, who participated in the Khánh Hòa Cardiovascular Study conducted between June 2019 and 2020. Fasting blood samples were collected to measure insulin and plasma glucose. Alcohol consumption was categorized as no consumers or consumers (< 1, 1-1.9, and ≥ 2 standard drinks per day). Smoking was categorized as never, former, and current smokers (≤ 10 or ≥ 11 cigarettes per day). The homeostatic model assessment (HOMA) was used to assess insulin secretion (HOMA-beta) and insulin resistance (HOMA-IR). A multilevel linear regression model was used to examine the associations of alcohol consumption and smoking with HOMA-beta and HOMA-IR. Effect modification by BMI was tested using the likelihood ratio test, and a set of stratified analyses according to BMI (23 kg/m²) was performed. Results: Alcohol consumption showed a dose-response association with low HOMA-beta in both the unadjusted and BMI-adjusted models. Cigarette smoking was not associated with HOMA-beta in either the unadjusted or BMI-adjusted models. Alcohol consumption was not associated with HOMA-IR when BMI was unadjusted, but the highest alcohol consumer group showed a significantly lower HOMA-IR after adjustment for BMI. Current smoking was significantly associated with lower HOMA-IR when BMI was unadjusted, which association became marginally significant after adjusting for BMI. Conclusions: Alcohol consumption was associated with reduced insulin secretion. Smoking was marginally associated with lower insulin resistance, potentially mediated by low BMI. Longitudinal studies are required to explore the mechanisms underlying the association between alcohol consumption, smoking, and glucose metabolism.

Background: Recent studies have primarily focused on the impact of environmental factors on gestational diabetes mellitus (GDM) in singleton pregnancies, with limited research on their effects in twin pregnancies. This study investigates how seasonal variations and environmental exposures impact GDM incidence and its subtypes in twin pregnancies, a high-risk group. Methods: In this retrospective analysis of 3769 twin pregnancies, we categorized recruited participants into GDM and non-GDM groups. We examined the effect of the screening season on oral glucose tolerance test (OGTT) glucose values and the incidence of GDM and its subtypes. Multivariable logistic regressions adjusted for confounders assessed the impact of first and second trimester temperatures and air pollutants on GDM risk. Interaction terms evaluated the combined effects of environmental factors on GDM incidence. Results: Seasonal changes significantly influenced GDM risk, with summer presenting the highest risk (p < 0.05). The first trimester's cooler temperatures were inversely related to GDM; T _mean was significantly and negatively associated with 1-h PG and AUC for glucose, with adjusted β (95% CI) of -0.009 (-0.017, -0.001) and -0.719 (-1.406, -0.031), respectively. While warmer second trimester temperatures increased the risk, T _mean was positively associated with FBG, 1-h PG, 2-h PG, and AUC for glucose, with adjusted β (95% CI) of 0.003 (0.001, 0.005), 0.018 (0.009, 0.026), 0.019 (0.011, 0.027), and 1.723 (0.998, 2.448), respectively. Air pollutant exposure showed varying correlations with GDM risk, with ozone (O₃) levels consistently posing a risk. Higher O₃ exposure in the first and second trimesters was associated with increased odds of GDM, with OR (95% CI) of 1.057 (1.004, 1.112) and 1.052 (1.011, 1.096), respectively. Interaction analysis indicated that certain environmental conditions in the first trimester could reduce GDM risk, while others, particularly involving O₃, increased it. Conclusion: Environmental temperatures and air pollutants, especially O₃, are associated with GDM risk in twin pregnancies, with differing effects between trimesters. These findings suggest that environmental factors should be considered in GDM screening and prevention strategies for twin pregnancies. Further research is needed to understand the underlying mechanisms and to develop trimester-specific interventions.

The prevalence and mortality rates of Type 2 diabetes mellitus (T2DM) continue to increase, imposing a significant burden on individuals and nations worldwide. The pancreas plays an important role in T2DM development, while exercise is a crucial nonpharmacological treatment. Although the pancreas comprises various cell types, current studies on the effects of exercise on diabetes have mainly focused on the beta cells. In this study, we aimed to enhance our understanding of the effects of exercise on other pancreatic cell types. This was aimed at facilitating the comprehensive analysis of the processes and principles by which exercise protects and enhances pancreatic function. Six-week-old male db/db mice were trained on a treadmill at a speed of 9 m/min for 10 weeks (50 min/day, 5 days/week). Single-cell RNA sequencing (scRNA-seq) was performed to analyze cell types in the pancreas. The results showed that exercise improved the body weight and pancreas profile of db/db mice. The scRNA-seq demonstrated that the pancreas was composed of 12 cell types, with obvious changes in endothelial cells (ECs) among all groups. Further subtype analysis suggested that ECs could be annotated into five subtypes, with capillary ECs and unknown EC 1 presenting remarkable differences among the groups. Additionally, Gene Ontology (GO) enrichment analysis showed the roles of regulation of EC proliferation and response to injury for capillary ECs and unknown EC 1, respectively. The two EC subtypes may be involved in the protective effect of exercise against pancreatic injury in db/db mice.

Diabetes and its complications are a major global public health issue. Conventional Western medicine has limitations in efficacy and safety in managing complications, while acupuncture, with multitarget regulation and low side effects, serves as an important supplementary therapy. This review discusses how acupuncture relieves macrovascular complications, such as angina and cerebral reperfusion, by inhibiting NF-κB, improving vascular endothelial function, and regulating autonomic nerves. In addition, acupuncture delays microvascular complications, such as retinopathy and proteinuria via vasodilation, anti-inflammatory effects, antioxidative effects, and neurotrophic promotion. Acupuncture also benefits other complications by enhancing microcirculation and neuroendocrine function. The mechanisms of acupuncture involve regulating the metabolic-inflammatory-neurovascular network, activating pathways (such as GLP-1 and SDF-1), and repairing cellular structures. Modern technologies-including artificial intelligence (AI) for individualized acupoint selection, functional magnetic resonance imaging (fMRI) for central regulation visualization, and biomaterial combination for diabetic foot repair-enhance the precision of acupuncture. However, clinical translation of acupuncture faces the following challenges: fragmented mechanisms; insufficient clinical evidence, including small samples, short follow-ups, and a lack of long-term safety data when used with new hypoglycemics; and technical nonstandardization, such as inconsistent acupoint selection, nonuniform operation parameters, and poor adaptability of AI to traditional Chinese medicine syndrome differentiation. Future research should deepen the exploration of the neuroendocrine-immune network via interdisciplinary integration, conducting large-sample long-term trials, establishing standardized protocols, and validating AI/fMRI-assisted precision acupoint selection to accelerate the transition of acupuncture from adjuvant to precision therapy to improve patients' quality of life.

Background and Purpose: Diabetic retinopathy (DR) is a chronic complication that affects approximately one-third of individuals with diabetes and represents a serious threat to vision. In recent years, increasing attention has been given to biomarkers and cytokines related to inflammation for their roles in disease mechanisms. This study is aimed at investigating the association between growth differentiation factor-15 (GDF-15) and the risk of DR in Handan, China, and developing a predictive model based on patients' clinical characteristics. Methods: Between January and July 2024, patients with Type 2 diabetes mellitus (T2DM) treated at Handan Central Hospital were enrolled and classified into two groups: 74 patients without DR (NDR) and 79 with DR. Stepwise regression was used to select variables, and a logistic regression model was constructed to predict the risk of DR. Additionally, 17 healthy individuals (control group, CG) were included to explore GDF-15 distribution across different populations. Results: Compared to the NDR group, patients with DR showed significantly lower levels of HB, ALB, CO₂, and 2h-CP and considerably higher levels of DvT, UREA, HDL-C, ApoA-1, and GDF-15. A logistic regression model incorporating six key variables-ALB, ApoA-1, CO₂, DvT, 2h-CP, and GDF-15-was developed, yielding an accuracy of 0.936 (95% CI: [0.786, 0.992]), which outperformed the model based solely on GDF-15. Comparison among the three groups showed that GDF-15 levels were highest in the DR group and increased progressively with diabetes severity. Conclusion: GDF-15 levels are significantly associated with the presence and progression of DR. The logistic regression model demonstrates high predictive value, suggesting that GDF-15 may serve as a promising biomarker for the early diagnosis and intervention of DR.

Aim: The aim was to design a study protocol for evaluating the efficacy of an interactive podcast program to assist Type 1 diabetes patients transitioning from adolescence to young adulthood. Design: The study design is a parallel 1:1 two-arm randomized controlled trial emphasizing treatment fidelity through standardized interventions and improved adherence to reduce biases in outcomes. Methods: This theoretical-based study will be conducted at two medical centers in northern Taiwan, enrolling 88 participants. Participants will be randomly assigned to either the experimental group, receiving the interactive podcast program "Living With Type 1 Diabetes to Grown-Up," or the active control group, receiving the e-book "Transitioning from Adolescence to Early Adulthood: The Ins and Outs of Type 1 Diabetes." The 3-month intervention will release 36 podcast episodes at a rate of three per week. Data will be collected at baseline, postintervention, and at 3 and 6 months postintervention to evaluate the efficacy of the intervention on disease control outcomes, emotional distress, diabetes knowledge, self-care behaviors, self-management confidence, interpersonal distress, and family conflict. Conclusion: This first evidence-based, rigorously designed podcast program will offer valuable guidelines for future interventions aimed at helping adolescents with Type 1 diabetes transition to adulthood. Impact: This study's positive findings could support podcasts as an innovative tool for helping adolescents with Type 1 diabetes transition to young adulthood. Additionally, it may provide valuable insights for future research and health policymakers, potentially transforming diabetes management approaches. Reporting Method: The authors adhered to CONSORT guidelines to ensure transparency and reliability. Patient or Public Contribution: There is no patient or public contribution. This Paper Contributes to the Wider Global Clinical Community: This paper provides an evidence-based framework for using podcasts to support self-management and well-being in adolescents with Type 1 diabetes and offers insights for future digital health strategies. Trial Registration: ClinicalTrials.gov identifier: NCT06464640.