Search Results (11,467)

Background: Hypertension (HTN) and type 2 diabetes mellitus are major global health challenges, and diabetic nephropathy (DN) is a critical complication of diabetes. Although observational studies link HTN to DN progression, causal evidence remains limited. We investigated the potential causal relationship between HTN and DN and quantified the global burden of HTN-attributable type 2 diabetic nephropathy (HTN-T2DN). Methods: We integrated two-sample Mendelian randomization (MR), Bayesian weighted MR, and sensitivity analyses with Global Burden of Disease (GBD) 2021 analyses. The burden of HTN-T2DN was assessed from 1990 to 2021 and projected to 2045. Results: MR provided genetic evidence supporting a potential causal role of HTN in DN (inverse-variance weighted odds ratio = 4.219, 95% CI: 1.807–9.853; p = 0.001). Globally, HTN-T2DN deaths increased to 50,689 and DALYs to 1,151,216 in 2021. Females had higher age-standardized mortality and DALY rates than males, and low-middle sociodemographic index (SDI) regions had the highest burden. By 2045, deaths and DALYs were projected to reach 162,392 and 4.04 million, respectively. Conclusions: HTN may play a potential causal role in DN development and progression. Strengthened blood pressure control, early screening, and tailored policies are essential, particularly for women, older adults, and populations in lower-SDI settings. Full article

Background/Objectives: There has been a growing concern about excessive caffeine consumption among heavy green tea drinkers on health outcomes, such as cardiovascular diseases or cancer. We evaluated the association between green tea consumption and risk of all-cause mortality in Vietnam. Methods: We used data from the Hanoi Prospective Cohort Study, an ongoing study comprising 42,146 participants aged 10 or older in Northern Vietnam who have been followed up between 2007 and 2019. Green tea intake was derived from a validated semi-quantitative food frequency questionnaire. We performed a Cox proportional hazard regression model to calculate the hazard ratio (HR) and respective 95% confidence intervals (95% CIs) for the association between green tea consumption and risk of all-cause mortality, adjusted for potential confounding factor. Results: After a median follow-up of 11 years (range: 0.13–11.64 years), we identified 2494 deaths. Overall, there was an inverse association between green tea intake and risk of all-cause mortality (HR_{perSDincrement} = 0.93; 95% CI, 0.89–0.97, P_trend < 0.001). This pattern was more pronounced in males (HR_{perSDincrement} = 0.93; 95% CI, 0.89–0.97, P_trend < 0.001) but not in females (HR_{perSDincrement} = 0.94; 95% CI, 0.86–1.02, P_trend = 0.12; P_{heterogeneity} = 0.81). In stratified analysis, the inverse association pattern was seen in both younger and old age groups, in individuals with BMI < 23 kg/m², in both ever and never smokers, among ever alcohol drinkers and never coffee drinkers, and in individuals with and without history of type 2 diabetes (P_{heterogeneity} = 0.31). Conclusions: Findings from the current study, the first prospective cohort study in Vietnam, suggest a protective effect of green tea consumption on risk of all-cause mortality. Further studies are warranted to validate our findings in similar population and settings. Full article

Background/Objectives: Chronic hepatitis C (CHC) infection is an independent risk factor for developing type 2 diabetes mellitus (T2DM). However, it is unknown if antiviral treatment, especially with direct-acting antivirals (DAAs), changes long-term glycemic outcomes. Methods: We conducted a retrospective comparative cohort study of 2489 patients with chronic hepatitis C (CHC) in southern Taiwan between 2005 and 2022 who underwent treatment with either an interferon (IFN)-based or direct-acting antiviral agent (DAA) regimen. Given the distinct treatment eras of IFN and DAA therapies, potential temporal confounding was considered in the analytical design. Patients with existing diabetes or co-infections were excluded. The incidence of new-onset T2DM and longitudinal HbA1c levels were compared between treatment groups over a mean follow-up period of 2.56 years. Results: DAA-treated patients demonstrated a lower crude cumulative incidence of T2DM compared with IFN-treated patients (2.46% vs. 6.91%). However, adjusted analyses did not demonstrate a statistically significant difference between treatment groups. The cumulative risk appeared to plateau after the third year among DAA recipients. Post-therapy, HbA1c levels remained stable in both groups at between 5.5% and 6.5% over as long as five years. Splitting regression revealed that BMI ≥ 30 kg/m², and not treatment type or achieved SVR, was an independent T2DM risk factor. The lowest rates of diabetes incidence were associated with pan-genotypic DAA regimens. Conclusion: DAA-treated patients showed lower crude T2DM incidence than IFN-treated patients; however, this difference was not consistently significant after adjustment for baseline factors. Viral eradication may be associated with favorable metabolic trends; however, the present findings do not establish a causal protective effect against incident T2DM. While increased BMI remained an independent predictor of post-treatment diabetes risk. Full article

Dipeptidyl peptidase-4 (DPP-4) is an established therapeutic target in the treatment of type 2 diabetes mellitus (T2DM), primarily due to its role in regulating incretin activity and glucose homeostasis. Although clinically approved DPP-4 inhibitors are widely used, their moderate efficacy has driven the search for novel compounds with improved properties. In this context, natural products have attracted considerable attention as a source of structurally diverse and biologically active molecules. At the same time, molecular docking has emerged as a key computational tool for the identification and evaluation of potential DPP-4 inhibitors. This review summarizes and critically analyzes current molecular docking studies of natural compounds targeting DPP-4. Over 150 studies were evaluated with respect to docking methodologies, selection of protein structures, and validation strategies. The results reveal substantial variability in computational protocols. Frequently used protein structures include ligand-bound DPP-4 models such as 1X70 and 6B1E. Among the investigated compounds, flavonoids represent the most extensively studied class, followed by alkaloids, phenolics, terpenoids, and peptides. Despite numerous reports of favorable binding interactions within the DPP-4 active site, many studies rely solely on docking results without further validation. The limited use of molecular dynamics simulations and experimental assays highlights a significant gap in the current literature. Overall, while molecular docking provides valuable preliminary insights, improved standardization and integration with complementary approaches are essential to enhance the reliability and translational relevance of in silico findings. Full article

The Mediterranean diet (MedDiet) has emerged as a promising dietary strategy for the prevention and management of type 2 diabetes mellitus (T2DM). This narrative review provides a comprehensive synthesis linking the biological pathways of the MedDiet with established clinical evidence. Adherence to this traditional dietary pattern—characterized by a high intake of fiber, complex carbohydrates, antioxidants, and healthy fats—has demonstrated significant benefits in terms of glycemic control, enhanced insulin sensitivity, and overall metabolic health. Mechanistically, the review explains how the MedDiet improves health by modulating key physiological processes, including anti-inflammatory and antioxidant pathways, the regulation of branched-chain amino acid metabolism, the enhancement of short-chain fatty acid production via gut microbiota modulation, and upregulated incretin effects. Importantly, this review explains how the MedDiet complements modern medications, including glucagon-like peptide-1 (GLP-1) receptor agonists and sodium–glucose cotransporter-2 (SGLT-2) inhibitors. By integrating molecular mechanisms with human clinical outcomes, this narrative review addresses multiple aspects of the MedDiet in both the prevention and management of T2DM including glycemic control, weight management, and cardiovascular risk reduction, rendering it a valuable dietary strategy for both the prevention and treatment of this chronic condition. Full article

Background: Exercise plays a crucial role in the prevention and management of type 2 diabetes. During self-motion, optic flow provides visual information about heading direction and influences postural control. This study investigated postural responses and muscle activation in individuals with type 2 diabetes exposed to optic flow stimuli simulating self-motion, and examined whether these responses varied according to habitual physical activity over 12 months. Methods: Surface electromyographic (EMG) and stabilometric data were collected from 23 individuals during quiet standing under different visual motion conditions. Participants were classified as physically active or inactive based on standardized criteria. EMG activity was recorded bilaterally from the tibialis anterior and soleus muscles at baseline, 6, and 12 months. Center of pressure (COP) displacement was measured using two force platforms. Results: Stabilometric analysis revealed a significant effect of visual stimulus on COP displacement in both antero-posterior and medio-lateral directions, as well as on COP speed, indicating that optic flow modulates postural control. COP speed changes over time differed by sex, while medio-lateral sway showed time-dependent variations across sides and physical activity groups. EMG analysis showed a significant effect of visual stimulus on soleus activation, with no consistent effects for tibialis anterior. Conclusions: Optic flow significantly modulated postural control and lower-limb muscle activation in individuals with type 2 diabetes. Preliminary differences in response profiles associated with habitual physical activity level were observed, though these should be interpreted cautiously given the exploratory nature of the study. Larger, adequately powered studies are warranted to further investigate these associations. Full article

Background/Objectives: Advanced technologies in type 1 diabetes mellitus (T1DM) management have reshaped the strategies used to achieve optimal glucose control. Continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems are effective alternatives to multiple daily injections (MDI). This study aims to evaluate glycemic regulation in children and adolescents transitioning from MDI to insulin pumps and to raise awareness among patients and their families regarding the benefits of these systems. Methods: 50 pediatric patients with T1DM (24 males, 26 females; mean age 10.76 ± 3.2 years) were evaluated. Cycle 1 established MDI metrics 3 months pre-transition. In cycle 2, patients transitioned either to an AID system (Medtronic MiniMed 780G, (Northridge, CA, USA), 78%), or a non-automated system (Omnipod DASH, 22%). Data were assessed at 3 and 6 months post-initiation. Parameters assessed were glycosylated hemoglobin (HbA1c), time in range (TIR), time above range (TAR), time below range (TBR), glucose management indicator (GMI) and coefficient of variation (CV). Results: The cohort exhibited a statistically significant increase in TIR (p = 0.0038) with mean values of 70.9% at 3 months and 73.2% at 6 months. TAR significantly reduced (p = 0.033) to 26.5% and 24.3% at 3 and 6 months, respectively. Sub-analysis in the AID group revealed a marked increase in TIR (p = 0.0001) alongside significant reductions in TAR (p = 0.0009) and GMI (p = 0.03). Conclusions: Transitioning from MDI to insulin pump therapy, particularly AID systems, leads to modest but significant improvements in specific sensor metrics (TIR, TAR) in real-world clinical practice. The consistency of these results across age groups indicates that AID systems can successfully overcome pediatric and adolescent diabetes management challenges. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder associated with substantial long-term morbidity and mortality. Routinely collected anthropometric, biochemical, and hematological variables may contain useful discriminatory information for data-driven classification. This study aimed to compare the apparent classification performance of multiple machine learning algorithms for distinguishing individuals with and without T2DM using routinely obtained clinical parameters in a single-center dataset. Methods: This single-center observational study included 160 adults (95 females, 65 males) evaluated at the Endocrinology Outpatient Clinic of Gaziantep Islam Science and Technology University, Faculty of Medicine, Ersin Arslan Training and Research Hospital. The dataset comprised anthropometric measurements, biochemical markers, and complete blood count parameters. SMOTE was applied only within the training folds to address class imbalance and to avoid information leakage. Following fold-internal data preprocessing, which included imputing missing values and feature standardization where appropriate, the dataset was evaluated using stratified 5-fold cross-validation. SHAP analysis was performed to interpret the model predictions. A calibration curve was used to assess the model’s reliability. Eight supervised machine learning models were evaluated with and without HbA1c: Logistic Regression, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Decision Tree, Random Forest, Extra Trees, Gaussian Naive Bayes, and k-Nearest Neighbors. Model performance was evaluated using accuracy, sensitivity, specificity, and F1 score, and ROC curves were used as a diagnostic tool. Results: The models were evaluated in two different ways: with and without HbA1c. Random Forest demonstrated the best classification performance in the cross-validated evaluation; without HbA1c, it achieved 92.2% accuracy, 93.9% sensitivity, 97.9% specificity, and a 95.9% F1 score. When HbA1c was included, it achieved 98.0% accuracy, 97.9% sensitivity, 98.8% specificity, and a 99.0% F1 score. Decision Tree and Extra Trees demonstrated strong performance with accuracy rates of 87.6% and 92.8%, respectively, without HbA1c, and 90% and 93.5% when HbA1c was included; in contrast, KNN yielded the lowest accuracy rate (70.6%). Overall, tree-based models performed better than linear classifiers on this dataset. Conclusions: Machine learning models based on routine clinical and anthropometric variables demonstrated promising performance for T2DM classification in this single-center dataset; tree-based approaches yielded the most promising results. Including HbA1c improved the models’ ability to classify individuals with and without T2DM. However, since HbA1c was included both as a predictor and as part of the operational definition of the diabetes group, the findings should be interpreted with caution due to the risk of target leakage. Therefore, these results should be considered exploratory rather than evidence of clinically applicable predictive performance, and an independent external validation study should be conducted prior to clinical application. Full article

Hypertrophic cardiomyopathy (HCM) is the most common inherited myocardial disorder and a major cause of heart failure (HF) and sudden cardiac death. Although sarcomeric gene mutations initiate the disease, increasing evidence identifies oxidative stress, mitochondrial dysfunction, and maladaptive nutrient signaling as key drivers of disease progression. Enhanced reactive oxygen species (ROS) production in HCM promotes energetic impairment, calcium mishandling, fibrosis, and the activation of pro-hypertrophic pathways, while disrupting protein quality control and endothelial function. Despite recent therapeutic advances, effective disease-modifying strategies targeting these molecular mechanisms remain limited. Sodium–glucose cotransporter 2 inhibitors (SGLT2i), originally developed for type 2 diabetes, have demonstrated robust cardioprotective effects in HF independent of glycemic control. Beyond their renal actions, SGLT2i modulate myocardial metabolism, reduce oxidative stress, improve mitochondrial function, restore sodium and calcium homeostasis, and attenuate inflammation and maladaptive mTOR activation. Emerging preclinical and translational data suggest that these pleiotropic mechanisms may counteract key pathophysiological processes underlying HCM. This review summarizes the molecular interplay between oxidative stress and hypertrophic remodeling in HCM and explores the rationale for SGLT2 inhibition as a potential disease-modifying therapeutic strategy. Full article

Background: Pathological aggregation of islet amyloid polypeptide (IAPP) contributes to β-cell dysfunction in type 2 diabetes. Our previous studies demonstrated that caveolin-1 (Cav-1) deficiency protects β-cells from palmitate-induced apoptosis. Microarray profiling further indicated that Cav-1 silencing alters IAPP expression. This study aimed to investigate the effects of Cav-1 depletion on IAPP secretion and expression and to explore the potential involvement of thioredoxin-interacting protein (TXNIP). Methods: We performed lentiviral-mediated Cav-1 knockdown in NIT-1 cells and isolated murine islets, and simultaneously generated an inducible β-cell-specific Cav-1 knockout (iβ-Cav1 KO) mouse model. IAPP secretion and expression were assessed by ELISA, Western blot, qPCR and immunofluorescence. The expression of IAPP-processing enzymes (PAM, PC1, and PC2) and degradation factors (IDE and BACE2) was examined. Co-immunoprecipitation (Co-IP) and immunofluorescence were performed to investigate the interaction between Cav-1 and TXNIP. Results: Cav-1 depletion significantly reduced both IAPP secretion and expression in vitro and in vivo. High-fat-diet-fed iβ-Cav1 KO mice exhibited the lowest serum IAPP levels. Mechanistically, Cav-1 depletion was associated with downregulation of PAM, PC1, and PC2 and upregulation of IDE and BACE2. Additionally, Cav-1 depletion decreased TXNIP expression. Immunofluorescence revealed co-localization of Cav-1 and TXNIP, and co-immunoprecipitation further demonstrated their direct physical interaction. Conclusions: Cav-1 is essential for IAPP secretion and expression in β-cells. The direct physical interaction between Cav-1 and TXNIP suggests that TXNIP may mediate the regulatory effects of Cav-1 on IAPP processing or secretion. These findings identify the Cav-1–TXNIP axis as a potential target for mitigating IAPP-related β-cell dysfunction. Full article

Background/Objectives: Exercise is pivotal for glycemic control in type 2 diabetes mellitus (T2DM), yet the relative efficacy of various exercise modalities remains inconclusive. This network meta-analysis aimed to evaluate and provide a preliminary ranking of exercise interventions on HbA1c levels in adults with type 2 diabetes mellitus, to facilitate clinically relevant network comparisons and to generate evidence for future large-scale comparative trials. Methods: A systematic review and network meta-analysis were conducted in accordance with PRISMA guidelines. Electronic databases (PubMed, MEDLINE, Cochrane Library, CINAHL, and ProQuest) were searched from inception to Dec 2024. Randomized controlled trials evaluating exercise interventions in adults with T2DM were included. Risk of bias was assessed independently by two reviewers using the JBI critical appraisal tool. The primary outcome was the change in HbA1c level. Results: Six randomized controlled trials involving a total of 511 participants (256 in the treatment group and 255 in the control group) were included in the final analysis. Both high-intensity interval training (MD = −0.322; 95% CI: −0.559 to −0.084; p = 0.008) and yoga (MD = −0.366; 95% CI: −0.534 to −0.198; p < 0.001) significantly reduced HbA1c compared with the active control. Although the preliminary ranking analysis suggested a higher probability of effectiveness for yoga (SUCRA 1) than for HIIT (SUCRA 0.5), the indirect comparison revealed no statistically significant difference in HbA1c reduction between the two interventions (MD = −0.044; 95% CI: −0.335 to 0.247; p = 0.766). Conclusions: These findings provide preliminary, evidence-generating; however, given the sparse network and absence of head-to-head trials, the treatment hierarchy should be interpreted with extreme caution and selected based on patients’ preferences and tolerance. Registration: PROSPERO [CRD42025650162]. Full article

Regular consumption of excess sugar is linked to nutrition-based diseases, including gut problems, Non-Alcoholic Fatty Liver Disease, and Type 2 Diabetes Mellitus. Increasing sweetness perception is a novel technique to decrease sugar consumption. This experiment compared the sweetness perception of sweetened and unsweetened almond milk in response to different virtual environments with music and visuals. Two music types, the classical song Goldberg Variations, BMV. 998-Variation 13 and a jazz song generated by AI were used. Additionally, fall and spring forest backgrounds were generated by the Blockade Labs 3D image generator. Each participant tasted sweetened and unsweetened almond milk in music-only, background-only, and combination music and background environments. Results revealed significant differences in sweetness ratings for music type (p = 0.015) and between milk types (p < 0.001). Viscosity rating differed significantly between backgrounds (p = 0.04) and by milk type (p < 0.001). Liking ratings varied significantly between backgrounds (p < 0.001) and between music genres (p = 0.011). The results suggest that altering music and background may be a strategy to change sweetness and viscosity perception in unsweetened beverages. Full article

Background: Post-COVID syndrome represents a significant medical and public health challenge, particularly among older adults and individuals with type 2 diabetes mellitus (T2DM), in whom disturbances in immune and metabolic homeostasis may contribute to the development and persistence of symptoms following SARS-CoV-2 infection. Objective: To investigate the clinical, immunological, and metabolic characteristics of post-COVID syndrome in older adults with T2DM. Methods: A cross-sectional comparative study was conducted involving 141 patients aged ≥ 60 years who were evaluated more than one year after SARS-CoV-2 infection. Clinical data, anthropometric measurements, complete blood count parameters, biochemical markers, glycated hemoglobin (HbA1c), and SARS-CoV-2-specific IgG antibodies were assessed. Statistical analyses were performed using nonparametric methods, while Pearson’s χ² test was applied for categorical variables. A p-value < 0.05 was considered statistically significant. Results: Symptoms consistent with post-COVID syndrome one year after SARS-CoV-2 infection were identified in 53.2% of participants. No significant differences in anthropometric characteristics, hematological parameters, or most biochemical markers were observed between patients with and without post-COVID syndrome. Patients with T2DM exhibited higher fasting glucose, HbA1c, and SARS-CoV-2–specific IgG antibody levels, reflecting underlying metabolic characteristics and differences in humoral immune responses during the late post-COVID period. Conclusions: Post-COVID syndrome symptoms were frequently observed among older adults at the time of assessment, more than one year after SARS-CoV-2 infection, despite normalization of most laboratory parameters. In patients with T2DM, higher glucose, HbA1c, and antibody levels likely reflect underlying metabolic characteristics rather than a direct effect of post-COVID syndrome. Further longitudinal studies are warranted to clarify the long-term clinical significance of the observed metabolic and immunological findings. Full article

This paper analyzes the role of cereal products in the diet of individuals with disorders of carbohydrate metabolism, with particular emphasis on their impact on postprandial glycemia and the risk of developing type 2 diabetes (T2D). Cereal products, as the main source of dietary carbohydrates, also provide dietary fiber, minerals, B vitamins, and key bioactive compounds such as β-glucans, arabinoxylans, resistant starch (RS), and polyphenols. These components may reduce the rate of starch digestion and glucose absorption in the small intestine by increasing the viscosity of intestinal contents or by directly inhibiting digestive enzymes such as α-glucosidase. It has been shown that fermentation of these compounds by the gut microbiota leads to the production of short-chain fatty acids (SCFAs), which improve insulin sensitivity and stimulate the secretion of incretin hormones such as GLP-1. A literature review confirms that regular consumption of whole-grain products is associated with a reduced risk of T2D, whereas refining processes and excessive grain fragmentation lead to an increased glycemic index of products. Based on clinical guidelines and a narrative synthesis of the available literature, minimally processed whole-grain products were identified as a fundamental component of dietary therapy for diabetes, which is illustrated by the cereal product pyramid presented in the paper. This review involved a comprehensive literature search in PubMed, Scopus, and Web of Science using relevant keywords. Peer-reviewed articles, reviews, and meta-analyses (mainly 2000–2025) were included based on their relevance. Full article

Background/Objectives: The increasing burden of non-communicable diseases, together with accelerating environmental degradation, highlights the urgent need for sustainable dietary patterns that promote both human and planetary health. The Mediterranean diet (MedDiet), traditionally followed in countries bordering the Mediterranean basin, has gained recognition as a model of sustainable nutrition due to its well-documented health benefits and relatively low environmental impact. However, its broader role within sustainable food systems requires comprehensive and interdisciplinary evaluation. The aim of this review is to provide a state-of-the-art synthesis of the evidence on the MedDiet as a sustainable dietary pattern, integrating its health, environmental, economic, and socio-cultural dimensions. Methods: This state-of-the-art narrative review synthesizes evidence from peer-reviewed literature on the MedDiet and sustainability. Relevant studies were identified through major scientific databases, focusing on publications addressing nutritional, environmental, economic, and socio-cultural dimensions. Both observational and interventional studies, as well as modeling and life cycle assessment analyses, were included. Additional sources from international organizations and policy reports were incorporated to contextualize global trends and challenges. Results: High adherence to the MedDiet is consistently associated with a reduced risk of cardiovascular disease, type 2 diabetes, cancer, and all-cause mortality. From an environmental perspective, the MedDiet is associated with lower greenhouse gas emissions, reduced land and water use, and enhanced biodiversity conservation compared with Western dietary patterns. Economically, it may represent a cost-effective dietary model and support local food systems when grounded in traditional practices, although affordability varies across contexts. Socio-culturally, the MedDiet promotes food heritage, culinary skills, and social cohesion. Nevertheless, globalization, urbanization, and the increasing consumption of ultra-processed foods have contributed to declining adherence, posing significant challenges to its sustainability and scalability. Moreover, the sustainability benefits of the MedDiet seem to be context-dependent rather than intrinsic, raising several challenges and limitations for its adoption. Conclusions: The MedDiet should be viewed not as a definitive solution to global food-system challenges but as a valuable reference model that illustrates how dietary practices can contribute simultaneously to human health, environmental sustainability, and cultural continuity. Modern sustainable dietary strategies should build upon the strengths of the MedDiet while recognizing its limitations, embracing contextual adaptation, and addressing the structural determinants that shape food choices. Full article