Search Results (1,142)

Diabetic cardiomyopathy (DCM) is a severe complication of diabetes, in which ferroptosis is a key pathogenic mechanism. This study examines how alpha-linolenic acid (ALA), a plant-derived omega-3 polyunsaturated fatty acid, protects against damage from ferroptosis in DCM. Using an in vitro model of H9C2 cardiomyocytes treated with high glucose/palmitate, combined with a high-fat diet and mouse model of low-dose streptozotocin (STZ)-induced diabetes, this research demonstrates for the first time that ALA significantly alleviates cardiac dysfunction and prevents ferroptosis. Mechanistically, ALA inhibits STAT3 phosphorylation by activating the AMPK signaling pathway, thereby reducing NCOA4-mediated ferritinophagy and mitigating mitochondrial iron overload and reactive oxygen species accumulation. It also enhances the function of the SLC7A11/GSH/GPX4 axis, reducing lipid peroxidation (LPO)-induced ferroptosis. Collectively, these findings indicate that ALA protects against diabetic cardiomyopathy by coordinating the regulation of ferritinophagy and antioxidant defense through the AMPK-STAT3 pathway, offering a potential therapeutic strategy for disease management. Full article

The therapeutic potential of functional nutrients has garnered considerable attention for enhancing resilience signaling and counteracting the damage to human health caused by microplastic pollutants. The intricate interactions between microplastics (MPs) and nanoplastics (NPs) and functional nutrients, including polyphenols, flavonoids, phenylpropanoids, phenolic acids, diterpenoids, and triterpenoids, have been shown to improve blood–brain barrier (BBB) homeostasis and brain function by inhibiting oxidative stress, ferroptosis, and inflammation linked to the pathogenesis of metabolic and brain disorders. Interestingly, nutrients exhibit biphasic dose–response effects by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway and stress-resilience proteins at minimum doses, thereby preventing or blocking MP and NP-induced damage. Notably, chronic exposure to environmental pollutants causes aberrant regulation of NFE2L2 gene and related antioxidant signaling, which can exacerbate selective susceptibility to brain insulin resistance under inflammatory conditions. This, in turn, impairs glucose metabolism and facilitates β-amyloid (Aβ) plaque synthesis leading to the onset and progression of Alzheimer’s disease (AD), also known as “Type 3 diabetes”. This pathological process triggered by oxidative stress, inflammation, and ferroptosis creates a vicious cycle that ultimately contributes to neuronal damage and loss. The review aims to investigate the therapeutic potential of functional nutrients targeting the Nrf2 pathway and stress resilience proteins to regulate epigenetic alterations, and to explore the underlying molecular mechanisms using innovative in vitro platforms for the development of promising preventive strategies and personalized nutritional interventions to attenuate oxidative stress, ferroptosis, and inflammation, with the goal of ultimately improving clinical outcomes. Full article

Glaucoma is a neurodegenerative disease characterized by progressive degeneration of optic nerve axons and loss of retinal ganglion cells (RGCs). Although elevated intraocular pressure (IOP) is a major risk factor, many patients develop glaucoma with normal IOP, highlighting the need for neuroprotective therapies. Sitagliptin, a dipeptidyl peptidase-4 inhibitor, has shown beneficial effects in diabetes-induced retinal neurodegeneration. This study aimed to evaluate whether sitagliptin eye drops, previously effective in diabetes-induced retinal neurodegeneration, could prevent corticosteroid-induced glaucoma. Glaucoma was induced in mice by periocular injection of dexamethasone (DEX) once weekly for five weeks. Sitagliptin or vehicle eye drops were administered from day 14 to 35. Untreated mice served as controls. DEX treatment caused significant loss of RGC bodies and optic nerve axons compared to controls, which was prevented by sitagliptin eye drops (p < 0.001), without affecting IOP. Sitagliptin also inhibited DEX-induced activation of macroglia and microglia and prevented oligodendrocyte loss. Furthermore, it suppressed overexpression of galectin-3 and gamma-synuclein in the optic nerve head (ONH) (p < 0.001), key mediators of inflammation and apoptosis. Sitagliptin eye drops exert a potent neuroprotective effect against corticosteroid-induced glaucoma, supporting their potential as a novel therapeutic strategy for glaucoma. Full article

Background: The high prevalence of overweight and obesity in Singapore necessitates scalable primary prevention strategies. This study evaluated the short-term effectiveness of FitterLife, a 12-week, digitally delivered, group-based behavioural weight management programme targeting at-risk adults without diabetes or hypertension in the community. Methods: In a retrospective matched cohort study, we compared 306 FitterLife participants (enrolled from October 2021 to January 2025) with 5087 controls identified from a population health data mart, matched on age, sex, ethnicity, and baseline body mass index (BMI). The primary outcome was achieving ≥5% weight loss or a ≥1 kg/m² BMI reduction at 12 weeks. Programme effectiveness was analysed using propensity score matching (1:1) and inverse probability weighted regression. Mixed-effects models assessed weight/BMI trajectories and modified Poisson regression identified behavioural factors associated with success. Results: After matching, FitterLife participants were more likely to achieve the weight loss target than controls (45.7% vs. 13.7%, coefficient = 0.32, 95% confidence interval [CI]: 0.26–0.38) and were over three times as likely to succeed (Adjusted incidence rate ratio [aIRR] = 3.37, 95% CI: 2.87–3.93). The programme group showed significant reductions in weight (−2.23 kg, 95% CI: −2.57 to −1.90) and BMI (−0.86 kg/m², 95% CI: −0.95 to −0.73) at the end of programme. Higher session attendance and improved behavioural factors were associated with success. Conclusions: FitterLife was effective in achieving clinically significant short-term weight loss in a real-world setting. The findings demonstrate the potential of a scalable, behavioural theory-informed, virtual group model as a viable primary prevention strategy within national chronic disease management efforts. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease worldwide. It greatly increases hepatic cirrhosis and cancer, cardiovascular disease, and chronic kidney disease. Despite the rising frequency of MASLD in Saudi Arabia, public understanding of its management is lacking. Objective: This study seeks to evaluate public knowledge, attitudes, and management barriers related to MASLD, thereby informing future educational and preventive strategies. Methods: A cross-sectional study was conducted from November 2023 to October 2024, involving 502 participants across Saudi Arabia, employing a modified self-administered online questionnaire. Data was analyzed using SPSS 25. Descriptive statistics and Chi-square tests were used to investigate correlations between knowledge or attitude levels and demographics, with a significance threshold of p < 0.05. Results: Less than half of the respondents who took part (47.2%) had heard of MASLD. Of them, 24.9% had good knowledge, 38.2% had fair knowledge, and 36.9% had low understanding. There were strong links between knowledge and age, education, and job status, but not between knowledge and gender (p = 0.514). People were somewhat aware that being overweight (48.4%) and having high cholesterol (51.8%) were risk factors, but they often had wrong ideas regarding diabetes and high blood pressure. Only 7.8% of those surveyed said they had been formally diagnosed, and 74.4% of those who had been were given advice on how to change their lifestyle. Barriers to management included the idea that lifestyle change alone suffices (46.7%), the absence of medical advice (46.7%), and insufficient disease awareness (33.3%). Conclusions: The research shows that many Saudis are unaware of MASLD and have misconceptions about it. Targeted health education programs, greater provider–patient communication, and primary care MASLD knowledge are needed to close these gaps and promote disease prevention and management. Full article

Background: Obesity is a chronic disease that has negative health consequences for children. Peer support models have been used to manage chronic diseases like diabetes; however, little is known about how a peer support intervention might promote healthy infant growth to prevent pediatric obesity. The aim of this project was to explore parental perspectives on how a peer support intervention might be developed to support healthy infant weight gain and nutrition. Methods: Data were collected from November 2022 to October 2023 at a single pediatric primary care clinic. Semi-structured interviews explored parents’ perspectives of how a peer parent coach could promote healthy infant nutrition and growth. Interviews focused on (1) common infant feeding and nutrition questions, (2) the role and importance of peer support during the newborn period, and (3) strategies for addressing and facilitating connections to food-related resources and addressing food insecurity. Results: A total of 18 interviews were conducted. Average parental age was 32.1 years (range 20–46 years). Thirty-three percent of the participants identified as Black, 28% identified as White, 11% identified as Asian, and the remaining identified as Other or preferred not to report. Half of the sample reported a household income of <$20,000, 67% reported having public insurance, and 11% reported household food insecurity. Themes that emerged included: peer parent coaches can (1) provide emotional support to families with young infants, (2) education focused on infant nutrition, and (3) facilitate connections with nutrition resources. Participants also noted the importance of understanding a family’s unique culture when counseling on infant growth and nutrition. Conclusions: Multiple themes were identified about how a peer support intervention could support healthy infant nutrition and growth. Future work should test the feasibility and acceptability of a peer support intervention to promote healthy infant weight gain. Full article

Physical exercise is a potent non-pharmacological strategy for the prevention and management of chronic non-communicable diseases (NCDs), including type 2 diabetes, cardiovascular diseases, obesity, and certain cancers. Growing evidence demonstrates that the benefits of exercise extend beyond its physiological effects and are largely mediated by coordinated molecular and cellular adaptations. This review synthesizes current knowledge on the key mechanisms through which exercise modulates metabolic health, emphasizing intracellular signaling pathways, epigenetic regulation, and myokine-driven inter-organ communication. Exercise induces acute and chronic activation of pathways such as AMPK, PGC-1α, mTOR, MAPKs, and NF-κB, leading to enhanced mitochondrial biogenesis, improved oxidative capacity, refined energy sensing, and reduced inflammation. Additionally, repeated muscle contraction stimulates the release of myokines—including IL-6, irisin, BDNF, FGF21, apelin, and others—that act through endocrine and paracrine routes to regulate glucose and lipid metabolism, insulin secretion, adipose tissue remodeling, neuroplasticity, and systemic inflammatory tone. Epigenetic modifications and exercise-responsive microRNAs further contribute to long-term metabolic reprogramming. Collectively, these molecular adaptations establish exercise as a systemic biological stimulus capable of restoring metabolic homeostasis and counteracting the pathophysiological processes underlying NCDs. Understanding these mechanisms provides a foundation for developing targeted, personalized exercise-based interventions in preventive and therapeutic medicine. Full article

Background: Oral health and cardiovascular disease share common inflammatory pathways, yet the relationship between tooth loss and post-myocardial infarction (MI) heart failure remains underexplored. Objective: To investigate the association between tooth loss and heart failure among patients with acute MI. Methods: In this cross-sectional study, 200 patients with documented MI were evaluated for tooth loss, cardiac function, and comorbidities. Heart failure was defined as an ejection fraction <40% or clinical diagnosis. Patients were categorized by tooth loss (0–8, 9–20, >20 missing teeth). Multivariate logistic regression was used to identify independent predictors of heart failure. Model performance was assessed using receiver operating characteristic (ROC) analysis. Results: The prevalence of heart failure was 38%. Mean ejection fraction declined progressively with greater tooth loss (50.1%, 44.8%, and 38.4% across the three categories; p for trend <0.001). After adjustment for age, sex, diabetes, and smoking, severe tooth loss (>20 missing teeth) remained independently associated with heart failure (adjusted OR 2.45; 95% CI, 1.15–5.23; p = 0.02). The final model demonstrated good discriminative ability (AUC = 0.78). Conclusions: Extensive tooth loss is strongly associated with heart failure among MI patients, suggesting a potential link between oral health deterioration and adverse cardiac remodeling. Integrating dental assessment into cardiovascular care may enhance risk stratification and promote holistic prevention strategies. Full article

Diabetes mellitus and its microvascular complications, including diabetic retinopathy (DR), present significant health challenges. DR is a leading cause of vision impairment and blindness among working-age individuals in developed countries. The prevalence of DR continues to rise, underscoring the need for more precise diagnostic and therapeutic strategies. Due to its multifactorial nature and despite advancements in understanding DR pathophysiology, predicting its onset and progression remains challenging. Traditional screening and treatment methods often fall short of addressing the heterogeneous nature of the disease, underscoring the need for personalised therapeutic strategies. Recent research has highlighted the vital role of genetic biomarkers in the development and progression of DR, paving the way for a precision medicine approach. Personalised eye care in patients with diabetes aims to accurately predict the risk of DR progression and visual loss in real time. A precision medicine approach that utilises genetic biomarkers offers a promising pathway for personalised diagnosis and treatment strategies. Each DR case is distinct in phenotype, genotype, and therapeutic response, making personalised therapy crucial for optimising outcomes. Advancements in genomics, including genome-wide association studies (GWAS) and next-generation sequencing (NGS), have identified numerous genetic markers associated with DR susceptibility and severity. Emerging evidence underscores the critical role of genetic factors, which account for 25–50% of the risk of developing DR. Advances in identifying genetic markers, such as gene polymorphisms and human leukocyte antigen associations, along with the development of targeted drugs, highlight a promising future for personalised medicine in DR. By identifying specific genetic variants associated with DR, we can enhance prevention and early diagnosis, tailor personalised treatment plans, and more accurately predict disease progression. This represents a critical step toward personalised medicine in DR management. Integrating genetic and epigenetic biomarkers into clinical models may transform DR care through earlier diagnosis and precision-guided interventions, gearing it toward precision ophthalmology. Full article

Background/Objective: Mexico has experienced an increase in the prevalence of overweight and obesity among schoolchildren, predisposing them to type 2 diabetes mellitus. In addition, rapid eating has been increasingly implicated in the dysregulation of appetite control, greater energy intake, and adverse metabolic outcomes in children. Prior evidence indicates that a faster eating pace is associated with excess adiposity and lipid metabolism. This study aimed to compare cardiovascular risk factors (waist circumference, waist-to-height ratio, body mass index (BMI), and lipid profile) among school-aged Mexican children according to self-reported eating speed. Design: Cross-sectional observational study. Setting: Public elementary schools in Mexico. Participants: Ninety school-aged children (52.2% female) aged 6–12 years old. Eating speed was assessed using an adapted and validated self-administered questionnaire. Intervention: No intervention was applied; participants were classified into slow-, normal-, or fast-eating groups according to their usual eating speed as reported in the instrument, which includes questions regarding self-perception and family perception. Main Outcome Measure: The primary outcomes included anthropometric parameters (BMI, waist circumference, and waist-to-height ratio), blood pressure (systolic and diastolic), and biochemical markers of lipid metabolism (triglycerides, total cholesterol, and HDL cholesterol). Analysis: Descriptive statistics were computed, and comparisons across eating speed groups were performed using one-way ANOVA for continuous variables and chi-square tests for categorical data. Statistical significance was set at p < 0.05. Results: Among the 90 children evaluated, 17.7% were classified as fast eaters. Although gender differences in eating speed were not statistically significant (χ²= 4.607, p = 0.100), a higher proportion of boys were classified as fast eaters. Children in the fast-eating group exhibited significantly higher BMI (1.4 kg/m²), waist circumference (4 cm greater), and modest elevations in triglyceride and total cholesterol levels, alongside lower HDL cholesterol, relative to their slow-eating peers (all p < 0.05). Among all variables, only diastolic blood pressure differed significantly across groups (F = 3.92, p = 0.022), with fast eaters showing the highest values. Nevertheless BMI, waist circumference, triglyceride levels, and total cholesterol were not statistically significant in the logistic regression, and HDL cholesterol demonstrated an association close to 95% [0.051 (0.011–0.226)] to a protective factor against cardiometabolic events, estimating an effect size of 1.64 using Cohen’s d, which is considered a large effect, when compared to their slower-eating peers. Conclusions and Implications: Faster eating speed was consistently associated with unfavorable anthropometric and lipid profile indicators, aligning with previous evidence linking rapid eating to early cardiometabolic alterations. These findings emphasize the relevance of including eating behavior assessments in pediatric cardiovascular risk screenings and prevention strategies. Full article

Objective: To establish a reliable machine-learning-based model for predicting the risk of lower limb amputation in patients with diabetic foot ulcers and to provide quantitative evidence for clinical decision-making and individualized prevention strategies. Methods: This retrospective study analyzed data from 149 hospitalized diabetic foot ulcer patients treated at Beijing Shijitan Hospital between January 2019 and December 2022. Patients were divided into amputation and non-amputation groups according to clinical outcomes. Candidate predictors—including infection biomarkers, vascular parameters, and nutritional indices—were first screened using the least absolute shrinkage and selection operator algorithm. Subsequently, a support vector machine model was trained and internally validated via five-fold cross-validation to estimate amputation risk. Model performance was evaluated by discrimination, calibration, and clinical utility analysis. Results: Among all enrolled variables, C-reactive protein and Wagner grade were identified as independent predictors of amputation (p < 0.05). The optimized support vector machine model achieved excellent discrimination, with an area under the Receiver Operating Characteristic curve of 0.89, and demonstrated a moderate level of calibration (Hosmer–Lemeshow χ² = 19.614, p = 0.012). Decision curve analysis showed a net clinical benefit of 0.351 when the threshold probability was set at 0.30. The model correctly classified 82.4% of cases in internal validation, confirming its predictive robustness and potential for clinical application. Conclusions: C-reactive protein and Wagner grade are key determinants of amputation risk in diabetic foot ulcer patients. The support vector machine-based prediction model exhibits strong accuracy, clinical interpretability, and personalized interventions. Full article

Background: Gestational diabetes mellitus (GDM) represents a pregnancy-specific associated pathology that bears a heavy burden on patients and also on the healthcare system. GDM displays an increasing incidence and short- and long-term materno-fetal consequences. Its prevention strategies include lifestyle interventions, diet changes, gestational weight gain control, moderate-intensity exercise, and smoking cessation. GDM screening is performed in the second half of pregnancy between 24 and 28 gestational weeks. Treatment options include medical nutrition therapy and pharmacologic therapy. In most cases, optimum glycemic control is obtained by medical nutrition therapy alone. Although there are screening and treatment options, the medical system in Romania lacks homogeneity in the diagnosis and further management of pregnancies complicated with GDM. There is an urgent need to improve the healthcare system and the basic medical knowledge of the population and to find efficient strategies, which include a national diabetes in pregnancy guideline to ensure pregnancy monitoring, GDM screening, and the diagnosis and personalized management of cases in order to promote good pregnancy outcomes and minimize adverse pregnancy events. Full article

Background/Objectives: Metabolic syndrome (MetS) increases the risk of type 2 diabetes and cardiovascular disease. We aimed to identify the key metabolic predictors of MetS in a Central European cohort and to compare classical statistics with modern machine learning (ML) models. Methods: We analysed 956 adults from the Lower Silesia Healthy Donors cohort. Clinical, anthropometric, biochemical, and lifestyle variables were collected using standardised procedures. Group differences were tested with Mann–Whitney U tests and effect sizes. A multivariable logistic regression (outcome: binary MetS defined as ≥3 harmonised components, MetS_bin) estimated adjusted odds ratios. In parallel, ML models (logistic regression, Random Forest, XGBoost, LightGBM, CatBoost) were trained with stratified 5-fold cross-validation. Performance was evaluated by accuracy, F1-macro, and area under the receiver-operating characteristic curve (ROC AUC). Model interpretability used SHAP values. Results: Overweight/obese participants had higher fasting glucose (median 92.0 vs. 84.6 mg/dL), fasting insulin (9.9 vs. 6.6 µU/mL), and systolic blood pressure (134 vs. 121 mmHg) and lower HDL cholesterol (53 vs. 66 mg/dL) compared to normal-BMI individuals (all p < 0.001, r ≈ 0.39–0.41). Participants with a higher waist circumference also showed markedly increased HOMA-IR (2.16 vs. 1.34; p < 0.001). In multivariable logistic regression, waist circumference, BMI, triglycerides, HDL cholesterol, fasting glucose, and systolic blood pressure were independently associated with MetS, yielding a test ROC-AUC of 0.98 and PR-AUC of 0.88. Machine learning models further improved discrimination: Random Forest, XGBoost, LightGBM, and CatBoost all achieved very high performance (test ROC-AUC ≥ 0.99, PR-AUC ≥ 0.98), with CatBoost showing the best cross-validated PR-AUC (~0.99) and favourable calibration. SHAP analyses consistently highlighted fasting glucose, triglycerides, HDL cholesterol, waist circumference, and systolic blood pressure as the most influential predictors. Conclusions: Combining classical regression with modern gradient-boosting models substantially improves the identification of individuals at risk of MetS. CatBoost, XGBoost, and LightGBM delivered near-perfect discrimination in this Central European cohort while remaining explainable with SHAP. This framework supports clinically meaningful risk stratification—including a “subclinical” probability zone—and may inform targeted prevention strategies rather than purely reactive treatment. Full article

Oral health is a critical factor in maintaining overall health, and its association with systemic diseases, including cardiovascular disease and diabetes mellitus, has been extensively investigated. Effective plaque removal through proper toothbrushing techniques is fundamental for preventing dental caries and periodontal diseases. Despite standardized guidelines, many individuals fail to adhere to correct brushing techniques, thereby increasing the risk of oral diseases. To address this issue, this study proposes a fine-grained toothbrushing region recognition approach incorporating six machine learning classifiers and two inertial measurement units (IMUs), which are embedded in the toothbrush holder and mounted on the right wrist of the participant, respectively. By analyzing the continuous motion signals, the proposed hierarchical approach is capable of identifying brushing and transition activities and subsequently recognizing specific toothbrushing regions based on the predicted brushing activities. To further improve recognition reliability, post-processing strategies such as contextual smoothing and majority voting are applied. Experimental results demonstrate that random forest achieves the highest recognition accuracy of 96.13%, sensitivity of 96.10%, precision of 95.51%, and F1-score of 95.60%. The results indicate that the proposed approach is both effective and feasible for providing fine-grained toothbrushing region recognition in toothbrushing monitoring. Full article

Background/Objectives: Colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM) are two of the most rapidly rising chronic diseases globally. Despite appearing distinct, an emerging body of literature identifies shared etiopathogenic mechanisms mediated by gut microbiota. This review synthesizes 38 peer-reviewed studies to evaluate the compositional, metabolic, immune, and translational intersections of gut dysbiosis in the pathogenesis of T2DM-associated CRC. Methods: This narrative literature review examined 38 primary research articles (human and animal studies) retrieved from PubMed, Scopus, and Embase. Studies were selected based on relevance to the microbiota-mediated mechanisms linking T2DM and CRC, with a focus on compositional analysis, metabolomic shifts, immune activation, and therapeutic interventions. Results: The findings highlight a mechanistically rich overlap between T2DM and CRC through shared dysbiosis, characterized by depletion of SCFA-producing taxa (e.g., Faecalibacterium, Roseburia, Butyricicoccus), enrichment of pathobionts (e.g., Fusobacterium nucleatum, Peptostreptococcus), and the disruption of mucosal immunity and epithelial integrity. Metabolic shifts include reduced butyrate and increased toxic bile acids (e.g., deoxycholic acid), TMAO, and oxidative metabolites, while immune dysregulation features elevated LPS, IL-1β, CXCL3, and NF-κB signaling. Therapeutically, microbiota modulation via diet, metformin, and probiotics shows promise. Conclusions: Gut microbiota lies at the nexus of T2DM and CRC, functioning as a modifiable mediator rather than a passive bystander. Future research should prioritize longitudinal, multi-omic, and intervention-driven studies to enable personalized prevention and treatment strategies. Full article