Search Results (1,234)

Objectives: This study sought to understand dietary behaviors among US Muslim people with Type 2 diabetes while managing diabetes and fasting during Ramadan, identify key psychosocial factors influencing behaviors, and examine how identified factors influence diet behaviors and health outcomes from the patient’s perspective. Methods: The study employed community-engaged research principles and qualitative research design. Twenty-two adult Muslim adults living with Type 2 diabetes for over 6 months participated in semi-structured one-on-one interviews. Participants were recruited from five US communities using purposive sampling. Three trained researchers used abductive coding, combining deductive and inductive approaches, to analyze the data. Results: Six main themes emerged from the data: (1) changes in dietary habits during Ramadan; (2) strong influence of religious, cultural and social practices on dietary behaviors; (3) variable self-efficacy in managing dietary behaviors; (4) impact of prior habits and current blood glucose status; (5) decision-making based on diabetes-related health outcomes (e.g., experiencing low blood sugar); (6) participants’ perception of Ramadan as an opportunity for sustainable behavioral changes. Conclusions: This study is among the first to document the dietary behaviors and key psychosocial factors influencing dietary behaviors and health outcomes for US Muslim people with Type 2 diabetes during Ramadan. The study suggests that interventions to improve diabetes control and promote diabetes remission among Muslims can benefit from cultural tailoring that draws on Ramadan religious, cultural and social practices to encourage sustainable behavioral change. Full article

This research introduces a hybrid framework that integrates stochastic modeling and machine learning for predicting postprandial glucose levels in individuals with Type 1 Diabetes (T1D). The primary aim is to enhance the accuracy of glucose predictions by merging a biophysical Glucose–Insulin–Meal (GIM) model with advanced machine learning techniques. This framework is tailored to utilize the Kaggle BRIST1D dataset, which comprises real-world data from continuous glucose monitoring (CGM), insulin administration, and meal intake records. The methodology employs the GIM model as a physiological prior to generate simulated glucose and insulin trajectories, which are then utilized as input features for the machine learning (ML) component. For this component, the study leverages the Light Gradient Boosting Machine (LightGBM) due to its efficiency and strong performance with tabular data, while Long Short-Term Memory (LSTM) networks are applied to capture temporal dependencies. Additionally, Bayesian regression is integrated to assess prediction uncertainty. A key advancement of this research is the transition from a deterministic GIM formulation to a stochastic differential equation (SDE) framework, which allows the model to represent the probabilistic range of physiological responses and improves uncertainty management when working with real-world data. The findings reveal that this hybrid methodology enhances both the precision and applicability of glucose predictions by integrating the physiological insights of Glucose Interaction Models (GIM) with the flexibility of data-driven machine learning techniques to accommodate real-world variability. This innovative framework facilitates the creation of robust, transparent, and personalized decision-support systems aimed at improving diabetes management. Full article

Dumping Syndrome (DS) is a significant complication following bariatric surgery, particularly Roux-en-Y gastric bypass (RYGB). This condition is characterised by gastrointestinal and vasomotor symptoms resulting from altered anatomy and hormonal dysregulation, notably accelerated gastric emptying and an exaggerated release of gut peptides. Based on the timing of symptom onset after food ingestion, DS is classified as early (EDS) or late (LDS). The critical roles of peptides such as GLP-1, GIP, insulin, and YY peptide are highlighted, along with the involvement of neuroendocrine pathways in symptom manifestation. Diagnosis relies on a combination of clinical evaluation and dynamic testing, with the oral glucose tolerance test (OGTT) often considered a key reference standard for diagnosis. Initial management involves dietary modifications, emphasising the glycaemic index of foods and meal distribution. In cases where nutritional interventions are insufficient, pharmacotherapy with agents such as acarbose, somatostatin analogues (octreotide and pasireotide), GLP-1 receptor agonists (liraglutide), calcium channel blockers (verapamil), and emerging therapies, including herbal medicine, may be considered. For refractory cases, surgical options like bypass reversal or partial pancreatectomy are reserved, although their efficacy can be variable. Despite advancements in understanding and treating DS, further large-scale, randomised controlled trials are essential to validate novel strategies and optimise long-term management. This review provides an updated and comprehensive overview of the aetiology, pathophysiological mechanisms, diagnostic approaches, and current management strategies for DS. Full article

Background/Objectives: Diabetes mellitus is a global public health crisis, with cases projected to rise to 1.3 billion by 2050. Lifestyle interventions are crucial in preventing and managing Type 2 diabetes. This study used a machine learning approach to explore the relationship between dietary components and fasting blood glucose in a young adult population, with a focus on potential sex-specific differences. Methods: This cross-sectional study analyzed data from 288 young adults (195 females, 93 males; mean age 23 years). Participants provided two-day diet records, and their fasting capillary blood glucose was measured. Machine learning was used to predict blood glucose based on a variety of dietary variables, including fiber, macronutrient proportions, and fat types. Energy expenditure was used as a proxy for energy intake. Models were created for the overall population, males, and females. Results: In the overall population, the most important predictor of fasting blood glucose was fiber intake. For females, the most important predictor was energy expenditure, followed by fat quality (linoleic to alpha-linolenic acid ratio and saturated fat intake). For males, the most predictive factor was the percentage of calories from fat, followed by alpha-linolenic acid intake. Conclusions: The findings suggest that predictors of blood glucose differ between males and females, highlighting the need for sex-specific strategies in blood glucose management. The models emphasize the importance of increasing fiber intake, maintaining a healthy energy intake, and improving fat quality by prioritizing essential fatty acids. This approach can be used to inform personalized dietary recommendations for the prevention and management of diabetes. Full article

The fermentation performance of Lactobacillus acidophilus is constrained by factors such as low cell density and fastidious nutritional and environmental requirements, which greatly limit its industrial-scale applications. This study aimed to develop an efficient fermentation condition for L. acidophilus CCFM137 through systematic optimization of both culture medium and environmental parameters, thereby enabling high-yield industrial-scale production of this strain. An optimized medium was developed, consisting of glucose (30 g/L), YEP FM503 (35 g/L), sodium acetate (5 g/L), ammonium citrate (2 g/L), K₂HPO₄ (2 g/L), MgSO₄·7H₂O (0.1 g/L), MnSO₄·H₂O (0.05 g/L), L-cysteine hydrochloride (0.5 g/L), and Tween 80 (1 mL/L), to achieve a viable cell count of 1.95 × 10⁹ CFU/mL, representing a 9.42-fold increase over that of standard MRS broth. Subsequent pH-stat fermentation trials in a 100 L fermenter using the optimized medium revealed morphological and growth characteristics of the strain in variable pH-stat environments. Optimal performance was observed under pH-stat 4.5 rather than the more commonly used 5.7, achieving maximum viable cell counts of 3.37 × 10⁹ CFU/mL, accompanied by a transformation of cell morphology toward shorter rod-shaped structures, as well as an increase in substrate utilization rate, cell recovery rate and lyophilization survival rate. The fermentation performance and cellular morphology of L. acidophilus CCFM137 were enhanced by both nutrient composition and pH environment. These results showed that this strategy has potential for application in high cell density fermentation of L. acidophilus CCFM137. Full article

A novel heterobimetallic ruthenium(II)–gold(I) complex featuring a bridging bis(diphenylphosphino)butane (dppb) ligand was prepared and fully characterized. Single-crystal X-ray diffraction revealed a piano-stool geometry around Ru(II) with η⁶-cymene, two chlorido ligands, and one phosphorus atom from dppb, while the Au(I) center adopts a linear P–Au–Cl coordination. Structural integrity in the solution was confirmed by 1D and 2D NMR spectroscopy, while solution behavior was further monitored by variable solvent ³¹P NMR and UV/Vis spectroscopy, indicating that the organometallic Ru–arene core remains intact, whereas the chlorido ligands coordinated to Ru exhibit partial lability. Complementary characterization included elemental analysis, FTIR, and UV/Vis spectroscopy. Spectrofluorimetric and FRET analyses showed that Au(dppb), Ru(dppb), and the heterobimetallic AuRu complex bind to BSA with apparent constants of 1.41 × 10⁵, 5.12 × 10², and 2.66 × 10⁴ M⁻¹, respectively, following a static quenching mechanism. In vivo biological evaluation in Wistar rats revealed no significant hepatotoxicity or nephrotoxicity, with only mild and reversible histological alterations and preserved hepatocyte nuclear morphology. Hematological analysis indicated a statistically significant reduction in leukocyte populations, suggesting immunomodulatory potential, while elevated serum glucose levels point to possible endocrine or metabolic activity. These findings highlight compound structural stability and intriguing bioactivity profile, making it a promising platform for further organometallic drug development and testing. Full article

The objective of this study was to assess the changes in adiponectin concentrations and inflammatory markers in men with abdominal obesity following physical exercise and exercise combined with dietary intervention. This study included 44 males with abdominal obesity (mean age 34.7 ± 5.5 years, waist circumference [WC] 110.3 ± 8.5, BMI 32.0 ± 3.9), who were randomly assigned to three groups: a control group without interventions (CG, n = 12), an experimental group engaging in aerobic-resistance exercise (EG, n = 16) and a group engaging in aerobic-resistance exercise combined with an ad libitum high-protein, low-glycemic index carbohydrate diet (EDG, n = 16). Body composition metrics: the body fat-, fat-free mass-, and abdominal fat-to body mass (BF/BM, FFM/BM, ABD/BM) indexes and the body adiposity index (BAI), along with biochemical blood analyses—adiponectin (ADIPO), interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), Castelli-II Index (CRI II) and fasting glucose–insulin (FG/I) ratio—were measured at baseline and after the intervention. The effects of the interventions on the analyzed variables across groups were assessed using mixed ANOVA tests with post hoc comparisons. Effect size (ES) was also calculated using partial eta squared (ηp²). The exercise intervention (EG) resulted in a significant reduction in the BAI (p < 0.01), insulin resistance FG/I (p < 0.02), and IL-6 concentrations (p < 0.01) and initiated an increase in ADIPO secretion (p = 0.03). The combined intervention (EDG) reduced the insulin resistance FG/I (p = 0.02) and atherogenic index CRI II (p = 0.01), decreased inflammatory markers IL-6 (p = 0.01) by 48% and hs-CRP (p = 0.04) by 30%, and simultaneously increased the ADIPO (p = 0.02) concentration by 15%. These effects were accompanied by significant changes in body composition: reductions in visceral fat ABD/BM (p < 0.01), total fat BF/BM (p < 0.01), and BAI (p = 0.02) and an increase in FFM/BM (p < 0.01). A crucial role in achieving these outcomes was played by dietary modifications, i.e., the inclusion of low-glycemic index carbohydrates (p < 0.01), a 23% increase in protein intake (p < 0.01), and a 50% increase in dietary fiber intake (p < 0.01), which consistently deepened the energy deficit (p < 0.01) and reduced fat intake (p < 0.01). These findings underscore that short-term interventions, whether exercise alone or combined with dietary modifications, can effectively reduce inflammation and lower insulin resistance in men with visceral obesity. However, the combined intervention, involving both exercise and dietary modifications, resulted in more pronounced beneficial changes in both body composition and concentrations of adipokines, inflammatory markers, and atherogenic indices and insulin resistance. Full article

Background: Small-molecule tyrosine kinase inhibitors (SMTKIs), widely used in cancer chemotherapy, have been reported to variably affect glycaemic control and metabolism, with some agents demonstrating hypoglycaemic effects while others show hyperglycaemic properties. This study aims to elucidate how small-molecule tyrosine kinase inhibitors affect glucose metabolism in C2C12 cells in vitro. Specifically, this study investigated their impact on glucose uptake, AKT expression, GLUT4 expression and translocation, and IL-6 expression. Methods: In this study, skeletal muscle (C2C12) preparations were separately treated with small-molecule tyrosine kinase inhibitors; imatinib, dasatinib, axitinib, and erlotinib for 24 h. Thereafter, the effect of the test drugs was assessed on cell viability using the MTT assay, while glucose uptake was determined by measuring residual glucose concentrations in the culture medium with a glucometer. The expression of AKT, GLUT4, and IL-6 and translocation of GLUT4 were evaluated using ELISA. Furthermore, the effect of the drugs was assessed on insulin-stimulated AKT phosphorylation and GLUT4 translocation. Imatinib, dasatinib, axitinib, and erlotinib were selected due to their effect of glucose metabolism, highlighted in the literature. Results and Discussion: C2C12 cells treated with SMTKIs were viable after 24 h. A concentration-dependent increase in glucose uptake in C2C12 cells treated with imatinib was observed as the concentration of imatinib increased. Axitinib, dasatinib, and erlotinib demonstrated glucose uptake levels comparable to the control across all concentrations. SMTKIs demonstrated an increase in GLUT4 translocation in the absence of insulin. GLUT4 expression was unchanged in cells treated with small-molecule tyrosine kinase inhibitors compared to the control. Small-molecule tyrosine kinase inhibitors showed an increase in AKT expression. C2C12 cells treated with SMTKI were observed to have elevated IL-6 expression compared to the control. Conclusions: The results show that SMTKIs, in particular dasatinib, impact glucose metabolism in C2C12 cells via their effect on GLUT4 translocation and expression and AKT expression. Dasatinib shows promising potential with regard to antidiabetic capabilities. Further research is needed to better understand SMKI effects on metabolic homeostasis, which can perhaps inform future therapeutic strategies. Full article

Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is widely used to reduce appetite and promote weight loss in patients with type 2 diabetes. However, individual variability may lead to paradoxical responses. We describe a 60-year-old woman with type 2 diabetes who experienced progressive weight gain and increased appetite during 12 months of semaglutide therapy, despite previous successful weight loss with sodium-glucose cotransporter 2 (SGLT2) inhibitors. Her body mass index (BMI) rose from 31.6 to 34.6 kg/m², accompanied by worsening glycemic control. Eating behavior assessment with the Dutch Eating Behavior Questionnaire revealed a maximum score for emotional eating, suggesting a strong psychological barrier to treatment efficacy. Genetic factors, such as GLP-1 receptor polymorphisms, may also contribute to reduced responsiveness. This case highlights the possible influence of both emotional and genetic factors on treatment outcomes and emphasizes the need for personalized approaches in the management of obesity and type 2 diabetes. Full article

The use of the HOMA (Homeostatic Model Assessment) index in veterinary medicine is emerging as a promising and valuable method for evaluating insulin resistance and beta-cell function in companion animals, particularly in dogs and cats. Originally developed for use in human medicine, HOMA enables a minimally invasive assessment of glucose and insulin homeostasis, offering clinicians a practical tool for diagnosing and monitoring diabetes mellitus in animals. Its application in veterinary practice brings several advantages, including cost-effectiveness, ease of use, and the potential for early detection of metabolic disturbances before clinical symptoms appear. Nonetheless, important limitations persist, such as inter-individual variability, the effects of stress and comorbidities on glucose and insulin values, and the absence of standardized, species-specific reference ranges. These factors highlight the need for methodological refinement and the establishment of validated protocols tailored to the unique physiological characteristics of dogs and cats. Despite these challenges, HOMA represents a promising avenue for advancing the understanding of diabetes pathophysiology in veterinary patients. Future longitudinal studies and controlled trials are essential to confirm its reliability and enhance its clinical relevance. With further development, the HOMA index could become an essential tool in improving diagnostic accuracy and optimizing the management of diabetes in companion animal practice. Full article

Streptococcus thermophilus is a Gram-positive, homofermentative lactic acid bacterium classified within the Firmicutes phylum, recognized for its probiotic properties and significant role in promoting human health. This review consolidates existing understanding of its metabolic pathways, functional metabolites, and diverse applications, highlighting evidence-based insights to enhance scientific integrity. S. thermophilus predominantly ferments lactose through the Embden-Meyerhof-Parnas pathway, resulting in L(+)-lactic acid as the primary end-product, along with secondary metabolites including acetic acid, formic acid, and pyruvate derivatives. Exopolysaccharides (EPS) are composed of repeating units of glucose, galactose, rhamnose, and N-acetylgalactosamine. They display strain-specific molecular weights ranging from 10 to 2000 kDa and contribute to the viscosity of fermented products, while also providing antioxidant and immunomodulatory benefits. Aromatic compounds such as acetaldehyde and phenylacetic acid are products of amino acid catabolism and carbohydrate metabolism, playing a significant role in the sensory characteristics observed in dairy fermentations. Bacteriocins, such as thermophilins (e.g., Thermophilin 13, 110), exhibit extensive antimicrobial efficacy against pathogens including Listeria monocytogenes and Bacillus cereus. Their activity is modulated by quorum-sensing mechanisms that involve the blp gene cluster, and they possess significant stability under heat and pH variations, making them suitable for biopreservation applications. In food applications, S. thermophilus functions as a Generally Recognized as Safe (GRAS) starter culture in the production of yogurt and cheese, working in conjunction with Lactobacillus delbrueckii subsp. bulgaricus to enhance acidification and improve texture. Specific strains have been identified to mitigate lactose intolerance, antibiotic-related diarrhea, and inflammatory bowel diseases through the modulation of gut microbiota, the production of short-chain fatty acids, and the inhibition of Helicobacter pylori. The genome, characterized by a G + C content of approximately 37 mol%, facilitates advancements in Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas technology and heterologous protein expression, with applications extending to non-dairy fermentations and the development of postbiotics. This review emphasizes the adaptability of S. thermophilus, showcasing the variability among strains and the necessity for thorough preclinical and clinical validation to fully utilize its potential in health, sustainable agriculture, and innovation. It also addresses challenges such as susceptibility to bacteriophages and limitations in proteolytic activity. Full article

Vitamin D plays a key role in pregnancy beyond calcium–phosphate regulation, modulating immune responses and glucose metabolism via the vitamin D receptor (VDR). Placental expression may be altered in gestational diabetes mellitus (GDM). This study aimed to assess placental VDR expression in GDM and evaluate its association with maternal vitamin D levels and clinical parameters. VDR expression in the placental tissue of 53 women with GDM and 26 healthy controls was assessed semi-quantitatively by immunohistochemistry. Maternal serum 25-hydroxyvitamin D (25(OH)D) levels, body mass index, weight gain, neonatal outcomes, and other variables were evaluated. Univariate and multivariate linear regression analyses were performed. VDR expression was significantly higher in the GDM group compared to controls (p = 0.0297 for mean, p = 0.0378 for median). No significant differences were observed in serum 25(OH)D concentrations between groups. Stepwise regression revealed that diabetes was the only independent predictor of VDR expression. Within the GDM subgroup, VDR expression was not associated with any clinical parameters, including maternal vitamin D status. Upregulated placental VDR in GDM may represent an adaptive response to metabolic stress. These findings suggest complex regulation of vitamin D signalling in diabetic pregnancies, warranting further investigation. Full article

Circulating levels of endothelial progenitor cells (EPCs) involved in endothelial homeostasis are often reduced in people with type 1 diabetes (T1D). The Glycemia Risk Index (GRI) quantifies the quality of glucose control by assessing both hypo- and hyperglycemia risk. We aim to investigate the association between the GRI and circulating EPC levels in people with T1D. This cross-sectional study included 132 adults with T1D, on intensive insulin therapy. We calculated GRI from 14 days continuous glucose monitoring-derived metrics and quantified EPCs count by flow cytometry, stratifying results by GRI zones, ranging from A (lowest risk) to E (highest risk). Higher GRI scores were significantly associated with poorer metabolic parameters. Circulating levels of CD34⁺, CD133⁺, KDR⁺, and CD34⁺KDR⁺ cells were lower in participants with a worse GRI compared to adults with a better GRI. Linear regression analyses showed a negative association between GRI and CD34⁺ (β = −1.079, p = 0.006), CD34⁺CD133⁺ (β = −0.581, p = 0.008), and CD34⁺KDR⁺ (β = −0.147, p = 0.010). No significant association was found between HbA_1c and any EPC phenotype. Adults with T1D and a high GRI level had a lower EPCs count. GRI was significantly associated with certain EPC phenotypes, suggesting its potential role as a biomarker for cardiovascular risk assessment. Full article

Understanding physiological variability in wild ungulates is essential for ecological monitoring and sustainable wildlife management. This study aimed to examine whether sex and season (autumn vs. early winter) significantly influence hematological and biochemical parameters in free-ranging red deer (Cervus elaphus) from the Eastern Carpathians, Romania. A total of 40 legally harvested adult individuals (20 males, 20 females) were included, and blood samples were collected post-mortem under standardized conditions to minimize pre-analytical variability. Hematological parameters (WBC, RBC, HGB, HCT, PLTs) and serum biochemical markers (glucose, urea, total cholesterol, triglycerides, total protein) were analyzed using automated veterinary analyzers. Statistically significant sex-related differences were found in hematocrit during autumn and hemoglobin concentration during winter, with higher values in males. Seasonal variation within sex groups was not significant but indicated a physiological trend toward hemoconcentration in winter. Biochemical values remained within reference ranges and showed no significant differences across groups. Pearson’s correlation analysis revealed a strong association between hematocrit and urea, and moderate correlations were observed between WBC and glucose, suggesting links between oxygen transport, protein metabolism, and energy balance. Environmental factors such as reduced food availability and temperature shifts during winter likely contribute to these physiological adjustments. These results provide baseline data for the physiological assessment of red deer populations and support the development of ecological health indicators in wildlife monitoring programs. Future studies incorporating hormonal and immunological biomarkers across multiple seasons are encouraged to further understand adaptive responses in cervids. Full article

Background/Objectives: Childhood obesity is associated with early metabolic complications, particularly insulin resistance (IR), which significantly elevates the long-term risk for type 2 diabetes and cardiovascular disease. Standard measures such as BMI may inadequately capture metabolic risk, particularly in children with atypical phenotypes such as TOFI (Thin Outside, Fat Inside). This study aimed to evaluate the prevalence and predictors of IR in a pediatric population with overweight and obesity, using both conventional biomarkers and bioelectrical impedance analysis (BIA). We also examined the predictive value of lipid ratios and fasting glucose and applied Principal Component Analysis (PCA) to identify underlying body composition dimensions. Methods: A retrospective cohort of 210 children aged 1–18 years, assessed in a tertiary pediatric endocrinology center in Romania, was analyzed. Clinical data included anthropometric measures, fasting laboratory results, and body composition parameters obtained via Tanita PRO DC430 MA BIA. Insulin resistance was defined as HOMA-IR > 2. ROC analysis assessed the predictive performance of triglyceride-to-HDL (Tg/HDL) ratio, fasting glucose, and BIA metrics. PCA was applied to BIA variables to explore dimensional structure. Results: Insulin resistance was present in 54.8% of the cohort. It was significantly associated with higher age, pubertal status, ALT, LDL-cholesterol, triglycerides, and BIA-derived fat-free mass (FFM), TBW, and PMM. ROC analyses showed moderate predictive power for Tg/HDL (AUROC = 0.645) and triglycerides (AUROC = 0.656) in identifying IR. BIA metrics had comparable discriminatory performance (AUROC~0.61). PCA reduced eight BIA parameters into two components: a fat-free mass axis (TBW, FFM, PMM, WATERM) and an adiposity axis (BMI, FATP, FATM, WATERP). Conclusions: This study highlights the high burden of insulin resistance among children with excess weight and supports the integration of BIA and composite biomarkers into early screening protocols. PCA-derived components may improve metabolic phenotyping in pediatric obesity. Full article