Search Results (667)

This study evaluated the protective effects of green coffee (Coffea arabica L.) extract (GCE) against metabolic and endocrine disturbances induced by fipronil (FIP) in male rats. Animals were randomly allocated into four groups (n = 6): control, GCE (100 mg/kg), FIP (4.85 mg/kg), and combined FIP + GCE, and treated orally for 90 days. FIP exposure significantly impaired glucose homeostasis, as indicated by a 14.8% increase in the oral glucose tolerance test (OGTT) response and a 2.4-fold increase in the homeostatic model assessment of insulin resistance (HOMA-IR). It also disrupted lipid metabolism, with marked elevations in triglycerides (74.10%) and total cholesterol (57.55%). Endocrine imbalance was evident, including increased resistin levels (113.86%) and reduced triiodothyronine (T3; −37.5%), adiponectin (−42.73%), and high-density lipoprotein (HDL; −9.31%). Oxidative stress and inflammation were significantly enhanced, as demonstrated by elevated malondialdehyde (MDA; +93.56%) and pro-inflammatory cytokines (IL-1β: +246.56%; IL-6: +275%), alongside a reduction in total antioxidant capacity (TAC; −45.24%). Additionally, serum albumin levels decreased markedly (−54%). Co-administration of GCE significantly improved metabolic, hormonal, and inflammatory parameters, including insulin resistance (HOMA-IR). Histopathological analysis further confirmed its protective effects on hepatic and renal tissues. Overall, GCE mitigates FIP-induced metabolic and endocrine dysfunction, likely through its antioxidant and anti-inflammatory properties. Full article

Noninvasive blood glucose monitoring is crucial for detecting early dysglycemia, yet continuous glucose monitors remain invasive and costly. Electrocardiogram (ECG) and its derived heart rate variability (HRV) measure may offer a noninvasive indicator of autonomic and cardiac responses associated with acute changes in glucose. In this study, 30 adults underwent a 75 g oral glucose tolerance test with concurrent ECG Holter and interstitial glucose monitoring. From these recordings, HRV and ECG features were extracted. A deep learning classifier with HRV and ECG was then trained to detect hyperglycemia (glucose ≥ 180 mg/dL). Cross-correlation analysis confirmed a significant association between HRV and glucose (Pearson r ~0.65, p < 0.05) when aligning each participant’s data according to individual response delays. The model achieved high classification performance under rigorous temporal validation (accuracy ~89%, area under the receiver operating characteristic curve ~0.89). Saliency analyses revealed that the classifier’s decisions focus on distinct ECG waveform transitions and key HRV features linked to glucose-induced autonomic changes. Overall, acute hyperglycemia elicited discernible changes in HRV and cardiac conduction, supporting the feasibility of this physiologically grounded approach for detecting the acute hyperglycemic phase under controlled conditions. This method holds promise for real-time implementation in wearable devices, enabling early diabetes risk screening. Full article

Background: Sex-related differences in insulin sensitivity during adolescence remain incompletely understood, particularly in the context of obesity. Whether these differences reflect variations in basal insulin resistance or dynamic insulin responses remains unclear. Objective: To investigate sex differences in glucose and insulin responses during the oral glucose tolerance test (OGTT) and to explore mechanisms underlying potential dissociation between glycemic and insulinemic profiles. Methods: A cross-sectional analysis of 753 adolescents with obesity who underwent a standard oral glucose tolerance test (OGTT). Plasma glucose and insulin were measured at fasting and at 30, 60, 90, and 120 min. Mixed-effects models were used to examine glucose and insulin trajectories over time, including sex-by-time interactions, and to adjust for body mass index standard deviation score (BMI_SDS), pubertal stage (Tanner), metabolic syndrome (MetS), and body composition (resistance index). Multiple linear regression models were fitted to assess associations of sex with HOMA-IR, HOMA-β, total area under the curve (AUC), and phase-specific insulin AUCs. Results: Glucose trajectories during OGTT were similar between sexes, with no significant sex or sex-by-time interaction effects after adjustment. In contrast, insulin trajectories differed significantly by sex (sex-by-time interaction β = −0.10, p < 0.001). Boys exhibited higher baseline insulin levels and greater total insulin exposure (β = −11.2, p < 0.001), independent of BMI_SDS, pubertal stage, MetS, and body composition. Sex differences were sustained across all OGTT phases. HOMA-IR did not differ by sex, whereas HOMA-β showed a sex-related difference. BMI was positively associated with both basal and dynamic insulin measures. Conclusions: In adolescents with obesity, sex differences are characterized by altered dynamic insulin responses rather than differences in glycemic control. Boys exhibit greater compensatory insulin exposure during glucose challenge, independent of BMI-based adiposity, BIA-derived body composition and pubertal development. Full article

Annona cherimola is a plant species widely used in Mexican traditional medicine, particularly in the management of diabetes. This study aimed to investigate the antihyperglycemic properties of the petroleum ether extract of A. cherimola leaves (PEEAcL), as well as to evaluate their effects on glycated hemoglobin and toxicity. In addition, the work was directed to determine its potential as an SGLT-1 and α-glucosidase inhibitor. The effect as a potential SGLT-1 and α-glucosidase inhibitor of PEEAcL was evaluated utilizing intestinal glucose absorption (IGA), oral glucose tolerance (OGT), oral sucrose tolerance (OST) and intestinal sucrose hydrolysis (ISH) tests. PEEAcL administered at doses of 200 mg/kg showed significant antihyperglycemic activity after 1 h of treatment, and the maximum effect was seen at 4 h in male and female diabetic mice. In the OST, OLT, and OGT tests, PEEAcL generated a reduction in the postprandial glucose peak at 2 h after the administration of a carbohydrate load, showing an effect comparable to that of acarbose and canagliflozin. In the IGA trial, PEEAcL significantly reduced glucose uptake in the small intestine. Similarly, in the ISH, PEEAcL recorded a significant reduction in glucose concentration in the external aqueous medium. Taken together, these results suggest that the antihyperglycemic effect of PEEAcL could be mediated, at least in part, by inhibition of SGLT-1 and the enzyme α-glucosidase. Full article

Background: Postpartum oral glucose tolerance test (OGTT) screening after gestational diabetes mellitus (GDM) enables early detection and prevention of type 2 diabetes, yet adherence is suboptimal, particularly in regional and rural areas. This study examined lifestyle behaviour and health-related quality-of-life factors associated with OGTT non-adherence over time. Methods: A longitudinal cohort study of women with prior GDM in regional and rural New South Wales, Australia, was conducted. Binary logistic regression models examined associations between lifestyle behaviours, health-related quality of life, and OGTT non-adherence at 3, 18, and 36 months postpartum. Results: OGTT non-adherence increased over time. Multivariable models were not statistically significant at any timepoint. At 3 months postpartum, several lifestyle and health-related quality-of-life variables were associated with non-adherence; however, these associations were not sustained at later timepoints. No consistent predictors of non-adherence were identified across follow-up. Conclusions: All women with prior GDM remain at risk of missed postpartum screening, with engagement declining over time. Findings should be interpreted as exploratory, reflecting time-specific patterns rather than stable predictors. Early postpartum represents a critical window for intervention, while longer-term strategies require flexible, integrated, and accessible models of care to support sustained diabetes prevention, particularly in regional and rural populations. Full article

This study aimed to investigate whether mixed heavy metal exposure (lead, cadmium, manganese, and arsenic) during pregnancy induces gestational diabetes mellitus (GDM)-like phenotypes and to explore the associated molecular alterations. We examined the effects of exposure on metabolic disturbances using a Sprague-Dawley rat model exposed to low- and high-dose mixed heavy metals, with doses selected based on biomonitoring data. The results showed that high-dose mixed heavy metal exposure significantly increased blood glucose levels in rats, elevated the area under the curve (AUC) during the oral glucose tolerance test (OGTT), and induced insulin resistance and dyslipidemia. Concurrently, pathological examinations revealed hepatocyte steatosis, inflammatory cell infiltration, and mitochondrial abnormalities in liver tissues. Transcriptomic and metabolomic analyses identified significant disruption of the glycerophospholipid metabolic pathway following heavy metal exposure, suggesting the involvement of this pathway in the observed metabolic disturbances. Lasso regression analysis identified Insig1 as a candidate gene associated with lipid metabolic alterations, a finding subsequently validated by qPCR. Overall, mixed heavy metal exposure during pregnancy was associated with GDM-like metabolic abnormalities in rats. Disruption of glycerophospholipid metabolism and altered Insig1 expression likely contribute to these effects, providing molecular evidence linking mixed heavy metal exposure to gestational metabolic dysfunction. Full article

Obesity in women of reproductive age is a major issue. It is associated with reduced fertility and an increased risk of obstetric and perinatal complications. Bariatric surgery is the most effective treatment for severe obesity, leading to substantial weight reduction, improvement of metabolic disorders, and enhanced fertility. Consequently, an increasing number of women are becoming pregnant after undergoing bariatric surgery. The aim of this paper is to review current recommendations and research data regarding the care of women after bariatric surgery in the periconceptional and perinatal periods, as well as throughout pregnancy, delivery, and the postpartum period. Research suggests that pregnancy after bariatric surgery is associated with a lower risk of gestational diabetes, hypertension, preeclampsia, and fetal macrosomia compared with pregnancies in women with similar baseline BMI (body mass index) who have not undergone surgical treatment. At the same time, an increased risk is observed for low birth weight, maternal micro- and macronutrient deficiencies, and complications characteristic of bariatric procedures, such as dumping syndrome or intra-abdominal hernias. Most scientific societies recommend postponing pregnancy planning for 12–18 months after surgery and using effective contraception, preferably methods that do not require gastrointestinal absorption. Regular monitoring of laboratory parameters, individually tailored supplementation, and interdisciplinary care are essential for the safe management of pregnancy after bariatric surgery. In particular, care should include achieving a stable body weight before conception, monitoring of nutritional status, verifying proper weight gain during pregnancy, and considering alternative methods for gestational diabetes screening (e.g., glycaemic monitoring instead of oral glucose tolerance testing) due to the risk of dumping syndrome. Appropriate preparation for pregnancy and proper management throughout its course allow for reducing the risk of perinatal complications. Bariatric surgery itself is not a contraindication to vaginal delivery. Full article

Background: Metabolic syndrome (MetS) leads to alterations in cardiac autonomic control that can be detected from electrocardiogram (ECG)-derived markers, particularly when the cardiovascular system is challenged during an oral glucose tolerance test (OGTT). Methods: In this paper, we present an automated framework for MetS identification using RR intervals and heart rate variability (HRV) features extracted from 12-lead ECG recordings acquired during the five OGTT stages in 40 male participants (15 with MetS, 10 controls, and 15 endurance-trained marathon runners). RR intervals were first derived using a multilead Pan-Tompkins approach with fusion-based validation. From these RR series, HRV descriptors were computed from time-domain statistics (RR mean, SDNN, rMSSD, pNN50), spectral indices (VLF, LF, HF, LF/HF), and nonlinear measures (SD1, SD2, SampEn, DFA-${\alpha }_1$). Conventional HRV analysis revealed pronounced physiological differences between groups: MetS subjects exhibited reduced parasympathetic activity, reflected by lower rMSSD and SD1, lower HF power, and higher LF/HF ratios, whereas marathoners showed greater vagal modulation, higher HF power, and increased signal complexity. Healthy controls showed an intermediate autonomic profile. Using RR sequences and HRV descriptors (256 samples per stage), we trained three multimodal classifiers: a CNN-MLP model with a softmax output, a CNN-MLP model with an SVM head, and a CNN + LSTM-MLP + SVM architecture. Results: All models achieved strong discriminative performance, with accuracies ranging from 0.92 to 0.95, F1-macro values from 0.92 to 0.95, and macro-AUC values from 0.96 to 0.97. The CNN-MLP model achieved the best overall performance, whereas the CNN + LSTM-MLP + SVM model showed strong class discrimination, particularly for endurance athletes, while maintaining competitive recall for MetS. Conclusions: These findings support the feasibility of ECG-based autonomic assessment as a complementary non-invasive approach for early metabolic risk detection in clinical and preventive cardiometabolic screening settings. Full article

Background/Objectives: Onion (Allium cepa) peems are an underutilized by-product rich in polyphenols. This study evaluated the physicochemical profile, and bioactive potential (antidiabetic, antimicrobial, antioxidant, and anticoagulant) of Moroccan red onion peels using integrated in vivo, in vitro, and in silico approaches. Methods: Moisture, pH, ash content, and mineral elements were determined, followed by phytochemical screening and three extractions: decoction E0, aqueous Soxhlet E1, and hydroethanolic Soxhlet E2 (70/30; ethanol/water, v/v). The measurement of polyphenols, flavonoids, and tannins was carried out using colorimetric methods, while the molecular profile was studied by high-performance liquid chromatography coupled to ultraviolet detection and electrospray ionization mass spectrometry (HPLC/UV-ESI-MS). Biological activities were determined using 2,2-diphenyl-1-picrylhydrazyl, ferric reducing antioxidant power, and total antioxidant capacity assays (in vitro antioxidant); microdilution (antimicrobial); prothrombin time and activated partial thromboplastin time (anticoagulant); and α-amylase/α-glucosidase enzymatic inhibition and oral glucose tolerance tests on normoglycemic rats. Also, acute toxicity was evaluated, and molecular interactions between these proteins and ligands (docking, molecular dynamics, and MM-PBSA) were analyzed. Results: Physicochemical analyses showed an acidic pH (3.06) and high ash content (15.21%), with the concentration of regulated elements remaining within FAO/WHO limits. The extractive content was between 6.90% E0 and 19.18% E2. The E1 extract had the maximum amount of total polyphenols (178.95 mg GAE/g); on the other hand, E2 was the richest in flavonoids by 121.43 mg QE/g. The HPLC/ESI-MS analysis of E0 revealed 20 compounds, among which flavonoids (84.93%) were predominant, with isorhamnetin (30.26%), followed by quercetin and its glycosylated forms. E1 showed the most potent antioxidant effects (IC₅₀ DPPH, 22.38 µg/mL, as that of ascorbic acid). The antibacterial activity of E0 was especially potent towards Enterobacter cloacae and Pseudomonas aeruginosa (MIC 75 µg/mL). A mild dose-dependent anticoagulant effect was seen. Antidiabetic activity was found to be outstanding: α-amylase (IC₅₀ 62.75 µg/mL) and α-glucosidase (IC₅₀ 8.49 µg/mL, stronger than acarbose) inhibitions were corroborated in vivo by a considerable decrease in the glycemic area under the curve. The molecular docking study in silico demonstrated strong molecular interactions, especially for quercetin 4′-O-glucoside with good binding energies. Conclusions: A. cepa peels from Morocco can be considered a safe plant matrix containing bioactive flavonoids with strong antioxidant and selective antimicrobial activities and promising antidiabetic effects, supported by molecular modeling. Full article

Background/Objective: Women with a history of gestational diabetes mellitus (GDM) are at increased risk of type 2 diabetes mellitus (T2DM), dysglycemia, and dyslipidemia. However, the role of postpartum weight change in long-term metabolic outcomes remains unclear. Here, we determined the long-term incidence of dysglycemia and dyslipidemia after GDM and evaluated whether postpartum changes in body mass index (BMI) independently predicted these outcomes. Methods: This single-center prospective cohort study included 205 Japanese women diagnosed with GDM. All participants underwent a 75 g oral glucose tolerance test at 6–12 weeks postpartum. The incidence of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), T2DM, and dyslipidemia was evaluated over a median follow-up of 3.6 years. Cumulative incidence was estimated using the Kaplan–Meier method, and Cox proportional hazards models identified independent risk factors, particularly postpartum BMI change. Results: During follow-up, 42.4%, 6.3%, and 35.6% of women developed IFG or IGT (prediabetes), T2DM, and dyslipidemia, respectively. The estimated cumulative incidence rates at 6 years postpartum were 57.1% and 50% for IFG/IGT and dyslipidemia, respectively, whereas the 5-year incidence of T2DM was 10.3%. Postpartum BMI increase was independently associated with new-onset dysglycemia. No independent predictor of T2DM progression was identified. Dyslipidemia was independently associated with higher pre-pregnancy BMI and multiparity, whereas postpartum BMI change was not independently associated after multivariable adjustment. Conclusions: Postpartum BMI change was independently associated with dysglycemia in women with a history of GDM. These findings suggest that postpartum weight change may help identify women at higher risk of subsequent metabolic abnormalities, particularly dysglycemia, in this high-risk population, although causal relationships cannot be inferred from this observational study. Full article

Insulin acts in the brain to promote satiety. Aging individuals may have brain insulin resistance and altered appetite perceptions. However, it is unclear if exercise impacts cerebral reward centers and appetite perception in middle-aged to older individuals. Purpose: To assess whether a single exercise bout alters cerebral blood flow (CBF) in reward centers in relation to appetite perceptions. Methods: Fifteen sedentary adults (12F; ~56 ± 2y; ~31 ± 1 kg/m²) completed a control and acute exercise condition (70% maximal oxygen consumption) in a randomized, counterbalanced order in the evening. Following an overnight fast, CBF in the accumbens, thalamus, and amygdala (pCASL MRI) was evaluated before and after intranasal insulin spray (INI, 40 IU) administration. Plasma glucose and insulin as well as an appetite visual analog scale (VAS) were assessed at fasting, 30, and 90 min post-INI, as well as at 30 min intervals of a 120 min 75 g oral glucose tolerance test (OGTT). Total area under the curve (tAUC) was calculated. Results: Exercise tended to lower blood glucose (p = 0.072) and plasma insulin (p = 0.007) tAUC, compared with rest. Exercise also raised right thalamus (p = 0.029) and left amygdala CBF (p = 0.023). The rise in fasting CBF in these regions, and the accumbens, correlated with reduced insulin tAUC (r = −0.55 to −0.73, p < 0.050). Although there was no difference in hunger, satisfaction, fullness, or prospective food consumption after exercise, changes in INI-stimulated thalamus CBF related to fullness tAUC after exercise (r = −0.57, p = 0.044). Conclusions: A single exercise bout might increase fasting CBF in some brain regions associated with appetite perception through a potential insulin-related mechanism. Full article

Background: Gestational diabetes mellitus (GDM) affects many pregnancies worldwide and is associated with adverse maternal and fetal outcomes. Current screening at 24–28 weeks limits opportunities for early intervention. We evaluated whether machine learning (ML) models using first-trimester clinical and dietary data can predict GDM risk before the standard oral glucose tolerance test. Methods: We analyzed data from 797 pregnant women enrolled in the BORN2020 prospective cohort study (Thessaloniki, Greece). Ten ML algorithms were evaluated across five class-imbalance handling strategies using stratified 5-fold cross-validation, with final evaluation on an independent 20% held-out test set. Features included maternal demographics, obstetric history, lifestyle factors, and 22 dietary micronutrient intakes from the pre-pregnancy period assessed by Food Frequency Questionnaire. Results: The best-performing model (Logistic Regression without resampling) achieved an AUC-ROC of 0.664 (95% CI: 0.542–0.777), with sensitivity of 0.783 and NPV of 0.932 at the pre-specified threshold. The high NPV should be interpreted in the context of the low GDM prevalence (14.7%), as NPV is mathematically dependent on disease prevalence. A reduced nine-feature model using only routine clinical and demographic variables achieved a numerically higher AUC of 0.712 (95% CI: 0.589–0.825), with overlapping confidence intervals, indicating that detailed FFQ-derived micronutrient data did not improve prediction. Maternal age and pre-pregnancy BMI were the strongest individual predictors by SHAP analysis. No model reached the AUC >0.80 threshold for good discrimination. Substantial miscalibration was observed (slope: 0.56; intercept: −1.83), limiting use for absolute risk estimation. Conclusions: This exploratory study demonstrates that first-trimester ML models achieve modest discriminative ability for early GDM prediction, with routine clinical variables performing comparably to models incorporating detailed dietary assessment. These findings should be interpreted with caution, as no external validation cohort was available and the low events-per-variable ratio (~3.8) constrains the reliability of individual model estimates. Substantial miscalibration further limits use for absolute risk estimation. Accordingly, these models should be regarded as exploratory risk-ranking tools only and require external validation and recalibration before any clinical implementation. Full article

While our group previously demonstrated the calming effects of Melissa officinalis extract (MOE) in dogs, the underlying brain-level mechanisms remain unclear. To address this, we investigated these mechanisms in rats using an untargeted metabolomics approach. Twenty-four male Wistar rats were divided into three groups (eight rats per group): control (standard diet, SD), a group fed a high-fat high-sucrose diet (HFHSD), and HFHSD administrated with a hydro-alcoholic standardized MOE (HFHSD MOE) at a dose of 200 mg/kg. Body weight, behavior through elevated plus maze (EPM), and glucose tolerance using the oral glucose tolerance test (OGTT) were monitored. After 12 weeks of supplementation, plasma and brain metabolomes were explored using non-targeted metabolomics. Although the EPM revealed no significant behavioral improvement, the OGTT showed a significant reduction in blood glucose area under the curve (AUC, p < 0.05), suggesting a metabolic effect of MOE. Metabolomic analysis highlighted two key pathways: (1) bile acid biosynthesis in plasma, as previously observed in our dog study, and (2) pentose phosphate metabolism in the brain. These results provide insight into central and peripheral mechanisms influenced by MOE and generate hypotheses on pathways potentially linked to previously reported behavioral effects in dogs, offering targets for nutritional interventions. Full article

Background/Objectives: In pregnancy, beta-cell function is of interest since not only insulin resistance but also beta-cell dysfunction is common, especially when gestational diabetes mellitus (GDM) occurs. Typically, model-based beta-cell function is assessed with (at least) five-sample oral glucose tolerance test (OGTT). The aim of this study was to investigate whether the clinically common three-sample OGTT is sufficient for model-based beta-cell function assessment in pregnancy. Methods: We studied a group of pregnant women undergoing a 2 h five-sample OGTT with glucose, insulin, and C-peptide measurement at early and/or mid-pregnancy, for a total of 152 OGTTs. The five-sample OGTT was used for model-based beta-cell function assessment, yielding three beta-cell function parameters, i.e., glucose sensitivity (GSENS), potentiation factor ratio (PFR), and rate sensitivity (RSENS). GSENS, PFR, and RSENS assessment was repeated with the three-sample OGTT (at 0, 60, 120 min) and related values were compared to those from the five-sample OGTT (reference). Results: We found that, for GSENS, regression and Bland–Altman analyses showed satisfactory results (conditional and marginal R² values: 0.56 and 0.75, p < 0.0001, and limits of agreement containing 94.2% of samples). Moreover, five-sample and three-sample OGTT GSENS versions were fully consistent in patient subgroup analyses. Results for PFR were less satisfactory but acceptable, whereas those for RSENS were not reliable. Conclusions: The three-sample OGTT is acceptable for model-based beta-cell function assessment in pregnancy, although not for all parameters. Our methodology may be used to explore the effect of time sample reduction in other in-silico models. Full article

Fipronil (FPN), a widely used insecticide, poses health risks through environmental contamination. Although its toxicity is increasingly recognized, the impact of fipronil on glucose metabolism remains poorly understood. In this study, mice on a normal diet (ND) or high-fat diet (HFD) received a daily oral administration of fipronil (0, 0.25, 1, or 4 mg/kg) for 35 days. Blood glucose and insulin were measured, and glucose/insulin/pyruvate tolerance tests were performed. We found that fipronil compromised glucose tolerance in mice fed an ND. Gut microbiota composition was assessed by 16S rRNA sequencing and the expression of inflammatory factors was detected in the tissues. Serum fibroblast growth factor 15 (FGF15) and bile acid were determined. In HFD-fed mice, fipronil exacerbated glucose metabolic disorders and enhanced insulin resistance. These metabolic disturbances were associated with gut microbiota dysbiosis, particularly a marked reduction in Akkermansia muciniphila (A. muciniphila) abundance, and increased systemic inflammation. Fipronil exposure also decreased serum FGF15 and elevated serum bile acids. Our results suggest that fipronil disrupts glucose metabolism in association with gut microbiota alterations, impairment of the FGF15-bile acid axis, and induction of inflammation, highlighting its potential relevance to diabetes risk. Further studies are warranted to validate our findings. Full article