Atherosclerosis, the primary pathological basis of cardiovascular diseases, exhibits a strong association with glucose metabolism dysregulation. While cross-sectional studies have linked fasting blood glucose (FBG) to atherosclerosis risk, the dose-response relationship and threshold characteristics of long-term FBG trajectories remain poorly characterized. This retrospective cohort study aimed to investigate longitudinal FBG trajectory patterns and their associations with atherosclerosis risk prevalence, incidence, and recovery in Chongqing, China, while also identifying population-specific risk thresholds. Based on the three-year longitudinal follow-up data collected annually from 2017 to 2019, a population-based trajectory model (GBTM) was adopted to identify the dynamic trajectory of FBG. The association between FBG and atherosclerosis risk was analyzed using multivariable logistic regression. Restricted cubic splines (RCS) were used to assess the non-linear relationship between FBG and atherosclerosis risk and to determine risk thresholds. Confounding factors such as age, sex, body mass index (BMI), blood pressure, and lipids were adjusted for in the regression models, and subgroup analyses were performed to examine the interactions of age, sex, and BMI. Longitudinal analysis showed that compared with the Trajectory Normal Glucose Regulation (NGR) group, the Trajectory Prediabetes Mellitus group (Pre-DM) group had significantly higher prevalence (OR: 2.02, 95% CI: 1.63-2.51) and incidence (OR: 1.66, 95% CI: 1.15-2.39) of atherosclerosis risk. The Trajectory Pre-DM group also had a significantly lower likelihood of atherosclerosis risk recovery than the Trajectory NGR group (OR: 0.55, 95% CI: 0.39-0.79). Dose-response analysis revealed a non-linear association between FBG and atherosclerosis risk prevalence, with a risk threshold at 5.10 mmol/L. This suggests that the atherosclerosis risk threshold in Chongqing is significantly lower than the international prediabetes standard of 5.60 mmol/L. Subgroup analyses showed sex and age differences, with lower thresholds in women and younger individuals. Long-term elevation of FBG was associated with increased atherosclerosis risk. The study suggests that intervention strategies should be based on dynamic blood glucose trajectories and population-specific thresholds, especially lower thresholds for women and younger individuals. This study provides evidence-based support for regional atherosclerosis risk prevention and control.

Hemoglobin A1c (HbA1c) interpretation can be affected by genetic and hematologic factors that alter erythrocyte turnover. This study investigated red blood cell (RBC) profiles and metabolomic alterations linked to glycemic variability in type 2 diabetes (T2D) and evaluated the effects of common RBC genetic disorders on HbA1c interpretation. Participants were recruited in Nakhon Si Thammarat, Thailand. In Phase 1, 244 normoglycemic participants and 447 individuals with T2D were enrolled. In Phase 2, 45 participants from each group were analyzed for hematologic and biochemical parameters. In Phase 3, liquid chromatography-mass spectrometry (LC-MS)-based RBC metabolomics were performed in 10 individuals without diabetes and 14 individuals with diabetes. Fasting blood glucose, fructosamine, and ferritin showed no significant differences, whereas HbA1c was significantly lower in those with RBC disorders for both individuals without diabetes (P = .001) and individuals with diabetes (P < .001) groups. Red blood cells with hypochromic microcytosis in β-thalassemia heterozygote (BTH) were used as a model to explore metabolomic changes associated with normal and high HbA1c levels. Multivariate analyses revealed distinct clustering patterns in high-HbA1c cases. Interestingly, 5-oxo-L-proline exhibited the highest fold change (FC = 6.90, P = .0004), followed by 5-aminolevulinate and D-gluconic acid, along with increased oxidized/reduced glutathione and decreased NADH and sphingomyelin. Distinct RBC metabolic signatures were observed in BTHs with elevated HbA1c, highlighting alterations in redox and heme metabolism. These findings provide a basis for future investigations into RBC-derived metabolites as complementary tools for glycemic assessment in individuals with thalassemia and hemoglobinopathies.

Hemoglobin (Hb) concentration is a fundamental physiological marker widely used in the diagnosis of anemia and the assessment of cardiovascular health. Although invasive blood testing provides high accuracy, its reliance on laboratory infrastructure limits scalability and real-time applicability. Here, we present Hb-PPG, a four-wavelength photoplethysmography (PPG) dataset designed to support research on non-invasive hemoglobin assessment and cardiovascular monitoring. The dataset comprises 1008 PPG signal segments acquired at 660, 730, 850, and 940 nm from 252 adult subjects, alongside reference measurements of hemoglobin, fasting blood glucose, and brachial artery systolic and diastolic blood pressure. Hb-PPG enables systematic investigation of wavelength-dependent PPG signal characteristics and their relationships with hematological and hemodynamic parameters. By providing high-quality, multi-wavelength optical signals with clinically grounded reference data, this dataset facilitates the development, validation, and benchmarking of non-invasive approaches for hemoglobin estimation and related vascular health applications. The dataset is intended to support algorithm development, benchmarking, and methodological studies in non-invasive hemoglobin estimation, rather than direct clinical diagnosis.

Harnessing Clinical and Biochemical Data for Personalized Cardiovascular Risk Prediction: a Machine Learning Approach Toward Precision Nutrition.

Quantitative evaluation of retinal vascular morphology based on the human visual bionic mechanism for the evaluation of diabetic retinopathy onset.

While cardiovascular-kidney-metabolic (CKM) syndrome has been recognised as a continuum of interconnected metabolic, renal, and cardiovascular dysfunction, practical risk stratification tools for cognitive outcomes in the early, modifiable stages of this syndrome remain lacking. This study aimed to develop an interpretable machine learning model to estimate long-term risk of incident cognitive impairment among early-stage CKM syndrome. This prospective cohort study leveraged data from the China Health and Retirement Longitudinal Study, a nationally representative cohort of adults. A total of 4462 participants with CKM stages 0-2 at baseline (2011) and complete follow-up through 2020 were included. Incident cognitive impairment was defined as cognitive performance >1 SD below the age-adjusted mean. Candidate predictors were screened using the Boruta algorithm and LASSO regression, followed by multicollinearity assessment. Nine machine learning models were trained and validated, and their discrimination, calibration, and clinical utility were evaluated. Model interpretability was assessed using Shapley Additive Explanations (SHAP). During 10 years of follow-up, 525 participants (11.8%) developed cognitive impairment. Ten predictors were retained, including education, total cholesterol, age, fasting blood glucose, uric acid, estimated glucose disposal rate, diastolic blood pressure, relative fat mass, CKM stage, and metabolic syndrome. The XGBoost model demonstrated the best performance (validation AUC = 0.726), strong calibration, and favourable decision curve benefit. SHAP analysis identified education, total cholesterol, and age as the top predictors. Our interpretable machine learning framework, built upon readily accessible clinical and metabolic parameters, provides a robust and clinically applicable tool for predicting 10-year risk of cognitive impairment among individuals with early-stage CKM syndrome.

Gegen Qinlian decoction ameliorates insulin resistance in type 2 diabetes: A systematic review and meta-analysis of RCTs with mechanistic insights into SIRT1/AMPK pathway activation.

Physiotherapist-led health promotion interventions in primary care can reduce metabolic risk factors for people with or at risk of metabolic syndrome: a systematic review.

The effect of whole-body cryostimulation treatments on the profile of selected adipokines and sirtuins in middle-aged individuals with varying degrees of body fatness.

Cholecystectomy with jejunoileal bypass ameliorates diabetic metabolism in mice with type 2 diabetes through modulation of FXR and TGR5 signaling.

Erucic acid, eicosapentaenoic acid, and docosahexaenoic acid consumption affect hepatic steatosis in mice fed a western diet.

Gardenia jasminoides Ellis polysaccharides improve gut microbiota disorder and glucose homeostasis in type 2 diabetic mice.

Renin inhibition improved muscular function by alleviating insulin resistance and AGEs/RAGE signaling in skeletal muscle associated with high glucose: Exploration of renin inhibitor tanshinone IIA.

Design, synthesis, and antidiabetic evaluation of triazolopyrimidine thioacetamides as potent and selective α-glucosidase inhibitors.

The effect of abdominal massage on gastrointestinal complications in enterally fed pediatric intensive care patients.

Design, synthesis and biological evaluation of hydroxycinnamoylamides derivatives as potent glucosidase inhibitors.

Metabolic dysregulation in critical illness may involve early changes in early morning fasting blood glucose (FBG) and high-density lipoprotein cholesterol (HDL-C), but the prognostic value of combining these measures is unclear. We analyzed adult ICU patients from MIMIC-IV (v3.1) with FBG (03:00-07:59) and HDL-C measured within 24h of admission. Using multivariable Cox models, we assessed the association between the FBG/HDL-C ratio and 28-day all-cause mortality, examining nonlinear effects via restricted cubic splines and exploratory mediation by white blood cell count (WBC) and blood-urea-nitrogen (BUN). Findings were externally validated in the eICU database. Elevated FBG/HDL-C ratios were independently associated with 28-day all-cause mortality, with a nonlinear threshold identified at 5.934 and an AUC of 0.773. This association may be partially mediated by systemic inflammation and renal impairment. Among critically ill patients with available FBG and HDL-C measurements, the FBG/HDL-C ratio was independently associated with short-term mortality, suggesting its potential as a supplementary risk stratification tool-though generalizability is limited by nonroutine HDL-C testing.

Purpose: This study examined the associations between fasting blood glucose (FBG), glycated hemoglobin (HbA1c), fructosamine, and depression among adults with type 2 diabetes mellitus (T2DM) using nationally representative data from the Korea National Health and Nutrition Examination Survey (KNHANES).Methods: A descriptive cross-sectional study was conducted using secondary data from the second year (2020) of the eighth KNHANES. Adults diagnosed with T2DM were included. Depression was assessed using the Patient Health Questionnaire-9. Complex-sample analyses were applied to account for the survey design, and hierarchical multivariable logistic regression analyses were performed to evaluate associations between glycemic indices reflecting different temporal windows and depression.Results: Depression was not significantly associated with FBG. In contrast, depression prevalence was significantly higher among participants with normal fructosamine levels, whereas it was significantly lower among those with normal HbA1c levels. Younger age and smoking were associated with higher odds of depression, while cohabitation and employment were associated with lower odds.Conclusion: Among adults with T2DM, glycemic indices representing different time frames demonstrated distinct associations with depression. Long-term glycemic control, as indicated by HbA1c, was associated with lower odds of depression, whereas intermediate-term glycemic control, reflected by fructosamine, showed an opposite association. These findings underscore the importance of considering the temporal characteristics of glycemic markers when interpreting their relationships with depression and highlight the need for longitudinal studies to clarify underlying mechanisms.

Background: Managing type 2 diabetes (T2D) is challenging, and doctors often need treatments that help with more than just blood sugar control. Dapagliflozin is one such medication, offering benefits for heart, kidney, and metabolic health. Yet, real-world evidence on dapagliflozin use and perspectives among physicians in India is limited. Therefore, this study aims to understand real-world clinical and cardio-renal outcomes with dapagliflozin in the management of T2D from Southern India. Methods: A questionnaire-based survey was conducted among physicians in southern India. It comprised 24 questions addressing the use of dapagliflozin in clinical practice and its effect on blood pressure, Hemoglobin A1c (HbA1C), fasting blood glucose, estimated glomerular filtration rate (eGFR), and its overall safety profile. Descriptive analysis was performed, and outcomes were expressed as percentages. Result: A total of 251 physicians were included in this study. Physicians reported significant clinical benefits from the use of dapagliflozin in routine practice. Most physicians (60.56%) observed an average HbA1c reduction of 1.1-1.5% within three months, with evident glycemic improvement often seen by 2-4 weeks. Combination therapy of dapagliflozin with metformin was common (93.63%). Dapagliflozin was frequently prescribed for adults aged 41-60 years. Among hypertensive patients, more than half of the physicians (60.56%) reported a 5-10 mmHg reduction in blood pressure. According to 60.16% of physicians, the key cardiovascular benefit was a reduction in major adverse cardiac events. Renal observations of physicians (69.72%) reported an initial mild decrease in eGFR followed by stabilization, and improved proteinuria in many patients. Metabolic improvements such as reduced triglycerides and increased high-density lipoprotein cholesterol were also reported (50.60%). Adverse events were infrequent, and most physicians (66.93%) had not encountered diabetic ketoacidosis. Conclusion: The survey demonstrated that physician’s favour dapagliflozin for managing T2D in a wide range of patients, and it is found to be both effective and well-tolerated in routine practice.

Background: Thyroid dysfunction (TD) is frequently observed in patients with type 2 diabetes mellitus (T2DM) and may influence glycemic control. Despite growing evidence globally, data from Bangladesh remain limited.Objective: To evaluate the prevalence of thyroid dysfunction and its association with glycemic and clinical parameters among T2DM patients attending a tertiary care hospital. Materials and Methods: A cross-sectional observational study was conducted from January to December 2025 in 120 T2DM patients at Jalalabad Ragib-Rabeya Medical College, Sylhet. Patients with type 1 diabetes, known thyroid disease, pregnancy, acute illness, or use of drugs affecting thyroid function were excluded. Demographic and clinical data, including age, sex, duration of diabetes, BMI, and blood pressure, were collected. Fasting blood glucose, 2-hour postprandial glucose, HbA1c, serum creatinine, FT3, FT4, and TSH were measured. TD was defined by abnormal thyroid hormone levels (FT3, FT4, TSH). Data were analyzed using t-tests, Chi-square tests, and Pearson’s correlation, with p &lt; 0.05 considered significant. Results: TD was observed in 50% of patients, more frequent in males (61.7%) than females (38.3%). Hypothyroidism (38.3%) predominated over hyperthyroidism (11.7%). T2DM patients with TD had significantly higher TSH levels (7.27 ± 5.25 vs 2.31 ± 1.48 µIU/mL; p &lt; 0.001), while other biochemical parameters were comparable. HbA1c positively correlated with TSH (r = 0.307; p = 0.001). Conclusion: Thyroid dysfunction is common among T2DM patients and is associated with poor glycemic control. Routine thyroid screening may aid in better diabetes management.