Sodium-glucose cotransporter 2 (SGLT2) inhibitors provide important glycemic, cardiovascular, and renal benefits in patients with type 2 diabetes mellitus (T2DM). However, their long-term effects on mineral and electrolyte homeostasis in routine clinical practice remain uncertain.

To assess the effects of dapagliflozin on serum calcium, magnesium, phosphorus, creatinine, and parathyroid hormone (PTH) levels in patients with T2DM over two years.

This retrospective cohort study included adults with T2DM treated with dapagliflozin at King Saud University Medical City, Riyadh, Saudi Arabia, between January 2023 and August 2025. Laboratory values were collected at baseline and after one and two years of treatment. Longitudinal changes were evaluated using descriptive statistics, one-way analysis of variance with post-hoc comparisons, and multivariable linear regression.

The study included 549 patients with a mean age of 62.9 ± 12.8 years, and 49.4% were male. Serum calcium increased significantly after one year of dapagliflozin therapy compared with baseline (p = 0.009), with no further significant increase during the second year. Serum magnesium decreased significantly by the second year (p < 0.001). Serum creatinine increased significantly at both follow-up points compared with baseline (p < 0.001). No significant longitudinal changes were observed in serum phosphorus or PTH. In multivariable analysis, the year of measurement independently predicted changes in serum magnesium and phosphorus levels.

Long-term dapagliflozin therapy was associated with statistically significant but clinically modest changes in serum calcium, magnesium, and creatinine, while phosphorus and PTH remained stable over two years. These findings support the overall metabolic safety of dapagliflozin in routine practice. Nevertheless, periodic monitoring of renal function and electrolyte levels, particularly magnesium, may be advisable in patients receiving prolonged therapy or those at increased risk of renal or electrolyte disturbances. Further prospective studies are needed to clarify relevance of these biochemical changes in vulnerable populations.

The global increase in obesity, type 2 diabetes mellitus (T2DM), and metabolic dysfunction-associated steatotic liver disease (MASLD) has led to a higher use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) among patients undergoing gastrointestinal endoscopy. Although GLP-1RAs provide significant metabolic, cardiovascular, and hepatic benefits, their tendency to slow gastric emptying has raised concerns about retained gastric contents (RGC), procedural complications, and a greater risk of pulmonary aspiration during sedation or anesthesia. This review offers a translational narrative synthesis of mechanistic, physiological, and clinical evidence connecting GLP-1RA therapy to changes in gastric motility and peri-endoscopic outcomes. Data from pharmacological studies, scintigraphic evaluations, large observational cohorts, and international consensus statements are combined to guide physiology-based procedural decisions. Evidence consistently indicates that GLP-1RA exposure is associated with a higher incidence of RGC and more frequent procedural disruptions during upper gastrointestinal endoscopy. However, it remains uncertain whether RGC leads to clinically significant aspiration. Consistent with this, real-world data reveal no increase in aspiration pneumonia among GLP-1RA users undergoing colonoscopy, with reported aspiration rates of approximately 0.01%-0.05%. Likewise, during upper gastrointestinal endoscopy, only a small absolute rise in aspiration-related events has been observed, involving fewer than 0.3% of procedures. Current guidelines favor continuing GLP-1RA therapy alongside dietary modification, structured risk assessment, selective gastric point-of-care ultrasound (POCUS), and multidisciplinary communication, rather than routine cessation. Emerging prospective evidence indicates that implementing a pre-procedural clear liquid diet, with individualized timing of weekly agents, may reduce the risk of clinically significant RGC, complementing existing dietary preparation strategies.

Type 2 diabetes mellitus (T2DM), atherosclerotic cardiovascular disease (ASCVD), heart failure with preserved ejection fraction (HFpEF), metabolic dysfunction-associated steatotic liver disease (MASLD), hypertension, and chronic kidney disease (CKD) share risk factors and may represent endpoints of a pathophysiological cardiometabolic continuum. We analyzed data suggesting these phenotypes arise along a unified cardiometabolic disease (UCD) continuum with distinct stages, biomarkers, and therapeutic targets.

A structured narrative review was conducted using PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar. Searches combined terms for mechanistic drivers (visceral adipose tissue, ceramides, lipotoxicity, NF-κB/NLRP3 signaling, gut microbiota, TMAO, adipokines, endothelial dysfunction, epicardial fat, metabolic flexibility) and clinical endpoints. Priority was given to peer-reviewed translational studies, major outcome trials, and consensus statements published between 2017-2026.

Current evidence supports a mechanistic framework in which visceral adipose tissue dysfunction and ectopic lipid accumulation, progressing through ceramide-mediated lipotoxicity, NF-κB/NLRP3-driven inflammation, gut microbiome-derived endotoxemia and TMAO, adipokine dysregulation, endothelial dysfunction, epicardial fat-mediated cardiac remodeling, impaired metabolic flexibility, and a cardiorenal amplification loop. Stage-specific mediators (e.g., ceramides, NLRP3, TMAO, leptin-adiponectin ratio) serve as biomarkers. The benefits of GLP-1 receptor agonists, SGLT2 inhibitors, and finerenone across T2DM, ASCVD, HFpEF, MASLD, and CKD reflect pharmacologic modulation of this continuum.

Data support a UCD model where T2DM, ASCVD, MASLD, HFpEF, hypertension, and CKD are manifestations of a progressive pathophysiological continuum. Framing these conditions as stages of a continuum informs risk stratification, biomarker development, and mechanism-guided therapy, providing a framework for designing trials targeting the continuum rather than individual endpoints.

Coronary heart disease (CHD) remains a leading cause of mortality worldwide, with individuals with diabetes mellitus (DM) facing markedly elevated risk due to complex inflammatory and metabolic disturbances. Emerging composite inflammatory and metabolic indices have demonstrated promise in enhancing cardiovascular risk stratification, yet research quantifying and comparing their respective predictive performance and assessing their relative contributions remains limited. This study aimed to develop a clinically applicable model for early CHD risk prediction in diabetic patients using novel composite inflammatory and metabolic indices.

This study utilized data from 3379 diabetic participants in the NHANES 1999-2018 survey cycles. Additionally, an independent external set of 902 patients from Qilu Hospital of Shandong University served as the validation cohort. Novel inflammatory and metabolic indices were calculated. Feature selection was performed via LASSO regression, the univariate logistic regression, and the Boruta algorithm. Nine machine learning (ML) models were developed using selected predictors. Model performance was evaluated using the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis. SHapley Additive exPlanations (SHAP) values were used to interpret model predictions and identify key contributing features.

Five composite indices UHR (uric acid-to-HDL ratio), MHR (monocyte-to-HDL ratio), NPAR (neutrophil-to-albumin ratio), NLR (neutrophil-to-lymphocyte ratio), and AIP (atherogenic index of plasma) were identified as robust predictors of CHD. The random forest (RF) algorithm achieved the highest performance, with an AUC of 0.852 in the internal validation set and 0.713 in the external cohort. Calibration plots, Brier scores, and decision curve analysis further confirmed the RF model's predictive reliability and clinical utility. SHapley Additive exPlanations (SHAP) value analysis revealed that UHR, MHR, NLR, age, and hypertension were the key features driving CHD prediction.

We developed and externally validated an ML model incorporating five composite inflammatory and metabolic indices (UHR, MHR, NLR, NPAR, AIP), which demonstrated promising performance in predicting CHD risk in diabetic patients.

Heart failure (HF) is a common complication in diabetes mellitus (DM), affecting approximately 40% of HF patients. While inflammation plays a crucial role in both conditions, the prognostic value of inflammatory markers in patients with both DM and HF remains unestablished.

To examine the associations of neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and (neutrophil + monocyte)/lymphocyte ratio (NMLR) with 30-day mortality in ICU patients with both DM and HF.

This retrospective cohort study analyzed 1318 patients with both HF and DM from the MIMIC-IV database. NLR, MLR, and NMLR were calculated from complete blood counts within 24 h of ICU admission. Multivariate Cox regression, restricted cubic spline analysis, and ROC curves assessed predictive performance.

Among 1318 patients, 239 died within 30 days. The deceased group had significantly higher median values of NLR (10.9 vs. 6.5), MLR (0.9 vs. 0.4), and NMLR (12.1 vs. 7.0) compared to survivors (all P < 0.001). After adjustment, each one-unit increase in MLR was associated with 11% increased mortality risk (HR = 1.11, 95% CI: 1.04-1.19, P = 0.002), while NMLR and NLR showed 1% increases, respectively (NMLR: HR = 1.01, 95% CI: 1-1.01; NLR: HR = 1.01, 95% CI: 1-1.01; both P < 0.001). MLR demonstrated the highest discriminative capacity (AUC = 0.672), followed by NMLR (AUC = 0.658) and NLR (AUC = 0.650).

NLR, MLR, and NMLR are independent predictors of 30-day mortality in ICU patients with DM and HF, with MLR showing superior discriminative capacity.

To investigate whether miR-145-5p regulates high-glucose-induced ferroptosis and injury in renal tubular epithelial cells through the KLF4/SIRT3/GPX4 signaling axis. Ferroptosis, a regulated form of iron-dependent cell death, has been increasingly implicated in DKD pathogenesis. The present investigation was designed to explore the functional significance and underlying molecular mechanisms of the miR-145-5p/KLF4/SIRT3/GPX4 signalling cascade in ferroptotic cell death of renal tubular epithelial cells during DKD.

A high-glucose-stimulated in vitro DKD model was constructed using human renal tubular epithelial cells (HK-2) exposed to 25.0 mmol/L glucose. Gene and protein expression profiles were characterised through RT-qPCR, Western blotting and immunofluorescence staining. Cellular viability, apoptotic rates and ferroptosis-associated biomarkers were quantified using CCK-8 assay, flow cytometric analysis, ELISA and JC-1 mitochondrial probe, respectively. Molecular binding interactions were confirmed through dual luciferase reporter assays and co-immunoprecipitation experiments. Intracellular reduced glutathione (GSH) content and GPX4 enzymatic activity were additionally measured to evaluate the functional status of the antioxidant arm of ferroptosis.

High glucose exposure triggered time-dependent cellular damage and ferroptotic responses in HK-2 cells, characterised by elevated miR-145-5p levels alongside diminished KLF4, SIRT3 and GPX4 expression. Forced expression of miR-145-5p aggravated cellular damage and ferroptotic phenotypes, whilst its functional suppression conferred cytoprotection. Mechanistic analyses demonstrated that miR-145-5p directly engages the 3'-UTR of KLF4 to repress its expression. Restoring KLF4 expression attenuated high-glucose-mediated cellular injury and enhanced SIRT3 and GPX4 levels. Co-immunoprecipitation assays verified a physical protein-protein association between KLF4 and SIRT3. Functionally, HG stimulation reduced intracellular GSH content and GPX4 enzymatic activity. These changes were aggravated by miR-145-5p overexpression but were partially reversed by miR-145-5p inhibition or KLF4 overexpression.

In the context of hyperglycemia, miR-145-5p facilitates ferroptotic cell death in renal tubular epithelial cells through KLF4 suppression, consequently attenuating the SIRT3/GPX4 signalling cascade and worsening DKD-related cellular injury. This regulatory axis may constitute a promising molecular intervention target for DKD treatment.

Mulberry ripe fruit (MP) is a popular berry known for its rich content of health-beneficial components such as anthocyanins and polysaccharides. While traditional Chinese medicine suggests therapeutic effects of mulberry fruits on diabetes, their high content of small-molecule sugars discourages diabetic patients from consuming them. This study utilized Lactobacillus plantarum CICC 24202 and Lactobacillus brevis YM 1301 to ferment mulberry homogenate at 37°C for 60 h. The fermented mulberry homogenate was freeze-dried to obtain fermented mulberry product (FMP). The content of small-molecular sugars in FMP decreased by approximately 50%, while the content of polysaccharides, the active components linked to the hypoglycemic effect of MP, increased by roughly 80%. The impact of FMP on type 2 diabetes (T2DM) was evaluated in a mouse model induced by a high-fat diet combined with STZ. The findings revealed that FMP and MP improved various parameters, including fasting blood glucose, serum insulin, serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol, and FMP exerted a superior improving effect on these indices than MP. In addition, FMP also elevated levels of glucagon-like peptide-1 (GLP-1) and adiponectin in serum, reduced epididymal fat accumulation, and alleviated renal function damage in diabetic mice. Therefore, lactic acid bacteria fermentation represents a promising strategy to reduce small-molecular sugars in mulberry, enrich product diversity, and improve the health-promoting properties of mulberry products.

Diabetic kidney disease (DKD) is a major microvascular complication of diabetes and remains one of the leading causes of end-stage renal disease, significantly affecting patients' survival rates and quality of life. Currently, commonly used clinical assessment indicators include proteinuria and estimated glomerular filtration rate (eGFR); however, these indicators have limited sensitivity, making it difficult to detect early kidney damage in a timely manner and to accurately monitor disease progression. This review provides a comprehensive overview of recent progress in identifying various urinary biomarkers that reflect renal tubular injury, oxidative stress, inflammatory responses, fibrotic remodeling, metabolic dysregulation, and exosomal components. Furthermore, we discuss the potential clinical applications of these biomarkers in DKD early diagnosis, disease stratification, and prognostic evaluation. Looking ahead to the future and the ongoing development of multiomics integration and artificial intelligence-assisted modeling, urinary biomarkers are expected to drive DKD diagnosis and management toward a future characterized by early detection, precision, dynamic monitoring, and noninvasive assessment.

Diabetic foot (DF) is a severe and common complication of diabetes mellitus, involving peripheral neuropathy, vascular disease, immune-inflammatory disorders, and impaired tissue repair, with high amputation rates and a heavy medical burden. The Notch1 signaling pathway is highly conserved and participates in regulating cell proliferation, differentiation, apoptosis, angiogenesis, and inflammatory responses. Emerging evidence indicates that dysregulated Notch1 signaling is closely associated with the pathological progression of diabetic foot ulcers (DFU). This review systematically summarizes the role of Notch1 signaling in angiogenesis, inflammation, peripheral neuropathy, and cell fate regulation during DF pathogenesis, and discusses the potential therapeutic strategies targeting Notch1 pathway for DFU. We aim to provide new insights into the molecular mechanism and targeted therapy of DF.Infographic available for this article.

Protein tyrosine phosphatase 1B (PTP1B) is a well-known and promising drug target involved in the negative regulation of insulin and leptin signaling, and new anti-diabetic molecules for the treatment of type 2 diabetes are directly in its hands. A series of PTP1B inhibitors was discovered and characterized using in silico techniques, including virtual screening, molecular docking, ADMET profiling, toxicity prediction, VEGA-QSAR analysis, molecular dynamics (MD) simulation, and density functional theory (DFT) calculations. A starting library of 1000 anti-diabetic compounds was screened, and PubChem CID 44560696 was identified as the most successful hit. The most potent inhibitor was then identified as CID 44560744 through chemical analogy-based refinement, with a binding free energy of - 9.13 kcal/mol and the ability to form several stabilizing hydrogen bonds and hydrophobic interactions with the key catalytic residues. DFT-optimized geometry and docking revealed that the lead compound shows high stability and strong PTP1B inhibition, showing superior binding affinity compared to ursolic acid, which exhibited a lower binding energy of - 6.34 kcal mol^-1. The MD simulations showed that the PTP1B-ligand complex was structurally stable and compacted during the 200 ns simulation, with desirable profiles for RMSD, RMSF, Rg, SASA, and hydrogen bonds. The DFT and FMO analyses indicated that the compound exhibits extreme chemical reactivity and electron-transfer capability, owing to its low HOMO-LUMO gap, high softness, and moderate electrophilicity. The results of ADMET and toxicity evaluations (SwissADME, ProTox-II, and VEGA-QSAR) pointed to satisfactory solubility, non-carcinogenicity, no mutagenicity, and high pharmacological safety. Overall, the synergy of the computational methods has made CID 44560744 a lead scaffold for the development and optimization of selective PTP1B inhibitors for T2DM therapy.