Objective: To investigate the clinical characteristics of symptoms and signs of ocular surface lesions in dry eye patients with type 2 diabetes mellitus (T2DM) of different disease durations. Methods: A cross-sectional study was conducted. Consecutive T2DM patients complicated with dry eye who visited the Special Clinic for Diabetic Ocular Surface Diseases at Qingdao Eye Hospital, Shandong First Medical University from January 2020 to December 2024 were enrolled as the T2DM group. Dry eye patients without T2DM from the Dry Eye Clinic and age-and gender-matched healthy volunteers were recruited as the non-T2DM group and control group, respectively. The T2DM group was further divided into four stages according to disease duration: Stage Ⅰ (duration≤5 years), Stage Ⅱ (5 years<duration≤10 years), Stage Ⅲ (10 years<duration≤20 years), and Stage Ⅳ (duration>20 years). Ocular symptoms were evaluated using the Ocular Surface Disease Index (OSDI) questionnaire. Ocular surface function was assessed by corneal sensitivity (CS), corneal fluorescein staining (CFS) score, Schirmer Ⅰ test (SⅠT), tear meniscus height (TMH), non-invasive first tear film break-up time (NIKf-BUT), non-invasive average tear film break-up time (NIKav-BUT), lipid layer thickness (LLT), and meibomian gland loss (MGL) grading score. Anterior segment optical coherence tomography was used to measure central corneal epithelial thickness (CCET) and central corneal thickness (CCT). In vivo confocal microscopy was performed to detect corneal nerve fiber parameters. Spearman's rank correlation analysis was used to evaluate the correlations between variables. Results: A total of 278 T2DM patients (556 eyes) were enrolled in the T2DM group, with a mean age of (60.25±8.71) years, a male-to-female ratio of 117∶161, and a mean disease duration of (11.09±8.02) years; among them, 84 cases were Stage Ⅰ, 81 cases Stage Ⅱ, 90 cases Stage Ⅲ, and 23 cases Stage Ⅳ. The non-T2DM group included 60 patients (120 eyes), with a mean age of (58.52±7.93) years and a male-to-female ratio of 23∶37. The control group comprised 53 healthy volunteers (106 eyes), with a mean age of (58.79±5.73) years and a male-to-female ratio of 21∶32. There were no statistically significant differences in age and gender distribution among the three groups (all P>0.05). Compared with the control group, the T2DM group showed significantly higher OSDI score (31.58%±20.56%), MGL grading score (3.59±0.95) and CFS score (1.84±3.01) (all P<0.05); while significantly lower SⅠT [(5.79±3.10) mm], NIKf-BUT [(5.81±3.14)s], NIKav-BUT [(9.31±4.85)s], LLT [(60.48±16.6) nm], CCET [(51.95±5.56) μm], CS [(56.9±8.30) mm], corneal endothelial cell density [(2 596±465.38)/mm²], and all corneal nerve parameters (including paracentral corneal nerve fiber density and length, etc.) (all P<0.05). Compared with the non-T2DM group, the T2DM group had significantly lower LLT, CCET, CS, OSDI score and all corneal nerve parameters, along with significantly higher MGL grading score and CFS score (all P<0.05); no statistically significant differences were found in SⅠT, NIKf-BUT and NIKav-BUT between the two groups (all P>0.05). In T2DM patients with disease duration≤5 years, compared with the control group, the OSDI score (23.98%±18.21%) and MGL grading score (3.35±0.91) were significantly increased, while SⅠT [(5.65±2.93) mm], LLT, NIKf-BUT and all corneal nerve parameters were significantly decreased (all P<0.05); meanwhile, compared with the non-T2DM group, this subgroup had significantly lower OSDI score and significantly higher MGL grading score (all P<0.05). When the disease duration exceeded 10 years, the OSDI score further increased to be comparable with that of the non-T2DM group, and NIKf-BUT [(5.44±2.92)s], CFS score (2.75±3.25), CCET [(51.36±4.17) μm], CS [(55.21±8.02) mm] showed statistically significant differences compared with both the control group and non-T2DM group (all P<0.05). Spearman's correlation analysis indicated that disease duration was significantly positively correlated with OSDI score, MGL grading score and CFS score, and significantly negatively correlated with NIKf-BUT, CCET, CS and all corneal nerve parameters (all P<0.05). Conclusions: Ocular surface lesion characteristics vary among dry eye patients with T2DM of different disease durations: decreased tear secretion, meibomian gland dysfunction and corneal nerve structural changes occur when the disease duration is ≤5 years, and corneal hypoesthesia and epithelial thinning develop when the duration exceeds 10 years, with lesions gradually worsening as the disease progresses. Compared with non-diabetic dry eye, significant differences exist in meibomian gland function, corneal nerves and epithelial barrier between the two groups.

Diabetic retinopathy (DR) is one of the most important microvascular complications of diabetes mellitus and remains a major cause of preventable blindness worldwide. Insulin resistance plays a pivotal role in the development of diabetes and its associated complications. The triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance derived from fasting plasma glucose and triglyceride levels, has gained attention as a simple and practical metabolic marker. However, data linking the TyG index with diabetic retinopathy, particularly in South Asian populations, are still limited. A hospital-based cross-sectional study was conducted at Bir Hospital, Kathmandu, Nepal, between April 2023 and October 2024. Adult patients with diabetes mellitus, excluding those with gestational diabetes, acute illness, non-diabetic causes of hypertriglyceridaemia, conditions affecting lipid or glucose metabolism, prior retinal interventions, or non-diabetic retinal diseases, underwent comprehensive clinical, biochemical, and ophthalmic evaluations. The triglyceride-glucose (TyG) index was calculated as ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL) / 2], and participants were categorized into quartiles. Diabetic retinopathy was graded using internationally accepted clinical severity scales. Associations were assessed using univariate and multivariate logistic regression, and ROC curve analysis evaluated the discriminatory performance of the TyG index. Among 83 patients with diabetes mellitus (median age 56 years [IQR 48.5-64], 50.6% male, median diabetes duration 6 years [IQR 3-12]), the median triglyceride-glucose (TyG) index was 9.98 (IQR 9.485-10.445). Diabetic retinopathy (DR) prevalence was 48.2%, increasing across TyG quartiles from 9.5% in Q1 to 85.7% in Q4 (p < 0.001), with a significant trend in DR severity (p < 0.001). TyG correlated moderately with HbA1c (Spearman r = 0.54, p < 0.001). In multivariable logistic regression adjusted for age, total cholesterol, and HDL, the odds ratio for DR per standard deviation increase in TyG was 4.00 (95% CI 1.75-9.16, p = 0.001); for Q4 vs. Q1, 24.15 (95% CI 3.15-185, p = 0.002). Findings were robust in sensitivity analyses excluding insulin users (OR 4.35, 95% CI 1.40-13.5, p = 0.011) and outliers (OR 3.80, 95% CI 1.60-9.00, p = 0.002), and stratified by diabetes duration (≥ 5 years: OR 5.20, 95% CI 1.80-15.0, p = 0.002) and sex (males: OR 3.80, 95% CI 1.20-12.0, p = 0.023; females: OR 4.50, 95% CI 1.30-15.5, p = 0.017). TyG predicted DR with an area under the ROC curve of 0.83 (95% CI 0.75-0.91), comparable to HbA1c (0.77, DeLong p = 0.29); optimal cutoff 9.78 (sensitivity 88%, specificity 67%). A higher triglyceride-glucose index was strongly associated with both the presence and severity of diabetic retinopathy. Given its simplicity and reliance on routinely available laboratory parameters, the TyG index may be a useful marker for identifying diabetic patients at increased risk of retinopathy, particularly in resource-limited settings. Not applicable. This was a cross-sectional observational study and did not involve a clinical trial requiring registration.

The most important factors for a successful colon capsule endoscopy (CCE) study are the quality of bowel preparation and the capsule excretion during battery life. Incomplete conventional colonoscopy is one of the main indications for CCE. The aim of this study was to analyze clinical and demographic factors for incomplete CCE after an incomplete conventional colonoscopy. A retrospective single-center study was conducted including patients who underwent CCE after an incomplete colonoscopy (IC). Complete CCE was defined as capsule excretion or visualization of hemorrhoidal pedicles within battery time. Demographic (gender and age) and clinical data (obesity, smoking history, diabetes mellitus, hypothyroidism, constipation, depression, psychotropic medication use and history of abdominal or pelvic surgery) were collected. A total of 197 patients were included (mean age 67±10years; 71.6% female). Complete CCE was achieved in 133 (67.5%) of cases. Adequate bowel preparation was observed in 145 (73.6%) of cases. The most common causes of incomplete conventional colonoscopy were colonic fixed angulation (56.3%) and irreducible loop (42.1%), with no significant difference in capsule completion between these groups (p=0.770). Obesity (OR 5.328; 95% CI 1.735-16.369; p = 0.003) and constipation (OR 2.999; 95% CI 1.264-7.114; p = 0.013) were independently associated with incomplete CCE. Obesity and constipation are risk factors for incomplete CCE. Adjustments or intensification of bowel preparation protocols may improve completion rates in these patients.

Plasma MicroRNA Expression Differentiates Individuals with Isolated Impaired Fasting Glycaemia from Normal Glucose Tolerance and Type 2 Diabetes Mellitus

Type 3c diabetes mellitus (T3cDM) is increasingly recognized with the rising incidence of pancreatitis, yet its risk profile and early diagnostic tools remain insufficient. Identifying independent risk factors and establishing reliable prediction models are essential for improving early detection and clinical management. A retrospective study was conducted on 864 patients with pancreatitis admitted to Zhengzhou Central Hospital from January 2020 to December 2022. They were randomly divided into a training set (n = 604) and a validation set (n = 260) using a 7:3 ratio. Collect baseline data, laboratory indicators, and outcomes of T3cDM through case follow-up. Single factor and multiple factor logistic regression were used to screen potential risk factors, and after excluding collinearity and clinically unrelated variables, a multiple factor logistic regression model was constructed; Evaluate model performance using receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve (DCA); Construct a column chart and dynamic prediction model based on independent risk factors, and use tenfold cross validation to verify the stability of the model. In addition, 172 patients from external hospitals were included for external validation. Furthermore, Kaplan-Meier (K-M) curve analysis was performed to evaluate the survival characteristics of T3cDM in patients with pancreatitis. In 864 patients with pancreatitis, the cumulative incidence rate of T3cDM was 16.67% (144/864). The baseline data of training set and verification set were balanced (P > 0.05), and there was no significant selection bias. Multivariate logistic regression showed that a history of pancreatitis (OR = 4.301, 95%CI: 2.370-7.804, P < 0.001), alcohol consumption factors (OR = 4.542, 95% CI: 1.669-12.360, P = 0.003), body mass index (BMI) (OR = 1.209, 95% CI: 1.038-1.409, P = 0.015), blood potassium (K⁺) (OR = 2.119, 95% CI:1.440-3.938, P = 0.018), maximum blood glucose(Max Glu) (OR = 1.079, 95% CI:1.015-1.146, P = 0.014), glycated hemoglobin (HbA1c%) (OR = 1.401, 95% CI: 1.145-1.716) Triglycerides (TG) (OR = 1.022, 95% CI: 1.006-1.039, P = 0.008), triglyceride glucose index (TyG) (OR = 1.802, 95% CI: 1.248-2.603, P = 0.002) are independent risk factors for T3cDM in patients with pancreatitis. The column chart model constructed based on the above factors has a training set ROC curve area under the curve (AUC) of 0.857 (95% CI: 0.815-0.899), a sensitivity of 80.3%, and a specificity of 80.4%; The AUC of the validation set is 0.773 (95% CI: 0.691-0.855), with a sensitivity of 72.0% and a specificity of 69.0%. The calibration curve shows that the average absolute error of the training set is 0.023, and the validation set is 0.017. The predicted risk is highly consistent with the actual risk; The DCA curve suggests that the net benefit of the model is significantly higher than that of the "full intervention" or "no intervention" strategies within the risk threshold of 0.05 ~ 0.80. External validation further confirmed the robust predictive performance (AUC = 0.904 [95%CI: 0.838-0.971]). Stratified analysis demonstrated that the model exhibited good predictive efficacy across different age and gender groups. Age-stratified analysis demonstrated that the model exhibited favorable performance across three patient cohorts: young adults (18-44years), middle-aged individuals (45-59years), and elderly patients (60-75years), with AUC values of 0.801, 0.956, and 0.903, respectively. Furthermore, the K-M curve showed no significant difference in T3cDM survival curves between the training and validation sets (Log rank P = 0.126, HR = 0.781, 95% CI: 0.545-1.120), and the overall population had a T3cDM free survival rate of approximately 32% at 60months of follow-up. The incidence rate of T3cDM in patients with pancreatitis is high. Previous pancreatitis history, drinking inducement, BMI, K+, Max Glu, HbA1c%, TyG, etc. are independent risk factors for T3cDM; The prediction model and column chart constructed based on the above factors have good discrimination, calibration, and clinical practicality, and can be used as an effective tool for T3cDM risk assessment in patients with pancreatitis. Furthermore, external validation further supports the model's applicability.

Objective: Irisin, a myokine involved in metabolism and glucose regulation, has been associated with obesity, type 2 diabetes mellitus (T2DM), and cardiovascular disease, with inconsistent findings. This study assessed irisin levels in individuals with overweight/obesity with and without newly diagnosed diabetes and examined its association with subclinical atherosclerosis. Methods: Ninety participants were divided into 3 groups: 30 individuals with newly diagnosed T2DM and overweight/obesity (Group 1), 30 individuals with overweight/obesity without diabetes (Group 2), and 30 controls (Group 3). Anthropometrics, glycemic markers, lipid profile, serum irisin, highsensitive C-reactive protein (hs-CRP), and carotid intimal-media thickness (CIMT) were measured. Spearman’s correlation and logistic regression were applied. Results: Serum irisin levels were higher in groups with overweight/obesity than in controls (P = .002) but did not differ by diabetic status. In subgroup analyses, irisin correlated positively with glycated hemoglobin (r = 0.56, P = .001), low-density lipoproteins (LDL-C) (r = 0.50, P = .005), hs CRP (r = 0.38, P = .038), and CIMT (r = 0.63, P &lt; .001) in Group 1 and with LDL-C (r = 0.37, P = .042) and CIMT (r = 0.40, P = .030) in Group 2. In multivariate regression, irisin remained independently associated with increased CIMT in individuals with T2DM and overweight/obesity (adjusted odds ratios (aOR) = 2.03 (95% CI = 1.04-3.94)) and in the overall cohort with overweight/obesity (aOR = 1.98 (95% CI = 1.15-3.42)). Conclusions: Serum irisin is elevated in obesity, irrespective of diabetic status, and is independently associated with subclinical atherosclerosis, suggesting its potential role as an early biomarker of cardiovascular risk. Cite this article as: Assaad SN, Abo Elwafa RA, Gamal Eldin OA, Hassanein NA, Bondok ME. Irisin and subclinical atherosclerosis in individuals with overweight/obesity with and without newly diagnosed type 2 diabetes mellitus. Endocrinol Res Pract. Published online February 6, 2026. doi: 10.5152/erp.2026.25739.

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by elevated blood glucose levels resulting from defects in insulin secretion, insulin action, or both. Persistent hyperglycemia in diabetes leads to disturbances in carbohydrate, fat, and protein metabolism. It is mainly classified into type I and type II DM. Type I Diabetes Mellitus (DM) is primarily managed through insulin replacement therapy, as pancreatic β-cell destruction results in absolute insulin deficiency. In contrast, Type II DM is typically treated with oral hypoglycaemic agents and, when necessary, insulin therapy. Combination therapy is often employed to achieve optimal glycaemic control and minimize complications. Globally, Diabetes Mellitus represents a major public health challenge, with an estimated 589 million adults projected to be affected by 2025, reflecting the increasing prevalence linked to sedentary lifestyles, obesity, and aging populations.

Objective To explore the role of Tai Chi training in improving Type 2 Diabetes Mellitus (T2DM) based on gut microbiota, serum inflammatory factors, and intestinal mucosal barrier function. Methods Thirty-six patients with T2DM underwent 6 months of Tai Chi training. Body composition, biochemical indicators (fasting blood glucose, glycated hemoglobin, etc.), serum inflammatory factors (Tumor Necrosis Factor-α (TNF-α), Interleukin-6 (IL-6), etc.), and gut microbiota (16S rRNA sequencing) were measured. Results After 6 months of Tai Chi training, significant reductions were observed in body weight, BMI, waist circumference, and body fat percentage ( p &amp;lt; 0.05), while lean body mass increased significantly ( p &amp;lt; 0.05). Fasting blood glucose, glycated hemoglobin, insulin resistance index (HOMA-IR), and total cholesterol levels decreased significantly ( p &amp;lt; 0.01). C-reactive protein (CRP), TNF-α, IL-6, IL-1β, and IL-8 levels decreased significantly ( p &amp;lt; 0.01), while the anti-inflammatory factor IL-10 increased significantly ( p &amp;lt; 0.01). The Chao1 and Shannon indices increased significantly ( p &amp;lt; 0.05). The abundance of beneficial bacteria increased significantly, while the abundance of harmful bacteria decreased significantly ( p &amp;lt; 0.01). Markers of intestinal mucosal barrier function, including D-lactate and zonulin, decreased significantly ( p &amp;lt; 0.01), while the level of milk fat globule-EGF factor 8 (MFG-E8) increased significantly ( p &amp;lt; 0.01). Conclusion Tai Chi training can improve blood glucose homeostasis, gut microbiota richness and diversity, intestinal mucosal barrier function, and systemic inflammatory status in T2DM patients. Tai Chi training may be an important approach for personalized treatment of T2DM.

Objectives: The incidence of stroke is higher among type 2 diabetes mellitus (T2DM) patients with a higher mortality rate. Prognostic scores for stroke patients can assist with treatment planning and counseling. The objective of this study was to create a machine-learning-based prognostic score to estimate in-hospital mortality in acute stroke with T2DM. Materials and Methods: This study used data from claims-based diabetes registry at Dr. Sardjito General Hospital, Yogyakarta, Indonesia, to identify patients diagnosed with acute stroke and T2DM between January 2016 and December 2020. Four machine learning algorithms were trained and evaluated based on standard performance metrics. Important features were selected from the best-performing model and implemented in a web-based in-hospital mortality prediction scoring system. Results: Of the 18,652 patients in the registry, the final analytic dataset comprised 749 patients (557 survivors and 192 non-survivors). The random forest showed superiority compared to other models. The six most important features were length of stay, sepsis, pneumonia, age, dyslipidemia, and hemiplegia. Using these features, the web-based system estimates the probability of in-hospital death for an individual patient. Conclusion: Machine learning analysis may support an in-hospital mortality prediction score for patients with acute stroke and T2DM patients by leveraging the key features identified by the random forest model.

It has been proven that diabetes mellitus plays an important role in the occurrence and development of joint fractures. In this study, a 2-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between diabetes and ankle fractures. We pooled the data from the published genome-wide association studies. Diabetes mellitus type 2 was derived from pooled genome-wide association study data of 655,666 European individuals (61,714 patients and 1178 controls). Data on ankle fractures were derived from pooled genome-wide association study data in a total of 460,340 European individuals (6479 patients and 453,861 controls). Using diabetes-associated loci as instrumental variables, we used inverse variance weighting, MR-Egger, weighted median, simple multivariate analysis and weighted multivariate analysis to evaluate the association between diabetes and ankle fracture risk. Reverse MR analysis was performed on the Diabetes mellitus type 2 that were found to be causally associated with ankle fractures in forward MR analysis. Sensitivity analysis was used to evaluate the robustness of the results. Statistical analysis showed a significant causal relationship between diabetes and ankle fractures (inverse variance weighting: OR = 1.07, 95% CI = 1.01-1.32, P = .02). Diabetes mellitus is associated with an increased risk of ankle fracture. The results of MR analysis can be used as a guide for the screening of diabetes and ankle fractures, which is helpful to improve the awareness of screening, early diagnosis and early treatment.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing complication risk. Practical, interpretable risk tools using routine patient data are limited. We conducted a cross-sectional analysis using data from adults with T2DM enrolled in the National Health and Nutrition Examination Survey between 2009 and 2023. DEP was classified based on a Patient Health Questionnaire-9 score of 10 or higher. Twenty-eight candidate predictors encompassing demographic characteristics, clinical and biochemical measurements, and lifestyle factors were initially included. Variable selection was performed using least absolute shrinkage and selection operator regression. Five machine learning algorithms - random forest, extreme gradient boosting (XGBoost), multilayer perceptron, logistic regression, and support vector machine - were trained and evaluated using 5-fold cross-validation. The best-performing model was interpreted through SHapley Additive exPlanations analysis to identify the most influential predictors. A streamlined version incorporating the top 10 predictors was further developed and implemented as a user-friendly web-based risk estimation tool. Among 2837 participants, 449 (15.8%) were identified as having comorbid DEP. The XGBoost model demonstrated the highest discriminative ability, with a validation area under the receiver operating characteristic curve of 0.888, accuracy of 0.834, F1-score of 0.715, sensitivity of 0.577, and specificity of 0.979, surpassing the performance of the other algorithms evaluated. SHapley Additive exPlanations analysis revealed gender, poverty-to-income ratio, sleep duration, smoking status, educational levels, race, age, high cholesterol, hypertension, and insulin use as the most influential predictors. A streamlined XGBoost model incorporating only these 10 variables achieved an area under the curve of 0.886, closely matching the predictive capability of the full model. The deployed web-based tool enables rapid and individualized estimation of DEP risk in patients with T2DM using routinely available clinical and demographic information. Explainable machine learning applied to nationally representative data can accurately identify adults with T2DM at heightened risk of DEP using a small set of noninvasive clinical features. The deployed tool offers a scalable, interpretable, and clinically actionable approach to support early detection and intervention, potentially improving mental health outcomes in this high-risk population.

Background: Local specific biomarkers for MASLD risk stratification are urgently needed in Argentina. Aim: The aim of the study was to characterize the interaction of gut microbiome signatures and genetic and clinical risk factors for MASLD in patients with diabetes from different regions of Argentina. Materials and Methods: We recruited 214 patients with diabetes from different regions of Argentina. Anthropometric, clinical, and lifestyle data were obtained from all participants, who also underwent abdominal ultrasound for MASLD diagnosis and oral swabbing. The PNPLA3 gene was amplified by PCR from the swabs, and the rs738409 genotype was determined via bidirectional sequencing. To profile the MASLD-associated microbiome, stool was collected from 170 participants. V4 16S rRNA gene sequencing was performed, and reads were analyzed using QIIME2 2024.10.1. R Studio 2023.05.1 was used for statistical analyses. Results: MASLD prevalence was 77.9%, with similar rates of occurrence in all regions represented. FIB-4 scores &lt; 1.3 and &gt; 2.67 were detected in 55.3% and 7.4% of patients, respectively. Half of the diabetic patients had the PNPLA3 GG genotype, with the highest rates occurring in patients from Northwestern Argentina (64.9%; p = 0.02 vs. Buenos Aires). The PNPLA3 GG genotype was an independent risk factor for FIB-4 score (p = 0.0008) and a protective factor against glycated hemoglobin (p = 0.004), fasting plasma glucose (p = 0.008), and cholesterol levels (p = 0.02). Marked regional differences were observed in microbiota diversity and composition in Argentina. After adjusting for geographical region, Negativibacillus genus was exclusively detected in diabetic patients with MASLD and GG carriers. The Catenibacterium genus was related to FIB-4 &gt; 2.67. Short-chain fatty acid-producing bacteria were linked to the absence of MASLD. Conclusions: Although some geographical regions of Argentina were not represented in this study and these results therefore cannot be generalized to the country as a whole, these specific signatures could be useful as biomarkers for MASLD risk stratification in Argentines with diabetes.

Background/Objectives: New guidelines for management of metabolic-dysfunction-associated steatotic liver disease (MASLD) patients recommend an individualized medicine approach mainly targeting patients with fibrotic metabolic-dysfunction-associated steatohepatitis (MASH) and metabolic risk factors for progression of disease. This cohort study reports real-world experience for the individual evaluation and final diagnosis of patients on suspicion of fibrotic MASH according to standardized international criteria. We aimed to identify patients with significant fibrosis (F2–F4). Methods: Adult patients with metabolic syndrome and/or elevated alanine aminotransferases (ALT &gt; 50) referred in a 5-year period (2018–2022) on suspicion of fibrotic MASH were included. Medical history, anthropometric measurements, and routine (blood tests, ultrasound) and specific examinations were applied. Liver biopsy was offered for definite diagnosis and to evaluate MASLD characteristics. Patient demographics and characteristics as well as the absolute number and proportion of patients with definite MASLD and fibrotic MASH are reported. Results: A total of 137 adult patients were included. Ten percent of patients were evaluated without liver biopsy and diagnosed with chronic liver diseases other than MASLD. Liver-biopsied patients (n = 123) had a mean age (SD) of 49 (14) years, and 50% were males. Overweight or obesity was present in 94%, dyslipidemia in 74%, hypertension in 40%, and type 2 diabetes mellitus in 34%. Of all 137 patients, 104 (76%) were diagnosed with definite MASLD and 80 (58%) with definite MASH. A total of 74 (54%) patients had definite fibrotic MASH, while 41 (30%) had significant (F2–4) fibrotic MASH. Eight patients (6%) had cirrhotic (F4) MASH. A multivariate logistic regression analysis indicated that patients with type 2 diabetes, older age, and higher BMI were associated with an apparent increased risk of F2–F4 fibrosis. Conclusions: The majority of referred patients had cardiometabolic–hepatic metabolic risk factors and were diagnosed with definite MASLD. More than half of these were diagnosed with fibrotic MASH. Older age, type 2 diabetes, and higher BMI were apparent risk factors for MASH F2–F4 fibrosis. We conclude that the individual cardiovascular–hepatic risk profile applied supports the new guidelines and may be useful for referral and further evaluation at expert care centers in a real-world setting.

Subhepatic cecums are rare conditions (0.3-0.5% of live births) that result from a malrotation event during embryologic development. Although this condition is uncommon, it presents unique challenges for diagnosing appendicitis due to the appendix being displaced to the right upper quadrant instead of its typical right lower quadrant location. An 85-year-old male cadaver with a medical history significant for type 2 diabetes mellitus, atrial fibrillation, systolic congestive heart failure, and severe protein malnutrition was used during routine dissections of the gastrointestinal system. A subhepatic cecum was identified with a vermiform appendix situated just below the liver. Further examination revealed a unique variation in the pathways of the ileocecal artery to accommodate the malrotation. Despite being rare, understanding this developmental variation is beneficial for the accurate diagnosis and treatment of patients with unusual presentations of appendiceal and colonic pathologies.

This study aimed to investigate the association between fasting glucagon levels and the risk of comorbid stroke in hospitalized patients with type 2 diabetes mellitus (T2DM). This study included 1,745 T2DM patients hospitalized at Tianjin Medical University General Hospital from September 1, 2022, to September 30, 2025. Patients were divided into a T2DM group and a T2DM with stroke group based on the presence of stroke. Fasting glucagon levels and other clinical data were collected. Binary logistic regression models were used to analyze the relationship between fasting glucagon and stroke risk. Among female T2DM patients, fasting glucagon levels were significantly higher in the T2DM with stroke group compared to the T2DM group (13.38 vs. 11.56 pmol/L, P=0.011). Multivariable logistic regression analysis showed that after adjusting for multiple confounding factors, including age, diabetes duration, BMI, hypertension, eGFR, HbA1c, dyslipidemia, and medication use, higher fasting glucagon levels are independently associated with the presence of comorbid stroke in female T2DM patients (Model 3: Q4 vs. Q1: OR = 2.396, 95% CI: 1.075-5.339, P=0.037). Additionally, the prevalence of stroke increased with ascending quartiles of glucagon levels in female patients (P=0.023). However, no significant association was observed between fasting glucagon levels and stroke risk in male patients. This study demonstrates that among hospitalized female patients with T2DM, higher fasting glucagon levels are independently associated with the presence of comorbid stroke. This association suggests a potential link between glucagon and cerebrovascular disease in this population, warranting further investigation to explore its role.

Thyroid nodule (TN) prevalence is rising globally, with particularly high rates among patients with type 2 diabetes mellitus, where insulin resistance and hyperinsulinemia may promote nodule formation via the thyroid-stimulating hormone (TSH)/insulin-like growth factor-1 axis. Metformin, the standard first-line therapy for T2DM, may exert additional effects on thyroid structure beyond glycemic control. This single-center retrospective cohort study enrolled 80 patients with T2DM and benign TNs, assigned to a metformin group (n = 40) or control group (n = 40), and followed for 12 months. Changes in TSH and nodule volume were assessed using multivariable regression, propensity score matching, and sensitivity and subgroup analyses to address confounding. After 12 months, metformin treatment was associated with a significant reduction in TSH (adjusted β = -0.32, 95% confidence interval: -0.57 to -0.06, P = .017) and nodule volume (adjusted β = -8.5, 95% confidence interval: -15.9 to -1.1, P = .024). These effects were consistent in sensitivity analyses, with stronger associations observed in men, patients with body mass index < 28 kg/m², and those with glycated hemoglobin < 8%. In conclusion, metformin significantly lowers TSH levels and reduces nodule size in T2DM patients with benign TNs, supporting its potential clinical utility. Confirmation through large, multicenter, long-term prospective trials is warranted.

Intestinal glucose excretion, defined as increased intestinal serum glucose uptake and secretion into the lumen, influences bariatric surgery-associated glycaemic control. Here, we investigate molecular mechanisms that activate intestinal glucose excretion. We evaluate altered transcriptomes in variable intestinal glucose excretion models and big data-based drug discovery systems. We show that protein kinase C (PKC) activation mimics transcriptome alterations observed during intestinal glucose excretion. Among PKC subfamilies, atypical PKC (aPKC) facilitates glucose transporter 1 (GLUT1)-mediated intestinal glucose excretion without inducing oncogenic proliferation. Intestinal aPKC activation via transposon expression vector induces serum glucose uptake into intestinal tissues and excretion into the lumen. Prostratin, a non-tumorigenic phorbol ester, activates aPKC and induces a similar effect on intestinal glucose excretion. We identify the prostratin and aPKC/GLUT1 signalling pathways as putative targets for treating diabetes, providing insights into the future development of antidiabetic and weight-loss drugs.

This study developed and validated a nomogram to predict the risk of residual dizziness lasting ≥ 7days in patients with benign paroxysmal positional vertigo (BPPV). We retrospectively analyzed 907 BPPV patients, randomly divided 7:3 into training (n = 635) and validation (n = 272) sets. Using residual dizziness (≥ 7days) as the outcome, predictors were selected via LASSO and multivariable logistic regression to construct and validate a nomogram. According to findings from LASSO regression and logistic regression screening, older age [odds ratio (OR) = 1.054], diabetes mellitus (DM; OR = 5.564), and depression (OR = 9.070) were identified as independent risk factors, while vestibular rehabilitation training (OR = 0.197) was a protective factor. The model demonstrated strong predictive performance. Receiver operating characteristic (ROC) analysis showed that the training set had an area under the curve (AUC) of 0.836 [95% confidence interval (CI): 0.805-0.867], with an optimal threshold of 0.589, sensitivity of 0.682, and specificity of 0.873; the validation set had an AUC of 0.802 (95% CI: 0.750-0.853), with an optimal threshold of 0.588, sensitivity of 0.643, and specificity of 0.907. Calibration curves showed good agreement between predicted and actual risks, and decision curve analysis confirmed its clinical utility across a wide risk threshold range. The nomogram model, constructed using age, DM, depression, and vestibular rehabilitation training, is a practical tool for identifying BPPV patients at high risk for prolonged residual dizziness.

The coexistence of type 2 diabetes mellitus (T2DM) and malaria presents a significant public health concern, particularly in malaria-endemic regions. T2DM's immunomodulatory effects may influence immune responses to infectious diseases, but its impact on naturally acquired antibodies against malaria vaccine candidate antigens remains unclear. This study investigated how T2DM-malaria comorbidity affects IgG responses to malaria vaccine candidate antigens (GLURP-R2, GLURP-RO, MSP3, MSP1, AMA-1 and CSP) among individuals in the Central Region of Ghana. This hospital-based case-control study recruited a total of 144 participants 40 with diabetes, 25 with both diabetes and malaria, 41 with malaria only, and 38 controls (hospital staff without malaria or diabetes matched by age and sex). Malaria status and parasitaemia were confirmed using microscopy, blood glucose levels were measured via glucometer, and antibody levels were quantified using indirect ELISA. Data were analyzed using parametric and non-parametric statistical methods. Patients with malaria-diabetes comorbidity exhibited significantly higher parasitaemia levels compared to those with malaria alone [1702 (IQR1 = 926.50, IQR3 = 4102) vs. 932 (IQR1 = 722.50, IQR3 = 1321), p = 0.02]. Relative to the negative control group, IgG responses to GLURP-R2 were markedly elevated, showing a 1.60-fold increase in the comorbidity group (β = 0.47 [95% CI: 0.10-0.83], p = 0.01) and a 1.43-fold increase in the malaria-only group (β = 0.36 [95% CI: 0.04-0.69], p = 0.03). Among individuals with comorbidity, IgG levels to GLURP-R0 and MSP1 were also 1.43-fold higher (β = 0.36 [95% CI: 0.03-0.68], p = 0.03) and 1.42-fold (β = 0.35 [95% CI: 0.09-0.61], p < 0.05), respectively. Conversely, antibody responses to MSP3, AMA1, and CSP did not differ significantly between the study groups (p > 0.05). In the multivariate regression model adjusted for age and sex, individuals with comorbidity exhibited significantly elevated IgG responses, showing a 1.38-fold increase to GLURP-R0 (β = 0.32 [95% CI: 0.07-0.59], p = 0.027) and a 1.34-fold higher response to MSP1 (β = 0.29 [95% CI: 0.02-0.47], p = 0.048), relative to the malaria-only group. These findings suggest that diabetes may enhance malaria parasite multiplication while also augmenting IgG antibody responses to malaria vaccine candidate antigens in individuals with comorbidity. Further research is required to elucidate the mechanisms by which diabetes influences antibody responses to malaria infection and its potential implications for malaria vaccine development.

Type-2-diabetes-mellitus (T2DM), often linked to obesity, raises risk of microvascular and macrovascular complications. International guidelines recommend triple-therapy to reach haemoglobin A1c (HbA1c) targets when dual therapy fails to adequately control blood glucose levels. Sitagliptin, enhances glycaemic control by prolonging incretin action, boosting insulin secretion, and lowering glucagon levels. When combined with glimepiride and metformin this triple-therapy targets multiple mechanisms. This study evaluated the effectiveness and safety of this combination for improved T2DM management in Indian patients. This real-world, multicentre, observational chart review evaluated the efficacy and safety of a triple fixed-dose combination therapy in 1235 adult patients with T2DM across 194 clinical sites in India. Data were retrospectively extracted from patient records over a 12-week period. Descriptive and analytical statistics was applied for the study endpoints using SPSS ver. 29.0.1.0(171) and Microsoft Excel 2019. The study population had a mean age of 56.89 ± 10.29 years, with 64.70% reporting a family history of type 2 diabetes mellitus (T2DM). Smoking was identified as a prominent risk factor, affecting 38.65% of participants. Significant improvements were observed in glycemic parameters over 12 weeks: HbA1c levels decreased from 8.20 ± 0.60% to 7.08 ± 0.77% (p < 0.0001), fasting blood glucose (FBG) from 188.54 ± 47.59 mg/dL to 146.01 ± 41.53 mg/dL (p < 0.0001), and 2-hour postprandial plasma glucose (PPG) from 234.74 ± 50.40 mg/dL to 179.40 ± 42.51 mg/dL (p < 0.0001). Additionally, body weight significantly reduced from 75.99 ± 8.67 kg to 74.76 ± 9.07 kg (p < 0.0001). No significant safety concerns identified during the treatment period. The triple-combination therapy (sitagliptin, glimepiride, and metformin) demonstrated superior efficacy in achieving glycemic control, as evidenced by significant reductions in HbA1c, fasting blood glucose (FBG), and postprandial plasma glucose (PPG). Furthermore, the therapy facilitated meaningful weight reduction, highlighting its clinical utility as a comprehensive therapeutic option for managing glycemic parameters in both T2DM with overweight and normal-weight patients.