Chronic diseases and cardiometabolic disorders are major public health and occupational health challenges in Taiwan, particularly among healthcare workers exposed to shift work, high occupational stress, and irregular schedules. Nurses and hospital staff are especially vulnerable to hypertension, type 2 diabetes mellitus, stroke, and cardiovascular disease risk. Using a localized digital risk assessment platform and machine learning-based data-driven modeling, this study aimed to evaluate chronic disease risk among medical center employees and identify high-risk occupational subgroups for precision health management.

This retrospective cross-sectional study included 1,916 employees aged 35-70 at a Northern Taiwan medical center from 2019 to 2024. Ten-year predicted risks for coronary artery disease, stroke, type 2 diabetes mellitus, hypertension, and major adverse cardiovascular events were estimated using the Chronic Disease Risk Assessment Platform. To assess associations between predicted risk and demographic or occupational variables, we used ordinal logistic regression, generalized linear models, and decision tree algorithms.

Hypertension exhibited the highest overall predicted risk (38.6%), followed by type 2 diabetes mellitus and MACE. Male employees had higher odds of being classified into a higher predicted HTN risk category than female employees (odds ratio [OR] = 4.18, 95% confidence interval [CI]: 3.21-5.44, p < 0.001). By occupational category, nurses had higher odds of being in a higher predicted 10-year HTN risk category than administrative staff (OR = 1.32, 95% CI: 1.04-1.68, p = 0.024). Multivariable generalized linear models identified increasing age and metabolic factors, including obesity, elevated blood pressure, hyperglycemia, and dyslipidemia, as the major predictors of predicted cardiometabolic risk, whereas occupational category was not independently associated with disease risk after adjustment. Significant interaction effects were observed for CAD, stroke, HTN, and MACE. Ten-fold cross-validated decision tree models identified age, waist circumference, blood pressure, and body mass index as key classification variables, with overall accuracies ranging from 86.9 to 91.7% and F1-scores ranging from 0.622 to 0.936 across the five outcomes.

This study applied disease risk prediction models developed by the Taiwan Health Promotion Administration platform, integrating clinical indicators and machine learning analyses to identify healthcare workers at increased disease risk. The findings suggest that localized digital prediction tools may be integrated into institutional health surveillance systems to support continuous health monitoring, early risk identification, and proactive preventive care in healthcare settings.

Diabetes mellitus is characterized by chronic hyperglycemia resulting from defects in insulin secretion, insulin action, or both. It is one of the major causes of premature deaths, which occurs on account of its complications due to uncontrolled diabetes. This demands an urgent need for strategies to control the emerging epidemic of diabetes. The objectives of this study were to estimate the proportion of poor glycemic control and to identify the factors influencing poor glycemic control among adults with type 2 diabetes mellitus in Puducherry district.

A community-based cross-sectional analytical study was conducted among 340 individuals with type 2 diabetes mellitus who had the disease for at least six months of duration in Puducherry district. A list of individuals who underwent HbA1c estimation at the biochemistry laboratory of a tertiary care hospital was obtained prospectively. The eligible participants were contacted and visited at their residences. A semi-structured questionnaire was used to collect sociodemographic, behavioral, and clinical profiles.

The proportion of people with poor glycemic control was 217 (63.8%). Determinants such as age, place of residence, alcohol consumption, and treatment adherence were found to be associated with poor glycemic control. However, when adjusted for confounders, irregular treatment adherence emerged as the only independent factor associated with poor glycemic control (adjusted odds ratio (AOR): 19.54; confidence interval (CI): 7.65-49.90, P-value = 0.000).

This study emphasizes the importance of treatment adherence at the primary care level in order to substantially improve glycemic outcomes and reduce diabetes-related complications.

This study aimed to evaluate the prevalence, types, and duration of diagnosed cancers among adult type 2 diabetes mellitus (T2DM) patients in a primary care setting in Türkiye and to examine associated clinical and demographic factors according to T2DM duration.

T2DM is a growing global health concern linked to increased risks of various cancers. Epidemiological data suggest a complex relationship involving shared risk factors and pathophysiological mechanisms such as hyperinsulinemia, inflammation, and obesity.

This descriptive, cross-sectional study was conducted at an education-family health centre (EFHC), analysing medical records and patient interviews. The sample included 442 patients with T2DM registered at Marmara University Tuzla EFHC, of whom 152 had a diagnosed cancer. Data collected encompassed cancer prevalence, types, sociodemographic characteristics, clinical features (including body mass index, T2DM duration, comorbidities), and cancer duration.

The prevalence of cancer among T2DM patients was 34.4%. The most common cancers were prostate in men and breast in women. No significant correlation was observed between T2DM duration and cancer duration; however, breast cancer was less frequent among women with longer T2DM duration compared to their cancer duration. A high rate of obesity and comorbidities was noted in the cohort. Cancer prevalence among Turkish T2DM patients in primary care is notably high, highlighting the importance of integrated screening and risk factor management. These findings underscore the need for targeted preventive strategies and personalized patient care to reduce cancer-related morbidity and mortality in diabetic populations.

Diabetic Kidney Disease (DKD), a prevalent microvascular complication of diabetes mellitus, represents the leading cause of end-stage renal disease worldwide. Its pathogenesis is multifactorial, involving metabolic disturbances, oxidative stress, inflammatory responses, and notably, mitochondrial dysfunction. Mitochondria, as the primary energy-producing organelles, undergo morphological and functional impairment under hyperglycemic conditions, including excessive reactive oxygen species generation, aberrant dynamics (fusion/fission imbalance), defective mitophagy, reduced biogenesis, and activation of mitochondria-mediated apoptosis. These interconnected abnormalities contribute to glomerular and tubular injury, ultimately promoting renal fibrosis and functional decline. Emerging evidence highlights the therapeutic potential of natural products-such as flavonoids, polyphenols, alkaloids, and saponins-in restoring mitochondrial homeostasis through multitarget mechanisms. These compounds activate the Nrf2/ARE and AMPK/SIRT1/PGC- 1α pathways to enhance antioxidant defense and promote mitochondrial biogenesis; regulate Drp1/Mfn1/2/OPA1 to restore mitochondrial dynamics; induce PINK1/Parkin- or BNIP3-mediated mitophagy to clear dysfunctional mitochondria; and modulate Bcl-2/Bax/caspase signaling to suppress apoptosis. Despite robust preclinical efficacy, clinical translation is hindered by poor bioavailability, batch-to-batch variability, lack of standardized formulations, and limited high-quality trials with mitochondrial-specific endpoints. Advances in kidney-targeted nanodelivery systems and AIdriven compound screening offer promising strategies to overcome these barriers. This review synthesizes current knowledge on the mechanisms by which natural products alleviate mitochondrial dysfunction in DKD, evaluates translational challenges, and proposes future directions for developing these compounds into adjunctive therapies.

Pheochromocytoma is an uncommon neuroendocrine tumor with myriad nonspecific clinical presentations. If not recognized and treated, it is associated with the development of target organ damage and complications such as myocarditis, cardiomyopathy, cerebrovascular accidents, and diabetes mellitus, among numerous others. The pheochromocytoma diagnosis is based on biochemical proof of catecholamine excess followed by imaging localization of the tumor. Patients with newly diagnosed pheochromocytoma should be seen by a multidisciplinary perioperative team, including the anesthesiologist, operating surgeon, endocrinologist, and cardiologist. Perioperative antihypertensive therapy should be instituted prior to adrenal resection to allow for cardiovascular recovery and to hopefully mitigate the hypertensive response to laryngoscopy and tumor manipulation. The anesthesiologist must be prepared to manage both intraoperative hypertension, hypotension, and glycemic disturbances, among other possible complications. Patients with previously undiagnosed pheochromocytoma who present for unrelated surgery represent a high-risk group. Once intraoperatively suspected, priority should be given to immediate stabilization, cessation of surgery when feasible, and close communication with the surgical team regarding whether the procedure should be aborted, limited, or continued based on the urgency of the operation and the patient's clinical status. In most cases, nonessential surgery should be aborted. The postoperative level of care should be based on intraoperative patient courses and institutional protocols and guidelines to monitor and manage postresection hypoglycemia and vasoplegia, when they occur. This narrative review aims to provide practicing anesthesiologists with an updated, practical framework for the perioperative recognition and management of pheochromocytoma. We integrate contemporary evidence with anesthesia-specific decision-making, including the management of catecholamine-induced cardiovascular dysfunction, perioperative fluid and vasoactive therapy, medication-triggered crises, and a dedicated approach to previously undiagnosed pheochromocytoma presenting during unrelated surgery.

To determine the influence of recipients' pre-existing diabetes mellitus on the outcomes of living donor kidney transplantation.

This prospective observational cohort study included 202 patients who underwent kidney transplantation between September 2022 and December 2023 at Dow University Hospital, Pakistan, and were stratified into two equal groups: pre-existing diabetes and non-diabetes. Patients with new-onset diabetes after transplantation were excluded. Demographic and clinical data were collected. Outcomes, including one-year patient survival and post-transplant complications, were assessed and compared.

Complications were high in the pre-existing diabetes group (57.4% vs. 28.7%, p <0.001). Infections occurred in 46.5% of patients with pre-existing diabetes versus 22.8% non-DM (p <0.001). Post-transplant cardiovascular events were observed in 6.9% of patients in the pre-existing DM group, whereas none were observed in the non-DM group (p = 0.014). One-year patient survival was 88.1% in the pre-existing DM group versus 95% in the non-DM group (p = 0.075). Graft-related complications did not differ significantly between the groups. Multivariate analysis identified pre-transplant congestive heart failure (HR = 99.431, [95% CI 7.709-128.441, p <0.001]), pre-transplant peripheral vascular disease (HR =7.787, [95% CI 1.197-50.682, p = 0.032]), post-transplant cardiovascular events (HR = 7.839, [95% CI 1.423-43.198, p = 0.018]), and post-transplant FBS (HR = 1.023, [95% CI 1.001-1.046, p = 0.040]) as independent predictors of mortality.

Diabetes did not influence one-year patient survival and graft-specific outcomes but led to frequent post-transplant complications. Pre- and post-transplant cardiovascular disease and elevated post-transplant FBS levels were associated with mortality. Therefore, structured pre-transplant cardiovascular assessment and optimization, ongoing post-transplant cardiovascular surveillance, and strict glycemic control are required.

Prediabetes, an intermediate metabolic state between normoglycemia and type 2 diabetes mellitus, has emerged as a silent global epidemic with a rising prevalence and substantial cardiometabolic risks. Despite the established diagnostic criteria from major health organizations, significant controversies persist regarding optimal screening definitions, inter-ethnic variability, and low concordance among fasting glucose, HbA1c, and postprandial glucose assessments. Pathophysiologically, prediabetes involves a dynamic interplay between tissue-specific insulin resistance (hepatic in impaired fasting glucose and skeletal muscle in impaired glucose tolerance), β-cell dysfunction, and multi-organ crosstalk, underpinned by chronic low-grade inflammation, mitochondrial dysregulation, and lipotoxicity. Within this complex landscape, acupuncture and moxibustion, rooted in traditional Chinese medicine yet increasingly validated by modern mechanistic studies, offer a multimodal therapeutic strategy. Emerging evidence from randomized controlled trials and meta-analyses has demonstrated that acupuncture-related therapies significantly reduce fasting blood glucose, postprandial glucose, and HbA1c levels, while improving insulin resistance, modulating the leptin signaling pathway, and restoring β-cell homeostasis via neuroendocrine regulation (eg, vago-islet axis, hypothalamic-pituitary-adrenal axis). Innovative protocols, including electroacupuncture, Zhuang medicine scraping combined with blood-letting, and auricular acupoint embedding have shown promising clinical efficacy and favorable safety profiles. Nevertheless, methodological heterogeneity, small sample sizes, and limited long-term follow-up remain challenges. This manuscript critically synthesizes the contemporary understanding of prediabetes, from diagnostic controversies and global epidemiology to integrated pathophysiology, and positions acupuncture and moxibustion as a scientifically grounded, low-risk, and scalable intervention. Future studies should prioritize large-scale multicenter trials, multi-omics mechanistic dissection, and standardized clinical protocols to fully harness the therapeutic potential of acupuncture in curbing the diabetes pandemic.

Gestational diabetes mellitus (GDM) affects 14-17% of pregnancies globally, imposing long-term public health burdens beyond pregnancy. Maternal hyperglycaemia increases offspring risk of metabolic disorders through epigenetic, hormonal and developmental programming. Growing evidence connects prenatal GDM exposure to childhood and adult metabolic diseases, yet the consistency and magnitude of these associations across different metabolic conditions remains unclear.

We systematically searched PubMed, Cochrane CENTRAL and Embase. Eligible studies included observational cohorts exploring associations between in-utero GDM exposure and offspring metabolic outcomes, and RCTs assessing maternal antenatal interventions. Bias risk was evaluated with Cochrane RoB 2 (for RCTs) and the Newcastle-Ottawa Scale (NOS) (for observational studies). Separate outcome-based pooled analyses were conducted, given the distinct clinical questions addressed by the two study designs. All meta-analyses used the random-effects inverse-variance model. Heterogeneity was assessed via I² and Cochran's Q statistic, and Egger's linear regression test was used to detect publication bias.

Sixteen studies (n=9 RCTs, n=7 observational cohorts) involving diverse populations across 11 countries were included. In observational cohorts, GDM-exposed offspring showed higher BMI (MD = 1.42 kg/m2, 95% CI: 0.94-1.89) and greater estimates for overweight/obesity in adulthood (OR = 2.09, 95% CI: 1.25-3.50, I² = 80.7%). The analysis of fasting glucose results displayed high variability (I² = 80.7%) yet produced no meaningful combined impact (MD = -0.016 mmol/L, 95% CI: -1.52 to 1.49). In RCTs, active antenatal GDM management was associated with a non-significant trend towards lower HOMA-IR (MD = -0.30, 95% CI: -0.61 to 0.01; I² = 68.2%) and HbA1c (MD = -0.41%, 95% CI: -0.85 to 0.03; I² = 99.1%) relative to usual care. There were no statistically significant combined effects found for 2-hour OGTT glucose levels total cholesterol levels triglyceride levels or HDL-C levels. Egger's test revealed no significant publication bias for either glucose (t = 0.82, p = 0.43) or lipid outcomes (t = -0.08, p = 0.94).

In-utero GDM exposure confers metabolic risks from childhood to adulthood; lifelong persistence requires verification via extended longitudinal research GDM interventions including diet, exercise and pharmacotherapy may lower offspring risk, although heterogeneity necessitates cautious interpretation.

Diabetic cardiomyopathy (DCM) is a major contributor to heart failure in diabetic patients, characterized by profound metabolic remodeling and diastolic dysfunction. However, the multi-layered epitranscriptomic and post-transcriptional networks involved in this disease remain poorly understood. To address this, we established a type 2 diabetes-associated DCM mouse model using a high-fat diet (HFD) combined with low-dose streptozotocin (STZ) injections. By integrating single-molecule direct RNA sequencing (DRS-seq), chromatin accessibility profiling (ATAC-seq), and conventional bulk RNA-seq, we constructed a comprehensive epigenetic-transcriptional regulatory map of DCM. Using DRS-seq, we identified 21,156 full-length transcripts, including 8,457 (39.97%) novel unannotated isoforms, and observed a systemic 3'-UTR elongation under diabetic stress. Joint ATAC-seq and DRS-seq analysis identified concurrent reductions in promoter chromatin accessibility and transcript abundance for four genes, including Fam210b (mitochondrial iron homeostasis), Cdh22 (intercalated disc adhesion), Fbxo10 (ubiquitin-mediated RAGE degradation), and Cenpx (DNA double-strand break repair), suggesting a potential link between altered chromatin accessibility and transcriptional regulation in DCM. Additionally, DRS-seq revealed extensive alterations in the cardiac epitranscriptome, identifying 1,719 differential m⁶A sites and 3,146 differential m⁵C sites at single-molecule resolution. Among these epitranscriptomic changes, we observed a potential post-transcriptional interplay between m⁶A and alternative polyadenylation (APA). Furthermore, by applying the CIBERSORT algorithm to the DRS-seq dataset, we characterized the cardiac immune microenvironment, revealing distinct pathological remodeling defined by decreased plasma cells and Th1 cells alongside a specific increase in CD4+ memory T-cell infiltration. Pearson correlation analysis showed that, among the candidate genes, only the down-regulated mitochondrial regulator Fam210b exhibited a significant negative correlation with CD4+ memory T-cell infiltration, suggesting a potential molecular association between mitochondrial dysfunction and local adaptive immune changes. Together, our study provides a high-resolution landscape of the native cardiac transcriptome and epitranscriptome, highlighting epigenetic-transcriptional coupling, m⁶A-APA cooperative decay, and Fam210b-associated local immune microenvironment remodeling as potential pathogenic contributor, thus offering candidate therapeutic targets for diabetic heart failure.

To systematically analyze factors influencing corneal endothelial cell density (ECD) in eye bank donors and provide robust evidence for optimizing donor screening strategies.

A retrospective analysis was conducted on 1438 corneas from 782 donors (2013-2025). Associations between ECD and donor age, sex, laterality, cause and season of death, cataract surgery, cancer, Diabetes Mellitus (DM), and death-to-preservation time (DTP) were evaluated using univariate analysis and a generalized linear mixed model (GLMM).

Univariate analysis showed ECD was significantly associated with age, cataract surgery, DTP, cause of death, and death season (all P < 0.05). The GLMM indicated that age, cataract surgery, and DTP were highly significant independent predictors (all P < 0.001): ECD was 287.737 cells/mm² higher in donors without cataract surgery (95% CI: 177.109-398.365), and decreased by 3.847 cells/mm² (95% CI: -5.561 to -2.134) per year of age and 18.342 cells/mm² (95% CI: -27.623 to -9.062) per hour increase in preservation time. Among causes of death, only the cardiovascular/cerebrovascular disease group differed significantly from the chronic organ failure group (P = 0.013); other factors including sex, eye laterality, cancer, DM, and death season showed no independent effects (all P>0.05).

Advanced age, prior cataract surgery, and prolonged death-to-preservation time were independently associated with lower ECD. Cause of death was not an independent predictor overall, although donors who died from CCVDs had significantly higher ECD than those with chronic organ failure. These findings provide a robust evidence base for clinical donor screening and allocation, thereby maximizing the utility of scarce donor corneas.