Background and objectives Stem cell therapy has emerged as a potential treatment for type 1 diabetes mellitus (T1DM), offering the possibility of modifying disease progression. This systematic review and meta-analysis aimed to assess the efficacy and safety of stem cell therapy in patients with T1DM. Methods We searched PubMed, Embase, Web of Science, and CENTRAL for randomised controlled trials (RCTs) published until January 2025 that evaluated stem cell therapy in T1DM. The primary outcome was the glycated haemoglobin (HbA1c) level. The secondary outcomes included fasting C-peptide levels, insulin dose reduction, insulin independence, and adverse events. The risk of bias was assessed using the Risk of Bias 2.0 tool. Results Eight reports from seven RCTs (169 participants) were included. Stem cell therapy was associated with a marginal reduction in HbA1c at 6 months [mean difference (MD): -0.57%, 95% CI: -1.13 to -0.02] but not at 12 months (-0.49%, -0.98 to 0.00). Fasting C-peptide levels (ng/mL) showed slight improvement at both 6 months (0.03, 0.03 to 0.03) and 12 months (0.09, 0.05 to 0.13). None of the participants achieved insulin independence or experienced serious adverse events. The certainty of the evidence was rated as very low for all outcomes. Interpretation and conclusions Stem cell therapy may offer marginal improvements in HbA1c and fasting C-peptide levels in T1DM; however, these benefits are of limited clinical significance. Given the small sample sizes, high heterogeneity, and very low certainty of evidence, well-designed, adequately powered RCTs are required to establish the therapeutic role of stem cells in T1DM.

Hard-to-heal wounds, such as diabetic foot ulcers (DFUs) and venous leg ulcers (VLUs), remain associated with poor healing outcomes despite optimised standard care. Although classified by aetiology, these wounds share common pathophysiological features that may be amenable to mechanism-targeted therapies. This manuscript aims to describe the design, scientific rationale and statistical framework of a mechanism-driven basket trial evaluating wound therapies across multiple wound aetiologies.

This multicentre, randomised, sham-controlled clinical trial was designed under a master protocol using aetiology-specific baskets. Adults with hard-to-heal DFUs or VLUs who failed to demonstrate adequate healing during a standardised run-in period were randomised 1:1 within each basket to standard care plus active therapy or standard care plus sham. Subject and assessor blinding, harmonised standards of care, and centralised endpoint adjudication were employed. The primary endpoint within each basket was complete wound closure by 12 weeks, confirmed at two consecutive visits. Bayesian statistical methods incorporating conservatively discounted historical control data via power priors were used to enhance efficiency while preserving indication-specific inference.

The basket design enabled simultaneous evaluation of a single mechanism-targeted intervention across heterogeneous wound aetiologies while maintaining methodological rigour, regulatory alignment and interpretability. Independent analysis of each basket preserved aetiology-specific conclusions while benefiting from shared infrastructure and standardised procedures.

This master-protocol basket trial adapted principles established in oncology to wound care, offering an innovative and scalable framework for evaluating therapies targeting shared biological barriers to healing. The approach may accelerate evidence generation and inform future clinical development strategies in hard-to-heal wounds.

To evaluate the diagnostic accuracy of Luminetics Core, a Food and Drug Administration-cleared artificial intelligence-based screening system, in the detection of diabetic retinopathy (DR) in a predominately non-White population and identify potential shortcomings in clinical implementation that should be addressed to mitigate disparities in health care.

Data were acquired via retrospective chart review and included 225 patients with a diagnosis of diabetes mellitus who were screened for DR using the LumineticsCore system (formerly IDx-DR) at the University Medical Center New Orleans (Louisiana). Metrics to assess DR detection efficacy included sensitivity, specificity, positive and negative predictive values, likelihood ratios, and indeterminate screening result rates. Stratified analyses regarding associated medical comorbidities also were performed. Clinic follow-up rates and time frames also were noted per screen result group.

The study population had a diverse demographic profile, with 69.0% of subjects identifying as African American, 13.1% Hispanic, 10.7% White, 3.6% Asian, and 3.6% of subjects who either did not identify with the above racial/ethnic groups or declined to self-identify. The system yielded favorable performance measures in the study population regarding detection accuracy. It was found, however, that although most patients with a positive screen had ophthalmology referrals placed, 29.8% of patients with positive screen results did not attend their scheduled ophthalmology visit.

The LumineticsCore system was found to be a reliable screening test for the detection of DR in the study population. The relatively high no-show rate for scheduled ophthalmology referrals in patients with positive screen results, however, sheds light on an implementation system issue in need of further evaluation.

This study aimed to determine the prevalence of food addiction (FA) in adults with type 1 diabetes mellitus (T1DM) and examine its associations with serum ghrelin levels and metabolic control parameters.

The study included 160 patients with a median age of 32.0 years (range: 19.0-60.0), of whom 51.3% (n = 82) were female. After recording anthropometric measurements, sociodemographic data, medical histories, and detailed physical examinations were obtained. Following an 8-hour fasting period, venous blood samples were collected to measure serum ghrelin levels and biochemical parameters. Serum ghrelin levels were assessed using the ELISA method. FA was evaluated using the modified Yale Food Addiction Scale 2.0 (mYFAS 2.0).

FA prevalence was 25.6% (n = 41). The FA group had higher median BMI (p = 0.047), while monthly income, diabetes duration, and insulin pump use were lower (p = 0.025, p = 0.009, and p = 0.046, respectively). Age, gender, education, and metabolic control indicators (HbA1c, lipids) were similar between groups. Serum ghrelin levels did not differ based on FA status. However, ghrelin showed modest negative correlations with BMI (r=-0.171; p = 0.030), waist circumference (r=-0.256; p = 0.001), and triglycerides (r=-0.168; p = 0.033).

Our findings indicate that the prevalence of FA is observed at considerable rates among patients with T1DM. Although no significant differences were observed in metabolic control parameters between patients with and without FA, the FA group exhibited a modestly higher BMI, suggesting a potential association between addiction-like eating behavior and adiposity in adults with T1DM.

Not applicable.

Post-transplant diabetes mellitus (PTDM) is a common metabolic complication after kidney transplantation and has been linked to adverse long-term outcomes. Evidence from sub-Saharan Africa remains limited. This study assessed the frequency, associated factors, and post-transplant outcomes of PTDM in a Sudanese kidney transplant cohort.

A retrospective cohort study was conducted among adult kidney transplant recipients followed at Dr Salma Centre for Kidney Diseases, Khartoum, Sudan. Recipients with documented pre-transplant diabetes were excluded from the PTDM analytic risk set. Clinical, transplant-related, treatment-related, and follow-up outcome variables were evaluated according to PTDM status. Factors associated with PTDM were examined using multivariable logistic regression, and associations between PTDM and post-transplant outcomes were assessed using modified Poisson regression with robust variance.

After exclusion of 152 recipients with pre-transplant diabetes, 640 recipients were included in the PTDM analytic cohort. PTDM was diagnosed during follow-up in 336 recipients (52.5%). After multivariable adjustment, higher odds of PTDM were observed for recipients older than 50 years at transplantation (OR 2.48, 95% CI 1.47-4.18), those with obesity (OR 3.12, 95% CI 1.76-5.53), pre-transplant ischemic heart disease (OR 1.58, 95% CI 1.03-2.43), tacrolimus-based therapy (OR 1.72, 95% CI 1.07-2.77), and maintenance corticosteroid exposure > 10 mg/day (OR 2.31, 95% CI 1.13-4.72). The estimate for dialysis duration > 30 months was weaker and did not reach conventional statistical significance (OR 1.41, 95% CI 0.97-2.06). PTDM was associated with a higher occurrence of post-transplant hypertension (RR 9.72), cardiovascular events (RR 6.18), dyslipidemia (RR 2.84), and infectious complications (RR 1.42). Graft failure and all-cause mortality were not statistically significant after adjustment.

PTDM was frequently observed in this cohort and coincided with a higher burden of metabolic, cardiovascular, and infection-related outcomes. Future prospective studies using uniform PTDM screening and well-defined event dates are needed to clarify these relationships.

Not applicable. This was a retrospective observational study using routinely collected clinical and follow-up data.

Dysglycaemia and periodontal inflammation frequently co-occur during pregnancy, but the microbial mechanisms linking these conditions and their potential for intervention remain incompletely understood. Here, we establish prospective pregnancy cohorts including more than 2500 volunteers and longitudinally profile oral microbiome dynamics in 534 pregnant women. We show that gestational diabetes mellitus (GDM) is associated with a progressive shift from Streptococcus-dominated oral microbiota to Prevotella/Porphyromonas-enriched dysbiosis. In mouse and cellular models, this dysbiotic oral microbiota induces periodontal inflammation, systemic IL-17 and IL-1β responses, suppression of glucagon-like peptide-1 and insulin, and exacerbation of hyperglycemia. Conversely, oral microbiota remodeling through transplantation of Streptococcus-dominated bacteria attenuates periodontal inflammation, restores glucagon-like peptide-1 and insulin levels, and improves glycaemic status in mice. Salivary metabolomics identifies docosahexaenoic acid (DHA) depletion in GDM, and in vitro assays show selective suppression of dysbiosis-associated oral pathogens by DHA. We therefore test topical gingival DHA in a double-blind randomized controlled trial of 40 pregnant women with GDM (ChiCTR2400080741), with probing depth and fasting blood glucose as primary endpoints and gingival index, attachment loss and plaque index as secondary endpoints. Daily gingival DHA application for six weeks improves probing depth and attenuates fasting glucose increase compared with placebo, with median fasting glucose changes from baseline of 0.10 versus 0.27 mmol/L. Together, these findings identify oral dysbiosis as a microbial driver of periodontal and glycaemic deterioration during pregnancy and support oral microbiome modulation as a potential adjunctive strategy for pregnancy care, although the clinical findings remain preliminary and require validation in larger trials with broader glycaemic endpoints.

Mild cognitive impairment may occur early in type 2 diabetes mellitus, but data on its prevalence and longitudinal dynamics in newly diagnosed patients without overt vascular complications remain limited.

We prospectively followed 937 adults with newly diagnosed type 2 diabetes mellitus without baseline microvascular or macrovascular complications for a mean of 62.7±21.5 months. Cognitive status was assessed using the Montreal Cognitive Assessment, and mild cognitive impairment was defined as Montreal Cognitive Assessment-defined cognitive impairment. We evaluated the prevalence of mild cognitive impairment at diagnosis, the rate of mild cognitive impairment remission among patients with baseline mild cognitive impairment, and the incidence of mild cognitive impairment among cognitively normal patients. Multivariable models were used to identify clinical correlates of these outcomes.

At baseline, 286 patients (30.5%) had mild cognitive impairment. During the follow-up, 43/286 patients (15.0%) experienced remission, whereas 96/651 cognitively normal patients (14.7%) developed incident mild cognitive impairment. Higher C-peptide was strongly associated with prevalent mild cognitive impairment, and continuous C-peptide remained significantly associated with Montreal Cognitive Assessment performance in multivariable analyses. Smoking was associated with a less favorable cognitive profile, uric acid showed an inverse association with prevalent mild cognitive impairment, and participation in therapeutic patient education was independently associated with a lower risk of incident mild cognitive impairment. Incident retinopathy was also associated with incident mild cognitive impairment.

In newly diagnosed, complication-free type 2 diabetes mellitus, mild cognitive impairment defined by Montreal Cognitive Assessment is common and clinically dynamic. Our findings suggest that metabolic, behavioral, educational, and microvascular factors are associated with cognitive outcomes, but they should be interpreted as observational and hypothesis-generating rather than as evidence for immediate clinical risk stratification.

Screening for type 2 diabetes (T2D) is not optimal, leading to a large number of patients being undiagnosed. Recently, deep learning (DL) applied to chest radiographs (CXRs) has shown promise for opportunistic T2D prediction. A prior study in a predominantly suburban non-Hispanic White cohort achieved an area under the curve (AUC) of 0.84 for prevalence. In this study, we evaluate the performance and generalizability of this DL model in an urban cohort with greater racial diversity, higher social deprivation, and higher T2D prevalence. We further assess whether integrating DL predictions with BMI and demographic variables improves T2D prediction beyond demographics and BMI alone.

This study aims to externally validate a previously developed DL-based CXR model for T2D prediction in a diverse urban population, to assess its performance for both prevalent and incident T2D, and to determine whether combining DL predictions with demographics and BMI improves predictive performance.

We studied adults (2010-2020) from a tertiary academic medical center in Chicago with at least one ambulatory CXR. First, we performed external validation of a previously developed DL-CXR model by applying it directly to our cohort. Second, we evaluated whether combining the DL model output with additional data, demographics, BMI, and social deprivation index improved the performance. T2D prevalence was modeled using extreme gradient boosting, while incidence was assessed with Cox proportional hazards models. Model performance was compared using AUC and concordance, and feature contributions were evaluated using feature importance and odds ratios.

Among 39,908 patients (n=21,311, 53.4% non-Hispanic Black; n=9179, 23% Latino; and n=5587, 14% non-Hispanic White), 26% (n=10,376) had T2D at their first CXR. The previously developed DL-T2D model maintained discrimination for prevalent T2D in this diverse urban cohort, with similar performance across racial groups (Latino: 0.818; non-Hispanic White: 0.819; non-Hispanic Black: 0.790), supporting generalizability. Adding DL output to demographics and BMI improved prediction compared with clinical variables alone (AUC 0.808 vs 0.766; P<.001). For a 3-year incident T2D, the full model achieved an AUC of 0.709 with concordance of 0.707; individuals in the highest risk quartile had a 7-fold higher incidence.

In a diverse urban cohort, a previously developed DL model applied to CXRs provided significant incremental value beyond demographics and BMI for T2D risk prediction. Despite substantial differences in population characteristics compared with the derivation cohort, the DL model remained effective for T2D screening. Incidence prediction was less accurate than prevalence, highlighting the need for further refinement, potentially incorporating hemoglobin A_1c when available. Although racial disparities in prevalence exist, predictive performance was comparable across groups. These findings support the generalizability of CXR-based DL for opportunistic T2D screening in diverse populations.

Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes mellitus (DM) and remains a major cause of visual impairment and blindness in adults. Accumulating evidence indicates that DR is not merely a microvascular disorder, but a complex neurovascular disease driven by long-standing hyperglycemia, metabolic dysregulation, oxidative stress, chronic inflammation, neurodegeneration, and impaired neurovascular coupling. Mitochondria are central regulators of cellular energy metabolism and redox homeostasis, and mitochondrial dysfunction is increasingly recognized as a pivotal mechanism linking hyperglycemia-induced metabolic abnormalities to retinal neurovascular unit injury. Under persistent hyperglycemic conditions, excessive glucose flux and metabolic overload promote mitochondrial reactive oxygen species (ROS) overproduction, mitochondrial DNA (mtDNA) damage, impaired oxidative phosphorylation, mitochondrial fusion-fission imbalance, defective mitochondrial biogenesis, dysregulated mitophagy, metabolic reprogramming, and epigenetic alterations. These abnormalities lead to ATP depletion, inflammatory amplification, and activation of multiple forms of programmed cell death, including apoptosis, ferroptosis, pyroptosis, necroptosis, and poly(ADP-ribose) polymerase 1 (PARP1)-dependent cell death. Mitochondrial injury affects retinal endothelial cells, pericytes, Muller cells, microglia, retinal ganglion cells, photoreceptors, and retinal pigment epithelial cells in a cell-type-specific manner, ultimately contributing to blood-retinal barrier disruption, capillary occlusion, neurovascular coupling impairment, retinal neurodegeneration, and progression from non-proliferative to proliferative DR. This review summarizes recent advances in mitochondrial dysfunction in DR, focusing on oxidative stress, mtDNA injury, mitochondrial metabolic reprogramming, mitochondrial dynamics, mitochondrial biogenesis, mitophagy, epigenetic regulation, mitochondria-associated cell death, and neurovascular unit dysfunction. Emerging mitochondria-targeted therapeutic strategies, including mitochondrial antioxidants, modulation of mitochondrial biogenesis and dynamics, mitophagy regulation, mtDNA protection, ferroptosis and inflammasome inhibition, epigenetic intervention, are also discussed. A deeper understanding of mitochondrial mechanisms may provide new therapeutic targets and translational opportunities for DR prevention and treatment.

Type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) commonly coexist and are associated with an increased risk of ischemic stroke. Finerenone has demonstrated benefits on composite renal and cardiovascular outcomes in randomized trials; however, ischemic stroke has generally been evaluated as part of composite endpoints, and real-world evidence focusing on this outcome remains limited.

We conducted a retrospective cohort study using the TriNetX Global Research Network to evaluate the association between finerenone use and incident ischemic stroke among adults with newly diagnosed T2DM who subsequently developed CKD. Finerenone users were compared with non-users. Propensity score matching was applied to balance demographic characteristics and baseline comorbidities. Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs).

A total of 125,086 eligible patients were identified before matching, including 1,990 finerenone users. After 1:1 propensity score matching, 1,990 finerenone users were matched with 1,990 non-users with adequate covariate balance. Finerenone use was associated with a lower observed hazard of ischemic stroke both before matching (adjusted HR, 0.30; 95% CI, 0.24-0.36) and after matching (adjusted HR, 0.33; 95% CI, 0.26-0.42).

In this real-world cohort of patients with T2DM and CKD, finerenone use was associated with a lower observed hazard of ischemic stroke.