Peroxiredoxin (Prx) is a critical cysteine-based peroxidase that detoxifies reactive oxygen species to maintain cellular peroxide homeostasis and prevent oxidative stress. Peroxiredoxin 5 (Prx5 or PRDX5) is the unique atypical 2-cysteine Prx in humans, which is able to scavenge the peroxides through redox-active cysteines. However, the precise regeneration mechanism of Prx5 by thioredoxin (Trx) within the catalytic cycle of Prx is not yet well understood. Here, we developed a design strategy through disulfide bond crosslinking to demonstrate that both Cys151 and Cys47 of Prx5 are able to form intermolecular disulfide bonds with thioredoxin 2 (Trx2). Gel filtration was further performed to validate the formation of Prx5-Trx2 complex in solution. We presented a scheme for obtaining the purified Prx5-Trx2 complex, and elucidated that this complex is a heterotetramer with a 1:1 molar ratio of both proteins. Predicted structure model of Prx5-Trx2 complex revealed that each Trx2 protein engages exclusively with a single subunit of the Prx5 dimer, which is distinctly different from the interaction mode observed in yeast Ahp1-Trx2 complex. Collectively, these results provide novel mechanistic insights into the transient Prx5-Trx2 complex formation and the electron transfer from electron donor Trx2 to Prx5 during the catalytic redox regeneration step.

Non-invasive tests (NITs) are widely used to risk-stratify patients with metabolic dysfunction-associated steatotic liver disease (MASLD); however, their performance may vary according to patient characteristics. We evaluated the accuracy of NITs in a large, multinational MASLD cohort across select subpopulations.

We analyzed 18,759 adults with biopsy-confirmed MASLD from 41 countries. NITs included FIB-4, liver stiffness measurement (LSM), and Agile-3+. Diagnostic performance for advanced fibrosis (F3-F4) was measured using AUCs across subgroups defined by age, sex, type 2 diabetes (T2D), obesity, and alcohol use. Subgroup-specific cutoffs were derived.

Advanced fibrosis was present in 37% of patients. Pooled AUCs were 0.79 for FIB-4, 0.83 for LSM, and 0.86 for Agile-3+. FIB-4 accuracy declined with age (AUC 0.70 in ≥65 years vs. 0.79 in <65 years, p<0.0001) and in middle-aged patients with T2D. The LSM performance remained stable across T2D status but was moderately reduced in patients with obesity and, more profoundly, morbid obesity (BMI >35). Sex and alcohol use had minimal impact on AUCs. Age- and T2D-specific FIB-4 cutoffs varied substantially to maintain predefined accuracy (sensitivity or specificity). The cutoffs for LSM also differed based on patients' BMI, with lower diagnostic cutoffs for advanced fibrosis required in non-obese MASLD (sensitivity 80%: 8.8 kPa in lean, 9.0 kPa overweight, 9.6 kPa in obesity, 11.0 kPa in morbid obesity).

Accuracy of non-invasive tests for advanced fibrosis in MASLD is influenced by age, T2D, and obesity. Age-adjusted FIB-4 thresholds may enhance risk stratification. Imaging-based and composite NITs (LSM and Agile-3+) provide more consistent performance across MASLD subpopulations.

Diabetic wounds represent a major clinical challenge due to their susceptibility to bacterial biofilm infections, persistent oxidative stress, and impaired tissue regeneration. Current therapeutic approaches typically address these pathological factors individually, limiting their overall efficacy in achieving complete wound closure. There is thus an urgent need for integrated platforms capable of simultaneously targeting multiple barriers to healing. Here we show that a self-healing hydrogel composed of quaternized chitosan-phenylboronic acid (QCSP), ceria nanoparticles (CeNPs), and embryonic stem cell-derived exosomes (ESC-Exo) effectively eradicates methicillin-resistant Staphylococcus aureus (MRSA) biofilms, scavenges reactive oxygen species, and promotes tissue regeneration in diabetic mice. The QCSP matrix provides inherent antibacterial activity and injectable, self-healing properties, while CeNPs function as catalytic antioxidants through reversible Ce³⁺/Ce⁴⁺ redox cycling. Incorporation of ESC-Exo further enhances angiogenesis and re-epithelialization. In an MRSA-infected diabetic wound model, this multifunctional hydrogel achieves near-complete wound closure within 12 days alongside significant biofilm clearance and collagen deposition. This work demonstrates that integrating natural polymer-based hydrogels with nanozymes and bioactive exosomes offers a promising strategy for managing complex chronic wounds.

Evaluate the efficacy and safety of faricimab for treatment-naïve and pre-treated diabetic macular oedema (DME) in a real-world setting.

This multicentre, retrospective cohort study examined consecutive DME patients treated with faricimab for ≥1 year. Data were collected at predefined time points. Primary outcomes were mean changes in corrected visual acuity (VA), centre-point retinal thickness (CRT) and central subfield thickness (CST) and treatment intervals and adverse events (AEs).

184 eyes with DME were included: 61 (33.2%) were treatment-naïve, and 123 (66.8%) were pretreated. In treatment-naïve eyes, VA improved from 69.7±15 Early Treatment of Diabetic Retinopathy Study letters at baseline to 73.9±14.1 after 12 months (p=0.014), while it remained stable in pretreated eyes (71.2±14.2 vs 73.0±12.9; p=0.14). CST decreased significantly in both groups (treatment-naïve (366.1±108.3 µm to 316.4±113.5 µm, p<0.001); pretreated (339.1±93.1 µm to 298.3±65.8 µm, p<0.001)). Thirty-one percent of naïve eyes and 21.1% of pretreated eyes were completely dry after 12 months. In treatment-naïve eyes, the mean treatment interval was 12.7±6.4 weeks at 12 months. In pretreated eyes, the interval increased from 6.0±3.0 to 7.8±3.6 weeks (p<0.001). Over 12 months, 8.1±2.1 and 9.4±2.5 injections were administered to naïve and pretreated eyes, respectively (p<0.001). Of the five recorded AEs, two cases of non-infectious intraocular inflammation and one cerebrovascular event were reported.

Over 12 months, faricimab demonstrated good efficacy and safety in both treatment-naïve and pretreated eyes with DME. There was a reduction in CST and improved VA in treatment-naïve eyes and stable VA in pretreated eyes. The low number of AEs supports a favourable risk-benefit profile of faricimab in a real-world setting.

To examine the associations between the inflammatory potentials of diet and lifestyle, as measured by the Dietary Inflammation Score (DIS) and Lifestyle Inflammation Score (LIS), with the risk of type 2 diabetes mellitus (T2DM), hypertension and chronic kidney disease (CKD).

This retrospective cohort study used data collected between 2000 and 2012 from the Multi-Ethnic Study of Atherosclerosis cohort, which was conducted across six US communities.

The study sample included 4736 participants for the analysis of T2DM, 2149 participants for hypertension and 4631 participants for CKD.

The primary outcomes were the incidence of T2DM, hypertension and CKD during follow-up.

During a median follow-up of 9.0 years, 537 participants developed T2DM, 1019 developed hypertension and 1067 developed CKD. DIS was not associated with T2DM in the overall population; however, women in the third quartile of DIS had a 52% higher risk of developing T2DM (HR 1.52; 95% CI 1.07 to 2.15). Also, individuals in the third quartile of DIS had a 22% higher risk of hypertension (1.22; 95% CI 1.02 to 1.47) in the overall population; however, no significant linear trend was observed across the quartiles (P-trend=0.397). Individuals in the fourth quartile of LIS had over twice the risk of developing T2DM (2.15; 95% CI 1.57 to 2.95), although no significant linear trend was observed across quartiles (P-trend <0.001). Additionally, the fourth quartile of LIS was associated with a 39% higher risk of hypertension (1.39; 95% CI 1.16 to 1.66) with a significant trend across quartiles (P-trend=0.001). The significant association between LIS and DIS and the risk of CKD was attenuated after adjusting for study confounders.

This study highlights the role of diet and lifestyle-related inflammation in the development of hypertension and T2DM risk, providing novel evidence from a large, multiethnic US cohort. The findings underscore the potential of dietary and lifestyle strategies that target inflammation to reduce cardiometabolic disease risk.

Before 2016, no Laotian child was known to have survived type 1 diabetes (T1D) into adulthood. There is an ongoing need for action. Our study explored, in supported youth, the impact of transitioning from a twice to multiple daily injection (MDI) regimen on glycaemic control, and their views/perceptions around how the switch affected their T1D management/quality of life.

Data were obtained from medical records/semi-structured interviews; participants recruited as they switched to an MDI regimen. Quantitative data were stratified into glycated haemoglobin (HbA1c) 6/12 months before/after the switch, and male/female sex; associations examined using t-tests. Qualitative data were analysed using Gibb's framework.

Overall, 24 youth (62.5% female) changed regimens. Mean±SD HbA1c 6/12-month periods before the switch were 8.8±2.3% (73.0 mmol/mol)/8.3±2.2% (67.0 mmol/mol), respectively. In the same periods after the switch, HbA1c improved to 7.6±2.7% (60.0 mmol/mol)/7.7±2.1% (61.0 mmol/mol), respectively. No differences were observed between sexes.Interviews were conducted with 15 youth (73.3% female); mean ages at T1D diagnosis/the switch time were 10.6 and 14.3 years, respectively. Describing how transitioning to an MDI regimen affected T1D management/quality of life, three themes emerged: pragmatism; empowerment and agency; and foundations of success.

The study provides valuable insights that will guide future work in supporting youth with T1D.

Gestational diabetes mellitus (GDM) is a common complication during pregnancy, with its incidence increasing year by year. It poses numerous adverse health effects on both mothers and newborns. Accurate prediction of GDM can significantly improve patient prognosis. In recent years, artificial intelligence (AI) algorithms have been increasingly used in the construction of GDM prediction models. However, there is still no consensus on the most effective algorithm or model.

This study aimed to evaluate and compare the performance of existing GDM prediction models constructed using AI algorithms and propose strategies for enhancing model generalizability and predictive accuracy, thereby providing evidence-based insights for the development of more accurate and effective GDM prediction models.

A comprehensive search was conducted across PubMed, Web of Science, Cochrane Library, EMBASE, Scopus, and OVID, covering publications from the inception of databases to June 1, 2025, to include studies that developed or validated GDM prediction models based on AI algorithms. Study selection, data extraction, and risk of bias assessment using the Prediction Model Risk of Bias Assessment Tool were performed independently by 2 reviewers. A bivariate mixed-effects model was used to summarize sensitivity and specificity and to generate a summary receiver operating characteristic (SROC) curve, calculating area under the curve (AUC). The Hartung-Knapp-Sidik-Jonkman method was further used to adjust for the pooled sensitivity and specificity. Between-study standard deviation (τ) and variance (τ²) were extracted from the bivariate model to quantify absolute heterogeneity. The Deek test was used to evaluate small-study effects among included studies. Additionally, subgroup analysis and meta-regression were conducted to compare the performance differences among algorithms and to explore sources of heterogeneity.

Fourteen studies reported on the predictive value for AI algorithms for GDM. After adjustment with the Hartung-Knapp-Sidik-Jonkman method, the pooled sensitivity and specificity were 0.78 (95% CI 0.69-0.86; τ=0.15, τ2=0.02; PI 0.47-1.09) and 0.85 (95% CI 0.78-0.92; τ=0.11, τ2=0.01; PI 0.59-1.11), respectively. The SROC curve showed that the AUC for predicting GDM using AI algorithms was 0.94 (95% CI 0.92-0.96), indicating a strong predictive capability. Deek test (P=.03) and the funnel plot both showed clear asymmetry, suggesting the presence of small-study effects. Subgroup analysis showed that the random forest algorithm exhibited the highest sensitivity (0.83, 95% CI 0.74-0.93), while the extreme gradient boosting algorithm exhibited the highest specificity (0.82, 95% CI 0.77-0.87). Meta-regression further revealed an evaluation in predictive accuracy in prospective study designs (regression coefficient=2.289, P=.001).

Unlike previous narrative reviews, this systematic review innovatively provided a comparative and quantitative synthesis of AI algorithms for GDM prediction. This established an evidence-based framework to guide model selection and identified a critical evidence gap. The key implication for real-world application was the demonstrated necessity of local validation before clinical adoption. Therefore, future work should focus on large-scale, prospective validation studies to develop clinically applicable tools.

The European Society for Paediatric Endocrinology (ESPE) e-Learning wesite is a free, globally accessible online resource to enhance learning in pediatric endocrinology and pediatric diabetes. The content is created by world-leading experts in pediatric endocrinology and pediatric diabetes and is closely aligned with published international consensus guidelines. In August 2022, 30 hours of e-learning courses received accreditation from the European Accreditation Council for Continuing Medical Education (CME). These CME courses cover three categories: (1) pediatric endocrinology, (2) pediatric diabetes, and (3) pediatric endocrinology in resource-limited settings.

This study aimed to assess learners' demographics and feedback from mandatory surveys after completion of CME e-learning courses and to identify areas for improvement.

The ESPE e-learning committee created a mandatory survey for each CME e-learning module. The survey includes baseline demographics and feedback on the quality of the learning content, assessed using a 5-point Likert scale. Data were extracted from the start of the CME modules in August 2022 until September 2025.

A total of 567 surveys were completed: 286 (50.4%) in the category pediatric endocrinology, 225 (39.7%) in the category pediatric diabetes based on the International Society for Pediatric and Adolescent Diabetes guidelines, and 56 (9.9%) in the category pediatric endocrinology in resource-limited settings. There was global participation, with most learners practicing in Europe (n=333, 59%), followed by Asia (n=124, 22%), Africa (n=53, 9%), the Americas (North America, n=45, 8%; and South America, n=11, 2%), and Oceania (n=1, 0%). Most of the users indicated that they were medical experts (n=210, 37%), followed by fellows or residents (n=223, 39%), and medical students and nurses (n=29, 5% and n=32, 6%, respectively); overall, 10% (n=56) of learners practice in resource-limited countries. Overall, the learning content was well received for all modules regarding accessibility, organization, level of interest, improvement of learners' clinical practice, appropriateness of content, and provision of feedback (median Likert score 4, IQR 4-5). Learners' free-text feedback identified some areas for improvement, including reducing text-heavy content and providing more graphical content and more interactive case reports. Most learners' free-text feedback consisted of encouraging and thankful comments.

The ESPE CME-accredited e-learning modules are well received, providing globally free CME education in pediatric endocrinology and pediatric diabetes. These findings support the continued development and promotion of open-access CME platforms, with the aim of improving global equity in specialist medical education and focusing on educational impact.

ObjectivesDiabetes mellitus (DM) is a common comorbidity in intensive care unit (ICU) patients. The Braden skin score (BSS) has increasingly been recognized as an indicator of patient frailty. However, the association between the BSS and clinical outcomes in critically ill diabetic patients remains unclear. This study aimed to investigate the relationship between the BSS and clinical outcomes in diabetic patients in ICU settings.MethodsA retrospective cohort of diabetic patients with measured BSS was identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The primary outcomes included mortality at 30, 60, and 90 days. The association between BSS and survival outcomes was evaluated using time-dependent Cox proportional hazards model. Further validation was conducted through Kaplan-Meier survival analysis, restricted cubic spline fitting, and subgroup analyses.ResultsA total of 20,590 patients were included in this study, those with higher BSS had a 14% decreased risk of 30-day mortality (HR: 0.86, 95% CI: 0.84-0.87, p < .01). Based on cutoff values of 13, patients were categorized into two risk groups. After adjusting for covariates, time-dependent Cox proportional hazards model indicated that the high-risk group exhibited a significantly increased 30-day all-cause mortality compared with the low-risk groups (HR: 1.76, 95% CI: 1.62-1.91, p < .01). Kaplan-Meier curves consistently demonstrated poorer survival across all time points in the high-risk group. Subgroup analysis further indicated that the association between BSS and mortality was particularly pronounced in patients with cerebrovascular disease.ConclusionsA low BSS was independently linked to higher mortality among critically ill patients with diabetes, especially in those with concomitant cerebrovascular diseases. These results support the potential utility of BSS as a prognostic indicator in this population. Further validation through larger prospective studies remains necessary.

The purpose of this study was to determine which baseline factors, including ultra-widefield fluorescein angiography (UWF-FA) nonperfusion and macular optical coherence tomography angiography (OCTA) metrics, predict 2-year progression of retinal nonperfusion on UWF-FA in diabetic retinopathy (DR).

This prospective observational study included 73 patients (110 eyes) with diabetes across the spectrum of DR severity, followed for 2 years. Retinal nonperfusion was manually quantified as ischemic index, and progression was calculated as the 2-year minus baseline ischemic index for gradable retina. For receiver operating characteristic (ROC) analyses, progression was further defined as a binary event when the 2-year ischemic index increase exceeded two standard deviations (SDs) above the mean progression observed in non-referable DR. Linear mixed-effects models evaluated baseline predictors, and ROC analyses assessed the discriminative performance of significant predictors.

Mean 2-year ischemic index progression was 0.45 ± 0.90%, with greater progression in moderate and severe nonproliferative DR than in non-referable DR. In multivariate models, greater baseline ischemic index (standardized β = 0.27, P = 0.002), higher deep capillary plexus (DCP) geometric perfusion deficit (β = 0.36, P = 0.006), and lower DCP vessel density (β = -0.22, P = 0.012) independently predicted total nonperfusion progression. Baseline ischemic index, DCP geometric perfusion deficit, and DCP vessel density yielded areas under the curve of 0.84, 0.77, and 0.70, respectively, for detecting binary nonperfusion progression.

In this cohort, baseline UWF-FA nonperfusion was the strongest predictor of retinal nonperfusion progression, whereas macular DCP OCTA metrics provided independent, noninvasive prognostic information. Macular DCP OCTA parameters may serve as adjunctive biomarkers to refine DR risk stratification, particularly when UWF-FA is unavailable.