BackgroundVascular calcification (VC) is common among patients with type 2 diabetes mellitus (T2DM) and is associated with adverse cardiovascular outcomes. Although experimental evidence suggests that elevated serum uric acid (SUA) may promote VC, its clinical relevance in patients with T2DM remains unclear.MethodsWe conducted a retrospective cohort study based on electronic medical records from the Central Hospital of Dalian University of Technology. The study included 665 hospitalized patients with T2DM who had no evidence of VC on baseline pulmonary computed tomography (CT) and underwent follow-up pulmonary CT. Incident VC was defined as newly detected, radiologically visible coronary artery calcification (CAC), aortic calcification, or both on mediastinal-window pulmonary CT. Associations between SUA and incident VC were assessed using Kaplan–Meier analysis, multivariable Cox regression, restricted cubic spline (RCS)analysis, subgroup analyses, and sensitivity analyses. Predictive performance was assessed using time-dependent receiver operating characteristic (ROC) analysis with inverse probability of censoring weighting (IPCW).ResultsDuring a median follow-up of 2.25 years, incident VC developed in 315 patients. In the fully adjusted model, each 1-standard-deviation (SD) increase in SUA was associated with a higher risk of incident VC (HR, 1.271; 95% CI, 1.138–1.420; P < 0.001). Compared with the lowest SUA quartile, the third and fourth quartiles were associated with higher risks of incident VC (HR, 1.634; 95% CI, 1.125–2.375; P = 0.010; and HR, 2.075; 95% CI, 1.432–3.006; P < 0.001, respectively). RCS analysis showed an approximately linear association between SUA and incident VC. Time-dependent areas under the curve (AUCs) for SUA were 0.666, 0.730, 0.777, and 0.847 at 1, 3, 5, and 10 years, respectively. Adding SUA to the fully adjusted base model yielded modest improvements in discrimination and prediction error.ConclusionAmong patients with T2DM, higher SUA levels were associated with an increased risk of incident, radiologically visible macrovascular calcification. SUA may help identify patients at higher risk of VC; however, the data-derived threshold of approximately 300 μmol/L should be considered exploratory and requires external validation. Whether lowering SUA reduces the risk of VC remains to be determined in prospective interventional studies.

Childhood obesity has become one of the most prevalent chronic health conditions and represents a major risk to normal growth and development in pediatric populations. As its global incidence continues to rise, increasing attention has been directed toward sarcopenic obesity (SO) as an important and emerging phenotype. This condition is defined by the coexistence of excessive adiposity and diminished muscle mass, which can negatively influence physical development as well as skeletal health in children. During childhood and adolescence, skeletal growth progresses rapidly and is highly sensitive to metabolic and hormonal influences. In this context, SO may impair bone formation via mechanical loading alterations, endocrine dysregulation, and chronic low-grade inflammation, ultimately contributing to reduced bone mineral content. Moreover, the combined impact of excess fat and insufficient muscle mass during these critical developmental stages may have long-term consequences that extend into adulthood, highlighting the importance of timely prevention and intervention. This narrative review examines the relationship between sarcopenic obesity and bone mass in children. It synthesizes recent evidence on epidemiology, underlying pathophysiological mechanisms, clinical features and evidence, as well as screening and management strategies, and further proposes recommendations focused on lifestyle-based interventions.

ContextNocturnal hypoglycemia (NH) is a common adverse event in elderly patients with type 2 diabetes (T2D). This study aims to develop a clinically applicable model for predicting the risk of NH in elderly patients with T2D.MethodsThis retrospective cohort study, conducted from May 2018 to June 2024, analyzed 1,128 elderly T2D patients undergoing continuous glucose monitoring, with an independent validation involving 100 outpatients. Clinical characteristics were collected, and feature engineering was performed to select a manageable set of clinically accessible features. An ensemble model was developed using multiple base models and a stacking approach. The best-performing model was deployed as an online risk calculator.ResultsOf the development set, 288 (25.5%) experienced NH, while 40 (40%) of the independent validation cohort experienced NH. The final ensemble model, “RF-ET-KNN”, combined random forest, Extra Trees, and K-nearest neighbor as base learners, with Extra Trees serving as the meta-learner. It incorporated eleven clinical features and achieved an AUROC of 0.926 and sensitivity of 0.853 on the test set, and an AUROC of 0.947 and sensitivity of 0.929 on the internal validation set. SHAP analysis identified that daytime lowest blood glucose (BG), fasting blood glucose (FBG), and daytime hypoglycemia events were closely related to NH. A user-friendly calculator is available at http://122.51.219.102:8000/.ConclusionThe “RF-ET-KNN” model, integrating eleven clinically accessible features, effectively predicts NH in elderly T2D patients. Daytime lowest BG, FBG, and daytime hypoglycemia events were significant risk factors.

BACKGROUND:Pre-diabetes is a transitional metabolic stage between health and diabetes, serving as a critical warning signal for disease progression. Early intervention targeting risk factors in prediabetic individuals prevents the progression to type 2 diabetes. AIM:To investigate the predictive value of the triglyceride-glucose (TyG) index and its derived indicators for new-onset diabetes in patients with pre-diabetes. METHODS:A prospective community-based cohort study was carried out based on subjects aged over 40 years with pre-diabetes in Dalian, Liaoning Province, China. A total of 1352 subjects with complete follow-up data attended the follow-up survey. Multivariable Cox regression models were performed to assess the association of the TyG index and its derived indicators with risk of diabetes in patients with pre-diabetes. The diagnostic values of the TyG index and derived indicators in predicting new-onset diabetes were analyzed, and suitable cutting points were determined using the receiver operating characteristic (ROC) curve. RESULTS:During a 3-year follow-up period, 153 cases with incident diabetes were identified, with a cumulative incidence of diabetes of 11.3%; 12.6% (43/341) in males and 10.9% (110/1011) in females (χ 2 = 0.760, P = 0.375). After adjusting for confounding factors including age, gender, body mass index (BMI) and insulin levels, the risk of diabetes with higher TyG and derived indexes [TyG-BMI and TyG-waist circumference index (TyG-WC)] increased significantly. The TyG index [hazard ratio (HR) = 1.389, 95% confidence interval (CI): 1.011-1.908, P = 0.043], TyG-BMI (HR = 1.010, 95%CI: 1.005-1.015, P = 0.000) and TyG-WC (HR = 1.003, 95%CI: 1.001-1.005, P = 0.001) were all strongly positively correlated with the risk of future diabetes. The ROC curve analysis showed that the area under the curve (AUCs) of the TyG, TyG-BMI and TyG-WC for predicting new diabetes were 0.578 (95%CI: 0.533-0.624), 0.622 (95%CI: 0.574-0.670) and 0.609 (95%CI: 0.562-0.657), respectively. The difference in AUC between TyG-BMI and TyG was significant (P = 0.047), while the differences between TyG-BMI and TyG-WC (P = 0.464) and between TyG-WC and TyG (P = 0.175) were not. The TyG-BMI had a larger AUC than the TyG and TyG-WC, and its difference from TyG was significant. The best cut-off points for predicting new diabetes were TyG > 8.6, TyG-BMI > 247 and TyG-WC > 860. Although the AUC values were modest, these indices may serve as preliminary screening tools in resource-limited settings. CONCLUSION:The TyG index and its derived indicators were risk factors for the pre-diabetes to diabetes outcome, and may be regarded as predictors of the outcome. The risk of conversion of pre-diabetes to diabetes increased with increases in the TyG index and its derived indicators. The TyG-BMI was better than TyG and TyG-WC in predicting the 3-year outcome for diabetes. Although these indices could aid in the initial risk stratification in primary care, their modest accuracy warrants cautious interpretation.

Childhood-onset systemic lupus erythematosus (cSLE) is a chronic, multisystem autoimmune disease characterized by marked clinical heterogeneity and substantial morbidity. Although rash, arthritis, and renal involvement are common manifestations, atypical presentations may delay diagnosis. In rare cases, growth retardation and delayed puberty may precede typical systemic features, posing a diagnostic challenge. We report the case of a 12-year-old Chinese girl who presented to the endocrinology clinic with progressive growth retardation and delayed pubertal development. Comprehensive growth assessment demonstrated discordance among height velocity, weight gain, and pubertal progression. Further evaluation revealed proteinuria, hypoalbuminemia, generalized lymphadenopathy, and immunological abnormalities, leading to a diagnosis of cSLE. Following immunosuppressive therapy, systemic manifestations improved and laboratory indices gradually normalized; however, longitudinal follow-up showed that impairment in growth and pubertal progression persisted despite disease control. This case highlights that cSLE, although a rare cause of growth retardation and delayed puberty, should be considered in adolescents with unexplained short stature or pubertal delay, particularly when accompanied by proteinuria or immunological abnormalities. Early recognition and multidisciplinary management are essential to improve long-term growth and overall clinical outcomes.

With changes in lifestyle and dietary patterns, paediatric hyperuricaemia has become an increasingly recognised metabolic condition worldwide. Its potential implications for skeletal health have attracted growing attention at the intersection of paediatric endocrinology, metabolism, and bone biology. This narrative review synthesises current evidence regarding the potential relationship between hyperuricaemia and skeletal health in children and adolescents. We discuss the epidemiology and clinical characteristics of paediatric hyperuricaemia, potential mechanisms linking urate dysregulation to bone metabolism, and available evidence concerning bone mineral density, bone microstructure, linear growth, and fracture risk. Because direct paediatric evidence remains limited, findings from adult populations, experimental models, and rare inherited metabolic disorders are considered primarily as indirect or hypothesis-generating evidence rather than as definitive proof of causality. We also discuss approaches to skeletal assessment, lifestyle management, and urate-lowering therapy, whilst highlighting major gaps in the current evidence base and priorities for future research.

IntroductionFamilial hypocalciuric hypercalcemia (FHH) is an autosomal dominant disorder caused by an inactivating mutation in the CASR gene, while Gitelman syndrome (GS) is an autosomal recessive renal tubular disorder resulting from a pathogenic mutation in the SLC12A3 gene. Both genetic disorders are relatively rare. This report presents a patient with both FHH and GS, exhibiting unique clinical and genetic complexities.Case summaryWe report a case of a 69-year-old Asian female patient who had previously presented to the hospital on multiple occasions with complaints of joint stiffness, fatigue, dizziness, or other symptoms. The patient was readmitted to the hospital at the age of 66, presenting with the following clinical findings: hypocalciuria, hypercalcemia, normal or mildly elevated parathyroid hormone (PTH) levels, hypokalemia, hypomagnesemia, hypophosphatemia, normal blood pressure, chondrocalcinosis (CC), and diabetes mellitus. Our careful analysis suggested that the patient might have the co-occurrence of GS and FHH. Genetic testing revealed a novel heterozygous CASR p.Tyr161* mutation and a homozygous SLC12A3 p.Thr60Met mutation, which ultimately confirmed the diagnosis of familial hypocalciuric hypercalcemia type 1 (FHH1) combined with GS.ConclusionFor the first time, we report a case of FHH combined with GS. The novel CASR mutation in this patient expands the variant spectrum of FHH, provides new genetic evidence for its pathogenesis, and underscores the importance of genetic counseling for consanguineous families. This case also suggests a potential association between FHH and CC, the mechanism of which warrants further investigation. In addition, this report highlights possible potential interactions between FHH and GS. Clinically, hypokalemia and hypomagnesemia associated with GS are more detrimental than hypercalcemia linked to FHH and should be prioritized in management. Finally, genetic testing and molecular diagnostics are crucial for pediatric and adolescent populations with FHH and/or GS, and further studies are needed to clarify the genotypic and phenotypic relationships between FHH and GS comorbidities.

INTRODUCTION:A retrospective cohort study was conducted to study the association between smoking and hyperuricemia (HUA). METHODS:By collecting and analyzing clinical data of 3196 patients with undiagnosed HUA at baseline in Dalian Municipal Central Hospital of China between 1 January 2010 and 1 January 2021, patients were grouped according to baseline smoking status and smoking index (the number of cigarettes smoked per day × number of years of smoking). Cox regression analysis was used to perform univariable and multivariable analyses of factors that may influence the occurrence of HUA. And further stratification was performed. RESULTS:The median follow-up time was 3.62 years. A total of 485 (15.2%) patients developed HUA (≥420 μmol/L). The incidence of HUA was significantly higher in the smoking group than in the non-smoking group (p<0.05). There was a statistically significant difference in the incidence of HUA between the smoking index 1-4 (>0) groups and the smoking index 0 (0) group (p<0.05). Multifactorial Cox regression analyses were performed separately and after adjustment for relevant influences, the results showed that smoking was an independent risk factor for the occurrence of HUA with a hazard ratio (HR) of 1.38 (95% CI: 1.11-1.72). And the smoking index groups 401-600 and ≥601 were independent risk factors for the occurrence of HUA, with HRs of 1.46 (95% CI: 1.20-1.70) and 1.53 (95% CI: 1.06-2.22), respectively. The further stratified analysis revealed that smoking remained an independent risk factor for the occurrence of HUA in all subgroups, and the smoking index ≥601 group was also an independent risk factor for the occurrence of HUA, with HRs greater than 1 (p<0.05). CONCLUSIONS:Smoking is an independent risk factor for the occurrence of HUA and is independent of gender, whether a woman is menopausal, body mass index (BMI), and alcohol consumption. The smoking index ≥601 was an independent risk factor for the occurrence of HUA.

A flexible bismuth (Bi)-based smartsensor capable of simultaneously detecting Cd2+, Tl+, and Pb2+ is proposed for the first time. Fabricated via a template-assisted electrodeposition method, this novel sensor demonstrates excellent selectivity in distinguishing these heavy metal ions (HMIs). The developed platform holds broad application prospects for on-site HMI monitoring.

The global rise in diabetes mellitus and its related complications represents a major threat to public health. Existing treatments for diabetes and its complications primarily focus on symptom management, with a significant gap in effective therapies for diabetic complications that can lead to mortality. This highlights the urgent need for more effective and safer treatment options. Recent studies have revealed a strong connection between ferroptosis and the progression of diabetes and its complications, suggesting that preventing or inhibiting ferroptosis could represent a groundbreaking strategy in diabetes management. Natural products (NPs), known for their ability to target multiple pathways, sustainability, and minimal toxicity, have gained significant interest as potential ferroptosis inhibitors for diabetes treatment. This review provides an in-depth overview of preclinical and clinical research on 41 NPs that target ferroptosis, including their nano-formulations, exploring their mechanisms and potential as novel therapeutic agents for managing diabetes and its complications.

BACKGROUND:Recently, patients with type 2 diabetes mellitus (T2DM) have experienced a higher incidence and severer degree of vascular calcification (VC), which leads to an increase in the incidence and mortality of vascular complications in patients with T2DM. HYPOTHESIS:To construct and validate prediction models for the risk of VC in patients with T2DM. METHODS:Twenty-three baseline demographic and clinical characteristics were extracted from the electronic medical record system. Ten clinical features were screened with least absolute shrinkage and selection operator method and were used to develop prediction models based on eight machine learning (ML) algorithms (k-nearest neighbor [k-NN], light gradient boosting machine, logistic regression [LR], multilayer perception [(MLP], Naive Bayes [NB], random forest [RF], support vector machine [SVM], XGBoost [XGB]). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, and precision. RESULTS:A total of 1407 and 352 patients were retrospectively collected in the training and test sets, respectively. Among the eight models, the AUC value in the NB model was higher than the other models (NB: 0.753, LGB: 0.719, LR: 0.749, MLP: 0.715, RF: 0.722, SVM: 0.689, XGB:0.707, p < .05 for all). The k-NN model achieved the highest sensitivity of 0.75 (95% confidence interval [CI]: 0.633-0.857), the MLP model achieved the highest accuracy of 0.81 (95% CI: 0.767-0.852) and specificity of 0.875 (95% CI: 0.836-0.912). CONCLUSIONS:This study developed a predictive model of VC based on ML and clinical features in type 2 diabetic patients. The NB model is a tool with potential to facilitate clinicians in identifying VC in high-risk patients.

Context The components of metabolic syndrome (MetS) are interrelated and associated with renal complications in patients with type 2 diabetes (T2D). Objective We aimed to reveal prevalent metabolic profiles in patients with T2D and identify which metabolic profiles were risk markers for renal progression. Methods A total of 3556 participants with T2D from a hospital (derivation cohort) and 931 participants with T2D from a community survey (external validation cohort) were included. The primary outcome was the onset of diabetic kidney disease (DKD), and secondary outcomes included estimated glomerular filtration rate (eGFR) decline, macroalbuminuria, and end-stage renal disease (ESRD). In the derivation cohort, clusters were identified using the 5 components of MetS, and their relationships with the outcomes were assessed. To validate the findings, participants in the validation cohort were assigned to clusters. Multivariate odds ratios (ORs) of the primary outcome were evaluated in both cohorts, adjusted for multiple covariates at baseline. Results In the derivation cohort, 6 clusters were identified as metabolic profiles. Compared with cluster 1, cluster 3 (severe hyperglycemia) had increased risks of DKD (hazard ratio [HR] [95% CI]: 1.72 [1.39-2.12]), macroalbuminuria (2.74 [1.84-4.08]), ESRD (4.31 [1.16-15.99]), and eGFR decline [P < .001]; cluster 4 (moderate dyslipidemia) had increased risks of DKD (1.97 [1.53-2.54]) and macroalbuminuria (2.62 [1.61-4.25]). In the validation cohort, clusters 3 and 4 were replicated to have significantly increased risks of DKD (adjusted ORs: 1.24 [1.07-1.44] and 1.39 [1.03-1.87]). Conclusion We identified 6 prevalent metabolic profiles in patients with T2D. Severe hyperglycemia and moderate dyslipidemia were validated as significant risk markers for DKD.

Ammonia (NH3) of high concentration will pose a threat to ecological environment or human health, and exhaled NH3 is significant in disease monitoring and diagnosis. Thus, developing a highly sensitive gas sensor is significant to monitor NH3 concentration in complex environments. However, traditional NH3 sensors either need high working temperature, or face the challenge of poor conductivity/ sensitivity. In this work, NH3 sensors based on self-assembled MXene membrane have been fabricated. As-prepared sensors show a high sensitivity of 2.10 ppm-1 towards extremely low concentrations of NH3 (ppb level) at room temperature, attributed to large surface area and high conductivity. In addition, the sensors also display low detection limit (50 ppb), fast response time (41 s), good recoverability, long-term stability (15 days) and excellent flexibility (1000 bending cycles) towards NH3. The results provide insights into the development of highly sensitive NH3 sensors for industrial or biomedical applications. image

Diabetes, characterized as a well-known chronic metabolic syndrome, with its associated complications pose a substantial and escalating health and healthcare challenge on a global scale. Current strategies addressing diabetes are mainly symptomatic and there are fewer available curative pharmaceuticals for diabetic complications. Thus, there is an urgent need to identify novel pharmacological targets and agents. The impaired mitochondria have been associated with the etiology of diabetes and its complications, and the intervention of mitochondrial dysfunction represents an attractive breakthrough point for the treatments of diabetes and its complications. Natural products (NPs), with multicenter characteristics, multi-pharmacological activities and lower toxicity, have been caught attentions as the modulators of mitochondrial functions in the therapeutical filed of diabetes and its complications. This review mainly summarizes the recent progresses on the potential of 39 NPs and 2 plant-extracted mixtures to improve mitochondrial dysfunction against diabetes and its complications. It is expected that this work may be useful to accelerate the development of innovative drugs originated from NPs and improve upcoming therapeutics in diabetes and its complications.

The advent of wearable sensors heralds a transformation in the continuous, noninvasive analysis of biomarkers critical for disease diagnosis and fitness management. Yet, their advancement is hindered by the functional challenges affiliated with their active sensing analysis layer. Predominantly due to suboptimal intrinsic material properties and inconsistent dispersion leading to aggregation, thus compromising sensor repeatability and performance. Herein, an innovative approach to the functionalization of wearable electrochemical sensors was introduced, specifically addressing these limitations. The method involves a proton-induced self-assembly technique at the organic-water (O/W) interface, facilitating the generation of biomarker-responsive films. This research offers flexible, breathable sensor capable of real-time precision tracking l-cysteine (l-Cys) precision tracking. Utilizing an activation mechanism for Prussian blue nanoparticles by hydrogen peroxide, the catalytic core exhibits a specific response to l-Cys. The implications of this study refine the fabrication of film-based analysis electrodes for wearable sensing applications and the broader utilization of two-dimensional materials in functional-specific response films. Findings illuminate the feasibility of this novel strategy for precise biomarker tracking and extend to pave the way for constructing high-performance electrocatalytic analytical interfaces.

BACKGROUND:Given the established link between obesity and hyperuricemia (HUA), the research want to investigate the relationship between different obesity indices and HUA, and further analyze which obesity index can better predict HUA. METHODS:The data were obtained from a longitudinal study involving middle-aged and elderly populations in Dalian, China. The research encompassed individuals who exhibited typical uric acid levels initially and tracked their progress over a three-year period. 8 obesity indices were evaluated retrospectively. Subgroup analyses were conducted to identify susceptible populations. Restricted cubic splines (RCS) were utilized to model the dose-response relationships between obesity indices and HUA. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of both traditional and new obesity indices for HUA. RESULTS:Among 4,112 individuals with normal baseline uric acid levels, 950 developed HUA. Significant associations with HUA were observed for body mass index (BMI), waist circumference (WC), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and abdominal volume index (AVI). Subgroup analysis indicated that all obesity indices proved more effective in assessing the onset of HUA in women without Metabolic Syndrome (MetS). Further analysis using RCS revealed non-linear dose-response relationships between LAP, CMI, VAI, and HUA in males, with similar non-linear relationships observed for all indices in females. The results from the ROC curves indicate that LAP may serve as a better predictor of HUA in males, and CVAI may serve as a better predictor in females. CONCLUSION:HUA is closely associated with obesity indices. Among females, CVAI emerges as the preferred predictive index for HUA. In males, LAP emerges as the preferred predictive index for HUA.