Introduction and Objective: Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, with progressive renal fibrosis driving irreversible renal decline. Current therapies inadequately target fibrotic mechanisms. Cathepsin L (CTSL), a hyperglycemia-induced lysosomal protease, has been implicated in tissue remodeling, but its mechanistic and translational relevance in DKD remains unclear. Methods: CTSL expression and localization were examined in human DKD kidney specimens. In vitro and in vivo models were used to investigate high-glucose-mediated regulation of CTSL maturation, trafficking, and activity. Functional effects of tubular CTSL were assessed using epithelial-fibroblast co-culture systems. Mice with tubular epithelial cell-specific deletion of CTSL were subjected to multiple renal fibrosis models. Translational studies were performed using an orally bioavailable, internally developed CTSL inhibitor in db/db mice. Results: CTSL was markedly upregulated in human DKD kidneys, with selective enrichment in tubular epithelial cells. High glucose enhanced CTSL maturation and enzymatic activity via increased mannose-6-phosphate glycosylation and lysosomal trafficking. Functionally, tubular CTSL induced epithelial-mesenchymal transition and promoted paracrine fibroblast-to-myofibroblast activation, driving extracellular matrix accumulation. Tubular CTSL deletion attenuated renal fibrosis across unilateral ureteral obstruction, ischemia-reperfusion injury, and diabetic nephropathy models. Treatment with the internally developed CTSL inhibitor reduced fibrotic burden and improved renal and metabolic parameters in db/db mice. Conclusion: Tubular epithelial CTSL is a metabolically regulated driver of renal fibrosis in DKD. Genetic ablation and pharmacologic inhibition using an internally developed CTSL inhibitor confer robust renoprotection, supporting CTSL as a translatable antifibrotic target. Disclosure M. Zhao: None. X. Li: None. M. Li: None. X. Yan: None. J. Yang: None. Funding National Natural Science Foundation of China (82300917, 82570960, 82341076)

Introduction and Objective: Diabetic kidney disease (DKD) is a major complication of type 2 diabetes (T2D), yet non-diabetic kidney disease (NDKD) is common. Although renal biopsy remains the diagnostic gold standard, its invasive nature limits routine use. We aimed to develop an interpretable machine learning (ML) model to noninvasively differentiate DKD from NDKD. Methods: From 19,404 renal biopsy cases across 14 centers in China, 2,047 patients with T2D and definitive pathological diagnoses were included. Six ML algorithms were trained using routinely available clinical variables optimized by recursive feature elimination. Model performance was assessed by area under the receiver operating characteristic curve (AUC-ROC), and interpretability was evaluated using SHapley Additive exPlanations (SHAP). The best-performing model was externally validated and deployed as a web-based tool. Results: Of the 2,047 biopsy-confirmed patients with T2D, 722 (35.3%) had DKD, 999 (48.8%) had NDKD, and 326 (15.9%) had mixed pathology. The Random Forest model achieved the highest discriminative performance (AUC 0.90 [95% CI 0.88-0.92], sensitivity 0.77, specificity 0.90). Performance remained robust in external validation (AUC 0.86). Diabetic retinopathy, diabetes duration, HbA1c, and serum creatinine were the strongest predictors of DKD. SHAP analysis identified diabetic retinopathy as the most influential positive contributor, whereas higher total cholesterol and BMI were inversely associated. The final model was deployed as an interactive web application (https://diagnosis-of-dkd-and-ndkd.streamlit.app/). Conclusion: This interpretable ML model accurately distinguishes DKD from NDKD using routine clinical data, potentially reducing reliance on renal biopsy and supporting personalized clinical decision-making in T2D. Disclosure J. Yang: None. F. Yang: None. J. Zhang: None. M. Li: None. X. Li: None. Funding National Natural Science Foundation of China (82570960)

Introduction and Objective: The global prevalence of obesity and diabetes has escalated dramatically in recent decades, driven by both obesogenic dietary patterns (e.g., high-fat diet, HFD) and environmental contaminants such as microplastics (MPs). However, the combined effects of chronic low-dose MPs exposure and HFD consumption on the progression of metabolic diseases remain poorly understood. This study aims to investigate the role of polystyrene microplastics (PS-MPs) in exacerbating HFD-induced metabolic dysfunction and its underlying mechanisms. Methods: Male C57BL/6J mice were randomized into four groups: normal chow diet (NCD), NCD + PS-MPs, HFD, and HFD + PS-MPs. PS-MPs (25-30 μg/kg body weight/day) was administered via oral gavage for 14-16 weeks. Metabolic parameters including body weight gain, energy expenditure, body fat composition, glucose tolerance, insulin sensitivity, and thyroid function were systematically evaluated. Results: PS-MPs exposure significantly exacerbated HFD-induced obesity and metabolic disorders, characterized by accelerated weight gain, reduced energy metabolism, impaired glucose homeostasis, and dysregulated lipid profiles. Mechanistically, in vivo and in vitro experiments confirmed that low-dose PS-MPs primarily disrupt the thyroid-brown adipose tissue (BAT) axis to mediate these adverse effects. Notably, thyroid hormone supplementation reversed the metabolic impairments, further validating the causal role of the thyroid-BAT axis in PS-MPs-induced metabolic dysfunction. Conclusion: These findings highlight the critical contribution of chronic low-dose PS-MPs exposure to the pathogenesis of obesity and diabetes, particularly in the context of pre-existing metabolic stress (e.g., HFD). The identification of the thyroid-BAT axis as a key mediator provides novel therapeutic targets for mitigating metabolic diseases associated with environmental MPs exposure. Disclosure G. Wei: None. F. Shen: None. F. Ma: None. W. Cao: None. J. Yang: None.

Introduction and Objective: N4-acetylcytidine (ac4C) is an emerging epitranscriptomic RNA modification, but its role in hepatic macrophages in metabolic dysfunction-associated fatty liver disease (MAFLD) is unknown. NAT10 is the sole known ac4C writer. We examined whether NAT10-mediated ac4C modification of peroxisome proliferator-activated receptor (PPAR) family mRNAs regulates hepatic macrophage polarization, lipid metabolism and inflammation in MAFLD. Methods: In high-fat diet (HFD)-fed mice, ac4C abundance and NAT10 expression were assessed in Kupffer cells. A macrophage-targeted AAV-NAT10 approach was used to evaluate the effects of macrophage-specific NAT10 overexpression on hepatic steatosis and inflammation. In vitro, primary macrophages were subjected to NAT10 overexpression or knockdown, fatty acid plus IL-4 stimulation, followed by assessment of macrophage phenotype and mitochondrial function. NAT10-dependent ac4C-modified transcripts were identified by integrated acRIP-seq and RNA-seq, and ac4C modification and stability of PPAR mRNAs were validated. Results: HFD feeding markedly reduced ac4C levels and NAT10 expression in Kupffer cells. Macrophage-specific NAT10 overexpression attenuated hepatic lipid accumulation and improved metabolic parameters in vivo. In fatty acid-treated macrophages, NAT10 enhanced fatty acid oxidation and oxidative phosphorylation, increased M2 markers, and suppressed pro-inflammatory M1 cytokines. PPAR family transcripts were major NAT10-dependent ac4C targets; NAT10 increased ac4C modification, mRNA stability, and protein expression of PPARs, whereas NAT10 knockdown had opposite effects. Pharmacologic PPAR inhibition partially reversed NAT10-driven metabolic reprogramming and M2 polarization. Conclusion: NAT10-ac4C signaling is disrupted in Kupffer cells during MAFLD. By stabilizing PPAR mRNAs, NAT10 promotes a shift toward an FAO/OXPHOS-dependent M2 reparative macrophage phenotype, reducing hepatic steatosis and inflammation. Disclosure F. Shen: None. G. Wei: None. W. Cao: None. F. Ma: None. Y. Wang: None. J. Yang: None.

Cathepsin L (CTSL) is a prominent therapeutic target for kidney injury, yet clinically available CTSL inhibitors remain limited. Here, we developed an artificial intelligence (AI)-assisted discovery strategy to identify novel CTSL inhibitors from a natural products library. Through a robust deep learning model and molecular docking, we screened 200 molecules from natural products library for experimental validation. Active candidates were further analyzed by molecular dynamics simulations to characterize binding modes and key CTSL-ligand interaction networks, followed by evaluation of therapeutic efficacy in kidney injury-relevant models. At a concentration of 100 µM, we found that 43 of them exhibited more than 50% inhibition of CTSL. Notably, nine molecules displayed over 90% inhibition and exhibited concentration-dependent effects. Molecular dynamics simulations indicated that Kuwanon G (KG), Iberverin, and Wighteone stably bind within the CTSL active site. In human renal cells, KG attenuated high glucose and high lipid induced inflammatory and injury responses. Collectively, these findings identify new CTSL inhibitors with therapeutic potential for renal injury and underscore the utility of AI-assisted strategies in accelerating drug discovery.

Background: Diabetes is associated with poor outcomes in hospitalized patients, but population-level evidence on how in-hospital mortality changed across the pre-pandemic, pandemic, and recovery periods remains scarce. We aimed to assess long-term trends in in-hospital mortality among diabetic inpatients, compare these trends with those in non-diabetic inpatients, and quantify pandemic-attributable excess mortality. Methods: In this large-scale hospital-based cohort study, we analysed administrative hospitalization records from all 207 hospitals in the greater Beijing area, China, from Jan 1, 2012, to Dec 31, 2024, obtained from the Beijing Municipal Health Big Data and Policy Research Center. Diabetes was identified using ICD-10 codes. Joinpoint regression was used to assess temporal trends in in-hospital mortality, Cox proportional hazards models to estimate period-specific mortality risks by diabetes status, and Bayesian structural time-series models to quantify excess mortality attributable to the pandemic. Findings: Among 27,471,563 unique hospitalized patients, 4,571,832 had diabetes and 146,282 died in hospital; among 22,899,731 patients without diabetes, 305,904 died in hospital. In-hospital mortality among diabetic patients was stable during 2012–19, increased during 2019–22, and declined during 2022–24. The increase was concentrated in adults aged 65 years or older. In fully adjusted Cox models, the hazard ratio for in-hospital death in 2022 versus 2012–19 was 14.5 in diabetic patients and 6.4 in non-diabetic patients. Counterfactual analyses showed 15–30% excess mortality among diabetic inpatients during 2020–22. Interpretation: The COVID-19 pandemic was associated with a substantial but transient increase in in-hospital mortality among diabetic inpatients, especially older adults, underscoring the need for targeted protection and continuity of high-quality inpatient care during future public health emergencies.

Helicobacter pylori (H. pylori) has been increasingly linked to extragastric conditions. However, the relationship between H. pylori infection and cardiovascular diseases (CVD) remains controversial. This study aims to investigate the association between H. pylori infection and 10-year cardiovascular risk. A total of 1,398 subjects who underwent health examinations at Beijing Tongren Hospital were included in this study. H. pylori infection was determined using 13C-breath test. The 10-year cardiovascular risk was assessed using the Framingham score. Insulin resistance was evaluated through the triglyceride-glucose (TyG) index and its derivatives. Logistic regression and subgroup analyses were performed to evaluate associations. Individuals with H. pylori infection exhibited significantly higher TyG index and its derivatives (all P < 0.001), indicating increased insulin resistance. All TyG-related indices were strongly correlated with 10-year CVD risk, with TyG-WHR showing the strongest association (R = 0.745, P < 0.001). The estimated 10-year CVD risk was significantly higher in the H. pylori-infected group (P = 0.003). After adjusting for potential confounders, H. pylori infection remained independently associated with high cardiovascular risk (OR = 2.552, 95

Aim Monogenic diabetes is a group of disorders arising from single gene mutations with a clear pathophysiology, most of which present with impaired beta cell function rather than insulin resistance. This study aims to evaluate the ability of TyG index and polygenetic risk score (PRS) to identify multi-type beta cell monogenetic diabetes (beta-cell-MgD) in Chinese early-onset type 2 diabetes (EOD) population. Methods A prediction model for beta-cell-MgD was established by logistic regression analysis in Cohort 1 (92 beta-cell-MgD, 512 EOD). Model performance was evaluated by receiver operating characteristic curves (ROC) and validated in an independent case-control sample (Cohort 2, 35 beta-cell-MgD, 50 EOD) and a newly diagnosed drug-naive EOD cohort (Cohort 3, 7 beta-cell-MgD, 176 EOD). PRS was constructed based on Genome-wide genotyping data from participants in Cohort 3. The ability of PRS to identify beta-cell-MgD was tested by ROC. Results The TyG-MgD score based on age at diagnosis, BMI and TyG presented a good performance to distinguish beta-cell-MgD (AUC=0.769), and achieving AUCs of 0.966 and 0.754 respectively in validation cohorts. At the optimal cutoff point -16.19, the model achieved a sensitivity of 66.3% and a specificity of 75.39%, allowing one case of beta-cell-MgD identified among every three patients. -16.85 could be used as the screening threshold prioritizing 80% sensitivity (with 59% specificity). Models combining TyG-MgD with East Asian PRS and beta-cell dysfunction-high proinsulin partitioned polygenetic score showed AUCs of 0.842 and 0.834 respectively for indentifying beta-cell-MgD. Conclusion We developed a clinical prediction model as a simple screening tool for multi-type beta-cell-MgD, identifying who are most likely to benefit from next genetic sequencing in Chinese population. PRS might be helpful for further screening of MgD.

AIMS:Diabetes is a major contributor to premature mortality, but whether declining mortality trends in the general population have been matched among people with diabetes remains uncertain in China. METHODS:Retrospective cohort study based on hospitalisation records from 207 public general hospitals in Beijing (excluding community-level primary care facilities and speciality hospitals), serving the city's 21.8 million registered residents, 2012-2024. Temporal trends by Joinpoint regression, and life expectancy using abridged life tables. RESULTS:Among 452,186 in-hospital deaths, 146,282 (32.3%) had diabetes. In-hospital mortality was 32.0 per 1000 admissions in patients with diabetes and 13.4 in those without diabetes. During 2012-2019, among adults ≥75 years, mortality declined in patients without diabetes (AAPC, -1.2%; p = 0.026) but remained stable in those with diabetes (AAPC, 0.9%; p = 0.082); among adults <75 years, declines were smaller in patients with diabetes (-2.4% vs. -4.0%). Life expectancy-estimated from hospitalisation records as a comparative measure of survival among admitted patients-was 5.0 years lower in patients with diabetes than in those without diabetes. Loss was greater with earlier diagnosis; diagnosis at ages 20-24 years was associated with a 4.8-year reduction. Loss was larger in women than in men (5.8 vs. 2.4 years). CONCLUSIONS:Diabetes was associated with substantially higher in-hospital mortality and smaller mortality improvements. Earlier diagnosis was linked to greater life expectancy loss, with disproportionate losses among women.

Introduction and Objective: People with diabetes experienced increased mortality during the COVID-19 pandemic, but long-term population-based evidence across epidemic phases and following public health interventions is limited. We assessed temporal changes in in-hospital case fatality among patients with diabetes before, during, and after the COVID-19 pandemic and compared outcomes with non-diabetic patients. Methods: Using the Beijing Municipal Health Big Data & Policy Research Center registry, we conducted a retrospective population-based analysis of in-hospital deaths among approximately 14.35 million permanent residents from 2012 to 2024. Diabetes was identified using ICD-10 codes. Study periods were defined as pre-pandemic (2012-2019), pandemic (2019-2022), and post-intervention (2022-2024). Analyses were stratified by age (5-year intervals) and sex. Temporal trends in in-hospital case fatality were evaluated using average annual percent change (AAPC). Results: From 2012 to 2019, in-hospital case fatality remained stable. During the COVID-19 pandemic, case fatality increased markedly across all age groups, with the largest increase observed in patients aged ≥65 years. Male patients consistently had higher case fatality than females. After public health policy interventions, in-hospital case fatality declined substantially. During the pandemic period, patients with diabetes had significantly higher case fatality than those without diabetes, with the absolute difference widening progressively with age; this pattern was consistent in both sexes. Conclusion: The COVID-19 pandemic disproportionately increased in-hospital mortality among patients with diabetes, while this excess risk declined substantially following public health interventions. Older patients with diabetes represent a key vulnerable population contributing to pandemic-related hospital mortality and should be prioritized for targeted protection during future public health emergencies. Disclosure M. Li: None. M. Zhao: None. Q. Li: None. J. Yang: None. Funding National Natural Science Foundation of China (82341076)

Introduction and Objective: Cathepsin L (CTSL) is a lysosomal cysteine protease that promotes tubular inflammation, extracellular matrix remodeling, and renal fibrosis in diabetic kidney disease (DKD). Although CTSL is a validated therapeutic target, the lack of clinically actionable inhibitors remains a major translational barrier. This study aimed to establish a deep learning-enabled discovery framework to identify CTSL inhibitors from natural products and evaluate their therapeutic potential in DKD-relevant models. Methods: An integrated pipeline combining deep learning-based activity prediction, structure-informed molecular docking, and multidimensional ranking was used to prioritize CTSL inhibitor candidates from a curated natural product library. Two hundred compounds were selected for experimental validation. CTSL enzymatic inhibition was assessed in vitro, followed by cytotoxicity screening in human renal tubular HK-2 cells. Lead compounds were evaluated in metabolically stressed DKD cellular models. Enzyme kinetic analyses and molecular dynamics simulations were performed to characterize inhibition mechanisms and target engagement. Results: Nine compounds showed reproducible, concentration-dependent CTSL inhibition. Kuwanon G, Iberverin, and Wighteone achieved greater than 50% inhibition at non-cytotoxic concentrations. Kuwanon G emerged as the lead compound, significantly reducing inflammatory signaling and fibrotic marker expression under high-glucose and high-lipid conditions. Kinetic analyses identified Kuwanon G as a competitive CTSL inhibitor, while molecular dynamics simulations demonstrated stable binding within the catalytic pocket. Conclusion: Deep learning-enabled drug discovery effectively accelerates CTSL inhibitor identification and overcomes key translational barriers in DKD. Kuwanon G represents a promising CTSL-targeted therapeutic candidate for further development. Disclosure F. Ma: None. S. Zhou: None. Q. Li: None. Z. Jingyi: None. F. Shen: None. J. Yang: None. Funding National Natural Science Foundation of China (Award No. 81930019), the Scientific Project of Beijing’s Municipal Science & Technology Commission (Award No. D171100002817005), the Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support Programme (Award No. ZYLX201823), the Training Fund for Open Projects at Clinical Institutes and Departments of Capital Medical University (Award No. CCMU2024ZKYXY005).

Quinolines and artemisinins are the two most important antimalarial drugs worldwide. In addition to antimalarial effects, quinine has been extensively documented to directly stimulate insulin secretion, potentially causing hypoglycemia in malaria patients undergoing treatment through the inhibition of KATP channels, and artemisinins have been recently identified as small molecules that increase insulin secretion by functionally promoting the conversion of pancreatic α cells into β cells, which is promising for the therapy of diabetes. Here, to detect the precise function of these drugs in insulin secretion, glucose-stimulated insulin secretion (GSIS) test with isolated mouse islets and insulin secretion experiment in mice were performed. Quinine was the most potent insulin secretagogue of all three quinoline drugs tested in this study. Low-dose quinine potentiated insulin secretion in a high glucose-dependent manner through KCNH6 current inhibition rather than through classical KATP inhibition. However, artemisinins did not promote insulin secretion in vitro or in vivo. In particular, artemether significantly suppressed insulin secretion, decreased Ca2+ influx and the expression levels of β-cell marker genes, contradicting the findings of previous studies suggesting that artemisinins promote the transformation of pancreatic α cells into β cells. Overall, our observations revealed the differential effects of two widely used antimalarial drugs, quinolines and artemisinins, on insulin secretion. Ascertaining the targets by which drugs affect insulin secretion may advance diabetes treatment.

OBJECTIVE:To assess the effect of dapagliflozin plus calorie restriction on remission of type 2 diabetes. DESIGN:Multicentre, double blind, randomised, placebo controlled trial. SETTING:16 centres in mainland China from 12 June 2020 to 31 January 2023. PARTICIPANTS:328 patients with type 2 diabetes aged 20-70 years, with body mass index >25 and diabetes duration of <6 years. INTERVENTIONS:Calorie restriction with dapagliflozin 10 mg/day or placebo. MAIN OUTCOME MEASURES:Primary outcome: incidence of diabetes remission (defined as glycated haemoglobin <6.5% and fasting plasma glucose <126 mg/dL in the absence of all antidiabetic drugs for at least 2 months); secondary outcomes: changes in body weight, waist circumference, body fat, blood pressure, glucose homoeostasis parameters, and serum lipids over 12 months. RESULTS:Remission of diabetes was achieved in 44% (73/165) of patients in the dapagliflozin group and 28% (46/163) of patients in the placebo group (risk ratio 1.56, 95% confidence interval (CI) 1.17 to 2.09; P=0.002) over 12 months, meeting the predefined primary endpoint. Changes in body weight (difference -1.3 (95% CI -1.9 to -0.7) kg) and homoeostasis model assessment of insulin resistance (difference -0.8, -1.1 to -0.4) were significantly greater in the dapagliflozin group than in the placebo group. Likewise, body fat, systolic blood pressure, and metabolic risk factors were significantly more improved in the dapagliflozin group than in the placebo group. In addition, no significant differences were seen between the two groups in the occurrence of adverse events. CONCLUSION:The regimen of dapagliflozin plus regular calorie restriction achieved a much higher rate of remission of diabetes compared with calorie restriction alone in overweight or obese patients with type 2 diabetes. TRIAL REGISTRATION:ClinicalTrials.gov NCT04004793.

Introduction and Objective: Quinoline drugs were used to treat malaria from as early as 17th century. However, aside from their potent anti-malarial effects, hypoglycemia was associated with the use of quinine during the treatment for malaria, which was attributed to the drug directly evoking insulin secretion through KATP channel inhibition. In this study, we aim to compare the effects of three quinoline drugs (quinine, quinidine and chloroquine) on insulin secretion and to investigate whether quinolines target KCNH6, a repolorizing Kv channel, to affect insulin secretion. Methods: we performed GSIS test with isolated mice islets and IPIRT/IPGTT test in mice. Ca2+ imaging was applied to detect the Ca2+ influx in dispersed mouse pancreatic β cells. we evaluated the inhibitory effect of drugs on KCNH6 channels by using patch clamp technique. Results: GSIS tests showed that quinine can directly evoke insulin secretion without glucose stimuli, but we did not observe chloroquine and quinidine inducing insulin secretion in low-glucose condition. In addition, all three quinolines inhibit KCNH6 channels at low micromolar concentrations, but only low-dose quinine potentiated insulin secretion in a high glucose-dependent way during GSIS test. Low-dose chloroquine even decreased Ca2+ influx and insulin secretion when compared with control. In vivo experiments showed that low-dose quinine improved glucose tolerance and increased glucose-induced insulin release in wild-type control mice but not in Kcnh6-β-cell-specific knockout (βKO) mice. Conclusion: Our observation identified quinine as the most potent insulin secretagogue among three quinoline drugs and proved that KCNH6 plays a critical role in quinine-potentiated insulin secretion. F. Xiong: None. J. Lu: None. J. Yang: None. National Natural Science Foundation of China (81930019) to Jin-Kui Yang; National Natural Science Foundation of China (8247090082070890) to Jing Lu; Beijing Natural Science Foundation (7232230) to Jing Lu.

Rare diseases, though individually uncommon, collectively affect a significant portion of the population. However, their epidemiology in China remains underexplored. A population-based rare disease registry comprising 14.31 million individuals was conducted between 2012 and 2023 by the Beijing Municipal Health Big Data and Policy Research Center. Rare disease cases were identified via ICD-10 codes mapped to China's national rare disease lists (2018 and 2023) and international databases. Age-standardized incidence rates (ASIR) were calculated per 100,000 person-years with 95% confidence intervals. Our analysis identified 12,371 rare disease cases, with the overall ASIR increasing from 6.109 in 2012 to 7.394 in 2023. Rare neurologic diseases accounted for 52.12% of cases, followed by systemic and rheumatologic diseases (16.89%) and rare neoplastic diseases (9.99%). The most frequently diagnosed rare diseases included generalized myasthenia gravis, ANCA-associated vasculitis, and malignant melanoma. Significant sex-based differences were observed, with female patients more affected by systemic and rheumatologic conditions, while male patients showed a higher incidence of respiratory disorders. Pediatric patients predominantly presented with inborn errors of metabolism and rare immune diseases. Comparisons with global data revealed notable disparities, such as a higher prevalence of Wilson's disease and a lower incidence of amyotrophic lateral sclerosis (ALS) in China. This study represents the first large-scale, population-based analysis of rare diseases in China, revealing distinct epidemiological patterns. These findings underscore the critical need for healthcare policies that address the unique challenges posed by rare diseases in China.

Mitochondrial glucose metabolism is critical for glucose-stimulated insulin secretion and glucose homeostasis in pancreatic β cells. We previously showed that KCNH6, a voltage-dependent potassium (Kv) channel, participated regulation of insulin secretion in pancreatic β cells, however, its role in mitochondrial metabolism remains unclear. Since we recently found that KCNH6 distributed in mitochondria, in this study, we investigated the role of KCNH6 in regulating mitochondrial function in pancreatic β cells by using a β cell-specific knockout (KCNH6-βKO) mouse model. Proteomics analysis of islets indicated that multiple proteins involved in mitochondrial metabolism were dysregulated in islets of KCNH6-βKO mice. Additionally, KCNH6-deficient β cells exhibited damaged mitochondria morphology and oxidative respiration dysfunction, which manifested as decreased glucose-induced ATP production, elevated NADH/NAD+ ratio and ROS levels. Impaired mitochondrial metabolism in βKO islets were significantly alleviated after the re-expression of KCNH6. Mechanistically, a physical interaction between KCNH6 and complex I assembly subunit Ndufa13 was detected, providing direct evidence of KCNH6's ability to regulate mitochondrial function. These results suggested that KCNH6 could be a promising therapeutic target for improving energy metabolism in β cells.

Ganoderma mushrooms are popularly used as dietary supplements to promote health around the world. However, their potential applications for the prevention and treatment of obesity needs to be further investigated. In this study, we isolated a novel triterpenoid from Ganoderma resinaceum, Resinacein S (Res S), and determined its absolute configuration. We reported that Res S treatment significantly inhibited the high-fat HF diet-induced body weight gain though increased thermogenesis and energy metabolism. Specifically, treatment with Res S promoted brown adipose tissue activation and browning of inguinal white adipose tissue, improving whole-body glucose and lipid homeostasis. Mechanistically, Res S treatment induced the expression of thermogenic genes and related protein, for example, uncoupling protein 1 and mitochondrial biogenesis in a cell-autonomous manner by activating the AMPK-PGC1α signaling pathway. These findings identify Res S as a potential therapeutic alternative for obesity in the setting of its increasingly high prevalence. HIGHLIGHTS: Resinacein S (Res S) exhibited potent anti-obesity effects in high-fat diet-fed mice; Res S treatment significantly promoted brown adipose tissue activation and browning of inguinal white adipose tissue; Res S treatment stimulated UCP1 expression and enhanced mitochondrial function; Res S induced adipocyte thermogenic activity through activating the AMPK-PGC1α axis.

Dear Editor, Type 2 diabetes mellitus(T2DM)has been identified as a risk factor for increased severity in acute pancreatitis(AP)(Mikó et al,2018).However,to date,no studies have simultaneously included healthy individuals,T2DM patients,and AP pa-tients to investigate which diabetes-asso-ciated metabolites are linked to AP severity.

Inborn errors of metabolism (IEMs) are a major subgroup of rare diseases, comprising over 1000 genetic disorders that disrupt essential biochemical pathways. Globally, they cause an estimated 23,500 childhood deaths annually. Despite diagnostic advances indicating a cumulative incidence of ∼1 in 800 births, population-based data from China remain scarce. We conducted a population-based study of 14.31 million permanent residents in the Great Beijing Area (2012-2023) using the municipal disease registry. Rare diseases were identified using ICD-10 codes mapped to the 2018 and 2023 National Rare Disease Catalog, from which 13 classified as IEMs were included in this study. Age-standardized incidence rates (ASIRs) were calculated, and disease patterns were compared with international newborn screening (NBS) data. Of 12,371 rare disease diagnoses, 314 (2.5 %) were IEMs. The ASIR was 0.180 per 100,000 person-years (95 % CI: 0.031-0.565) in 2012 and remained stable at 0.159 (95 % CI: 0.023-0.532) in 2023. Early-onset cases (<1 year) comprised 41.7 %. The mean diagnostic age was 11.0 years, with a median of 1.0 year. Methylmalonic acidemia without homocystinuria (40.8 %), phenylketonuria (29.9 %), and Fabry disease (6.7 %) were most common; males accounted for 60.5 % of cases. Although the prevalence of certain IEMs was broadly consistent with global data, the markedly low ASIR suggests substantial underdiagnosis of IEMs in China. This first large-scale, population-based study of IEMs in China reveals underestimation of true disease burden. Expanding and standardizing NBS coverage, broadening genetic testing, implementing mandatory screening, and integrating long-term care into health systems are urgent policy priorities.