Hypoglycemia, a frequent complication of diabetes therapy, induces severe cognitive impairment; however, the underlying mechanisms remain elusive. We aimed to investigate the critical role of the cyclophilin A (CypA)-mediated CD147/nuclear factor-kappa B (NF-κB)/matrix metalloproteinase-9 (MMP-9) inflammatory pathway in hypoglycemia-induced cognitive dysfunction in diabetes and to evaluate the therapeutic potential of CypA inhibition. We employed in vivo diabetic mouse models subjected to hypoglycemia and in vitro human brain vascular pericyte cultures under GD. Quantitative proteomics (tandem mass tag), behavioral assessments (Morris Water Maze), biochemical analyses (western blotting and immunofluorescence), and functional assays (mitochondrial function, migration, and apoptosis) were used to elucidate pathological mechanisms. Cyclosporin A (CsA) was used as a pharmacological cyclophilin inhibitor, and orthogonal pharmacological controls (FK506 and NIM811) were included to assess specificity in vitro. Hypoglycemia induced mitochondrial stress and activated CypA/CD147/NF-κB/MMP-9 signaling, causing pericyte dysfunction, blood-brain barrier (BBB) leakage, neuronal damage, and cognitive deficits in diabetic mice. Pharmacological inhibition of CypA with CsA effectively attenuated these inflammatory signaling changes. CsA treatment ameliorated mitochondrial dysfunction by reducing calcium overload and restoring oxygen consumption rate, decreased pericyte migration and apoptosis, restored BBB integrity, protected neurons, and significantly reversed hypoglycemia-induced cognitive impairment. Proteomic analysis further implicated pericyte and BBB dysfunction in hypoglycemia-induced neural damage. Collectively, our findings identify the CypA-mediated CD147/NF-κB/MMP-9 inflammatory pathway as a key mechanism driving hypoglycemia-induced cognitive dysfunction in diabetes via pericyte injury and BBB disruption. These data support pharmacological cyclophilin/CypA inhibition as a promising strategy for neurovascular protection and cognitive improvement.

BackgroundThe non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) is a novel, reliable indicator of dyslipidemia. However, its association with cardiac outcomes in patients with type 2 diabetes mellitus (T2DM) following percutaneous coronary intervention (PCI) remains unclear. We investigated the association of the NHHR with the risks of major adverse cardiovascular events (MACEs) following PCI in adults with T2DM.MethodsThis retrospective cohort study included 1176 adults with T2DM undergoing PCI after new-onset acute myocardial infarction between January 1, 2019, and December 31, 2023. Patients were categorized into NHHR quartiles. The relationship between the NHHR and post-PCI MACE risk was investigated using univariate and multivariate Cox regression analyses. Restricted cubic splines and smooth curve fitting evaluated the nonlinear association between the NHHR and MACE risk; receiver operating characteristic (ROC) curves determined the prognostic significance of the NHHR.ResultsOver 21.0 ± 6.6 months, 246 MACEs occurred. In multivariate analysis, the NHHR was associated with MACE incidence, even after adjustments (vs. group Q1: hazard ratio [95% confidence interval] in groups Q3 and Q4, 4.00 [2.47–6.48] and 6.28 [3.92–10.05], respectively; both P < 0.05). The NHHR and MACEs were non-linearly related. Within the threshold of 3.12–5.10, every 1-unit rise in the NHHR elevated the MACE risk 1.4-fold. The area under the ROC curve of the NHHR combined with the Global Registry of Acute Coronary Events risk score was 0.84 for predicting post-PCI MACEs (sensitivity, 71.54%; specificity, 83.86%). The NHHR/MACE association persisted in subgroup analysis. No significant interactive effects were found for age, sex, hypertension, smoking, body mass index, glycated hemoglobin, and medications (P for interaction > 0.05).ConclusionsOur findings suggested a nonlinear positive association between NHHR and MACE risk in T2DM patients undergoing PCI. Routine NHHR assessment may facilitate early risk identification and tailored care for these patients.

BACKGROUND:Finerenone is a novel nonsteroidal mineralocorticoid receptor antagonist. However, robust evidence about its efficacy and safety in primary aldosteronism is scarce. METHODS:In this prospective, multicenter, single-arm, and exploratory trial, we enrolled adults (aged ≤75 years) with primary aldosteronism, an office blood pressure (BP) ranging from 140 to 180/90 to 120 mm Hg, and an estimated glomerular filtration rate ≥60 mL/min per 1.73 m². Eligible patients received finerenone (20-40 mg/d) treatment for 12 weeks. The primary outcome was the change in daytime systolic BP at 12 weeks. RESULTS:Fifty-seven patients were ultimately treated. Per-protocol analysis revealed that finerenone treatment significantly reduced mean daytime systolic BP (-6.69±1.60 mm Hg; P<0.001) and diastolic BP (-4.55±1.06 mm Hg; P<0.001) according to ambulatory monitoring. Mean office BP decreased even more substantially (systolic BP, -15.58±1.69 mm Hg; diastolic BP, -8.61±1.02 mm Hg; both P<0.001). The mean increase in serum potassium concentration was 0.39±0.05 mmol/L, and 94.5% of patients exhibited a normal concentration after 12 weeks of treatment (versus baseline 61.8%; P<0.001). Plasma renin activity increased, and 32.7% of patients exhibited a plasma renin activity concentration ≥1 ng/mL per h. According to the Primary Aldosteronism Medical Treatment Outcome criteria, 29.1% and 20.0% of patients achieved complete biochemical and clinical responses, respectively. Treatment was well tolerated. CONCLUSIONS:This study demonstrated the efficacy and safety of finerenone in the treatment of primary aldosteronism, supporting its use as a potential alternative therapy for the condition. Nevertheless, further prospective and head-to-head randomized controlled trials are essential to establish finerenone as a viable substitute for spironolactone. REGISTRATION:URL: https://www.clinicaltrials.gov; Unique identifier: NCT06381323.

Early radiation-induced lung injury remains a clinically relevant complication after thoracic radiotherapy. We compared pretreatment, posttreatment, delta radiomics, and combined models based on paired CT scans for early prediction of lung injury. This retrospective study included 82 patients with paired CT scans acquired before and after thoracic radiotherapy. The cohort was divided into a training set (n = 57) and an independent test set (n = 25). The endpoint was grade 1 or higher radiation-induced lung injury within 3 months after radiotherapy according to Common Terminology Criteria for Adverse Events Version 5.0 (CTCAE V5.0). Delta radiomics features were defined as posttreatment minus pretreatment values. Five signatures were constructed: clinical, pre, post, delta, and combined. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration analysis, DeLong testing, and decision curve analysis (DCA). Only nodal (N) classification remained significant in multivariable analysis (OR 1.189, 95

Patients with hypothyroidism admitted to the intensive care unit (ICU) frequently develop hypothyroidism-associated delirium (HAD), a condition strongly linked to adverse prognostic outcomes. The primary objective of this study was to develop a machine learning (ML) -based predictive model for the early identification of HAD. Patient data were retrieved from two non-overlapping datasets: Medical Information Mart for Intensive Care IV (MIMIC-IV) database and MIMIC-III database. Specifically, data from MIMIC-IV were split into a training set and an internal validation set, whereas MIMIC-III data served as an external validation set. Least Absolute Shrinkage and Selection Operator (LASSO) regression was utilized for feature variable selection, and predictive models were constructed using nine approaches. Model performance was assessed across discrimination, calibration, and clinical utility. SHAP (SHapley Additive exPlanations) was employed to visualize model characteristics and individual case predictions. A model with 13 variables was built. Among all constructed models, the Gradient Boosting Machine (GBM) model demonstrated the optimal performance and was therefore selected as the final model (internal validation area under the receiver operating characteristic curve (AUROC)=0.806; external validation AUROC=0.788). Notably, the GBM model outperformed other approaches in HAD prediction. Key predictors included Glasgow Coma Scale (GCS), Sequential Organ Failure Assessment (SOFA), Sedatives, ICU Length of Stay (ICU_Day), Peripheral Oxygen Saturation SPO2, Calcium, Red Cell Distribution Width (RDW), and Mean Arterial Pressure(MAP). A user-friendly interface was developed for clinical use. The establishment of this predictive model enables earlier HAD identification compared with traditional delirium assessment methods, and it is particularly applicable to patients for whom conventional delirium evaluation is challenging.

Severe hypoglycemia (SH) is associated with adverse cardiac outcomes in individuals with diabetes; however, the underlying mechanisms remain poorly understood. Our previous study demonstrated that the myocardium of diabetic mice, characterized by hyperglycemia and hyperlipidemia, exhibited greater susceptibility to SH than that of non-diabetic mice. This study aimed to investigate the effects of glucose deprivation on cardiomyocytes pretreated with high glucose and lipids. The results indicated that brief exposure to high glucose and lipid levels maintained cardiomyocyte viability and enhanced PTEN-induced kinase 1 (PINK1)/Parkin-related mitophagy. However, glucose deprivation following high glucose and lipid treatment significantly increased cardiomyocyte susceptibility to injury compared with glucose deprivation after high glucose treatment alone. This was evidenced by reduced cell viability, increased apoptosis, and mitochondrial dysfunction—characterized by disrupted mitochondrial structure, depolarization, decreased adenosine triphosphate production, and impaired PINK1/Parkin-related mitophagy in the cells. These adverse effects were reversed by treatment with the mitophagy activator urolithin A. Our findings suggest that glucose plays a critical role in maintaining lipid tolerance via mitophagy in cardiomyocytes, a mechanism that may contribute to the pathogenesis of SH-induced myocardial injury.

BackgroundThe gut microbiome is a critical regulator of host health, but how it mediates the therapeutic effects of drugs targeting neurodegenerative diseases like diabetic cognitive impairment (DCI) is unclear. Here, we investigated whether the neuroprotective effects of the GLP-1 agonist semaglutide (SE) are linked to its modulation of the gut-brain axis.MethodsWe used an integrative multi-omics approach in a mouse model of DCI. We combined fecal shotgun metagenomics and targeted bile acid profiling with cerebral proteomics and metabolomics to characterize the gut-brain crosstalk following a 12-week SE treatment. Animal behavior, neuronal survival and synaptic integrity were assessed to confirm therapeutic efficacy.ResultsSE treatment reversed cognitive deficits, rescued hippocampal neuronal loss, and restored synaptic integrity in diabetic mice. At the ecosystem level, metagenomics revealed that SE treatment profoundly remodeled the gut microbiota, enhancing microbial α-diversity, enriched beneficial genera (Bacteroides, Barnesiella), and depleted the pro-inflammatory genus Desulfovibrio. This microbial shift was associated with normalized fecal and cerebral bile acid profiles. Mechanistically, our analysis implicated a dysregulated sphingolipid pathway in the DCI brain, characterized by the upregulation of the transporter ATP-binding cassette transporter A2 (ABCA2) and the enzymes sphingosine-1-phosphate phosphatase 1 (SGPP1) and ceramide synthase 2 (CERS2). SE treatment dynamically modulated this pathway: it downregulated ABCA2 in a potentially weight-independent manner and SGPP1 in a weight-dependent fashion, linked to the normalization of cerebral bile acid profiles. In contrast, CERS2, a robust marker of disease severity, was not altered by SE.ConclusionOur study uncovers a novel “gut microbiota–bile acid–sphingolipid” axis in DCI and suggests that SE acts via a dual mechanism. It drives a weight-dependent restoration of the gut-brain axis, normalizing microbial and bile acid profiles to regulate SGPP1, while also exerting weight-independent effects, potentially through direct modulation of targets like ABCA2. This work highlights the gut microbiome as a key component in the therapeutic action of SE and reveals the multifaceted nature of its neuroprotective effects.

Antithyroid drug-induced agranulocytosis (ATDIA) is a life-threatening adverse drug reaction with strong population-specific genetic predispositions. This study aimed to develop a pharmacogenomic risk-stratification model and to evaluate the indicative screening efficiency of targeted pretherapeutic screening in the mainland Southern Han Chinese population. This retrospective case-control study enrolled 171 patients with Graves’ disease: 36 with ATDIA, 59 with antithyroid drug-induced neutropenia (ATDIN), and 76 ATD-tolerant controls. High-throughput genotyping of HLA-B, HLA-DRB1, and 32 candidate single nucleotide polymorphisms (SNPs) was performed. Genetic associations, predictive modeling with 1,000-resample bootstrap internal validation, and indicative economic impact estimations were evaluated. HLA-B*38:02 (OR = 48.667, 95

Lysosomes, as organelles with degradative, secretory and signaling functions in eukaryotic cells, play a pivotal role in maintaining cellular energy homeostasis and biological recycling processes. In recent years, lysosomal dysfunction has garnered extensive attention from scholars for its implications in neurodegenerative and autoimmune diseases. however, its role in the occurrence and progression of diabetes mellitus and its complications remains to be further explored. Therefore, this article summarizes the research progress on lysosomal dysfunction in diabetes and its complications, hoping to highlight a promising therapeutic direction.

BACKGROUND:Alzheimer's disease (AD) is a degenerative disease of the central nervous system characterized by progressive memory decline. The increasing prevalence of AD has attracted considerable attention globally. The glucagon-like peptide-1 analog, liraglutide, a drug widely used in the treatment of type 2 diabetes, has shown promising neuroprotective effects in AD, including enhancing neuronal survival, reducing amyloid beta protein accumulation, improving synaptic plasticity, and reducing tau protein hyperphosphorylation. However, its potential impact on cognitive function remains unclear. METHODS:We evaluated the effects of liraglutide (25 nmol/day for 8 weeks) on the cognitive ability of 12-month-old 5 × familial AD (FAD) mice. The Morris water maze test was used to evaluate the spatial learning ability of mice. Histological evaluations were performed by Nissl staining and transmission electron microscopy. Neuroinflammation was detected by double immunofluorescence staining and enzyme-linked immunosorbent assay. Protein expression in the cortex and hippocampus was detected by immunohistochemistry and Western blotting. RESULTS:The spatial cognitive ability improved in 5 × FAD mice after liraglutide administration and was associated with an increased number of pyramidal cells in the cortex and hippocampus. Liraglutide also alleviated ultrastructural changes in the chemical synapses and reduced both local and systemic inflammation in AD mice. Furthermore, liraglutide reduced amyloid β protein expression, which may be associated with the regulation of nuclear factor kappa B/beta-secretase 1 pathways in AD mice. CONCLUSIONS:The potential of liraglutide to improve cognitive function in AD mice offers an effective pharmacological approach for treating neurodegenerative diseases.

ObjectiveTo address the overestimation of levothyroxine (L-T4) doses in conventional weight-based regimens for individuals who are overweight and obese, this study aimed to identify the most predictive body weight metrics and establish an optimized dosing model for accurate thyroid-stimulating hormone (TSH) suppression following total thyroidectomy in differentiated thyroid carcinoma (DTC).MethodsThis retrospective study included 385 patients with DTC treated at our institution between October 2019 and December 2024. Patients were stratified by TSH targets (A1: <0.1 mIU/L; A2: 0.1–0.5 mIU/L; A3: 0.5–2.0 mIU/L) and body mass index (BMI) according to Chinese criteria (normal: <24 kg/m²; overweight: 24–27.9 kg/m²; obesity: ≥28 kg/m²). Linear regression analysis was used to analyze correlations between the final stable L-T4 dose and weight metrics, including total body weight, adjusted body weight, lean body weight, ideal body weight, and body surface area, followed by model validation. Model performance was internally validated using a hold-out method. Efficacy was estimated as the accuracy of the model-predicted dose compared with the actual dose required when a patient first achieved their TSH target within the first postoperative year.ResultsThe baseline characteristics showed no significant intergroup differences (P>0.05). Postoperative TSH levels varied significantly according to BMI (P<0.05). Patients with higher BMI required higher total L-T4 doses (µg/d) (P<0.001) but lower weight-adjusted doses (µg/kg/d) (P<0.001). Adjusted body weight best predicted L-T4 dose for patients with BMI ≤ 23.9 kg/m2, while lean body weight was optimal for those with BMI≥24.0 kg/m2. The new model achieved a significantly higher rate of accurate initial dose prediction compared with that via empirical dosing (68.0% vs. 30.2%, P<0.001).ConclusionThe BMI-stratified L-T4 dosing formula based on optimized body weight metrics demonstrated improved accuracy, expediting TSH suppression and reducing adverse events.

Recurrent non-severe hypoglycemia (RH) in diabetes is an independent risk factor for cognitive dysfunction. However, the mechanisms and potential therapeutic strategies remain poorly understood. In this study, we aimed to elucidate the mechanisms underlying RH-induced diabetic cognitive impairment. We investigated the effects of RH on lactate metabolism and cognitive function in male C57BL/6 J diabetic mice. After RH, diabetic mice showed decreased brain lactate and adenosine triphosphate levels, decreased expression of lactate transporter proteins MCT1 and MCT4, increased neuroapoptosis, and decreased astrocyte glycolysis in vitro. This was accompanied by increased neuronal mitochondrial reactive oxygen species levels, decreased mitochondrial COX IV activity, impaired mitochondrial morphology and function, impaired synaptic morphology, and decreased expression of synaptic plasticity proteins. Intraperitoneal lactic acid injection improved lactate transport restored neuronal mitochondrial morphology and function, upregulated synaptic plasticity proteins brain-derived neurotrophic factor and early growth response 1, enhanced synaptic ultrastructure, and ultimately improved cognitive dysfunction following RH in diabetic mice. These findings provide insights into the prevention and treatment of cognitive dysfunction in patients with diabetes mellitus caused by RH.

To analyze data from non-intensive care unit (non-ICU) inpatients with diabetes to predict the risk of hypoglycemia using electronic health records (EHRs) and point-of-care (POC) blood glucose values. Patient demographics, laboratory results, POC blood glucose, and procedures were performed during the hospital stays on Days 0–2 to predict hypoglycemic episodes (blood glucose ≤ 3.9 mmol/L) on Days 3–6. The dataset was randomly split into a training set and an independent verification set at a 7:3 ratio. Logistic Regression (LR) and Artificial Neural Network (ANN) were compared using the area under the curve (AUC). A nomogram plot was also constructed to display the predicted hypoglycemia probabilities. Data from 16,593 diabetic patients (January 2017 to June 2022) were analyzed. Predictive factors from the LR model included the use of insulin; previous hypoglycemia in Days 0–2; respiratory rate; blood urea nitrogen; potassium; D-dimer levels; coefficient variation of blood glucose (BG CV) > 31

AIMS:To evaluate the cost-effectiveness of liraglutide, semaglutide, tirzepatide, benaglutide, and lifestyle management for the treatment of obesity from the perspective of the Chinese healthcare system. MATERIALS AND METHODS:This study gathered clinical trial data from literature reviews of each treatment strategy for patients with obesity without diabetes, and efficacy data were synthesized using network meta-analysis. The data were subsequently incorporated into an constructed Markov model to simulate the lifetime treatment trajectory of patients, with a cycle length of one year. The model integrated epidemiological data from China, clinical efficacy, treatment costs, and utilities, calculating the total treatment costs and quality-adjusted life years, followed by incremental cost-effectiveness analysis. The willingness-to-pay (WTP) threshold was set at three times the per capita gross domestic product (GDP), amounting to $37 067.75. Sensitivity analysis and scenario analysis were performed. RESULTS:The incremental cost-effectiveness ratios compared to lifestyle management for benaglutide, liraglutide, semaglutide, tirzepatide (10 mg), and tirzepatide (15 mg) were $227 355.26, $47 994.81, $42 818.20, $72 380.49, and $89 147.19. The base-case results indicated that, under the WTP threshold, none of the four glucagon-like peptide-1 receptor agonist (GLP-1RA) or glucose-dependent insulinotropic polypeptide (GIP)/GLP-1RA therapies were cost-effective compared with lifestyle management. In the probabilistic sensitivity analysis, under the WTP threshold, lifestyle management was the most likely to be cost-effective. Scenario analysis showed that, in the severe obesity patient population and in first-tier cities in China, semaglutide is the most cost-effective treatment option. CONCLUSIONS:GLP-1 RA or GIP/GLP-1RA are not cost-effective for obesity treatment in China currently. Nevertheless, semaglutide exhibits relatively favourable economic potential across multiple subgroups.

Type 2 diabetes mellitus (T2DM) is a global health challenge, necessitating innovative antidiabetic treatments. Levels of plasminogen activator inhibitor-1 (PAI-1) are elevated in patients with T2DM and may be an important but underappreciated risk factor for diabetes. However, its relationship with T2DM remains unclear. To this end, we developed a potent and highly specific PAI-1 inhibitor named PAItrap3. We aimed to elucidate the metabolic effects of PAItrap3 using a preclinical db/db mouse model. PAItrap3 was administered to mice intravenously, followed by an assessment of biochemical markers, histopathological examination of the liver and pancreas, and evaluation of the expression of hepatic proteins integral to insulin signaling. PAItrap3 demonstrated potent efficacy in alleviating hyperglycemia and enhancing glycemic control. This therapeutic action was supported by its ability to enhance β-cell function, consequently mitigating β-cell apoptosis and preserving their integrity. Furthermore, PAItrap3 alleviated hepatic insulin resistance through the regulation of lipid and glucose metabolism, thereby maintaining the delicate homeostasis of systemic lipid and glucose metabolism. These findings suggest that PAItrap3 is a promising therapeutic candidate for T2DM. The multifaceted benefits of PAItrap3 highlight its potential to vastly improve the effectiveness and specificity of T2DM treatment paradigms.

Delirium is a frequent complication in critically ill patients and is associated with adverse outcomes such as long-term cognitive impairment and increased mortality. The relationship between the dynamic changes in blood glucose and the onset of acute delirium remains unclear. This study aims to explore the effect of 24-h blood glucose trajectory on acute delirium in patients via latent category trajectory modeling, and additionally investigate its association with in-hospital mortality in this population. This retrospective cohort study examined patients in the intensive care unit (ICU) using the MIMIC-IV database. Changes in the trajectories of blood glucose within 24 h after admission to the ICU were categorized using latent category trajectory modeling. The outcome examined was the occurrence of acute delirium during ICU hospitalization, with the secondary outcome being in-hospital mortality. The study included 21,940 critically ill patients, of which 2,633 developed acute delirium during ICU hospitalization. The blood glucose trajectories within 24 h were classified into four categories using the LCMM model. After fully adjusting for various confounders, Classes 4 and 2 were associated with a higher risk of acute delirium compared with Class 1, and the respective ORs (95% CIs) were 1.34 (1.08-1.64) and 1.18 (1.04-1.35). For the secondary outcome, a similar trend was observed between Class and in-hospital mortality: OR (95% CI) was 1.62 (1.29-2.02) for Class 4 and 1.45 (1.25-1.67) for Class 2. The 24-h blood glucose trajectory is significantly associated with both the risk of acute delirium and in-hospital mortality in critically ill patients. Focusing on levels of blood glucose trajectory may be beneficial to assess the potential risk of acute delirium and in-hospital mortality.

Hyperthyroidism, a multifaceted endocrine disorder, is strongly associated with specific human leukocyte antigen (HLA) alleles, which also play a critical role in drug-induced complications such as agranulocytosis. Conventional HLA genotyping methods often face limitations in simultaneously achieving high accuracy, rapidity, and operational simplicity. To address these challenges, we developed a multimodal biosensing platform for the highly sensitive detection of alleles. This platform synergistically integrates three modalities. After molecular recognition, Electrochemiluminescence resonance energy transfer (ECL-RET) was employed using nanomaterials to generate ECL signals, Hybridization chain reaction (HCR) was incorporated to produce fluorescence signals, while nanozyme-mediated colorimetric reactions were coupled to generate visual signals. The combination of these strategies ensures exceptional sensitivity, specificity, and assay stability. Furthermore, spatial separation of the recognition and signal generation domains was implemented to minimize matrix interference from complex biological samples, significantly enhancing clinical applicability. This innovative approach establishes a novel paradigm for the precise analysis of HLA alleles, offering transformative potential for clinical diagnostics and advancing the frontiers of biosensing technologies.

This study aimed to investigate the effects of PAItrap3, a novel PAI-1 inhibitor, on lipid metabolism, and autophagy pathways in diabetic mice. db/db diabetic mice were administered PAItrap3 (5.7 mg/kg/day, IV) for 21 consecutive days, and its impact on metabolic, gene expression, and lipidomic profiles was assessed. Western blot analysis was performed to examine lipid metabolism-related proteins in white adipose tissue (FASN, HSL, CPT1A, ACADM) and autophagy markers (LC3B, P62, Parkin, PGC1α, PPARGC1B). Additionally, RNA-seq and targeted lipidomics were employed to analyze gene expression and lipid metabolic alterations. PAItrap3 significantly reduced blood glucose and glycated hemoglobin levels while improving insulin sensitivity. In lipid metabolism, FASN and HSL levels were upregulated, whereas CPT1A and ACADM levels were downregulated in the DMP group. Regarding the autophagy pathway, PPARGC1B, LC3B, and PGC1α expression levels were increased, while P62 and Parkin levels were decreased. Lipidomics analysis revealed that triglycerides (TG) and diacylglycerols (DG) were generally downregulated, with TG (18:2/18:2/18:2) (0.96 [0.8491, 1]), LPI (18:0) (0.96 [0.8491, 1]), and MLCL (14:3/20:4/22:6) (0.96 [0.8491, 1]) identified as key metabolites. This study finds that PAItrap3 modulates lipid metabolism, energy homeostasis, and autophagy pathways, thereby improving metabolic dysfunction in diabetic mice. These findings highlight its potential therapeutic value for treating diabetes-associated lipid metabolic disorders.

Background: Thyroid eye disease (TED) is a debilitating autoimmune disorder linked to thyroid dysfunction. There is limited knowledge of TED in Asian populations. This multicenter study characterizes the clinical features and treatment response of TED in a large Chinese cohort. Methods: A retrospective multicenter study included 4157 patients with TED from nine Chinese hospitals from February 2016 to July 2023. Disease severity and activity were evaluated according to the European Group on Graves' Orbitopathy standards. We examined associations of variables including sex, age, smoking status, I131 treatment, consultation department, and geographical region with clinical outcomes. Logistic regression and nomogram models were developed to examine associations with sight-threatening TED and, in a subgroup analysis (n = 126), patients' responsiveness to intravenous glucocorticoid (IVGC) therapy. Results: We included 4157 patients with mean age and standard deviation (SD) 45.96 ± 16.44 years. Of these, 63.6% (n = 2644) were females. Over half (55.6%, n = 2310) of participants were in the inactive phase, with a mean clinical activity score of 2.19 ± 1.61 (SD) for all patients. TED severity was categorized as mild (9.3%, n = 385), moderate-to-severe (82.5%, n = 3428), and sight-threatening (8.2%, n = 344). The average degree of exophthalmos was 20.04 ± 5.27 mm, and 48.8% (n = 2029) of patients had diplopia. Patients treated with I131 had higher disease activity (47.5%, n = 468, vs. 43.5%, n = 1379, p < 0.05). Coastal region patients exhibited more severe TED (sight-threatening cases: 10.1%, n = 195, vs. 7.2%, n = 147) and higher diplopia scores (1.00 ± 1.10 vs. 0.86 ± 1.09, p < 0.001) than inland counterparts. TED severity was also greater in patients treated in Ophthalmology departments (mild cases: 6.0%, n = 213; moderate-to-severe cases: 85.6%, n = 3055) compared with Endocrinology departments (mild cases: 29.3%, n = 172; moderate-to-severe cases: 63.5%, n = 373). Nomograms had an area under the receiver operating curve of 0.742 (confidence interval [CI] 0.716-0.768) for sight-threatening TED and 0.759 (CI 0.674-0.843) for IVGC therapy responsiveness. Conclusions: We characterized the clinical features and treatment response of TED in a large Chinese cohort. These findings offer valuable insights informing TED risk stratification in Asian patients and forming a foundation for future prospective studies.