BACKGROUND:Polyendocrine metabolic ovarian syndrome (PMOS), previously named polycystic ovary syndrome (PCOS), is the most common endocrine disorder among women of reproductive age and a leading cause of anovulatory infertility. However, the evolving global burden of PMOS and the role of adiposity, particularly regional fat distribution, remain incompletely understood. We integrated global epidemiological analysis, genetic causal inference, and clinical prediction modeling to investigate the burden and adiposity-related determinants of PMOS. METHODS:Using the Global Burden of Disease (GBD) 2021 database, we assessed age-specific and socio-demographic index (SDI)-specific patterns of PMOS burden. Two-sample Mendelian randomization (MR) was performed to examine genetic evidence linking overall and regional adiposity traits to PMOS and anovulation-associated infertility. Machine-learning (ML) models were subsequently developed and internally validated in a clinical cohort with detailed body-composition measurements, and SHapley Additive exPlanations (SHAP) were applied to interpret model predictions. RESULTS:In 2021, PMOS affected approximately 69.5 million women globally, with an age-standardized prevalence rate of 1,757.8 per 100,000. The highest modeled incidence occurred in the 10-14-year age group, and approximately 12.5 million infertility cases were attributable to PMOS worldwide. MR analyses provided genetic evidence supporting adiposity as a risk factor for PMOS, including body mass index (OR = 2.60, 95% CI 1.84-3.66), body fat percentage (OR = 3.32, 95% CI 1.97-5.58), trunk fat mass (OR = 2.54, 95% CI 1.79-3.60), and left-leg fat mass (OR = 3.44, 95% CI 2.19-5.40), whereas fat-free mass showed no significant association. In ML analyses, XGBoost achieved the best predictive performance in the testing set (AUC = 0.701), and SHAP identified left-leg fat mass, trunk fat mass, percent body fat, and protein mass as the most influential predictors. CONCLUSIONS:Adiposity, particularly regional fat distribution, appears to be a clinically relevant determinant of PMOS. The convergence of global epidemiological patterns, genetic evidence, and clinical prediction supports the importance of body-composition phenotypes beyond conventional obesity measures in understanding PMOS risk.

BackgroundLiver fibrosis is an important predictor of mortality in patients with type 2 diabetes mellitus (T2DM). Current clinical practice relies on total 25-hydroxyvitamin D, which does not distinguish between its two main circulating isoforms, 25(OH)D2 and 25(OH)D3, although these metabolites may differ in their associations with liver fibrosis and long-term prognosis.MethodsWe analyzed two independent T2DM cohorts: hospitalized Chinese patients with T2DM (n = 1,978) and US adults with T2DM from the National Health and Nutrition Examination Survey (NHANES) 2007–2018 (n = 4,616). Serum 25(OH)D2 and 25(OH)D3 were quantified by liquid chromatography–tandem mass spectrometry (LC–MS/MS). Isoform-specific associations with advanced fibrosis, defined by the NAFLD Fibrosis Score (NFS) and Fibrosis-4 index (FIB-4), were examined using multivariable logistic regression and restricted cubic spline (RCS) analyses. In NHANES, multivariable Cox proportional-hazards models were used to evaluate all-cause, cardiovascular, and diabetes-related mortality according to vitamin D status.ResultsIn both cohorts, lower serum 25(OH)D3 was non-linearly associated with a higher risk of advanced liver fibrosis. By contrast, 25(OH)D2 showed no protective association; in NHANES, the highest tertile was associated with a higher risk of NFS-defined fibrosis (OR = 1.41, P = 0.003). RCS analyses suggested cohort-specific apparent inflection regions for 25(OH)D3 at 11.88 ng/mL in the Chinese cohort and 23.86 ng/mL in NHANES; these exploratory estimates were not intended as clinical cut-offs. In longitudinal NHANES analyses, lower 25(OH)D3 was associated with higher cause-specific mortality among participants with advanced fibrosis; however, estimates within the FIB-4 high-risk stratum were based on sparse events and were therefore regarded as exploratory and interpreted with caution. Bioinformatic analysis implicated the AGE–RAGE and PI3K–Akt signaling pathways as candidate mechanisms.ConclusionLower serum 25(OH)D3, but not 25(OH)D2, was associated with advanced liver fibrosis in T2DM after multivariable adjustment. Among participants with advanced fibrosis, lower 25(OH)D3 was also associated with higher cardiovascular mortality, although cause-specific estimates based on sparse events were exploratory. These findings may support further investigation of isoform-specific 25(OH)D3 assessment for risk stratification in this population.

Type 1 diabetes mellitus (T1DM) results from autoimmune-mediated destruction of pancreatic β-cells, leading to absolute insulin deficiency. Current treatments rely on insulin replacement and do not prevent β-cell loss. 4-Methylumbelliferone (4-MU), an inhibitor of hyaluronan synthesis, has shown anti-inflammatory and cytoprotective effects, but its therapeutic potential and mechanisms in T1DM remain unclear. A streptozotocin (STZ)-induced mouse model of T1DM was treated with 4-MU for three weeks. Blood glucose levels and glucose tolerance were evaluated. Pancreatic islet morphology and cell composition were assessed by immunofluorescence. In parallel, STZ -injured MIN6 and βTC6 β-cells were used to investigate the effects of 4-MU on cell viability, oxidative stress, intracellular Ca²⁺ homeostasis, and glucose-stimulated insulin secretion. Network pharmacology, molecular docking, qPCR, and Western blot analyses were conducted to explore the underlying mechanisms. 4-MU significantly reduced hyperglycemia and improved glucose tolerance in T1DM mice, accompanied by preservation of β-cell mass, normalization of the β/α-cell ratio, and reduced islet inflammation. In vitro, 4-MU protected β-cells from STZ-induced injury by decreasing reactive oxygen species (ROS) accumulation, restoring intracellular Ca²⁺ balance, and improving insulin secretion. Network pharmacology identified 48 shared targets between 4-MU and T1DM, with KEGG pathway enrichment highlighting the PI3K/Akt signaling pathway. Molecular docking revealed stable binding of 4-MU to key regulators, including EGFR, Akt, ESR1, INSR, and IGF1R. Consistently, 4-MU enhanced the phosphorylation of EGFR, PI3K, and Akt in injured β-cells. 4-MU exerts protective effects in T1DM by preserving pancreatic β-cells survival and function, potentially through activation of the EGFR/PI3K/Akt signaling pathway.

Semaglutide-associated non-arteritic anterior ischaemic optic neuropathy (NAION) mechanisms are unclear. We report a 28-year-old man with type 2 diabetes who developed right NAION 4-5 months after starting semaglutide. Multimodal imaging confirmed NAION and bilateral buried optic disc drusen. The affected eye was short, whereas the fellow eye was highly myopic and longer. Serial bioimpedance showed a 1.9 L decline in total body water over 7 weeks, with preserved fat mass and stable extracellular-to-total-body-water (ECW/TBW) ratio. We propose a hypothesis-generating 'two-hit' model in which anatomical susceptibility and sustained hypohydration together precipitate NAION. Heightened clinical awareness may be warranted and prospective studies are required.

This perspective aims to propose a mechanomedicine framework integrating the body’s intrinsic “mechanical intelligence” (MI) with artificial intelligence (AI), offering new potential approaches for diagnosis and treatment of weight rebound. Weight rebound after weight loss remains a significant challenge in obesity management. Traditional explanations focus on hormonal and metabolic adaptations, but emerging evidence underscores the importance of mechanical cues in adipose tissue. Persistent fibrosis and extracellular matrix (ECM) stiffness after weight loss may create a mechanical memory that favors weight rebound. We explore the biomechanics of adipose tissue during weight fluctuations, highlight the potential role of mechanobiology, and examine how AI help enhance mechanodiagnostics and mechanotherapy. Both physiological and mechanical factors contribute to weight rebound after initial loss. The integration of MI (biomechanics and mechanobiology) in adipose tissue with AI-driven mechanodiagnostics and mechanotherapy may offer a novel perspective and promising future solutions to prevent weight rebound and transform obesity treatment.

Weight rebound remains the core challenge in the long-term management of obesity. Although current mechanistic understanding mainly focuses on physiological adaptations, the role of biomechanical factors remains largely unexplored. This study aims to investigate the contribution of lysyl oxidase (LOX)-mediated adipose tissue (AT) stiffening to the process of weight rebound. Our clinical analysis first established a correlation among obesity, elevated AT stiffness, and higher LOX levels. We then demonstrated that the weight rebound model mice displayed accelerated lipid accumulation and worsened metabolic functions. Importantly, AT stiffness dynamically increased during obesity, failed to normalize after weight loss due to persistent fibrosis, and reached its highest level during the regain stage. LOX expression followed an identical temporal pattern, showing a strong positive correlation with tissue stiffness. Mechanistically, mimicking a high-stiffness microenvironment in vitro promoted adipocyte differentiation and lipid accumulation in a LOX-dependent manner. Crucially, pharmacological inhibition of LOX in vivo significantly attenuated the rate of weight rebound. Our findings provide supportive evidence that LOX-mediated AT stiffening creates a pro-adipogenic mechanical microenvironment that contributes to accelerated weight rebound and metabolic deterioration, highlighting the LOX-stiffness axis as a potential therapeutic target for preventing weight rebound.

BACKGROUND:Growth hormone (GH) reduces visceral adiposity, increases lean body mass, and improves the lipid profile in obese adults. However, high-dose GH regimens have been associated with frequent adverse effects. The efficacy and safety of low-dose GH treatment in obese individuals without GH deficiency remain unclear. This study aims to evaluate the effects of recombinant human growth hormone (rhGH) on body composition, lipid profile, glucose metabolism, and adverse events in this population. METHODS:A systematic review and meta-analysis were conducted in accordance with the PRISMA statement. PubMed, Cochrane Library, and EMBASE databases were systematically searched up to December 2024. Eligible studies included randomized controlled trials (RCTs) involving obese individuals without GH deficiency, with at least one endpoint related to body composition, lipid profile, or glucose metabolism. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO, #CRD42023464234). RESULTS:A total of 10 RCTs involving 420 participants were included. The mean age of participants ranged from 18 to 65 years, and treatment durations varied from 4 to 72 weeks. Low-dose rhGH therapy resulted in a significant reduction in visceral adipose tissue (SMD: -0.34, 95%CI: -0.57 to -0.12, p = 0.003) and a significant increase in thigh muscle area (MD: 6.33 cm2, 95%CI: 1.72 to 10.95, p = 0.007) compared to placebo. Additionally, fasting glucose levels were modestly elevated (MD: 4.18 mg/dL, 95%CI: 0.68 to 7.67, p = 0.02). No serious adverse events were reported in association with low-dose rhGH treatment across the included studies. CONCLUSIONS:Low-dose rhGH therapy significantly reduces visceral fat and enhances thigh muscle mass in obese individuals without GH deficiency. These findings suggest that low-dose rhGH may offer therapeutic potential for sarcopenic obesity, warranting further investigation in larger, longer-term studies.

Background Type 2 diabetes (T2D) and chronic gastritis/duodenitis (CGD) are both strongly associated with the onset of depression. However, the impact of T2D-CGD comorbidity on incident depression and all-cause mortality remains unclear. Method This retrospective cohort study utilized data from 387,149 participants in the UK Biobank to examine the relationship between T2D-CGD comorbidity, incident depression, and all-cause mortality. Outcome Patients with T2D are more likely to develop CGD compared to those without T2D (OR = 2.10, 95% CI = [1.97, 2.24]). T2D-CGD comorbidity was identified as a significant risk factor for both incident depression (adjusted HR = 2.29, 95% CI = [1.84, 2.85]) and all-cause mortality (adjusted HR = 2.57, 95% CI = [2.28, 2.88]). The synergistic effect of T2D and CGD on all-cause mortality was 1.92 times that of their individual effects combined (synergy index = 1.92, 95% CI = [1.56, 2.31]). The comorbidity was associated with a higher risk of depression and all-cause mortality within 15 years of disease onset. White matter hyperintensity, particularly near the cerebral ventricles, partially mediated the relationship between T2D-CGD comorbidity and incident depression. Interpretation Integrated screening and long-term monitoring strategies should be prioritized for population with the comorbidity of T2D and CGD, as it significantly elevates the risk of both incident depression and all-cause mortality. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement BH has received funding from the National Natural Science Foundation of China [grant number 82302148]. YY has received funding from the Key Science and Technology Program of Shaanxi Province [grant number 2023-YBSF-331] and Fourth Military Medical University [grant number 2023XC045]. GBC has received funding from the National Natural Science Foundation of China [grant number 82471936]. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used ONLY openly available human data that were originally located at UK Biobank. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced are available online at UK Biobank.

INTRODUCTION:Polycystic ovary syndrome (PCOS), a common metabolic-endocrine disorder, is linked to low-quality carbohydrate intake, though evidence remains controversial. This research aimed to evaluate carbohydrate quantity/quality impacts on PCOS by combining global trends from the Global Burden of Disease (GBD) 2021 database with pooled study from individual-level data. METHODS:We analyzed GBD 2021 data to assess annual trends in PCOS incidence and low-grain/high-sugar-sweetened beverage consumption. Six databases were searched until February 2025 to identify population-based studies for meta-analysis. Results were expressed as mean differences (MD) with 95 % CIs, and heterogeneity was evaluated using χ2 tests and I2 statistics. RESULTS:GBD 2021 data revealed rising PCOS incidence alongside increased low whole-grain intake and high sugar-sweetened beverage consumption. This meta-analysis of 25 studies (n = 20,738) found no significant difference in total carbohydrate intake between PCOS and non-PCOS women. However, women with PCOS had significantly higher refined grain intake (SMD (95 % CI) = 0.66 [0.09, 1.24]) and lower whole grains (SMD (95 % CI) = -0.64 [-1.34, 0.07]) and fiber intake (MD (95 % CI) = -1.83 [-3.80, 0.13]). Subgroup analyses demonstrated significantly reduced fiber intake in overweight (MD = -2.92 [95 % CI: 4.64 to -1.21]) and non-diabetic women with PCOS (MD = -1.40 [95 % CI: 2.42 to -0.38]). CONCLUSION:Compared with carbohydrate quantity, lower-quality carbohydrate intake-characterized by higher refined grain consumption and lower intake of fiber and whole grains-appears to be more closely associated with PCOS. Different metabolic phenotypes in PCOS may require personalized dietary strategies.

Background Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment, affecting life quality. The progression of cognitive decline and its neural basis in T2DM are unclear due to limitations in previous studies. This study integrates Event-Based Model (EBM) and Principal Component Analysis (PCA) to explore these aspects in T2DM patients. Methods This study assessed 119 T2DM patients and 87 healthy controls with neuropsychological tests (CVLT, Stroop, WCST) and MRI for gray matter volume (GMV). PCA simplified cognitive scores into composites for memory and executive function. EBM estimated the sequence of cognitive and neurostructural changes. Partial correlation analyses were used to examine associations with clinical factors with controlling covariance. Results Cognitive decline in T2DM began with attention and working memory, followed by executive function and episodic memory. GMV loss started in the insular gyrus, spreading to other regions. T2DM showed advanced disease progression (0.54 (0.12) vs. 0.49 (0.10), P = 0.001). A negative correlation linked long-delay memory (CVLT-PC4) to random blood glucose ( r = -0.581, P FDR = 0.025). Conclusion This study reveals the sequence of cognitive and neuroanatomical changes in T2DM. Memory decline and insular gyrus atrophy may serve as early biomarkers for T2DM-related cognitive impairment, which may be helpful in the development of personalized interventions to improve life quality.

Aims:Sex differences in the incidence of thyroid nodules (TNs) are broadly recognized, but further analysis is lacking. Thus, the aim of this study was to evaluate the association between TNs and anthropometric parameters in type 2 diabetic males and females. Materials and Methods:This cross-sectional study included 747 patients with type 2 diabetes mellitus (T2DM). All patients underwent clinical examination, thyroid ultrasound, laboratory tests, anthropometrics and body composition. Multivariable logistic regression assessed factors associated with TNs, and a simple nomogram was finally developed. Results:In total, the incidence of TNs was 36.95% (276/747) and was significantly higher in females (52.75%) than in males (27.85%). Age was positively correlated with TNs risk in patients with T2DM (males: OR = 4.141, 95% CI [1.999-8.577], females: OR = 4.630, 95% CI [1.845-11.618]). Obesity (OR = 2.655, 95% CI [1.257-5.607]) and hyperuricemia (OR = 1.997, 95% CI [1.030-3.873]) were only associated with the risk of TNs independent of other risk factors in type 2 diabetic females, as well as other obesity factors such as weight, BMI, waist-hip ratio, percent body fat, visceral curve area, and upper arm circumference, but not in type 2 diabetic males. However, the diameter of the largest thyroid nodule was only related to age (R = 0.226, p < 0.01). Finally, the nomogram for evaluating TNs in female T2DM patients was established, and the C-index of the nomogram was 0.704 (95% CI [0.89-0.94]). Conclusion:TNs occur with a significantly higher frequency in type 2 diabetic females than in males, especially those with hyperuricemia and obesity. Modifiable metabolic factors, such as obesity and hyperuricemia, are a major focus for improving TNs risk in women.

OBJECTIVE:Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI). Here, we identified a T2DM-specific effective connectivity (EC) network, the dynamic features of which could be used to distinguish T2DM patients with MCI from healthy controls (HC) and correlation with cognitive performance. METHODS:Local and multicentered T2DM patients and matched HC who underwent functional magnetic resonance imaging were recruited. Their static and dynamic effective connectivity were compared. The relationships between connectome characteristics and cognitive performance were also evaluated. RESULTS:The nodes of the T2DM-related static causality network included the anterior central gyrus, tail of the parahippocampal gyrus, posterior superior temporal sulcus, posterior central parietal lobe, posterior central gyrus and V5 region of the occipital lobe. The V5 region of the visual cortex was the core node. In the multicentered dataset, compared with the HC group, the T2DM with MCI group had significantly greater fractional window and mean dwell time. Fractional windows of the state, which was dominated by the interaction of the nodes from SomMot_Network, Limbic_Network, Default_Network, in the T2DM-specific network increased with poorer cognitive performance in T2DM with MCI patients. CONCLUSION:Our findings provide insights into the neurobiological mechanisms of the cognitive impairment of T2DM patients from a dynamic network perspective, which may ultimately inform more targeted and effective strategies to prevent MCI.

Brown adipose tissue (BAT) is a compelling therapeutic target against metabolic diseases. Mechanical cues regulate BAT function and may offer novel, non-pharmacological therapeutic approaches. Herein, we discuss the biomechanical pathways underlying BAT activation, highlight advances in mechanotherapeutic strategies, and consider how emerging technologies may enhance these interventions.

Type 2 diabetes mellitus (T2DM) is an important risk factor for cognitive impairment. Prior research has shown cognitive deficits and neural alterations across multiple domains in T2DM patients. However, the sequential dynamics of cognitive decline in this population remain poorly understood. This study employs an integrative approach combining Principal Component Analysis (PCA) and the Event-Based Model (EBM) to identify the temporal sequence of cognitive changes and underlying neural mechanisms in T2DM. This study assessed 119 T2DM patients and 87 healthy controls with neuropsychological tests and Magnetic Resonance Imaging for gray matter volume (GMV). PCA was used to reduce dimensionality in CVLT, STROOP, and WCST due to their substantial number of items, enabling integration into the EBM model. EBM estimated the sequence of cognitive and neurostructural changes. Partial correlation analyses were used to examine associations with clinical factors with controlling covariance. Cognitive decline in T2DM began with attention and working memory, followed by executive function and episodic memory. GMV loss started in the insular gyrus, spreading to other regions. T2DM patients exhibited significantly more advanced disease progression than healthy controls (EBM stage 0.54 (0.12) vs. 0.49 (0.10), P = 0.001). A negative correlation linked long-delay memory (CVLT-PC4) to random blood glucose (r = -0.581, PFDR = 0.025). Memory decline and insular gyrus atrophy may serve as early biomarkers for T2DM-related cognitive impairment. These findings highlight potential targets for early intervention and suggest strategies for developing personalized treatments to improve life quality in affected individuals.

IntroductionThe rising global prevalence of polycystic ovary syndrome (PCOS) poses a significant threat to women’s metabolic and reproductive health. The carbohydrate quality—particularly dietary fiber, glycemic index (GI), and glycemic load (GL)—in addressing metabolic and reproductive abnormalities remains debated due to the condition’s heterogeneity. “The ongoing debate regarding PCOS arises from its complexity and heterogeneity, including variations in clinical symptoms, underlying causes, and treatment responses.” This study aimed to perform a meta-analysis of randomized clinical trials to examine the effects of high fiber and low glycemic index (LGI)/low glycemic load (LGL) dietary interventions on metabolic parameters in women with PCOS.MethodsA systematic literature search was conducted using PubMed, EMBASE, the Cochrane Library, Web of Science, Ovid MEDLINE, and Scopus to identify eligible studies. The outcomes were reported as standardized mean differences (SMD) with 95% confidence intervals (CI). Heterogeneity among studies was evaluated using the chi-square test and the I2 statistic.ResultsThe study showed high dietary fiber and LGI significantly reduced fasting glucose and insulin resistance. Both high fiber and the LGI diet significantly reduced triglycerides and Low-density lipoprotein cholesterol (LDL-C), with fiber also increasing High-density lipoprotein cholesterol (HDL-C). High-fiber and LGI diets increased Sex Hormone-Binding Globulin (SHBG) and reduced Free androgen index (FAI).DiscussionThis meta-analysis highlights the significant benefits of optimizing dietary carbohydrate quality on glycolipid metabolism, sex hormone levels, and weight in women with PCOS. While further high-quality studies are needed, the findings suggest that dietary fiber and LGI/LGL consumption have distinct effects on metabolic parameters. Therefore, treatment strategies should incorporate personalized dietary interventions tailored to the specific needs of women with PCOS within a shared decision-making framework.Systematic review registrationwww.crd.york.ac.uk, identifier PROSPERO CRD42024579681.

Skeletal muscle insulin resistance (IR) is a critical deficiency in IR pathophysiology that substantially affects overall metabolic health. Skeletal muscle is mechanically sensitive since its structure and function are significantly influenced by factors such as mechanical stretching and tissue stiffness. These mechanical stimuli can cause adaptive changes that enhance muscle performance and resilience. In this review, we discuss the current state of skeletal muscle IR research from the perspective of mechanomedicine. We also systematically and comprehensively present the evolution of mechanomedicine in addressing skeletal muscle IR by various disciplines, including biomechanics, mechanobiology, mechanodiagnosis, and mechanotherapy. The goal of the review is to provide important theoretical insights and practical methods for elucidating the pathogenesis of IR and to advance diagnostic and therapeutic approaches informed by mechanomedicine.

Episodic memory decline is a common complication of type 2 diabetes (T2D). To comprehensively explore the neural mechanisms underlying it, we aimed to explore the sequence that episodic memory-related behavioral and brain-imaging biomarkers appear abnormal in the progression of T2D. We enrolled 62 healthy controls and 110 patients with T2D. The California Verbal Learning Test, Montreal cognitive assessment, and Stroop color word test was used to assess the episodic memory, general cognitive function, and executive function. Principal component analysis was applied to extract behavioral biomarkers. Imaging biomarkers included structural and functional MRI features of the entorhinal cortex-hippocampus and hippocampus-anterior cingulate cortex pathways. We used a novel discriminative event-based model to determine the sequence that memory-related biomarkers appear abnormal and estimate the stage of memory decline. T2D patients exhibited poorer memory, general cognitive function, and executive function compared to healthy controls after controlling age, sex, and education level. In the progression of T2D, functional interaction between brain regions showed abnormalities first, followed by memory tests, the cerebral spontaneous neural activity, and finally the gray matter volume. Besides, abnormalities appeared earlier in the entorhinal cortex than in the anterior cingulate cortex. Later stage of memory decline was distributed in older patients with T2D and was associated with higher systolic blood pressure, postprandial blood glucose, and low-density lipoprotein. In T2D, behavioral and brain imaging biomarkers of episodic memory appear abnormal in a specific sequence, and the stage of memory decline was closely associated with old age and vascular risk factors. NCT02420470, ClinicalTrials.gov ( https://www.clinicaltrials.gov/ ).

Background:Diabetic kidney disease (DKD) is a common complication in patients with type 2 diabetes (T2DM), and early screening and diagnosis are crucial for preventing end-stage renal disease (ESRD). The extracellular water/total body water (ECW/TBW), as measured by bioelectrical impedance analysis (BIA), may be closely associated with the development of DKD. This study aimed to evaluate the relationship between ECW/TBW and albuminuria in T2DM patients and to explore its potential as an early diagnostic tool. Materials and methods:This study included 1,034 T2DM patients. Demographic information, medical history, medication use, and laboratory test results were collected, including glycated hemoglobin (HbA1c), creatinine, lipid profile, and the urine albumin-creatinine ratio (UACR). BIA was used to measure parameters such as ECW/TBW. Multivariate logistic regression analysis explored the correlation between ECW/TBW and UACR. Ultimately, two simple nomograms were established to predict macroalbuminuria from patients with normoalbuminuria and microalbuminuria, respectively. Results:The ECW/TBW increased significantly with rising UACR levels. Multivariate logistic regression analysis showed that ECW/TBW was significantly associated with macroalbuminuria compared to both normo-albuminuria and microalbuminuria (OR = 2.082, 95% CI [1.476-2.937], P < 0.001; and OR = 1.642, 95% CI [1.129-2.386], P = 0.009, respectively). In the analysis stratified by renal function, a similar relationship was found only in patients with eGFR ≥ 60 mL/min/1.73 m2 (OR = 2.108, 95% CI [1.479-3.004], P < 0.001) but not in patients with eGFR < 60 mL/min/1.73 m2. Finally, two nomograms for predicting macroalbuminuria were established. The C-index of the nomogram model for predicting the macroalbuminuria in patients with normoalbuminuria was 0.795 (95% CI [0.752-0.838]), and the C-index of the nomogram model for predicting the macroalbuminuria in patients with microalbuminuria was 0.761 (95% CI [0.711-0.812]). Conclusions:This study demonstrated a significant correlation between the ECW/TBW and UACR levels in Chinese T2DM patients. In patients with normal or mildly impaired renal function (eGFR ≥ 60 mL/min/1.73 m2), ECW/TBW was significantly associated with macroalbuminuria, potentially serving as a diagnostic marker for macroalbuminuria.

Objectives Type 2 diabetes (T2D) and chronic gastritis/duodenitis (CGD) are both strongly associated with the onset of depression. However, the impact of T2D-CGD comorbidity on incident depression remains unclear. Methods This prospective cohort study utilized data from 387 149 participants in the UK Biobank to examine the relationship between T2D-CGD comorbidity and incident depression. Results Patients with T2D exhibited a significantly higher likelihood of developing CGD than those without T2D (odds ratio = 2.10, 95% CI = [1.97, 2.24]). Both T2D and CGD were independently associated with an increased risk of incident depression, with their comorbidity demonstrating the strongest associations (adjusted hazard ratio = 2.29, 95% CI = [1.84, 2.85]). Notably, the comorbidity was linked to an elevated risk of depression within 15 years of disease onset. White matter hyperintensity, particularly near the cerebral ventricles, partially mediated the relationship between T2D-CGD comorbidity and incident depression. Conclusions Integrated screening and long-term monitoring strategies should be prioritized for population with the comorbidity of T2D and CGD, as it significantly elevates the risk of incident depression. White matter hyperintensity can serve as an imaging biomarker for detecting the risk of depression in patients with T2D-CGD comorbidity.