Sarcopenia and diabetic kidney disease (DKD) commonly coexist in people with type 2 diabetes, but the temporal direction of their association and potential subgroup differences are not fully understood. In this hospital-based prospective cohort, we performed bidirectional analyses. We evaluated baseline sarcopenia as a predictor of incident DKD among participants without DKD at baseline (n= 4,826), and baseline DKD as a predictor of incident sarcopenia among participants without sarcopenia at baseline (n= 4,798). Sarcopenia was defined using the AWGS 2019 criteria based on appendicular skeletal muscle mass index (ASMI), handgrip strength, and 4 m gait speed, requiring low muscle mass plus low muscle strength or low physical performance. DKD was defined as eGFR < 60 mL/min/1.73 m² and or persistent UACR ≥ 30 mg/g, supported by physician diagnosis after excluding primary non-diabetic kidney diseases. Associations were examined using stepwise multivariable Cox models, restricted cubic splines to assess nonlinearity, and prespecified subgroup analyses with interaction testing. Baseline sarcopenia was associated with a higher risk of incident DKD, with incidence rates of 69.49 and 40.39 per 1,000 person-years in participants with and without sarcopenia, respectively. The fully adjusted hazard ratio was 1.587 (95

This study aimed to investigate the association between early-onset type 2 diabetes (EOT2D) and the risk of falls, focusing on the role of sarcopenic obesity. A total of 580 patients (290 with EOT2D and 290 with late-onset type 2 diabetes [LOT2D]) were selected through propensity score matching. Participants were categorized into four groups: non-sarcopenia/non-obesity, obesity-only, sarcopenia-only, and sarcopenic obesity. Binary logistic regression models were employed to examine the relationships between age at diabetes onset, sarcopenic obesity, and fall risk. Additionally, 472 patients were followed longitudinally to assess the associations between EOT2D, LOT2D, sarcopenic obesity, and fall risk. Patients with EOT2D exhibited a higher prevalence of sarcopenic obesity compared to those with LOT2D. EOT2D was significantly associated with an increased risk of falls, both directly and indirectly via sarcopenic obesity (β = 0.81, ORSO−VFA = 2.25, 95

Objective:Type 2 diabetes mellitus (T2DM) predisposes patients to osteosarcopenia, a debilitating condition characterized by concurrent bone loss and muscle wasting. This study aimed to develop and internally validate a nomogram for predicting osteosarcopenia risk in T2DM patients aged ≥ 40 years. Methods:The test cohort included 5,412 hospitalized T2DM patients (January 2010-July 2024), and the temporal validation cohort included 1,671 patients (August 2024-December 2025) from the First Affiliated Hospital of Fujian Medical University. Logistic regression and machine learning algorithms (Boruta, random forest, LASSO) were combined for feature selection. The nomogram was constructed via multivariable logistic regression. We carried out receiver operating characteristic (ROC) curve analysis, calibration, decision curve analysis (DCA), and bootstrap validation for assessing the nomogram. Restricted cubic splines were employed for exploring potential nonlinear associations. Results:Eight independent predictors, which encompassed gender, age, BMI, WHtR, fracture history, diabetic foot ulcer (DFU), smoking status, and diabetic kidney disease (DKD), were identified. These predictors were incorporated into the nomogram. The nomogram achieved AUCs of 0.864 and 0.904 in the test cohort and validation cohort, respectively. Accordingly, favorable calibration and positive net benefit on DCA was demonstrated. Higher BMI served as a protective factor (OR = 0.56, 95% CI: 0.53-0.59). Besides, higher WHtR acted as a risk factor (OR = 1.47, 95% CI: 1.28-1.69). Restricted cubic spline analysis revealed a significant negative nonlinear relationship between BMI and osteosarcopenia risk, and a significant positive nonlinear relationship between WHtR and osteosarcopenia risk. Conclusion:This nomogram, based on eight readily available clinical variables, exhibits excellent discriminative performance and clinical utility for predicting osteosarcopenia risk in T2DM patients aged ≥ 40 years. Further multicenter external validation is warranted.

This study aimed to develop and validate nomogram risk estimation models for assessing the risk of microvascular complications, specifically diabetic retinopathy (DR) and diabetic kidney disease (DKD), in patients with type 2 diabetes mellitus (T2DM). A retrospective cross-sectional study was conducted involving 6,043 T2DM patients. Clinical and laboratory data were collected. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to identify significant risk factors from 38 initial variables. These selected variables were then incorporated into multivariate logistic regression analyses to build the risk estimation models. The models were presented as nomograms and were internally validated using bootstrap resampling. Their performance was evaluated by assessing discrimination (using Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC)), calibration (using calibration plots), and clinical utility (using Decision Curve Analysis (DCA)). The LASSO regression identified 8 and 15 independent risk factors for DR and DKD, respectively. The DR model included age, DM duration, insulin use, peripheral neuropathy, heart rate, HbA1c, and total protein. The DKD model included carotid atherosclerosis, diabetic foot, DM duration, α-glucosidase inhibitor use, insulin use, hypertension history, systolic blood pressure, lymphocyte count, total cholesterol, triglycerides, albumin, BMI, uric acid, and creatinine. Multivariate logistic analysis confirmed these associations. The nomograms demonstrated acceptable discrimination, with AUCs of 0.703 (training) and 0.732 (validation) for the DR model, and 0.802 (training) and 0.713 (validation) for the DKD model. Calibration curves showed good agreement between estimated and observed probabilities. This study successfully established and validated effective nomogram models for estimating the risk of DR and DKD in T2DM patients. Utilizing readily available clinical parameters, these models demonstrate moderate discriminative ability and clinical utility, potentially aiding in the early identification of high-risk individuals for targeted screening and improved management of microvascular complications in T2DM.

ABSTRACT Background Musculoskeletal complications in type 2 diabetes (T2DM) are inadequately captured by body mass index (BMI). Waist‐to‐BMI ratio (WBR) may better reflect adverse body composition. We examined cross‐sectional and longitudinal associations between WBR and musculoskeletal disorders in T2DM. Methods This two‐phase study was conducted within an ongoing hospital‐based cohort at the First Affiliated Hospital of Fujian Medical University (Fuzhou, China). The cross‐sectional analysis included 4157 adults with T2DM recruited between March 2012 and August 2023 (54.3% men; mean age 59.4 ± 10.3 years), using data from their first assessment. Associations of waist circumference (WC), waist‐to‐height ratio (WHtR), waist‐to‐hip ratio (WHR), BMI and WBR with osteopenia, sarcopenia, sarcopenic osteopenia (SOs), sarcopenic obesity (SOb) and fractures were evaluated. The prospective cohort comprised a longitudinal subset enrolled between March 2012 and June 2022, ensuring at least 1 year of follow‐up prior to administrative censoring in August 2023. A total of 440 individuals (57.0% men; mean age 59.7 ± 9.7 years) were followed for a median of 34.0 months (20.0–57.0). Associations between time‐dependent WBR and incident outcomes were assessed using Cox models. A nested exploratory analysis was conducted within the cohort. Thirty participants with extreme annualised WBR change (ΔWBR/yr) were selected. Baseline serum samples collected at enrolment, prior to outcome occurrence, were analysed using phage immunoprecipitation sequencing (PhIP‐Seq). Results Cross‐sectionally, WBR was negatively correlated with bone mineral density and appendicular skeletal muscle mass index and positively correlated with osteopenia, sarcopenia, SOs, SOb and fractures (all p < 0.01), whereas BMI, WC, WHtR and WHR showed weaker associations. After adjustment, higher WBR was independently associated with osteopenia (men: OR 1.723, 95% CI 1.614–1.840; women: OR 1.420, 1.348–1.495), sarcopenia (men: OR 4.779, 4.165–5.484; women: OR 2.991, 2.683–3.334), SOs (men: OR 6.261, 5.314–7.377; women: OR 4.336, 3.753–5.010), SOb (men: OR 4.737, 3.975–5.646; women: OR 4.652, 3.715–5.825) and fractures (men: OR 1.236, 1.093–1.397; women: OR 1.103, 1.003–1.213; all p < 0.05). Prospectively, higher time‐dependent WBR predicted incident osteopenia (HR 1.365, 95% CI 1.024–1.820), sarcopenia (HR 1.282, 1.086–1.512), SOs (HR 1.408, 1.176–1.686), SOb (HR 1.634, 1.262–2.116) and fractures (HR 1.369, 1.029–1.821). PhIP‐Seq analysis identified differential autoantibody reactivity related to muscle structural organisation and cytoskeletal regulation, while bone‐related differences were enriched in Wnt signalling and hormone‐related pathways. Conclusions Higher WBR and longitudinal increases were independently associated with osteopenia, sarcopenia, sarcopenic phenotypes and fractures in individuals with T2DM.

This study aims to compare the predictive efficacy of different diagnostic criteria for sarcopenia in forecasting the occurrence of osteoporosis (OP) and fractures. Utilizing data from the Global Health Data Exchange, the burden of musculoskeletal disorders (MSDs) was assessed through indicators including incidence, prevalence, and disability-adjusted life years. Trends in MSD burden were analyzed using the Joinpoint regression model to calculate the average annual percentage change. A retrospective cohort study was conducted on clinical data from 8180 patients who received care at the Endocrinology Department of the First Affiliated Hospital of Fujian Medical University between April 2008 and June 2024. Patients were categorized into four groups based on sarcopenia diagnostic criteria established by the European Working Group on Sarcopenia in Older People (EWGSOP), the International Working Group on Sarcopenia (IWGS), the Asian Working Group on Sarcopenia 2019 (AWGS 2019), and the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project. We compared demographic data, chronic disease history, body composition, bone mineral density, FRAX fracture risk, and the incidence of osteoporosis to evaluate the predictive validity of each diagnostic criterion for osteoporosis and fracture risk in patients with sarcopenia. (1) The prevalence of sarcopenia, as defined by the IWGS, FNIH, EWGSOP, and AWGS 2019 diagnostic criteria, was 39.2%, 28.3%, 55.0%, and 30.1%, respectively. (2) After adjusting for age, gender, and body mass index (BMI), a significant association between osteoporosis and sarcopenia was observed across all four diagnostic criteria (all P < 0.05). Furthermore, sarcopenia, as determined by the EWGSOP and AWGS 2019 criteria, was associated with a moderate-to-high risk of major osteoporotic fractures and hip fractures within the next 10 years (P < 0.05). (3) Spearman’s correlation coefficients for sarcopenia with Procollagen type I N-terminal propeptide (PINP), appendicular lean mass (ALM), ALM/height squared (Ht2), and ALM/BMI were − 0.034, − 0.308, − 0.261, and − 0.252, respectively. PINP, ALM, ALM/Ht2, and ALM/BMI were identified as significant factors influencing osteoporosis, with odds ratios of 0.996, 0.765, 0.535, and 0.010, respectively. The burden of MSDs is increasing in China and globally, driven primarily by population aging. Sarcopenia is significantly associated with osteoporosis and a moderate-to-high risk of fracture when diagnosed using the FNIH and EWGSOP criteria. PINP and ALM are protective factors against osteoporosis development in patients with sarcopenia.

OBJECTIVE:The stress hyperglycemia ratio (SHR) quantifies the intensity of stress hyperglycemia by highlighting the rate of change in fasting blood glucose during stress. Several studies have validated the association of SHR with poor prognosis in cardiovascular disease. However, the value of SHR in diabetic patients with severe heart failure requiring ICU admission remains unclear. The aim of this study was to investigate the predictive value of SHR for poor prognosis in diabetic patients with heart failure. METHODS:This study was based on the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and included diabetic patients with a diagnosis of heart failure. The primary outcome event was all-cause mortality. Patients were grouped according to quartiles of SHR, and the association between SHR and all-cause mortality was assessed using restricted cubic spline analysis, survival analysis, and Cox proportional hazards regression analysis. RESULTS:A total of 1470 patients (55.7% male) were enrolled in this study. In-hospital mortality and intensive care unit (ICU) mortality reached 12.2% and 7.8%, respectively. In-hospital mortality was significantly higher in the highest quartile group of SHR. After correction for confounders, the risk of death was significantly higher in the highest quartile group compared with the lowest quartile group. Restricted cubic spline plot analysis showed a positive linear relationship between SHR and in-hospital and ICU mortality. CONCLUSION:SHR was significantly associated with in-hospital and ICU all-cause mortality in severe patients. This finding suggests that SHR may be useful in identifying diabetic patients with severe heart failure at high risk for all-cause mortality.

AIMS:Current hypertension guidelines fail to discriminate between fasting and postprandial blood pressure (BP) measurements. Meal ingestion often triggers a marked increase in splanchnic blood flow, potentially inducing a sustained fall in systolic BP of ≥20 mmHg, termed postprandial hypotension (PPH). This study aimed to evaluate BP responses to a 75 g glucose drink and its implications for detecting hypertension and PPH in community-dwelling adults. METHODS AND RESULTS:A stratified multi-stage random sampling method was used to obtain a nationally representative sample of n = 4429 adult residents between April 2020 and January 2021 in China. BP and heart rate (HR) were measured before, and 1 and 2 h after, a 75 g glucose drink. When fasting, 38.4% of the study population had high BP (BP ≥140/90 mmHg). Following the glucose drink, SBP and DBP decreased (SBP by 6.2 [95% CI: 5.8, 6.6] mmHg and 8.1 [7.7, 8.5] mmHg, DBP by 4.7 [4.4, 4.9] mmHg and 6.1 [5.8, 6.4] mmHg), and HR increased (by 4.3 [4.0, 4.5] bpm and 2.6 [2.4, 2.9] bpm) at 1 and 2 h (P < 0.001 for all), with only 30.9% and 27.0% of the study population having high BP at 1 and 2 h, respectively. After adjustment for age and sex distribution, 19.9% of the general population was estimated to have PPH. Postprandial hypotension was associated with an increased risk of combined cardiovascular disease and stroke. CONCLUSION:Ingestion of a 75 g glucose drink often lowers BP, frequently leading to PPH and influencing the detection of hypertension. Accordingly, guidelines for measurements of BP and interpretation of outcomes should consider the potential impact of meal ingestion on BP.

In diabetes mellitus osteoporosis (DMOP), a common and severe chronic complication of diabetes mellitus (DM), long-term challenges are posed to public health. Recent evidence has implicated ferroptosis-a form of regulated cell death driven by iron-dependent lipid peroxidation-in the pathogenesis of DMOP. Ferritin heavy chain 1 (FTH1) plays a critical role in regulating iron metabolism during ferroptosis. To elucidate the regulatory mechanisms by which FTH1 modulates osteoblast (OB) ferroptosis and aberrant bone metabolism under high glucose and high fat (HGHF) conditions, we performed quantitative LFQ-DIA proteomics combined with bioinformatic analysis. MC3T3-E1 cells cultured under high glucose and high palmitic acid (HGPA) conditions were subjected to lentiviral-mediated FTH1 knock down (KD) or over expression (OE), and their protein expression profiles were systematically compared. We identified 857 differentially expressed proteins (DEPs) in the FTH1KD/HGPA group and 129 DEPs in the FTH1OE/HGPA group. Gene Ontology (GO) analysis revealed that, relative to HGPA/NC controls, DEPs in the KD/HGPA group were predominantly enriched in pyruvate biosynthesis and ADP metabolic processes, whereas DEPs in the OE/HGPA group were mainly associated with retinoid-like and glucuronate metabolic processes; in the HGPA/NC group, DEPs were enriched in cell-cell adhesion and regulation of inflammatory response. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these DEPs are involved in glycolysis, glutathione metabolism, and ferroptosis pathways. Protein-protein interaction (PPI) network analysis further identified minichromosome maintenance complex component 5(MCM5) and glucose 6 phosphate isomerase (GPI) as top hub proteins in the KD group. Functional validation of MCM5-the highest-scoring node by MCODE (score = 18.0)-demonstrated that FTH1KD significantly upregulated MCM5 expression, whereas MCM5KD reduced OBs ferroptosis, enhanced osteogenic differentiation, and activated WNT signaling. These results suggest that MCM5 is a key mediator of OB differentiation under HGHF conditions. Collectively, our findings reveal that altered FTH1 expression under HGHF conditions reshapes the OB protein interaction network and identify MCM5 as a potential therapeutic target for DMOP.

Diabetic foot ulcers (DFUs) are a leading cause of disability and mortality, with endothelial dysfunction playing a key role in the development of non-healing ulcers. A primary driver of endothelial cell impairment in this context is endoplasmic reticulum (ER) stress, triggered by glycolipotoxicity, though the underlying mechanisms are not fully understood. In this study, we observed that diabetic mice displayed poor ulcer healing associated with reduced angiogenesis and downregulated Reticulocalbin 1 (RCN1) expression. Proteomic analysis in human umbilical vein endothelial cells (HUVECs) identified a strong link between RCN1 and the damaging effects of glycolipotoxicity on endothelial cell function, leading to impaired tubule formation, reduced migratory capacity, and increased apoptosis in endothelial cells. Mechanistic RNA sequencing analysis highlighted a significant role for RCN1 in regulating ER function. RCN1 overexpression alleviated ER stress by reducing Protein kinase R-like endoplasmic reticulum kinase (PERK) phosphorylation and C/EBP homologous protein (CHOP) expression, both induced by glycolipotoxicity or Thapsigargin (TG), while RCN1 silencing intensified these effects. Additionally, TRIM11-mediated ubiquitination, influenced by glycolipotoxicity, regulated RCN1 stability, specifically promoting angiogenesis through RCN1 modulation. RCN1 overexpression accelerated ulcer healing in diabetic mice by suppressing ER stress proteins and enhancing angiogenesis, whereas RCN1 inhibition further delayed ulcer healing. In human DFU samples, proteomic analysis revealed that low RCN1 levels were linked to disrupted ER functional proteins, with RCN1 serum levels decreasing as diabetes progressed to DFU. Following surgical debridement treatment, RCN1 levels increased in patients with improved DFU healing outcomes. These findings suggest that ER stress, initiated by RCN1 inhibition in response to glycolipotoxicity, leads to endothelial dysfunction and apoptosis, ultimately contributing to the non-healing of DFUs.

Mitochondrial dysfunction is a critical mechanism underlying diabetic bone loss, which is driven by the inhibition of osteoblast differentiation due to glucolipotoxicity. The molecular mechanisms through which glucolipotoxicity induces mitochondrial dysfunction remain poorly understood. In this study, we observed an upregulation of Toll-like receptor 4 (TLR4) expression in osteoblasts subjected to glycolipotoxic conditions, which was associated with mitochondrial dysfunction. Proteomic analysis revealed that TLR4 plays a crucial role in glucolipotoxicity and is closely linked to mitochondrial function in osteoblasts. Knockdown of TLR4 was found to alleviate osteoblast differentiation disorders and mitochondrial dysfunction as well as mitochondria-mediated apoptosis induced by glucolipotoxicity. In contrast, overexpression of TLR4 exacerbated the detrimental effects of glucolipotoxicity. Mechanistically, glucolipotoxicity activates TLR4, resulting in increased expression of NLRP3 (NOD-like receptor protein 3) and MAVS (Mitochondrial antiviral signaling protein), which promotes the interaction between NLRP3 and MAVS. This cascade leads to increased intracellular reactive oxygen species, decreased ATP levels, elevated expression of Caspase-1, GSDMD, Bax, and reduced expression of the anti-apoptotic protein Bcl-2. Furthermore, TLR4 knockout was shown to mitigate bone loss in diabetic rats. Proteomic analysis revealed that the improvement in the expression of proteins related to mitochondrial function and osteogenic function in diabetic rats is associated with TLR4 knockout. Diabetic osteoporosis may be associated with increased TLR4 expression and disturbed oxidative phosphorylation. In conclusion, glucolipotoxicity activates TLR4, which subsequently induces the expression and interaction of NLRP3-MAVS, leading to mitochondrial dysfunction and inhibition of osteoblast differentiation. This process contributes to bone mass loss in diabetes.

This study aimed to explore the relationship between appendicular lean mass (ALM), osteoporosis (OP), and fracture risk in postmenopausal patients with type 2 diabetes mellitus (T2DM). A total of 1418 hospitalized postmenopausal patients with T2DM were enrolled. Bone mineral density (BMD) and ALM were measured using dual-energy X-ray absorptiometry (DXA). Based on BMD T-values, patients were categorized into OP and non-OP groups. General demographic data, biochemical markers, and body composition indices were compared between groups. Logistic regression analysis, nomogram construction, and receiver operating characteristic (ROC) curve analysis were performed to identify predictors and assess model performance. The prevalence of OP was significantly higher in patients with sarcopenia (SAC) compared to those without (P < 0.05). Significant between-group differences were observed in age, heart rate, 25-hydroxyvitamin D, height, weight, BMI, systolic blood pressure, presence of peripheral neuropathy, lymphocyte count, LDL cholesterol, total cholesterol, alanine aminotransferase, albumin, uric acid, creatinine, β-CTX, ALM/Ht2, and ALM (P < 0.05). Logistic regression identified ALM [OR = 0.785, 95% CI 0.697-0.884] and BMI [OR = 0.880, 95% CI 0.839-0.923] as protective factors against OP. A nomogram prediction model was developed using multiple independent predictors. ROC analysis showed good predictive performance, with an area under the curve (AUC) of 0.80 (95% CI 0.77-0.82), sensitivity of 82.0%, specificity of 67.8%, and an optimal cut-off value of 0.466. Lower age, BMI, and ALM were significantly associated with increased risk of OP. ALM and BMI emerged as independent protective factors. The developed nomogram can assist healthcare professionals in identifying key risk factors for OP in elderly postmenopausal patients with T2DM and support early screening and intervention strategies to reduce fracture risk.

This study aimed to identify causal effects and potential molecular mechanisms of genes associated with THCA development. Bioinformatic analyses were performed to identify differentially expressed genes (DEGs) associated with THCA. Subsequently, Mendelian randomization (MR) analysis was conducted using large-scale eQTL data and THCA GWAS summary statistics to screen for candidate genes. The intersection of DEGs and MR-derived candidate genes was used to determine DEGs with potential causal associations with thyroid carcinogenesis. Functional enrichment analysis, pathway analysis, and immune cell infiltration profiling were performed. External datasets were used for validation. Additionally, prognostic modeling and pan-cancer analyses of the candidate genes were conducted. IVW-based MR analysis revealed that elevated expression levels of ALOX15B [OR = 1.647, 95

Osteoporosis (OP) is a prevalent chronic bone metabolic disorder that affects the elderly population, leading to an increased susceptibility to bone fragility. Despite extensive research on the onset and progression of OP, the precise mechanisms underlying this condition remain elusive. The m6A modification, a prevalent form of chemical RNA modification, primarily regulates posttranscriptional processes, including RNA stability, splicing, and translation. Numerous studies have underscored the crucial functions of m6A regulators in OP. This study aimed to explore the relationship between OP and RNA m6A methylation, investigating its underlying mechanisms through comprehensive bioinformatic analysis and experimental validation. The mRNA sequencing (mRNA-seq) and methylated RNA immunoprecipitation sequencing (MeRIP-seq) were performed on control mice as well as ovariectomized mice to discover differentially expressed genes (DEGs) and m6A regulators in OP. The results revealed dysregulation of a majority of bone metabolism-related genes and m6A regulators in ovariectomized mice, indicating a closely linked relationship between them. Our research findings indicated that m6A modification is essential in regulating OP, offering potential insights for prevention and treatment.

BACKGROUND:Diabetes osteoporosis is a debilitating condition that significantly impacts human health. However, it is often underdiagnosed and not addressed in a timely or appropriate manner. METHODS:Recent studies were reviewed to explore the roles of energy metabolism, sarcopeina, low-grade inflammation and gut microbiota in the development of diabetes osteoporosis. RESULTS:Osteoporosis in diabetic patients differs from primary osteoporosis. Novel biomarkers and risk factors that are biologically, physiologically, and pathologically linked to the development of diabetes osteoporosis are emerging, necessitating a shift in strategies for diagnosis, risk stratification, and prevention of diabetes osteoporosis. CONCLUSIONS:There is an urgent need to approach this disorder from a fresh perspective, initiating a range of basic research and clinical investigations.

Objective This study aimed to determine whether a relationship exist between pre-therapy 25-hydroxyvitamin D levels and the remission/negative conversion rates of thyrotropin receptor antibody (TRAB) during treatment in patients with newly diagnosed Graves' disease (GD). Methods 171 patients were included from the Endocrinology Department of the First Affiliated Hospital of Fujian Medical University in March 2013 to April 2016. Ninety-five patients of them were diagnosed at our hospital but transferred to local hospitals for treatment. Seventy-six patients were followed and treated at our hospital with a median follow-up time of 11.03 (range 6–27) months. Patients were divided into 3 groups according to baseline 25-hydroxyvitamin D levels; <20 ng/mL (31,43.05%), 20–29 ng /mL (20,27.78%), and ≥ 30 ng/mL (20,29.17%). The TRAB remission rate and negative conversion rate was assessed among each group. Results There was a higher TSH and lower TRAB titer in the 20–29 ng/mL group at initial diagnosis. Cox regression analysis suggested that 20–29 ng/mL group had significantly higher remission rates [RR; 95% CI: 7.505 (1.401–40.201), 8.975 (2.759–29.196),6.853(2.206–21.285), respectively] and negative conversion rates [RR; 95% CI: 7.835 (1.468–41.804),7.189(1.393–37.092), 8.122(1.621–40.688)] at the 6-, 12-, and 24-month follow-up, respectively .The level of 25-hydroxyvitamin D at the time of initial diagnosis was not associated with the re-normal of free Triiodothyronine(FT3), free thyroxineIndex(FT4) or TSH levels during the follow-up. Conclusion Newly diagnosed GD patients with appropriate baseline 25-hydroxyvitamin D levels (20–29 ng/mL) are beneficial for the reduction of TRAB during antithyroid therapy.

The primary cause of mortality among individuals with diabetes stems from complications. Identifying related factors for these complications holds immense potential for early prevention. Previous research predominantly employed traditional machine-learning techniques to establish prediction models utilizing medical indicators for related factor selection. However, uncovering the intricate correlations among complication labels and identifying similar characteristics among medical indicators has been challenging. We propose a novel embedded multi-label feature selection approach called LCFSM(Label Cosine and Feature Similar Manifold) to address the issue. LCFSM introduces manifold constraints into the objective function to uncover risk factors associated with diabetes complications. Label cosine similarity is set to optimize feature weights, forming label manifold constraints. Similarly, feature manifold constraints are established to utilize feature kernel similarity in optimizing feature weights. LCFSM formulates an objective function based on the $\ell _{2,1}$ regularized Least Squares and previous manifolds constraints, employing the Sylvester equation for convergence assurance. The experimental evaluation compares LCFSM against eight baselines, demonstrating superior performance in top-10 feature selection and feature stacking.LCFSM is applied to identify primary risk factors for diabetes complications. Related factors involve Electromyogram, Urine Routine Protein Positive, etc, offering valuable insights for early treatment.

Background: Identifying β-cells dysregulation in type 2 diabetes mellitus (T2DM) is crucial. Weight fluctuations are frequently observed during diabetes treatment. However, the relationship between body composition changes and islet β-cell function in individuals with T2DM remains insufficiently investigated. Methods: This retrospective longitudinal study encompassed a cohort of 775 T2DM patients, who underwent body composition measuring using dual-energy X-ray absorptiometry (DEXA) and followed up for a median of 2.29 years. Key metrics included body mass index (BMI), fat mass index (FMI), trunk fat mass index (TFMI), muscle mass index (MMI), appendicular skeletal muscle mass index (ASMI), muscle/fat mass ratio (M/F), and the appendicular skeletal muscle mass/trunk fat mass ratio (A/T) were then categorized and grouped. Insulin, C-peptide, and glucose levels were assessed concurrently following a glucose load. β-cell function included insulin resistance (HOMA-IR), insulin sensitivity (Matsuda index (MI)), and insulin secretion evaluated by HOMA-β and C-peptidogenic index (CGI). Results: Although no significant changes in BMI were observed, patients with T2DM at readmission exhibited higher FMI, TFMI, and ASMI, as well as elevated levels of HOMA-IR, MI, and CGI compared to baseline measurements. And lower MI, higher levels of CGI, and HOMA-IR were observed in BMI increased group. Univariate correlation analysis revealed a negative association between changes in BMI (ΔBMI) and ΔMI, while positive associations were observed in both ΔHOMA-IR and ΔCGI. Among body composition indexes, ΔFMI exhibited the strongest correlation with ΔHOMA-IR (r = 0.255, p < 0.001), and ΔASMI was positively associated with ΔMI and ΔCGI (r = 0.131 and 0.194, respectively). Moreover, increased levels of BMI and FMI were associated with a greater risk of progressive insulin resistance compared to the decreased, whereas the trend was converse in ASMI and A/T. Conclusions: Increased FMI may partially contribute to the deterioration of insulin resistance, while increased ASMI is associated with improved insulin sensitivity and secretion. Maintaining an appropriate BMI and muscle/fat ratio is conductive to prevent the progression of insulin resistance in patients with T2DM.

Osteoporosis is a chronic disease that endangers the health of the elderly. Inhibiting osteoclast hyperactivity is a key aspect of osteoporosis prevention and treatment. Several studies have shown that interferon regulatory factor 9 (IRF9) not only regulates innate and adaptive immune responses but also plays an important role in inflammation, antiviral response, and cell development. However, the exact role of IRF9 in osteoclasts has not been reported. To elucidate the role of IRF9 in osteoclast differentiation, we established the ovariectomized mouse model of postmenopausal osteoporosis and found that IRF9 expression was reduced in ovariectomized mice with overactive osteoclasts. Furthermore, knockdown of IRF9 expression enhanced osteoclast differentiation in vitro. Using RNA sequencing, we identified that the differentially expressed genes enriched by IRF9 knockdown were related to ferroptosis. We observed that IRF9 knockdown promoted osteoclast differentiation via decreased ferroptosis in vitro and further verified that IRF9 knockdown reduced ferroptosis by activating signal transducer and activator of transcription 3 (STAT3) to promote osteoclastogenesis. In conclusion, we identified an essential role of IRF9 in the regulation of osteoclastogenesis in osteoporosis and its underlying mechanism.