The Association Between Triglyceride-Glucose Index and Its Combination with Obesity Indicators and Lower Extremity Peripheral Artery Disease in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study.

Background: Lower extremity peripheral artery disease (LEAD) is a significant chronic complication of type 2 diabetes mellitus (T2DM) that significantly contributes to disability and mortality. The subtle presentation of LEAD symptoms often leads to underrecognition and misdiagnosis. Therefore, identifying simple and effective evaluation indicators is essential for the early detection and management of LEAD. Insulin resistance is closely associated with diabetes and its complications. However, the specific relationship between insulin resistance-measured by the triglyceride-glucose (TyG) index-and obesity indicators in relation to LEAD remains unclear. Objective: This study aims to investigate the association between the TyG index and its combination with obesity indicators in participants with T2DM and LEAD. Methods: We performed a univariate analysis on 3176 T2DM patients to identify risk factors for LEAD. Patients were then divided into quartiles based on the TyG index combined with various obesity indicators. The chi-square test was used to compare the prevalence of LEAD across these groups. Logistic regression analysis was conducted to examine the association between the TyG index, in combination with different obesity indicators, and the occurrence of LEAD. Finally, we assessed the predictive ability of the TyG index combined with obesity indicators for LEAD by comparing the area under the ROC curve (AUC). Results: The study included 3176 T2DM patients (1691 males and 1485 females) with a mean age of 56.16±10.60 years. Among them, 106 individuals had LEAD. The prevalence of LEAD varied significantly across quartiles of the TyG index, TyG-WC, and TyG-WHR (Q4 > Q3 > Q2 > Q1; P < 0.05). Multiple logistic regression analysis showed that the TyG index, TyG-WC, and TyG-WHR were positively associated with the risk of LEAD in T2DM patients. ROC curve analysis identified the best cutoff values for predicting LEAD: 9.8059 for the TyG index (sensitivity: 49.1%, specificity: 67.9%, AUC: 0.583), 808.8397 for TyG-WC (sensitivity: 70.8%, specificity: 47.8%, AUC: 0.603), and 8.8543 for TyG-WHR (sensitivity: 75.5%, specificity: 44.6%, AUC: 0.607). Conclusion: In T2DM patients, the TyG index, TyG-WHR, and TyG-WC are positively associated with the occurrence of LEAD. TyG-WHR and TyG-WC exhibit a stronger correlation with LEAD compared to the TyG index alone, indicating their superior diagnostic value.

Association of social determinants, lifestyle, and metabolic factors with mortality in Chinese adults: A nationwide 10-year prospective cohort study.

Nationwide estimates of the impact of common modifiable risk factors on mortality remain crucial. We aim to assess the influence of social determinants, lifestyle, and metabolic factors on mortality in 174,004 adults aged ≥40 years from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We reveal that 17 modifiable factors are independently associated with mortality, accounting for 64.8% of all-cause mortality, 77.4% of cardiovascular mortality, and 44.8% of cancer mortality. Low education emerges as the leading factor for both all-cause and cancer mortality, while hypertension is predominant for cardiovascular mortality. Moreover, low gross domestic product per capita and high ambient particulate matter with a diameter of <2.5 µm (PM2.5) air pollution account for 7.8% and 4.3% for all-cause mortality, respectively, using a different method. Gender-specific analyses reveal distinct patterns, with women's mortality primarily associated with social determinants and men exhibiting stronger associations with lifestyle factors. Targeted health interventions are essential to mitigate mortality risks effectively in China.

Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.

INTRODUCTION: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2-h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population. METHODS: Data from 54301 eligible participants were obtained from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study in China. Data from 37740 participants were used to develop the diagnostic system. External validation was performed among 16561 participants. Three machine learning algorithms were used to create the predictive models, which were further evaluated by various classification algorithms to establish the best predictive model. RESULTS: Ten features were selected to develop an IPH diagnosis system (IPHDS) based on an artificial neural network. In external validation, the AUC of the IPHDS was 0.823 (95% CI 0.811-0.836), which was significantly higher than the AUC of the Taiwan model [0.799 (0.786-0.813)] and that of the Chinese Diabetes Risk Score model [0.648 (0.635-0.662)]. The IPHDS model had a sensitivity of 75.6% and a specificity of 74.6%. This model outperformed the Taiwan and CDRS models in subgroup analyses. An online site with instant predictions was deployed at https://app-iphds-e1fc405c8a69.herokuapp.com/. CONCLUSIONS: The proposed IPHDS could be a convenient and user-friendly screening tool for diabetes during health examinations in a large general population.

Serum Medium-Chain Fatty Acids and the Risk of Incident Diabetes: Findings from the 4C Study.

CONTEXT: Emerging studies have revealed associations between dietary medium-chain fatty acids (MCFAs) and glucose homeostasis. However, the relationship between serum MCFAs and the incidence of diabetes, and potential interactions with genetic predisposition, remains unclear in prospective cohort studies. OBJECTIVE: To investigate associations and genetic susceptibility between serum MCFAs and diabetes risk. METHODS: We investigated baseline serum MCFAs (n=5) in a nested case-control study comprising incident diabetes cases (n=1,707) and matched normoglycemic control subjects (n=1,707) from the China Cardiometabolic Disease and Cancer Cohort Study. Associations between MCFAs and type 2 diabetes mellitus (T2DM) were examined, both overall and stratified by diabetes genetic susceptibility. Genetic risk scores (GRS) were calculated based on 86 T2DM-associated genetic variants. RESULTS: In the fully adjusted conditional logistic regression model, serum octanoic acid and nonanoic acid exhibited inverse dose-response relationships with diabetes risk, showing odds ratios (95% confidence intervals) of 0.90 (0.82-0.98) and 0.84 (0.74-0.95), respectively. Subgroup analysis demonstrated that inverse associations between MCFAs and incident diabetes were more pronounced among individuals with physical inactivity (Pinteraction = 0.042, 0.034, and 0.037, for octanoic, nonanoic and decanoic acid, respectively). Moreover, inverse associations of octanoic acid with diabetes risk were notably enhanced among individuals with high genetic risk compared to those with low genetic risk. Significant interactions were observed between octanoic acid and GRS on T2DM risk (Pinteraction = 0.003). CONCLUSIONS: These findings provide evidence supporting inverse associations between serum MCFAs and T2DM risk, and reveal potential interplay between genetic susceptibility and circulating octanoic acid in modulating diabetes risk.

Dynamical Attention Hypergraph Convolutional Network for Group Activity Recognition.

Recently, group activity recognition (GAR) has drawn growing interests in video analysis and computer vision communities. The current models of GAR tasks are often impractical in that they suppose that all interactions between actors are pairwise, which only models and leverages part of the information in real entire interactions. Motivated by this, we design a distinct dynamical attention hypergraph convolutional network framework, referred to as DAHGCN, for precise GAR, modeling the entire interactions and capturing the high-order relationships among involved actors in a real-life scenario. Specifically, to learn complementary feature representations for fine-grained GAR, a multilevel feature descriptor (MLFD) module is proposed. Furthermore, for learning higher order interaction relationships, we construct a DAHGCN to accommodate complex group interactions, which can dynamically change the topology of the hypergraph and learn these key representations by virtue of the "similarity-based shared nearest-neighbor (SSNN) clustering" and "attention mechanisms" on hypergraph. Finally, a multiscale temporal convolution (MSTC) module is utilized to explore various long-range temporal dynamic correlations across different frames. In addition, comprehensive experiments on three commonly used GAR datasets clearly demonstrate that, when compared with the state-of-the-art methods, our proposed method can achieve the most optimal performance.

Association between gut microbiota and adrenal disease: a two-sample Mendelian randomized study.

Background: Some observational studies and clinical experiments suggest a close association between gut microbiota and metabolic diseases. However, the causal effects of gut microbiota on adrenal diseases, including Adrenocortical insufficiency, Cushing syndrome, and Hyperaldosteronism, remain unclear. Methods: This study conducted a two-sample Mendelian randomization analysis using summary statistics data of gut microbiota from a large-scale genome-wide association study conducted by the MiBioGen Consortium. Summary statistics data for the three adrenal diseases were obtained from the FinnGen study. The study employed Inverse variance weighting, MR-Egger, and MR-PRESSO methods to assess the causal relationship between gut microbiota and these three adrenal diseases. Additionally, a reverse Mendelian randomization analysis was performed for bacteria found to have a causal relationship with these three adrenal diseases in the forward Mendelian randomization analysis. Cochran's Q statistic was used to test for heterogeneity of instrumental variables. Results: The IVW test results demonstrate that class Deltaproteobacteria, Family Desulfovibrionaceae, and Order Desulfovibrionales exhibit protective effects against adrenocortical insufficiency. Conversely, Family Porphyromonadaceae, Genus Lachnoclostridium, and Order MollicutesRF9 are associated with an increased risk of adrenocortical insufficiency. Additionally, Family Acidaminococcaceae confers a certain level of protection against Cushing syndrome. In contrast, Class Methanobacteria, Family Lactobacillaceae, Family Methanobacteriaceae, Genus. Lactobacillus and Order Methanobacteriales are protective against Hyperaldosteronism. Conversely, Genus Parasutterella, Genus Peptococcus, and Genus Veillonella are identified as risk factors for Hyperaldosteronism. Conclusions: This two-sample Mendelian randomization analysis revealed a causal relationship between microbial taxa such as Deltaproteobacteria and Desulfovibrionaceae and Adrenocortical insufficiency, Cushing syndrome, and Hyperaldosteronism. These findings offer new avenues for comprehending the development of adrenal diseases mediated by gut microbiota.

Association of white blood cell count to mean platelet volume ratio with type 2 diabetic peripheral neuropathy in a Chinese population: a cross-sectional study.

BACKGROUND: The white blood cell count to mean platelet volume ratio (WMR) is considered a promising inflammatory marker, and its recognition is increasing. Inflammation is closely related to metabolic diseases such as diabetes and its complications. However, there are currently no reports on the correlation between WMR and type 2 diabetic peripheral neuropathy (DPN). This study aims to explore the correlation between WMR and DPN in type 2 diabetes patients. By understanding this association, we hope to provide a theoretical basis for preventing DPN through the improvement of inflammatory responses. METHODS: This was a cross-sectional study involving 2515 patients with T2DM. Logistic regression analysis was conducted to assess the associations between WMR and DPN. Finally, the receiver operating characteristic curve (ROC curve) was employed to evaluate the predictive efficacy of WMR for DPN. RESULTS: Patients in higher WMR quartiles exhibited increased presence of DPN. Additionally, WMR remained significantly associated with a higher odds ratio (OR) of DPN (OR 4.777, 95% confidence interval [CI] 1.296-17.610, P < 0.05) after multivariate adjustment. Moreover, receiver operating characteristic curve analysis indicated that the optimal cutoff value for WMR in predicting DPN presence was 0.5395 (sensitivity: 65.40%; specificity: 41.80%; and area under the curve [AUC]: 0.540). CONCLUSIONS: In patients with T2DM, WMR was significantly increased in DPN and independently associated with an increased risk of DPN presence in Chinese patients. This suggests that WMR may serve as a useful and reliable biomarker of DPN, highlighting the importance of paying more attention to T2DM patients with high WMR to further prevent and reduce the development of DPN and related unfavorable health outcomes.

The causal relationship between plasma protein-to-protein ratios and type 2 diabetes and its complications: Proteomics mendelian randomization study.

AIM: In recent years, proteomics research has surged, with numerous observational studies identifying associations between plasma proteins and type 2 diabetes. However, research specifically focusing on the ratios of plasma proteins in type 2 diabetes remains relatively scarce. METHODS: This study primarily employed a two-sample, two-step Mendelian randomization (MR) approach, leveraging genetic data from several large, publicly accessible genome-wide association studies, wherein single nucleotide polymorphisms served as proxies for exposures and diseases. Within this framework, we applied two-sample MR to assess the associations between the 2821 plasma protein-to-protein ratios and type 2 diabetes along with its complications and utilized reverse MR to confirm the unidirectionality of these causal relationships. In addition, we employed two-step MR to investigate the potential mediating role of body mass index in these associations. To augment the robustness of our findings, we systematically implemented a series of sensitivity analyses. RESULTS: The results gleaned from the inverse-variance weighted method elucidated that a cumulative sum of 23 protein-to-protein ratios bore a causal nexus with type 2 diabetes across both sample cohorts. With each incremental elevation of 1 standard deviation in the genetically anticipated protein-to-protein ratio, the susceptibility to type 2 diabetes oscillated from 0.93 (95% confidence interval: 0.87, 1.00) for the CNTN3/NCSS1 protein level ratio to 1.13 (1.06, 1.22) for the DBNL/NCK2 protein level ratio. Moreover, a tally of eight protein-to-protein ratios correlated with a minimum of one complication linked to type 2 diabetes. Diverse sensitivity analyses corroborated the robustness of these observations. CONCLUSIONS: The outcomes of our investigation unveiled correlations between 23 plasma protein-to-protein ratios and type 2 diabetes, with eight of these ratios entwined with complications of type 2 diabetes. These discoveries offer novel perspectives on the diagnosis and management of type 2 diabetes and its associated complications.

Association between triglyceride glucose index and breast cancer in 142,184 Chinese adults: findings from the REACTION study.

Background: The triglyceride glucose (TyG) index has been associated with an increased risk in breast cancer. However, this association remains unclear among the Chinese population. This study aimed to investigate whether the TyG index is associated with the risk of prevalent breast cancer in Chinese women. Methods: This cross-sectional study included 142,184 women from the REACTION (Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal) Study, which recruited adults aged 40 years or older from 25 centers across mainland China between 2011 and 2012. The TyG index was calculated according to the formula: Ln (fasting triglycerides [mg/dL] × fasting glucose [mg/dL]/2). Multivariable-adjusted logistic regression models were used to evaluate odds ratios (ORs) and 95% confidence intervals (CIs) regarding the associations between the TyG index and breast cancer. Results: Multivariable-adjusted logistic regression analysis showed that compared with the lowest quartile of the TyG index, the highest quartile of the TyG index was significantly associated with an increased risk of prevalent breast cancer, with an OR (95% CI) of 1.61 (1.19-2.17). In the stratified analysis, the association of each 1 SD increase in the TyG index with risk of prevalent breast cancer was more dominant in individuals with menarche at age 13-17, those who were postmenopausal, those with a history of breastfeeding, and those who had two to four children, with the ORs (95% CIs) of 1.35 (1.09-1.68), 1.27 (1.05-1.54), 1.26 (1.05-1.52), and 1.32 (1.08-1.62), respectively. Moreover, among those without discernible insulin resistance (homeostatic model assessment-insulin resistance [HOMA-IR] ≥2.5), hyperglycemia and dyslipidemia, each 1 SD increase in the TyG index was associated with a 1.36-fold increase in breast cancer risk, with an OR (95% CI) of 2.36 (1.44-3.87). Conclusion: The TyG index is significantly associated with the prevalent breast cancer risk among middle-aged and elderly Chinese women.

Association Between Triglyceride-Glucose Index and Waist-To-Hip Ratio with Type 2 Diabetic Retinopathy in the Chinese Population: A Cross-Sectional Study.

BACKGROUND: The triglyceride-glucose (TyG) index serves as a convenient indicator of insulin resistance, which has been demonstrated to be associated with diabetic retinopathy(DR). However, the relationship between TyG-WHR, a novel index combining TyG with the central obesity indicator WHR, and retinopathy in patients with type 2 diabetes remains unclear. Therefore, this study aims to investigate the correlation between TyG-WHR and DR in adult patients with type 2 diabetes. METHODS: This cross-sectional study included 1702 patients with T2DM. Logistic regression analysis was performed to examine the associations between TyG-WHR and DR. Additionally, the receiver operating characteristic curve (ROC curve) was utilized to assess the predictive efficacy of TyG-WHR for DR. RESULTS: Patients in higher TyG-WHR quartiles demonstrated an increased presence of DR, and TyG-WHR increased with the severity of DR. Moreover, TyG-WHR remained significantly associated with a higher odds ratio (OR) for DR (OR 1.223, 95% confidence interval [CI] 1.078-1.387, p < 0.05) after multivariate adjustment. Additionally, receiver operating characteristic curve analysis indicated that the optimal cutoff value for TyG-WHR in predicting DR presence was 8.8983, with a sensitivity of 61.00%, specificity of 48.50%, and area under the curve (AUC) of 0.555. CONCLUSIONS: In patients with T2DM, TyG-WHR was significantly elevated in those with DR and independently associated with an increased risk of DR presence in Chinese patients. This implies that TyG-WHR could potentially serve as a valuable and dependable biomarker for DR, underscoring the importance of giving greater consideration to T2DM patients with elevated TyG-WHR to effectively prevent and mitigate the onset of DR and associated adverse health outcomes.

Adaptive Signal Modulation Evolved by the Inherent Nonlinearity of Phase-Change Quantum-Dot String.

To simulate a topological neural network handling weak signals via stochastic resonance (SR), it is necessary to introduce an inherent nonlinearity into nanoscale devices. We use the self-assembly method to successfully fabricate a phase-change quantum-dot string (PCQDS) crossing Pd/Nb:AlNO/AlNO/Nb:AlNO/Pd multilayer. The inherent nonlinearity of phase change couples with electron tunneling so that PCQDS responds to a long signal sequence in a modulated output style, in which the pulse pattern evolves to that enveloped by two sets of periodic wave characterized by neural action potential. We establish an SR mode consisting of several two-state systems in which dissipative tunneling is coupled to environment. Size oscillations owing to NbO QDs adaptively adjust barriers and wells, such that tunneling can be periodically modulated by either asymmetric energy or local temperature. When the external periodic signals are applied, the system first follows the forcing frequency. Subsequently, certain PCQDs oscillate independently and consecutively to produce complicated frequency and amplitude modulations.

Sodium Crotonate Alleviates Diabetic Kidney Disease Partially Via the Histone Crotonylation Pathway.

Diabetic kidney disease (DKD) is a common microvascular complication of diabetes, inflammation and fibrosis play an important role in its progression. Histone lysine crotonylation (Kcr) was first identified as a new type of post-translational modification in 2011. In recent years, prominent progress has been made in the study of sodium crotonate (NaCr) and histone Kcr in kidney diseases. However, the effects of NaCr and NaCr-induced Kcr on DKD remain unclear. In this study, db/db mice and high glucose-induced human tubular epithelial cells (HK-2) were used respectively, and exogenous NaCr and crotonoyl-coenzyme A (Cr-CoA) as intervention reagents, histone Kcr and DKD-related indicators were detected. The results confirmed that NaCr had an antidiabetic effect and decreased blood glucose and serum lipid levels and alleviated renal function and DKD-related inflammatory and fibrotic damage. NaCr also induced histone Kcr and histone H3K18 crotonylation (H3K18cr). However, NaCr and Cr-CoA-induced histone Kcr and protective effects were reversed by inhibiting the activity of Acyl-CoA synthetase short-chain family member 2 (ACSS2) or histone acyltransferase P300 in vitro. In summary, our data reveal that NaCr may mitigate DKD via an antidiabetic effect as well as through ACSS2 and P300-induced histone Kcr, suggesting that Kcr may be the potential molecular mechanism and prevention target of DKD.

Manipulating the Rate and Overpotential for Electrochemical Water Oxidation: Mechanistic Insights for Cobalt Catalysts Bearing Noninnocent Bis(benzimidazole)pyrazolide Ligands.

Electrochemical water oxidation is known as the anodic reaction of water splitting. Efficient design and earth-abundant electrocatalysts are crucial to this process. Herein, we report a family of catalysts (1-3) bearing bis(benzimidazole)pyrazolide ligands (H 2 L1-H 2 L3). H 2 L3 contains electron-donating substituents and noninnocent components, resulting in catalyst 3 exhibiting unique performance. Kinetic studies show first-order kinetic dependence on [3] and [H2O] under neutral and alkaline conditions. In contrast to previously reported catalyst 1, catalyst 3 exhibits an insignificant kinetic isotope effect of 1.25 and zero-order dependence on [NaOH]. Based on various spectroscopic methods and computational findings, the L3Co2 III(µ-OH) species is proposed to be the catalyst resting state and the nucleophilic attack of water on this species is identified as the turnover-limiting step of the catalytic reaction. Computational studies provided insights into how the interplay between the electronic effect and ligand noninnocence results in catalyst 3 acting via a different reaction mechanism. The variation in the turnover-limiting step and catalytic potentials of species 1-3 leads to their catalytic rates being independent of the overpotential, as evidenced by Eyring analysis. Overall, we demonstrate how ligand design may be utilized to retain good water oxidation activity at low overpotentials.

Association of circulating long-chain free fatty acids and incident diabetes risk among normoglycemic Chinese adults: a prospective nested case-control study.

BACKGROUND: Long-chain free fatty acids (FFAs) are associated with risk of incident diabetes. However, a comprehensive assessment of the associations in normoglycemic populations is lacking. OBJECTIVES: Our study aimed to comprehensively investigate the prospective associations and patterns of FFA profiles with diabetes risk among normoglycemic Chinese adults. METHODS: This is a prospective nested case-control study from the China Cardiometabolic Disease and Cancer Cohort (4C) study. We quantitatively measured 53 serum FFAs using a targeted metabolomics approach in 1707 incident diabetes subjects and 1707 propensity score-matched normoglycemic controls. Conditional logistic regression models were employed to estimate odds ratios (ORs) for associations. Least Absolute Shrinkage and Selection Operator (LASSO) penalty regression and quantile g-computation (qg-comp) analyses were implemented to estimate the association between multi-FFA exposures and incident diabetes. RESULTS: The majority of odd-chain FFAs exhibited an inverse association with incident diabetes, wherein the ORs per SD increment of all 7 saturated fatty acids (SFAs), monounsaturated fatty acid (MUFA) 15:1, and polyunsaturated fatty acid (PUFA) 25:2 were ranging from 0.79 to 0.88 (95% CIs ranging between 0.71 and 0.97). Even-chain FFAs comprised 99.3% of total FFAs and displayed heterogeneity with incident diabetes. SFAs with 18-26 carbon atoms are inversely linked to incident diabetes, with ORs ranging from 0.81 to 0.86 (95% CIs ranging between 0.73 and 0.94). MUFAs 26:1 (OR: 0.85; 95% CI: 0.76, 0.94), PUFAs 20:4 (OR: 0.84; 95% CI: 0.75, 0.94), and 24:2 (OR: 0.87; 95% CI: 0.78, 0.97) demonstrated significant associations. In multi-FFA exposure model, 24 FFAs were significantly associated with incident diabetes, most of which were consistent with univariate results. The mixture OR was 0.78 (95% CI: 0.61, 0.99; P = 0.04159). Differential correlation network analysis revealed pre-existing perturbations in intraclass and interclass FFA coregulation before diabetes onset. CONCLUSIONS: These findings underscore the variations in diabetes risk associated with FFAs across chain length and unsaturation degree, highlighting the importance of recognizing FFA subtypes in the pathogenesis of diabetes.

Positive Association of Pulse Pressure with Presence of Albuminuria in Chinese Adults with Prediabetes: A Community-Based Study.

Purpose: There has been limited evidence for the association between pulse pressure (PP) and proteinuria in prediabetes. The aim of our study was to explore the association between PP and albuminuria in community-dwelling Chinese adults with prediabetes. Materials and Methods: PP and urinary albumin-to-creatinine ratio (ACR) were measured in 2012 prediabetic patients and 3596 control subjects with normal glucose tolerance. Multivariate logistic regression models were used to evaluate the possible association of PP with the risk of presence of albuminuria. Results: PP was positively associated with the presence of albuminuria, and subjects in the higher PP quartiles had higher urinary ACR and presence of albuminuria as compared with those in the lowest quartile in both prediabetes and control groups (all P < 0.01). Multivariate logistic regression analysis demonstrated that the highest PP quartile was positively associated with increased risk of presence of albuminuria in all prediabetic subjects [odds ratio (OR): 2.289, 95% confidence interval (CI) 1.364-3.842, P < 0.01) and prediabetic subjects without anti-hypertensive drugs (OR: 1.932, 95% CI 1.116-3.343, P < 0.01), whereas higher PP quartile has nothing to do with the risk of presence of albuminuria in control subjects with and without anti-hypertensive drugs after adjustment for potential confounders (all P > 0.01). Consistently, stratified analysis showed that in the prediabetes group, the risks of presence of albuminuria progressively elevated with increasing PP quartiles in men, those aged 60 years or older, and with overweight/obesity, normal high-density lipoprotein cholesterol, and appropriate low-density lipoprotein cholesterol (all P for trend <0.05). Conclusion: Higher PP is independently related to increased risk of presence of albuminuria in community-dwelling Chinese adults with prediabetes.

FedIOD: Federated Multi-Organ Segmentation From Partial Labels by Exploring Inter-Organ Dependency.

Multi-organ segmentation is a fundamental task and existing approaches usually rely on large-scale fully-labeled images for training. However, data privacy and incomplete/partial labels make those approaches struggle in practice. Federated learning is an emerging tool to address data privacy but federated learning with partial labels is under-explored. In this work, we explore generating full supervision by building and aggregating inter-organ dependency based on partial labels and propose a single-encoder-multi-decoder framework named FedIOD. To simulate the annotation process where each organ is labeled by referring to other closely-related organs, a transformer module is introduced and the learned self-attention matrices modeling pairwise inter-organ dependency are used to build pseudo full labels. By using those pseudo-full labels for regularization in each client, the shared encoder is trained to extract rich and complete organ-related features rather than being biased toward certain organs. Then, each decoder in FedIOD projects the shared organ-related features into a specific space trained by the corresponding partial labels. Experimental results based on five widely-used datasets, including LiTS, KiTS, MSD, BCTV, and ACDC, demonstrate the effectiveness of FedIOD, outperforming the state-of-the-art approaches under in-federation evaluation and achieving the second-best performance under out-of-federation evaluation for multi-organ segmentation from partial labels.

Cross-and-Diagonal Networks: An Indirect Self-Attention Mechanism for Image Classification.

In recent years, computer vision has witnessed remarkable advancements in image classification, specifically in the domains of fully convolutional neural networks (FCNs) and self-attention mechanisms. Nevertheless, both approaches exhibit certain limitations. FCNs tend to prioritize local information, potentially overlooking crucial global contexts, whereas self-attention mechanisms are computationally intensive despite their adaptability. In order to surmount these challenges, this paper proposes cross-and-diagonal networks (CDNet), innovative network architecture that adeptly captures global information in images while preserving local details in a more computationally efficient manner. CDNet achieves this by establishing long-range relationships between pixels within an image, enabling the indirect acquisition of contextual information. This inventive indirect self-attention mechanism significantly enhances the network's capacity. In CDNet, a new attention mechanism named "cross and diagonal attention" is proposed. This mechanism adopts an indirect approach by integrating two distinct components, cross attention and diagonal attention. By computing attention in different directions, specifically vertical and diagonal, CDNet effectively establishes remote dependencies among pixels, resulting in improved performance in image classification tasks. Experimental results highlight several advantages of CDNet. Firstly, it introduces an indirect self-attention mechanism that can be effortlessly integrated as a module into any convolutional neural network (CNN). Additionally, the computational cost of the self-attention mechanism has been effectively reduced, resulting in improved overall computational efficiency. Lastly, CDNet attains state-of-the-art performance on three benchmark datasets for similar types of image classification networks. In essence, CDNet addresses the constraints of conventional approaches and provides an efficient and effective solution for capturing global context in image classification tasks.

Glucose regulation of adipose tissue browning by CBP/p300- and HDAC3-mediated reversible acetylation of CREBZF.

Glucose is required for generating heat during cold-induced nonshivering thermogenesis in adipose tissue, but the regulatory mechanism is largely unknown. CREBZF has emerged as a critical mechanism for metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD). We investigated the roles of CREBZF in the control of thermogenesis and energy metabolism. Glucose induces CREBZF in human white adipose tissue (WAT) and inguinal WAT (iWAT) in mice. Lys208 acetylation modulated by transacetylase CREB-binding protein/p300 and deacetylase HDAC3 is required for glucose-induced reduction of proteasomal degradation and augmentation of protein stability of CREBZF. Glucose induces rectal temperature and thermogenesis in white adipose of control mice, which is further potentiated in adipose-specific CREBZF knockout (CREBZF FKO) mice. During cold exposure, CREBZF FKO mice display enhanced thermogenic gene expression, browning of iWAT, and adaptive thermogenesis. CREBZF associates with PGC-1α to repress thermogenic gene expression. Expression levels of CREBZF are negatively correlated with UCP1 in human adipose tissues and increased in WAT of obese ob/ob mice, which may underscore the potential role of CREBZF in the development of compromised thermogenic capability under hyperglycemic conditions. Our results reveal an important mechanism of glucose sensing and thermogenic inactivation through reversible acetylation.

Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

The clinical value of iodine-125 seed implantation in the treatment of iodine-refractory differentiated thyroid carcinoma.

Objective: To explore the clinical benefits of 125I seed implantation for iodine-refractory differentiated thyroid cancer (RAIR-DTC). Methods: A retrospective analysis was conducted on 36 patients with RAIR-DTC who underwent radioactive 125I seed implantation from January 2015 to February 2022, involving 73 lesions. Prescription dose: 80~120 Gy. All cases were followed up at 1, 3, and 5 months postoperatively to monitor changes in tumor size, serum thyroglobulin (Tg), and serum anti-thyroglobulin antibody levels in thyrotropin-inhibited states, pain scores, and postoperative adverse reactions. The data were processed and analyzed using IBM SPSS 26.0. LER (Local Effective Rate) and LCR (Local Control Rate) were expressed as n (%), tumor diameter, Tg, and pain scores were represented as Median (Q1, Q3). Pairwise comparisons were conducted using the Wilcoxon signed-rank test, and a p-value of less than 0.05 indicated statistical significance. Results: Tumor size was significantly reduced after treatment (all P < 0.001): tumor length diameters were 32.67 (17.70, 45.72) mm, 27.45 (12.30, 39.98) mm, 20.70 (11.98, 37.58) mm, and 20.39 (10.56, 33.20) mm in the preoperative, 1-, 3-, and 5-months postoperative periods, respectively. Additionally, two consecutive post-treatment results were more minor and statistically significant than the previous results (P < 0.001). The LER at 1-, 3-, and 5-months post-surgery was 23.73%, 38.98%, and 52.54%, respectively, while the LCR at the same time points was 98.31%, 96.61%, and 94.92%, respectively. Patients' serum Tg levels decreased significantly after surgery. (P < 0.001). Serum Tg levels were measured before surgery and 1-, 3-, and 5-months post-surgery. The results showed that serum Tg levels were 249.45 (79.39, 4718.75) ng/ml, 193.40 (44.53, 2829.00) ng/ml, 192.10 (25.58, 1758.00) ng/ml, and 136.25 (16.57, 1553.25) ng/ml, respectively. Two consecutive post-treatment results were more minor and statistically significant than the previous results (P < 0.001). The patients' pain symptoms were significantly relieved after 125I brachytherapy (P < 0.001). The pain scores before 125I seed implantation and at 1, 3, and 5 months after the operation were 5.00 (4.00, 6.00), 3.00 (2.25, 4.00), 2.00 (2.00, 3.00), and 2.00 (1.00, 3.00), respectively. Conclusion: Most lesions treated with 125I seed implantation in RAIR-DTC patients showed shrinkage and improved pain symptoms. Clinical trial registration: https://www.clinicaltrials.gov, identifier NCT06362772.