Generalization of a Deep Learning Model for Continuous Glucose Monitoring-Based Hypoglycemia Prediction: Algorithm Development and Validation Study.

Background: Predicting hypoglycemia while maintaining a low false alarm rate is a challenge for the wide adoption of continuous glucose monitoring (CGM) devices in diabetes management. One small study suggested that a deep learning model based on the long short-term memory (LSTM) network had better performance in hypoglycemia prediction than traditional machine learning algorithms in European patients with type 1 diabetes. However, given that many well-recognized deep learning models perform poorly outside the training setting, it remains unclear whether the LSTM model could be generalized to different populations or patients with other diabetes subtypes. Objective: The aim of this study was to validate LSTM hypoglycemia prediction models in more diverse populations and across a wide spectrum of patients with different subtypes of diabetes. Methods: We assembled two large data sets of patients with type 1 and type 2 diabetes. The primary data set including CGM data from 192 Chinese patients with diabetes was used to develop the LSTM, support vector machine (SVM), and random forest (RF) models for hypoglycemia prediction with a prediction horizon of 30 minutes. Hypoglycemia was categorized into mild (glucose=54-70 mg/dL) and severe (glucose<54 mg/dL) levels. The validation data set of 427 patients of European-American ancestry in the United States was used to validate the models and examine their generalizations. The predictive performance of the models was evaluated according to the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: For the difficult-to-predict mild hypoglycemia events, the LSTM model consistently achieved AUC values greater than 97% in the primary data set, with a less than 3% AUC reduction in the validation data set, indicating that the model was robust and generalizable across populations. AUC values above 93% were also achieved when the LSTM model was applied to both type 1 and type 2 diabetes in the validation data set, further strengthening the generalizability of the model. Under different satisfactory levels of sensitivity for mild and severe hypoglycemia prediction, the LSTM model achieved higher specificity than the SVM and RF models, thereby reducing false alarms. Conclusions: Our results demonstrate that the LSTM model is robust for hypoglycemia prediction and is generalizable across populations or diabetes subtypes. Given its additional advantage of false-alarm reduction, the LSTM model is a strong candidate to be widely implemented in future CGM devices for hypoglycemia prediction.

Correlation Between Blood Urea Nitrogen and Short- and Long-Term Glycemic Variability in Elderly Patients with Type 2 Diabetes Mellitus Who Were hospitalized:A Retrospective Study.

Objective: Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by insulin resistance and progressively impaired insulin secretion resulting in dynamic fluctuations in glucose levels.High blood urea nitrogen (BUN) levels have been linked to decreased insulin sensitivity, suppressed insulin synthesis and increased risk of incident diabetes mellitus in humans as well as insulin use in patients with T2DM.This study characterize the association between BUN levels and short-term and long-term glycemic variability(GV) in the elderly patients with T2DM who were hospitalized. Methods: A total of 927 elderly patients with T2DM were included in the study. The short-term GV was quantified using parameters such as standard deviation (SD), coefficient of variation (CV), time in range (TIR), and mean amplitude of glycemic excursions (MAGE), based on multi-point fingertip blood glucose monitoring. The long-term GV was quantified using parameters such as SD, CV, variation independent of the mean (VIM), and average successive variability (ARV), based on fasting blood glucose(FPG). The relationship between BUN levels and short-term and long-term GV in elderly T2DM who were hospitalized was explored using methods such as Spearman correlation coefficient, linear regression analysis, logistic regression analysis, and interaction tests. Results: In elderly patients with T2DM were hospitalized, there is a significant correlation between BUN levels and both short-term and long-term GV. BUN is negatively correlated with the GV parameter TIR (r=-0.12, P=0.000), and positively correlated with SD (r=0.12, P=0.000), CV (r=0.07, P=0.026), MAGE (r=0.11, P=0.001), FPG-SD (r=0.08, P=0.013), and FPG-CV (r=0.08, P=0.014).Furthermore, the association remains consistent across different age, gender, BMI, and haemoglobin A1c (HbA1c) subgroups (P interaction > 0.05). Conclusion: In elderly patients with T2DM were hospitalized, BUN levels were positively associated with GV.Therefore, monitoring BUN levels were beneficial in assessing the degree of GV.

Reduced sensitivity to thyroid hormones is associated with lung function in euthyroid individuals.

Background: The thyroid gland exhibits a subtle interconnection with the lungs. We further investigated the correlation between thyroid hormone sensitivity and lung function in euthyroid individuals. Methods: Data on spirometry and mortality for participants aged 19-79 years were extracted from the NHANES database. Obstructive lung function was defined as a forced expiratory volume in 1 s to forced vital capacity ratio (FEV1/FVC) < 0.70, while restrictive lung function was considered when FEV1/FVC ≥0.70 and baseline FVC <80 % predicted. Central and peripheral sensitivities to thyroid hormones were mainly evaluated by Thyroid Feedback Quantile-based Index (TFQI) and Free Triiodothyronine/Free thyroxine (FT3/FT4) ratio. Logistic regression and subgroup analysis were used to examine potential associations between thyroid hormone sensitivity and lung function. The association between TFQI and all-cause mortality risk was also investigated. Results: A total of 6539 participants were analyzed, 900 with obstructive lung function and 407 with restrictive lung function. The prevalence of impaired lung function, both obstructive and restrictive, increased with higher TFQI levels. Logistic regression analysis showed that increased TFQI and decreased FT3/FT4 levels were independent risk factors for obstructive and restrictive lung function (P < 0.05). After adjusting for the impact of lung function, TFQI (HR = 1.25, 95 % CI 1.00-1.56, P = 0.048) was an independent risk factor for all-cause mortality. Conclusion: Reduced sensitivity to thyroid hormones has been linked to impaired lung function. TFQI and FT3/FT4 are potential epidemiological tools to quantify the role of central and peripheral thyroid resistance in lung function.

Association Between Remnant Cholesterol and Risk of Hyperuricemia: A Cross-Sectional Study.

Remnant cholesterol (RC) is closely related to metabolic diseases. Our study aims to explore the relationship between RC and hyperuricemia. This cross-sectional study included 14 568 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2018 in the United States. RC is calculated by subtracting high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c) from total cholesterol (TC). Hyperuricemia is defined by serum uric acid (SUA) levels≥7 mg/dl in men and≥6 mg/dl in women. The independent association between RC and hyperuricemia was evaluated. As the quartile range of RC levels increases, the prevalence of hyperuricemia also rises (7.84% vs. 13.71% vs. 18.61% vs. 26.24%, p<0.001). After adjusting for confounding factors, the fourth quartile of RC was associated with an increased risk of hyperuricemia compared with the first quartile (OR=2.942, 95% CI 2.473-3.502, p<0.001). Receiver Operating Characteristic (ROC) analysis shows that RC outperforms other single lipid indices in hyperuricemia. Further Restricted Cubic Splines (RCS) analysis suggests a nonlinear relationship between RC levels and hyperuricemia. Elevated RC levels were found to be linked to hyperuricemia. Further studies on RC hold promise for both preventing and addressing hyperuricemia.

The relationship between weight-adjusted-waist index and diabetic kidney disease in patients with type 2 diabetes mellitus.

Purpose: Obesity, particularly abdominal obesity, is seen as a risk factor for diabetic complications. The weight-adjusted-waist index (WWI) is a recently developed index for measuring adiposity. Our goal was to uncover the potential correlation between the WWI index and diabetic kidney disease (DKD) risk. Methods: This cross-sectional study included adults with type 2 diabetes mellitus (T2DM) who participated in the NHANES database (2007-2018). The WWI index was calculated as waist circumference (WC, cm) divided by the square root of weight (kg). DKD was diagnosed based on impaired estimated glomerular filtration rate (eGFR<60 mL/min/1.73m2), albuminuria (urinary albumin to urinary creatinine ratio>30 mg/g), or both in T2DM patients. The independent relationship between WWI index and DKD risk was evaluated. Results: A total of 5,028 participants with T2DM were included, with an average WWI index of 11.61 ± 0.02. As the quartile range of the WWI index increased, the prevalence of DKD gradually increased (26.76% vs. 32.63% vs. 39.06% vs. 42.96%, P<0.001). After adjusting for various confounding factors, the WWI index was independently associated with DKD risk (OR=1.32, 95%CI:1.12-1.56, P<0.001). The area under the ROC curve (AUC) of the WWI index was higher than that of body mass index (BMI, kg/m2) and WC. Subgroup analysis suggested that the relationship between the WWI index and DKD risk was of greater concern in patients over 60 years old and those with cardiovascular disease. Conclusions: Our findings suggest that higher WWI levels are linked to DKD in T2DM patients. The WWI index could be a cost-effective and simple way to detect DKD, but further prospective studies are needed to confirm this.

Atomic-Level Matching Metal-Ion Organic Hybrid Interface to Enhance Energy Storage of Polymer-Based Composite Dielectrics.

In this work, a distinctive "metal-ion organic hybrid interface" (MOHI) between polyimide (PI) and calcium niobate (CNO) nanosheets is designed. The metal ions in the MOHI can achieve atomic-level matching not only with the inorganic CNO, but also with the PI chains, forming uniform and strong chemical bonds. These results are demonstrated by experiment and theory calculations. Significantly, the MOHI reduces the free volume and introduces deep traps across the filler-matrix interfacial area, thus suppressing the electric field distortion in PI-based composite dielectrics. Consequently, PI-based dielectric containing the MOHI exhibits excellent energy storage performance. The energy storage densities (Ue) of the composite dielectric reach 9.42 J cm-3 and 4.75 J cm-3 with energy storage efficiency (η) of 90% at 25 °C and 150 °C respectively, which are 2.6 and 11.6 times higher than those of pure PI. This study provides new ideas for polymer-based composite dielectrics in high energy storage.

Effect of emerging digital technologies and methodologies combined with incentives on HbA1c in patients with type 2 diabetes mellitus: study protocol for a parallel, open randomized controlled trial.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a common metabolic disease that requires long-term management and treatment. Digital intervention, as an emerging medical model, has been widely used in the treatment of T2DM patients. Behavioral economics theory provides a favorable perspective for studying the effect of digital intervention because it can reveal the decision-making mechanisms behind human behavior and provide more effective interventions for digital intervention. The purpose of this trial is to evaluate the impact of behaviorally based digital intervention on T2DM patients' HbA1c, self-monitoring of blood glucose (SMBG) testing rate, diabetes self-efficacy, and other indicators compared to conventional treatment. METHODS: This trial is a prospective randomized controlled trial conducted at the First People's Hospital of Kunshan City from April 1, 2023, to December 31, 2024, with a follow-up period of 3 months. The specific randomization method was established and implemented through the EDC clinical trial center's randomization system. We will measure and collect baseline data from three groups, including Group A: digital intervention + virtual incentives + conventional treatment, Group B: digital intervention + physical incentives + conventional treatment, and Group C: conventional treatment. HbA1c, weight, SMBG testing rate, diabetes self-efficacy, and diabetes-related medical expenses will be recorded at baseline, 1 month, 2 months, and 3 months for all three groups. The Shapiro-Wilk test will be used to test for normality, and Pearson correlation analysis will be used for correlation analysis. Dropouts will be analyzed separately. Analysis of variance or exact probability calculation will be used to compare demographic data and other baseline indicators. DISCUSSION: This study is a novel clinical trial that integrates multiple disciplines (economics and medicine) and uses digital technology to deliver the intervention. Most published studies were offline interventions based on behavioral economics theory, but very few were on online interventions for T2DM patients. This study has both novelty and social value. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300070753. Registered on 2023/04/22.

Causal relationships between circulating inflammatory cytokines and diabetic neuropathy: A Mendelian Randomization study.

BACKGROUND: Emerging evidence suggests systemic inflammation as a critical mechanism underlying diabetic neuropathy. This study aimed to investigate the causal relationship between 41 circulating inflammatory cytokines and diabetic neuropathy. METHODS: Summary statistics from previous Genome-Wide Association studies (GWAS) included pooled data on 41 inflammatory cytokines and diabetic neuropathy. A two-sample Mendelian Randomization (MR) design was employed, and the robustness of the results was confirmed through comprehensive sensitivity analyses. RESULTS: Our study reveals that the linkage between increased levels of IFN_G (OR = 1.31, 95 %CI: 1.06-1.63; P = 0.014), IP_10 (OR = 1.18, 95 %CI: 1.01-1.36; P = 0.031) and an elevated risk of diabetic neuropathy. Conversely, higher levels of IL_9 (OR = 0.86, 95 %CI: 0.75-1.00; P = 0.048) and SCF (OR = 0.83, 95 %CI: 0.73-0.94; P = 0.003) are genetically determined to protect against diabetic neuropathy. Furthermore, the sensitivity analysis affirmed the results' dependability, revealing no heterogeneity or pleiotropy. CONCLUSION: Our MR research identified four upstream inflammatory cytokines implicated in diabetic neuropathy. Overall, these findings suggest the potential for innovative therapeutic strategies. Further large-scale cohort studies are required for validation.

Impaired sensitivity to thyroid hormones is associated with albuminuria in the euthyroid population: results from NHANES.

PURPOSE: The relationship between thyroid hormone sensitivity and albuminuria remains unclear. We aimed to investigate the association between thyroid hormone sensitivity and the risk of albuminuria in a euthyroid population. METHODS: This cross-sectional study included 7634 euthyroid adults collected from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2012. Central sensitivity to thyroid hormones was evaluated using the thyroid-stimulating hormone index (TSHI), the thyrotrophic thyroxine resistance index (TT4RI), and the thyroid feedback quantile-based index (TFQI). Peripheral sensitivity to thyroid hormones was measured using the free triiodothyronine/free thyroxine (FT3/FT4) ratio. Furthermore, the independent relationship between sensitivity to thyroid hormones and albuminuria was assessed. RESULTS: The proportion of albuminuria increased with a higher interquartile range of TFQI levels (7.31% vs. 7.89% vs. 7.95% vs. 9.89%, P = 0.024). Furthermore, TFQI was found to be independently associated with the risk of albuminuria after adjusting for confounding factors (OR = 1.28, 95% CI 1.01-1.60, P = 0.037). Subgroup analysis revealed a significant relationship between TFQI and albuminuria, especially among individuals over 60. CONCLUSIONS: In euthyroid subjects, impaired central sensitivity to thyroid hormones is associated with albuminuria. TFQI holds significant potential as an epidemiological tool for quantifying the impact of impaired central sensitivity on the risk of albuminuria.

Identification of Senescence-Associated Biomarkers in Diabetic Glomerulopathy Using Integrated Bioinformatics Analysis.

Background: Cellular senescence is thought to play a significant role in the onset and development of diabetic nephropathy. The goal of this study was to explore potential biomarkers associated with diabetic glomerulopathy from the perspective of senescence. Methods: Datasets about human glomerular biopsy samples related to diabetic nephropathy were systematically obtained from the Gene Expression Omnibus database. Hub senescence-associated genes were investigated by differential gene analysis and Least Absolute Shrinkage and Selection Operator analysis. Cluster analysis was employed to identify senescence molecular subtypes. A single-cell dataset was used to validate the above findings and further evaluate the senescence environment. The relationship between these genes and the glomerular filtration rate was explored based on the Nephroseq database. These gene expressions have also been explored in various kidney diseases. Results: Twelve representative senescence-associated genes (VEGFA, IQGAP2, JUN, PLAT, ETS2, ANG, MMP14, VEGFC, SERPINE2, CXCR2, PTGES, and EGF) were finally identified. Biological changes in immune inflammatory response, cell cycle regulation, metabolic regulation, and immune microenvironment have been observed across different molecular subtypes. The above results were also validated based on single-cell analysis. Additionally, we also identified several significantly altered cell communication pathways, including COLLAGEN, PTN, LAMININ, SPP1, and VEGF. Finally, almost all these genes could well predict the occurrence of diabetic glomerulopathy based on receiver operating characteristic analysis and are associated with the glomerular filtration rate. These genes are differently expressed in various kidney diseases. Conclusion: The present study identified potential senescence-associated biomarkers and further explored the heterogeneity of diabetic glomerulopathy that might provide new insights into the diagnosis, assessment, management, and personalized treatment of DN.

Causal relationships between gut microbiota and hypothyroidism: a Mendelian randomization study.

BACKGROUND: Previous studies have shown that the gut microbiota plays an important role in the maintenance of thyroid homeostasis. We aimed to evaluate the causal relationships between gut microbiota and hypothyroidism. METHODS: Summary statistics for 211 gut microbiota taxa were obtained from the largest available genome-wide association study (GWAS) meta-analysis conducted by the MiBioGen consortium. Summary statistics for hypothyroidism were obtained from two distinct sources: the FinnGen consortium R9 release data (40,926 cases and 274,069 controls) and the UK Biobank data (22,687 cases and 440,246 controls), respectively. A two-sample Mendelian randomization (MR) design was employed, and thorough sensitivity analyses were carried out to ensure the reliability of the results. RESULTS: Based on the FinnGen consortium, we found increased levels of Intestinimonas (OR = 1.09; 95%CI = 1.02-1.16; P = 0.01) and Ruminiclostridium5 (OR = 1.11; 95%CI = 1.02-1.22; P = 0.02) may be associated with a higher risk of hypothyroidism, while increased levels of Butyrivibrio (OR = 0.95; 95%CI = 0.92-0.99; P = 0.02), Eggerthella (OR = 0.93; 95%CI = 0.88-0.98; P = 0.01), Lachnospiraceae UCG008 (OR = 0.92; 95%CI = 0.85-0.99; P = 0.02), Ruminococcaceae UCG011 (OR = 0.95; 95%CI = 0.90-0.99; P = 0.02), and Actinobacteria (OR = 0.88; 95%CI = 0.80-0.97; P = 0.01) may be associated with a lower risk. According to the UK Biobank data, Eggerthella and Ruminiclostridium5 remain causally associated with hypothyroidism. The sensitivity analysis demonstrates consistent results without evidence of heterogeneity or pleiotropy. CONCLUSION: This study highlights the impact of specific gut microbiota on hypothyroidism. Strategies to change composition of gut microbiota may hold promise as potential interventions.

High-Temperature Polymer Dielectrics Designed Using an Invertible Molecular Graph Generative Model.

Generating new molecules with the desired physical or chemical properties is the key challenge of computational material design. Deep learning techniques are being actively applied in the field of data-driven material informatics and provide a promising way to accelerate the discovery of innovative materials. In this work, we utilize an invertible graph generative model to generate hypothetical promising high-temperature polymer dielectrics. A molecular graph generative model based on the invertible normalizing flow is trained on a data set containing 250k polymer molecular graphs (mostly generated by an RNN-based generative model) to learn the invertible transformations between latent distributions and molecular graph structures. When generating molecular graphs, a sample vector is drawn from the latent space, and then an adjacency tensor and node attribute matrix are generated through two invertible flows in two steps and assembled into a molecular graph. The model has the merits of exact likelihood training and an efficient one-shot generation process. The learned latent space is used to generate polymers with a high glass-transition temperature (Tg) and a wide band gap (Eg) for the application of high-temperature energy storage film capacitors. This work contributes to the efficient design of high-temperature polymer dielectrics by using deep generative models.

The relationship between triglyceride-glucose index and albuminuria in United States adults.

Purpose: Triglyceride-glucose (TyG) index is a simple and reliable indicator of metabolic dysfunction. We aimed to investigate a possible relationship between TyG index and albuminuria in the United States adult population. Methods: This cross-sectional study was conducted among adults with complete TyG index and urinary albumin/urinary creatinine (UACR) from 2011-2018 National Health and Nutrition Examination Survey (NHANES). The independent relationship between TyG index and albuminuria (UACR>30mg/g) was evaluated. TyG index was compared with insulin resistance represented by homeostatic model assessment of insulin resistance (HOMA-IR), and metabolic syndrome. Subgroup analysis was also performed. Results: A total of 9872 participants were included in this study, and the average TyG index was 8.53 ± 0.01. The proportion of albuminuria gradually increased with the increase of TyG index quartile interval. Elevated TyG index was independently associated with albuminuria, and this association persisted after additional adjustments for HOMA-IR or dichotomous metabolic syndrome. The area under the ROC curve (AUC) of TyG index was larger than that of log (HOMA-IR). Subgroup analysis suggested that the relationship between TyG index and albuminuria is of greater concern in age<60, overweight/obese, diabetic, and metabolic syndrome patients. Conclusion: The TyG index may be a potential epidemiological tool to quantify the role of metabolic dysfunction, rather than just insulin resistance, in albuminuria in the United States adult population. Further large-scale prospective studies are needed to confirm our findings.

PMAT variant rs3889348 is associated with metformin-induced gastrointestinal among Chinese Type 2 diabetes patients.

Aim: This study examined intronic gene variants for their association with metformin intolerance in a Chinese population, focusing on the plasma monoamine transporter (PMAT) cis-protein expression quantitative trait loci (cis-eQTL) variant rs3889348. Methods: We recruited Type 2 diabetes patients from two hospitals and identified 111 metformin-intolerant patients using a questionnaire, and selected 206 metformin-tolerant patients from 2180 Type 2 diabetes mellitus patients. Genetic testing revealed an association between adverse gastrointestinal (GI) effects and SLC22A1 and PMAT. Results: The single-nucleotide polymorphism rs3889348 is associated with metformin-induced adverse GI effects. Each additional copy of the G allele increases the score by 5.23 (95% CI: 1.82-8.64; p = 0.003). Patients taking more transporter inhibitors were more likely to respond to metformin-induced GI intolerance (p = 0.042). Conclusion: PMAT cis-eQTL rs3889348 was significantly associated with metformin-induced adverse GI effects.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review.

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Identification of Basement Membrane Genes and Related Molecular Subtypes in Nonalcoholic Fatty Liver Disease.

Basement membranes (BMs) are widely distributed and highly specialized extracellular matrix (ECM). The goal of this study was to explore novel genes associated with nonalcoholic fatty liver disease (NAFLD) from the perspective of BMs. Sequencing results of 304 liver biopsy samples about NAFLD were systematically obtained from the Gene Expression Omnibus (GEO) database. Biological changes during NAFLD progression and hub BM-associated genes were investigated by differential gene analysis and weighted gene co-expression network analysis (WGCNA), respectively. The nonalcoholic steatohepatitis (NASH) subgroups were identified based on hub BM-associated genes expression, as well as the differences in Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and immune microenvironment between different subgroups were compared. Extracellular matrix (ECM) seems to play an important role in the development of NAFLD. Three representative BM-associated genes (ADAMTS2, COL5A1, and LAMC3) were finally identified. Subgroup analysis results suggested that there were significant changes in KEGG signaling pathways related to metabolism, extracellular matrix, cell proliferation, differentiation, and death. There were also changes in macrophage polarization, neutrophils, and dendritic cells abundance, and so on. In conclusion, the present study identified novel potential BM-associated biomarkers and further explored the heterogeneity of NASH that might provide new insights into the diagnosis, assessment, management, and personalized treatment of NAFLD.

A Bilayer High-Temperature Dielectric Film with Superior Breakdown Strength and Energy Storage Density.

The further electrification of various fields in production and daily life makes it a topic worthy of exploration to improve the performance of capacitors for a long time, including thin-film capacitors. The discharge energy density of thin-film capacitors that serves as one of the important types directly depends on electric field strength and the dielectric constant of the insulation material. However, it has long been a great challenge to improve the breakdown strength and dielectric constant simultaneously. Considering that boron nitride nanosheets (BNNS) possess superior insulation and thermal conductivity owing to wide band gap and 2-dimensional structure, a bilayer polymer film is prepared via coating BNNS by solution casting on surface of polyethylene terephthalate (PET) films. By revealing the bandgap and insulating behavior with UV absorption spectrum, leakage current, and finite element calculation, it is manifested that nanocoating contributes to enhance the bandgap of polymer films, thereby suppressing the charge injection by redirecting their transport from electrodes. Worthy to note that an ultrahigh breakdown field strength (~ 736 MV m-1), an excellent discharge energy density (~ 8.77 J cm-3) and a prominent charge-discharge efficiency (~ 96.51%) are achieved concurrently, which is ascribed to the contribution of BNNS ultrathin layer. In addition, the modified PET films also have superior comprehensive performance at high temperatures (~ 120 °C). The materials and methods here selected are easily accessible and facile, which are suitable for large-scale roll-to-roll process production, and are of certain significance to explore the methods about film modification suitable for commercial promotion.

Effects of metabolic factors in mediating the relationship between Type 2 diabetes and depression in East Asian populations: A two-step, two-sample Mendelian randomization study.

BACKGROUND: Observational studies suggested a close link between type 2 diabetes (T2D), metabolic factors and depression, while the causal relationships remained poorly understood. OBJECTIVE: To determine the causality between T2D and depression, and to investigate the roles of metabolic factors in mediating the relationship between T2D and depression in East Asians. METHODS: Using summary statistics from the largest and most up-to-date genome-wide association studies of depression (12,588 cases and 85,914 controls) and T2D (36,614 cases and 155,150 controls) among East Asians, two-step and two-sample MR analyses were performed to estimate the causal mediation effects of metabolic factors including lipid profiles, blood pressure (BP) and fasting insulin (FI) on the relationship between T2D and depression. RESULTS: Genetically predicted T2D was significantly associated with depression (OR [95 % CI]:1.06 [1.01, 1.11], P = 0.043), but not vice versa. T2D was causally associated with lower levels of HDL-C and higher levels of LDL-C, triglycerides (TG), BP and FI. Furthermore, the causal effects of T2D on depression were significantly mediated by LDL-C (ß [95 % CI]: -0.003 [-0.005, -0.001], P = 0.007), and suggestively mediated by TG (0.001 [0.001, 0.003], P = 0.049) and FI (0.006 [0.001, 0.012], P = 0.049). LIMITATIONS: First, depression was defined by several methods, like symptom questionnaires or self-completed surveys. Second, two-sample MR approach is unable to detect the non-linear causal relationships. Third, independent data sets were not available for replication of our findings. CONCLUSION: T2D was causally associated with the risk of depression, and LDL-C, TG, and FI were potential causal mediators of the effect of T2D on depression. Understanding the causality among T2D, metabolic factors and depression is crucial for identifying potential targets for early intervention.

Effect of cognitive behavior therapy (CBT) on lowering of blood glucose levels in gestational diabetes mellitus (GDM) patients: study protocol for a prospective, open-label, randomized controlled trial.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common perinatal condition. Convincing evidence has shown that hyperglycemia and other chronic comorbidities of diabetes during the prenatal period increase maternal and fetal risk. Several guidelines have identified lifestyle management as the first-line therapy in GDM patients. To improve the efficacy of lifestyle intervention, cognitive behavior therapy (CBT) is proposed as a solution to improve clinical outcomes. The objective of this trial is to determine the efficacy in treating hyperglycemia of mobile-based CBT interventions in GDM patients, compared with conventional face-to-face interventions.  METHODS: This trial is designed as a prospective randomized controlled trial, which enrolled the patients diagnosed with GDM in First People's Hospital of Kunshan affiliated with Jiangsu University from September 2021 to March 2023 with a 3-month follow-up. The specific randomization method was established and implemented through the central randomization system of EDC clinical trials. The percentage of all blood glucose levels collected within the normal range between the two groups at baseline, during the intervention period, and postpartum infant and maternal outcomes will be measured. Summary statistics for continuous variables will include the number of subjects, mean, median, SD, or the standard error, minimum, and maximum. The chi-square test, t test, and paired-sample t test were used for statistical analysis of differences between groups. DISCUSSION: This trial investigates the effects of mobile-based CBT intervention on blood glucose levels in GDM patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR2100048527) [registered: 2021/07/09].

Enhanced High-Temperature Capacitive Performance of a Bilayer-Structured Composite Film Employing a Charge Blocking Layer.

The great development potential of polymer dielectric capacitors in harsh environments urgently requires enhancing capacitive performance at high temperatures. However, the exponentially increased conduction loss at high temperature and high field results in a drastic drop in energy density and charge-discharge efficiency. Here, a bilayer-structured polyimide (PI) composite film containing a wide-band gap inorganic layer as a charge blocking layer is designed. The inorganic layer improves the charge trapping ability and regulates the charge mobility at the electrode/dielectric interface. The charge injection mechanism in the interface-optimized PI/boron nitride nanosheet (BNNS) composite films is investigated by finite element simulation, and the effect of the BNNS layer on high temperature conduction is further understood. An appropriate thickness of the charge blocking layer establishes an effective energy barrier. Therefore, the composite films exhibit significantly suppressed conduction loss and excellent capacitive performance at a high temperature. A high energy density of 4.37 J cm-3 with efficiency of 92% is obtained at 200 °C and 500 MV m-1, which is superior to reported high-temperature dielectric polymers and their composite films. This work provides a promising approach to improve the energy storage performance of polymer materials at high temperatures.