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.

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.

Recent Progress and Future Prospects on All-Organic Polymer Dielectrics for Energy Storage Capacitors.

With the development of advanced electronic devices and electric power systems, polymer-based dielectric film capacitors with high energy storage capability have become particularly important. Compared with polymer nanocomposites with widespread attention, all-organic polymers are fundamental and have been proven to be more effective choices in the process of scalable, continuous, and large-scale industrial production, leading to many dielectric and energy storage applications. In the past decade, efforts have intensified in this field with great progress in newly discovered dielectric polymers, fundamental production technologies, and extension toward emerging computational strategies. This review summarizes the recent progress in the field of energy storage based on conventional as well as heat-resistant all-organic polymer materials with the focus on strategies to enhance the dielectric properties and energy storage performances. The key parameters of all-organic polymers, such as dielectric constant, dielectric loss, breakdown strength, energy density, and charge-discharge efficiency, have been thoroughly studied. In addition, the applications of computer-aided calculation including density functional theory, machine learning, and materials genome in rational design and performance prediction of polymer dielectrics are reviewed in detail. Based on a comprehensive understanding of recent developments, guidelines and prospects for the future development of all-organic polymer materials with dielectric and energy storage applications are proposed.

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.

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.

Hydrolytic transformation mechanism of tetracycline antibiotics: Reaction kinetics, products identification and determination in WWTPs.

Antibiotic residues and antibiotic resistance have been widely reported in aquatic environments. Hydrolysis of antibiotics is one of the important environmental processes. Here we investigated the hydrolytic transformation of four tetracycline antibiotics i.e. tetracycline (TC), chlortetracycline (CTC), oxytetracycline (OTC) and doxycycline (DC) under different environmental conditions, and determined their parents and transformation products in the wastewater treatment plants (WWTPs). The results showed that the hydrolysis of the four tetracyclines followed first-order reaction kinetics, and the acid-catalyzed hydrolysis rates were significantly lower than the base-catalyzed and neutral pH hydrolysis rates. The effect of temperature on tetracycline hydrolysis was quantified by Arrhenius equation, with Ea values ranged from 42.0 kJ mol-1 to 77.0 kJ mol-1 at pH 7.0. In total, nine, six, eight and nine transformation products at three different pH conditions were identified for TC, CTC, OTC and DC, respectively. The main hydrolysis pathways involved the epimerization/isomerization, and dehydration. According to the mass balance analysis, 4-epi-tetracycline and iso-chlortetracycline were the main hydrolytic products for TC and CTC, respectively. The 2 tetracyclines and 4 hydrolysis products were found in the sludge samples in two WWTPs, with concentrations from 15.8 ng/g to 1418 ng/g. Preliminary toxicity evaluation for the tetracyclines and their hydrolysis products showed that some hydrolysis products had higher predicted toxicity than their parent compounds. These results suggest that the hydrolysis products of tetracycline antibiotics should also be included in environmental monitoring and risk assessment.

All-Organic Dielectrics with High Breakdown Strength and Energy Storage Density for High-Power Capacitors.

Polymer-based film capacitors with high breakdown strength and excellent flexibility are crucial in the field of advanced electronic devices and electric power systems. Although massive works are carried to enhance the energy storage performances, it is still a great challenge to improve the energy density of polymer composites under the premise of large-scale industrial production. Herein, a general strategy is proposed to improve the intrinsic breakdown strength and energy storage performances by blending core-shell structured methyl methacrylate-butadiene-styrene (MBS) rubber particles into a polymer matrix. Good compatibility and uniform dispersion state of MBS particles are observed in the matrix. Polarizing microscopy images show that blended films exhibit clear reduction of crystalline grains with the addition of MBS particles. Accordingly, an increased breakdown strength of 515 MV m-1 and discharged energy density of 12.33 J cm-3 are observed in poly(vinylidene fluoride-co-hexafluoropropylene)-based composite films. Through comprehensive characterizations, it is believed that the superior energy storage performance of composite films is attributed to decreased crystalline grains, improved mechanical properties, and restriction on carrier motion. These results provide a novel design of dielectric polymers for high breakdown strength and discharged energy density applications.

Comparative effect of saxagliptin and glimepiride with a composite endpoint of adequate glycaemic control without hypoglycaemia and without weight gain in patients uncontrolled with metformin therapy: Results from the SPECIFY study, a 48-week, multi-centre, randomized, controlled trial.

AIMS: To compare the efficacy and safety of saxagliptin and glimepiride in type 2 diabetes (T2D) patients who are inadequately controlled with metformin monotherapy. MATERIALS AND METHODS: In this 48-week, multi-centre, open-label, randomized, parallel trial (NCT02280486, clinicaltrials.gov), a total of 388 T2D patients were randomized 1:1 to saxagliptin or glimepiride groups. The primary endpoint was achievement of HbA1c <7.0%, without hypoglycaemia, defined as blood glucose <3.9 mmol/L and weight gain <3.0% after 48 weeks of treatment. RESULTS: Over 48 weeks, a greater proportion of patients achieved the primary endpoint with saxagliptin compared with glimepiride (43.3% vs 31.3%; odds ratio, 1.38, 95% CI, 1.05-1.82; P = 0.019), especially among patients with baseline HbA1c <8.0%, duration <5 years or baseline BMI ≥25 kg/m2 . Mean reduction in HbA1c was similar in the two treatment groups at Week 48 (-0.94% with saxagliptin vs -0.98% with glimepiride; P = 0.439). Bodyweight decreased with saxagliptin, but increased with glimepiride over the treatment period, and the treatment difference was -1.6 kg (P < 0.001) at Week 48. The proportion of patients experiencing hypoglycaemia was much lower with saxagliptin vs glimepiride (3.1% vs 12.8%; P < 0.001). CONCLUSIONS: This study provides evidence that, compared to glimepiride, saxagliptin more effectively achieves a composite endpoint of adequate glycaemic control without hypoglycaemia and without weight gain in T2D patients who are inadequately controlled with metformin monotherapy, especially in overweight patients with moderate hyperglycaemia and a relatively short duration of diabetes.

Investigating the relationship between 25-hydroxyvitamin D and thyroid function in second-trimester pregnant women.

This study aims to explore the correlation between serum 25-hydroxyvitamin D and thyroid hormones during the second trimester. In total, 277 pregnant women at 13-28 weeks of gestation were enrolled. According to the level of thyrotropic-stimulating hormone, they were divided into a reduced TSH group, a normal TSH group and an elevated TSH group. In this study, we found that the prevalence of vitamin D deficiency was as high as 94.58%. The 25-hydroxyvitamin D level in the reduced TSH group was lower than that in the normal thyroid function group (p = .0005), and the 25-hydroxyvitamin D level in the elevated TSH group was higher than that in normal TSH group (p=.0339). A positive correlation was observed between 25-hydroxyvitamin D and thyrotropic-stimulating hormone (r = 0.3034, p = .0000). Furthermore, 25-hydroxyvitamin D was negatively correlated with the free thyroxine level (r = -0.1286, p = .0323) as well as the free triiodothyronine level (r = 0.1247, p = .0380). These data suggest that the relationships between 25-hydroxyvitamin D and thyroid parameters were characterized during the second trimester. Pregnant women in the second-trimester who are diagnosed with transient hyperthyroidism should be evaluated for the possibility of vitamin D deficiency.

[Analysis of professor Lin Yi's experience for metastasis breast cancer by data mining].

Data mining method based on the traditional Chinese medicine(TCM) inheritance system(V2.5) was adopted to analyze professor Lin Yi's experience for metastasis breast cancer(MBC) by analysing the high frequency medicine, drug categories，drug properties，the key symptoms and key drugs of different metastasis regions and different syndromes, drug symptom analysis in the effective prescriptions for treating MBC by Lin from January 2013 to December 2017. A total of 89 MBC patients, 5 syndromes and 117 prescriptions were involved. The first 10 most frequently used were Atractylodis Macrocephalae Rhizoma, Poria, Dioscoreae Rhizoma, Coicis Semen, Crataegi Fructus, Hordei Fructus Germinatus, Galli Gigerii Endothelium Corneum, Hedyotis Diffusa, Codonopsis Radix, Astragali Radix. The warm and placid property was higher, the most herbs had Gan taste, the first two channel tropisms were spleen and the stomach. Drug symptom analysis in 5 different metastasis regions and 6 different syndromes were also been done. The conclusion showed that professor Lin's experience as: recognizing the basis of diseases,differentiating the syndrome, combinating disease and syndrome, cautiously grasping pathogenesis,combinating tonification and purgation together, regulating balance, treating the symptoms and origin, regulating spleen and stomach, caring for the postnatal throughout, prefering ancient prescription,rational compatibility, using medicine gently.

Hepatic ALT isoenzymes are elevated in gluconeogenic conditions including diabetes and suppressed by insulin at the protein level.

BACKGROUND: Alanine transaminase (ALT) plays an important role in gluconeogenesis by converting alanine into pyruvate for glucose production. Early studies have shown that ALT activities are upregulated in gluconeogenic conditions and may be implicated in the development of diabetes. ALT consists of two isoforms, ALT1 and ALT2, with distinctive subcellular and tissue distributions. Whether and how they are regulated are largely unknown. METHODS: By using Western blotting analysis, we measured hepatic ALT isoforms at the protein level in obese and diabetic animals and in Fao hepatoma cells treated with dexamethasone and insulin. In addition, we measured glucose output in Fao cells over-expressing ALT1 and ALT2. RESULTS: Both ALT isoforms in the liver were increased in diabetic Goto-Kakizaki rats and during fasting. However, in ob/ob mice, only ALT2, but not ALT1, protein levels were elevated, and the increase of ALT2 was correlated with that of ALT activity. We further demonstrated that, in vitro, both ALT1 and ALT2 were induced by glucocorticoid dexamethasone, but suppressed by insulin in Fao cells. Finally, we showed that the over-expression of ALT1 and ALT2 in Fao cells directly increased glucose output. CONCLUSIONS: We have shown the similarity and difference in the regulation of ALT isoforms in gluconeogenic conditions at the protein level, supporting that ALT isoenzymes play an important role in glucose metabolism and may be implicated the development of insulin resistance and diabetes.

Residual amount of HBV DNA in serum is related to relapse in chronic hepatitis B patients after cessation of nucleos(t)ide analogs.

OBJECTIVE: To investigate the relationship between relapse and the levels of the residual amount of HBV DNA in serum at cessation in chronic hepatitis B patients meeting 2008 Asian Pacific Association for the Study of the Liver (APASL) nucleos(t)ide analogs (NAs) cessation criteria. METHODS: A total of 72 chronic hepatitis B patients who took NAs and had reached 2008 APASL cessation criteria entered the study. Patients were followed up for 6 months or longer after antiviral therapy was stopped. Serum HBV DNA level at cessation was detected by a highly sensitive polymerase chain reaction assay with detection limitation of 2 IU/mL. RESULTS: Of all the 72 patients, 42 patients (65.3%) relapsed after NA cessation. The detectable rate of the trace amount of HBV DNA at cessation was 41.7% by highly sensitive polymerase chain reaction reagents. The detectable rate of patients with consolidation treatment duration of <18 months was higher than that with consolidation duration of ≥18 months (47.5% vs. 15.4%, P=0.034), and the detectable rate of patients with HBeAg seroconversion within 6 months of treatment was lower than that of ≥6 months (25.0% vs. 61.5%, P=0.036). The residual amount of HBV DNA and detectable rate at cessation showed significant differences between relapsed and nonrelapsed patients (130.4±420.90 vs 44.6±155.16 IU/mL, P=0.004; 55.3% vs. 16.0%, P=0.001). The cutoff value predicting relapse was 2.24 IU/mL, with a sensitivity of 0.553 and specificity of 0.840. CONCLUSIONS: Residual amount of HBV DNA in serum at NA cessation is associated with HBV relapse. The cutoff value predicting relapse was 2.24 IU/mL, with a sensitivity of 0.553 and specificity of 0.840.

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.

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.

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.

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.

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.

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.

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.