Association between Mixed Heavy Metal Exposure and Arterial Stiffness, with Alkaline Phosphatase Identified as a Mediator.

Elevated arterial stiffness has been associated with exposure to heavy metals such as lead (Pb) and cadmium (Cd). However, the collective impact of multiple metals and the underlying mechanisms are not fully elucidated. The purpose of this study was to assess the combined effects of exposure to nine heavy metals on arterial stiffness and explore whether serum alkaline phosphatase (ALP) acts as a mediator in this relationship. In the retrospective analysis, data from 8,700 participants were retrieved from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. Arterial stiffness was measured by estimated pulse wave velocity (ePWV). The cumulative impact of exposure to multiple metals was examined using adaptive elastic-net, environmental risk score, weighted quantile sum regression, and quantile g-computation. Additionally, mediation analysis was conducted to explore the potential mediating role of serum ALP. We found that combined exposure to multiple metals was consistently associated with elevated ePWV, with Ba, Pb, and Sb exhibiting the greatest contributions. Notably, serum ALP partially mediated the associations between individual (Pb, Sb) and mixed metal exposure with ePWV, with mediation proportions at 10.76% for Pb, 18.22% for Sb, and 11.07% for mixed metal exposure. In conclusion, this study demonstrates a clear association between exposure to heavy metals, either individually or in combination, and heightened arterial stiffness. Furthermore, the findings suggest that serum ALP activity may act as a mediator in these relationships.

Evolving pathogen trends and spatial-temporal dynamics of hand, foot, and mouth disease in Fengxian District, Shanghai (2009-2022).

Hand, foot, and mouth disease (HFMD) is a prevalent acute infectious disease caused by enteroviruses, presenting substantial public health challenges in Shanghai, especially among children. The dynamic nature of HFMD's etiology necessitates an ongoing evaluation of its epidemiological and virological trends to inform effective control strategies. This study aims to investigate the epidemiological patterns and viral evolution of HFMD in Fengxian District, Shanghai, China, with a focus on shifts in predominant viral strains over a 14-year period. We conducted a retrospective analysis of HFMD cases reported to the National Notifiable Disease Reporting System in Fengxian District from January 1, 2009 to December 31, 2022. Epidemiological trends, strain prevalence, and demographic impacts were assessed. A total of 27,272 HFMD cases were documented during the study period, with incidence showing pronounced seasonal fluctuations-peaking in spring and summer and a lesser peak in autumn. The disease incidence demonstrated significant positive correlations with several meteorological variables: daily average temperature (r = 0.30, P < 0.05), relative humidity (r = 0.20, P < 0.05), wind speed (r = 0.17, P < 0.05), and precipitation (r = 0.17, P < 0.05). Geographically, Nanqiao Town, Fengcheng Town, and Xidu Subdistrict reported the highest incidence rates. The demographic analysis revealed a male-to-female ratio of 1.60:1, predominantly affecting children aged 1-3 years. Prior to 2017, Enterovirus 71 (EV71) and Coxsackievirus A16 (CoxA16) were the primary detected strains; post-2017, Coxsackievirus A6 (CoxA6) emerged as the dominant strain. Statistical analysis confirmed significant year-to-year variations in virus detection rates, with decreasing trends for EV71 and other enteroviruses and an increasing trend for CoxA6. The findings indicate a distinct seasonal incidence of HFMD in Fengxian District. This study underscores the need for targeted public health education, enhanced surveillance, and proactive measures in childcare facilities to mitigate disease spread during peak seasons. Moreover, the evolving viral landscape warrants accelerated efforts in vaccine development against new strains to reduce HFMD incidence.

Whole-genome analysis of circulating influenza A virus (H3N2) strains in Shanghai, China from 2005 to 2023.

Seasonal influenza A virus subtype H3N2 (A/H3N2) circulates globally and has been linked to higher hospitalization rates and summer outbreaks in temperate regions. Here, A/H3N2 circulation in Shanghai, China was systematically studied using data and materials generated by the Shanghai influenza surveillance network from 2005 to 2023. Time-series analysis of incidence and subtyping data showed that A/H3N2 co-circulated with other (sub)types and dominated in multiple seasonal influenza peaks, preferentially in summer. Whole genomes of 528 representative strains were sequenced, and spatiotemporal phylodynamic analysis using these and GISAID-archived sequences demonstrated that in the years before the COVID-19 pandemic, phylogenetically similar strains were circulating locally and elsewhere. However, clade 1a.1 (within 3C.2a.1b.2a), circulated in and only in Shanghai and domestically in 2022, while the sibling clade 2 predominated in other regions. Interestingly, clade 1a.1 was swiftly and completely replaced by clade 2, mostly 2a.3a.1, at the start of 2023. In hemagglutination inhibition and neutralization assays, sera from healthy donors collected in 2022 displayed higher or similar reactivity against 2a.3a.1 compared to 1a.1. By contrast, transcription and replication competence of 2a.3a.1 in MDCK cells was higher than 1a.1. These results indicated that instead of antigenicity differences enabling evasion of pre-existing immunity, higher replicative capability more likely contributed to 2a.3a.1 viruses achieving dominance in China. In addition to summarizing patterns of A/H3N2 local circulation in Shanghai, this work revealed an unusual episode in A/H3N2 global circulation and evolution dynamics in connection to the COVID-19 pandemic and explored possible mechanistic explanations.

Low Remnant Cholesterol and In-Hospital Bleeding Risk After Ischemic Stroke or Transient Ischemic Attack.

BACKGROUND: Bleeding risk brought by intensive lipid-lowering therapy and low low-density lipoprotein cholesterol is concerning, while evidence regarding the relationship between remnant cholesterol and bleeding is frightening. This study aimed to investigate the association between remnant cholesterol at admission and an in-hospital bleeding event after acute ischemic stroke or transient ischemic attack (TIA). METHODS AND RESULTS: A total of 3222 eligible patients admitted to Shanghai Huashan Hospital between 2015 and 2021 with complete lipid data were analyzed. Patients were classified into low (<20.0 mg/dL), moderate (20.0-29.9 mg/dL), and high (≥30 mg/dL) groups by remnant cholesterol. The mean age of patients was 63.0± 13.1 years, including 2301 (71.4%) men and 651 (20.2%) with TIA. The median (interquartile range) of remnant cholesterol was 18.6 (13.5-25.9) mg/dL. After adjustment for confounding variables, patients with low remnant cholesterol had a higher risk of bleeding events (odds ratio, 2.56 [95% CI, 1.12-6.67]) than those with moderate remnant cholesterol. The high remnant cholesterol group was not significantly associated with bleeding risk. Combined assessment of low-density lipoprotein cholesterol and remnant cholesterol further identified patients with the highest risk of bleeding events. CONCLUSIONS: Low remnant cholesterol levels were associated with bleeding events during the acute stage of ischemic stroke and TIA. The assessment of remnant cholesterol could inform the bleeding risk during hospitalization both for patients and physicians in clinical practice.

Greater variability in HDL-C was associated with an increased risk of cognitive decline in the middle- and elderly Chinese: A cohort study.

BACKGROUND: Previous studies into relationship between high-density lipoprotein cholesterol (HDL-C) and cognitive decline were constrained to a single measurement, leaving the association between HDL-C variability and risk of cognitive decline unclear. METHODS: We identified 5930 participants from the China Health and Retirement Longitudinal Study (CHARLS) who were devoid for stroke, dementia, and memory-related diseases at baseline and underwent a minimum of 2 sequential health examinations during 2011-2015. Variability in HDL-C was defined as (1) variability independent of the mean (VIM), (2) average real variability (ARV), and (3) standard deviation (SD) of HDL-C change from baseline and follow-up visits. Cognitive function was evaluated in 2018 by Mini-mental state examination (MMSE) in the Chinese version. Logistic regression was employed to explore the association between HDL-C variability and cognitive decline. Odd ratios (OR) and 95 % confidence intervals (CI) were reported. RESULTS: The study included participants from CHARLS, mean age of 57.84±8.44 years and 44 % male. After adjustment for covariates, the highest quartile of VIM was associated with an increased risk of cognitive decline [OR:1.049, 95 %CI: 1.014-1.086] compared to the lowest quartile. For each SD increment of VIM, the OR was 1.015 (95 %CI:1.003-1.027). Strong dose-response relationships were identified (P for trend: 0.005). Consistent results were obtained for other measures of HDL-C variability (ARV and SD). Similar patterns were identified in different dimensions of cognition. CONCLUSIONS: Elevated HDL-C variability was associated with increased cognitive decline risk. Strategies to reducing HDL-C variability may lower the risks of cognitive decline among the general population.

The Association between Dietary Nutrient Intake and Acceleration of Aging: Evidence from NHANES.

The acceleration of aging is a risk factor for numerous diseases, and diet has been identified as an especially effective anti-aging method. Currently, research on the relationship between dietary nutrient intake and accelerated aging remains limited, with existing studies focusing on the intake of a small number of individual dietary nutrients. Comprehensive research on the single and mixed anti-aging effects of dietary nutrients has not been conducted. This study aimed to comprehensively explore the effects of numerous dietary nutrient intakes, both singly and in combination, on the acceleration of aging. Data for this study were extracted from the 2015-2018 National Health and Nutrition Examination Surveys (NHANES). The acceleration of aging was measured by phenotypic age acceleration. Linear regression (linear), restricted cubic spline (RCS) (nonlinear), and weighted quantile sum (WQS) (mixed effect) models were used to explore the association between dietary nutrient intake and accelerated aging. A total of 4692 participants aged ≥ 20 were included in this study. In fully adjusted models, intakes of 16 nutrients were negatively associated with accelerated aging (protein, vitamin E, vitamin A, beta-carotene, vitamin B1, vitamin B2, vitamin B6, vitamin K, phosphorus, magnesium, iron, zinc, copper, potassium, dietary fiber, and alcohol). Intakes of total sugars, vitamin C, vitamin K, caffeine, and alcohol showed significant nonlinear associations with accelerated aging. Additionally, mixed dietary nutrient intakes were negatively associated with accelerated aging. Single dietary nutrients as well as mixed nutrient intake may mitigate accelerated aging. Moderately increasing the intake of specific dietary nutrients and maintaining dietary balance may be key strategies to prevent accelerated aging.

Associations between sleep duration trajectories and cognitive decline: A longitudinal cohort study in China.

OBJECT: The relationship between sleep duration trajectories and cognitive decline remains uncertain. This study aims to examine the connections between various patterns of sleep duration and cognitive function. METHODS: Group-based trajectory modeling (GBTM) was employed to identify longitudinal trajectories of sleep duration over four-year follow-up period, while considering age, sex and nap duration as adjustments. Logistic regression was utilized to analyze the association between sleep trajectories and cognition, with odds ratios (OR) and 95 % confidence intervals (CI) reported. Subgroup analyses based on various demographic characteristics were conducted to explore potential differences in sleep trajectories and cognitive decline across different population subgroups. RESULTS: A total of 5061 participants were followed for four years, and three sleep duration trajectories were identified: high increasing (n = 2101, 41.6 %), stable increasing (n = 2087, 40.7 %), and low decreasing (n = 873, 17.7 %). After adjustment for basic demographic information, health status, and baseline cognition, the high increasing trajectory was found to be associated with cognitive decline in terms of global cognition (OR:1.52,95 %CI:1.18-1.96), mental intactness (OR:1.36,95 %CI:1.07-1.73) and episodic memory (OR:1.33, 95 %CI:1.05-1.67), as compared to stable increasing trajectory. These associations were particularly prominent among the non-elderly population (≤65 years) and those without depressive symptoms. CONCLUSION: This study suggests that both high increasing and low decreasing sleep duration trajectories are linked to cognitive decline, as compared to the stable increasing trajectory. Long-term attention to changes in sleep duration facilitates early prevention of cognitive decline.

Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

Objectives. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by devising and externally validating a Multimodal Integrated Feature Neural Network (MIFNN). We hypothesize that the fusion of deep learning algorithms with morphological nodule features will significantly enhance diagnostic accuracy.Materials and Methods. Data were retrospectively collected from the Lung Nodule Analysis 2016 (LUNA16) dataset and four local centers in Beijing, China. The study includes patients with small pulmonary nodules (≤10 mm). We developed a neural network, termed MIFNN, that synergistically combines computed tomography (CT) images and morphological characteristics of pulmonary nodules. The network is designed to acquire clinically relevant deep learning features, thereby elevating the diagnostic accuracy of existing models. Importantly, the network's simple architecture and use of standard screening variables enable seamless integration into standard lung cancer screening protocols.Results. In summary, the study analyzed a total of 382 small pulmonary nodules (85 malignant) from the LUNA16 dataset and 101 small pulmonary nodules (33 malignant) obtained from four specialized centers in Beijing, China, for model training and external validation. Both internal and external validation metrics indicate that the MIFNN significantly surpasses extant state-of-the-art models, achieving an internal area under the curve (AUC) of 0.890 (95% CI: 0.848-0.932) and an external AUC of 0.843 (95% CI: 0.784-0.891).Conclusion. The MIFNN model significantly enhances the diagnostic accuracy of small pulmonary nodules, outperforming existing benchmarks by Zhanget alwith a 6.34% improvement for nodules less than 10 mm. Leveraging advanced integration techniques for imaging and clinical data, MIFNN increases the efficiency of lung cancer screenings and optimizes nodule management, potentially reducing false positives and unnecessary biopsies.Clinical relevance statement. The MIFNN enhances lung cancer screening efficiency and patient management for small pulmonary nodules, while seamlessly integrating into existing workflows due to its reliance on standard screening variables.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Temporal relationship between elevated serum uric acid levels and dyslipidemia: A 5-year cohort study using cross-lagged panel analysis.

BACKGROUND AND AIM: Previous studies have demonstrated an association between SUA and dyslipidemia. This study aims to explore the temporal relationship between SUA and dyslipidemia. METHODS AND RESULTS: Based on the Beijing Health Management Cohort conducted from 2013 to 2018, the data of a physical examination population was collected, including a total of 6630 study subjects. Cross-lagged panel analysis was employed to examine the temporal relationship between elevated SUA levels and dyslipidemia, indicated by either elevated TG or decreased HDL-C. The path coefficient and the 95 % CI from baseline TG to follow-up SUA were as follows: in the general population, men, women, and people with BMI ≥25 kg/m2were 0.027 (0.008-0.045), 0.024 (0.001-0.048), 0.032 (0.001-0.063) and 0.033 (0.006-0.059) (P < 0.05); however, the path coefficient from baseline SUA to follow-up TG and the 95 % CI were not statistically significant. Furthermore, the path coefficients and 95 % CIs between elevated SUA and decreased HDL-C were not statistically significant, both in the general population and in populations stratified by gender and BMI. CONCLUSIONS: We found a temporal relationship from elevated TG to elevated SUA in the general population and the populations stratified by gender and BMI (≥25 kg/m2). However, we did not observe a reverse relationship from elevated SUA to elevated TG. Additionally, we did not find a temporal relationship between decreased HDL-C and elevated SUA in both the general population and the stratified populations.

Association of Abnormal Lung Function and Its Subtypes With Arterial Stiffness: A Longitudinal Cohort Study.

BACKGROUND: Prior studies have reported the cross-sectional relationship between lung function and arterial stiffness, while the longitudinal association remains unclear to date. This study aimed to investigate whether abnormal lung function and its subtypes at baseline are associated with increased arterial stiffness using a cohort. METHODS AND RESULTS: This was a secondary analysis extracting 2461 participants from Beijing Health Management Cohort as baseline and annually followed for development of arterial stiffness. Abnormal lung function was defined by forced expiratory volume in 1s <80% of the predicted value, forced vital capacity of the predicted value, or forced expiratory volume in 1s/forced vital capacity ratio <70%. Increased arterial stiffness was determined by brachial-ankle pulse wave velocity ≥1400 cm/s. Cox proportional hazards model was used to calculate the hazard ratio and population attributable fraction. The mean age was 42.8±8.1 years, and 444 (18.0%) cases developed increased arterial stiffness during a median follow-up of 3.0 years. The adjusted hazard ratio (95% CI) of arterial stiffness was 1.47 (95% CI, 1.10-1.96) for abnormal lung function, with a population attributable fraction of 3.9% (95% CI, 0.8-7.1). Of subtypes, only obstructive ventilatory dysfunction was significantly associated with arterial stiffness (adjusted hazard ratio, 2.06 [95% CI, 1.27-3.36]), not restricted ventilatory dysfunction (adjusted hazard ratio, 0.95 [95% CI, 0.54-1.65]). Consistent results were observed on multiple sensitivity analyses. CONCLUSIONS: Our study indicated a longitudinal association of abnormal lung function with increased arterial stiffness using a large cohort, especially for the obstructive ventilatory dysfunction.

Intraindividual difference in estimated GFR by creatinine and cystatin C, cognitive trajectories and motoric cognitive risk syndrome.

BACKGROUND: Intraindividual differences between estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) and creatinine (eGFRcr) can convey important clinical information regarding the health status. However, the clinical implications of these differences (eGFRdiff) for risk of cognitive decline and motoric cognitive risk syndrome (MCR) remains unclear. We aimed to investigate the longitudinal associations of eGFRdiff with cognitive trajectories and incident MCR. METHODS: Based on the China Health and Retirement Longitudinal Study, we identified two study sub-cohorts: one for cognitive trajectory follow-up (6423 participants; years:2011-2018) and another for incident MCR follow-up (2477 participants; years:2011-2015). The eGFRdiff was defined as eGFRcys minus eGFRcr. Adjusted ordinal and binary logistics regression models were separately used to assess the associations of eGFRdiff with cognitive trajectories and incident MCR. We also performed discordance analyses for eGFRdiff vs eGFRcys, eGFRcr or eGFR based on both creatinine and cystatin C (eGFRcys-cr). RESULTS: In the first sub-cohort, four distinct 7-year cognitive trajectories were identified. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was associated with a lower risk of poorer cognitive trajectories (OR: 0.909, 95% CI: 0.877-0.942). In the second sub-cohort, 121 participants developed incident MCR after a 4-year follow-up. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was linked with a 25.3% (95%CI: 16.6%-33.2%) decreased risk for MCR. The above associations persisted in individuals with normal kidney function. Additionally, the risk for cognitive decline and incident MCR was more strongly associated with eGFRcys than eGFRcr and eGFRcys-cr. For the discordance analyses, 'discordantly high eGFRdiff/low eGFR' group, but not 'discordantly low eGFRdiff/high eGFR', exhibited a significantly lower risk of poorer cognitive trajectories and MCR compared to the concordant group. CONCLUSIONS: A large negative difference between eGFRcys and eGFRcr (eGFRcys lower than eGFRcr) was associated with higher risk of cognitive decline and incident MCR. The eGFRdiff could capture additional valuable risk information beyond eGFRcys, eGFRcr, and eGFRcys-cr.

Association between nonalcoholic fatty liver disease and type 2 diabetes: A bidirectional two-sample mendelian randomization study.

OBJECTIVE: The aim of this study was to explore the mutually causal relationship between NAFLD and type 2 diabetes. METHODS: Based on the data obtained from GWAS, this study employed bidirectional two-sample MR analysis to investigate the causal relationship between NAFLD and type 2 diabetes, and also examined the causal relationship between liver fat accumulation and type 2 diabetes as well as the relationship between NAFLD and FPG, IR. RESULTS: In MR analysis of NAFLD and type 2 diabetes, when NAFLD as an exposure and type 2 diabetes as a result, the OR (95 % CI) was 1.10890 (1.00135-1.22801); in the reverse analysis, the OR value was not statistically significant. In MR analysis of NAFLD, FPG and IR, there was no statistical significance in both directions. In MR analysis of liver fat accumulation and type 2 diabetes, when liver fat as an exposure and type 2 diabetes as a result, the OR (95 % CI) was 1.17516 (1.02054-1.35321); in the reverse analysis, the OR value (95 % CI) was 1.06283 (1.02879-1.09799). CONCLUSION: There is a unidirectional causal relationship between NAFLD and type 2 diabetes. Furthermore, a bidirectional causal relationship exists between liver fat accumulation and type 2 diabetes.

Machine Learning Model of ResNet50-Ensemble Voting for Malignant-Benign Small Pulmonary Nodule Classification on Computed Tomography Images.

BACKGROUND: The early detection of benign and malignant lung tumors enabled patients to diagnose lesions and implement appropriate health measures earlier, dramatically improving lung cancer patients' quality of living. Machine learning methods performed admirably when recognizing small benign and malignant lung nodules. However, exploration and investigation are required to fully leverage the potential of machine learning in distinguishing between benign and malignant small lung nodules. OBJECTIVE: The aim of this study was to develop and evaluate the ResNet50-Ensemble Voting model for detecting the benign and malignant nature of small pulmonary nodules (<20 mm) based on CT images. METHODS: In this study, 834 CT imaging data from 396 patients with small pulmonary nodules were gathered and randomly assigned to the training and validation sets in an 8:2 ratio. ResNet50 and VGG16 algorithms were utilized to extract CT image features, followed by XGBoost, SVM, and Ensemble Voting techniques for classification, for a total of ten different classes of machine learning combinatorial classifiers. Indicators such as accuracy, sensitivity, and specificity were used to assess the models. The collected features are also shown to investigate the contrasts between them. RESULTS: The algorithm we presented, ResNet50-Ensemble Voting, performed best in the test set, with an accuracy of 0.943 (0.938, 0.948) and sensitivity and specificity of 0.964 and 0.911, respectively. VGG16-Ensemble Voting had an accuracy of 0.887 (0.880, 0.894), with a sensitivity and specificity of 0.952 and 0.784, respectively. CONCLUSION: Machine learning models that were implemented and integrated ResNet50-Ensemble Voting performed exceptionally well in identifying benign and malignant small pulmonary nodules (<20 mm) from various sites, which might help doctors in accurately diagnosing the nature of early-stage lung nodules in clinical practice.

Bidirectional relationship between nonalcoholic fatty liver disease and serum creatinine-to-body weight ratio as a proxy for skeletal muscle mass index.

BACKGROUND AND AIM: Although an association between skeletal muscle mass index and nonalcoholic fatty liver disease (NAFLD) has previously been demonstrated, the causal direction remains unclear. Herein, we investigated the directional association between NAFLD and the serum creatinine-to-body weight ratio (sCr/bw), a surrogate marker of the muscle mass index, using longitudinal data. METHODS: We recruited 9662 participants in 2017 and performed follow-up over 4 years. We evaluated whether sCr/bw was related to NAFLD development (Analysis I) and whether NAFLD was associated with a low sCr/bw incidence (Analysis II) using logistic regression models. Furthermore, a random intercept cross-lagged panel model was applied to evaluate the bidirectional association between sCr/bw ratio and NAFLD (Analysis III). RESULTS: Analysis I demonstrated an association between sCr/bw and incident NAFLD (odds ratio [OR] = 0.160, 95% confidence interval [CI]:0.107-0.232). Analysis II indicated a relationship between NAFLD and subsequent low sCr/bw ratio (OR = 1.524, 95% CI: 1.258-1.846). Analysis III indicated that the standard regression coefficient from sCr/bw to subsequent hepatic steatosis (HS) was -0.053 for ßsCr/bw2017 â†’ HS2019 and -0.060 for ßsCr/bw2019 â†’ HS2021 and the coefficient from HS to subsequent sCr/bw was -0.093 for ßHS2017 â†’ sCr/bw2019 and -0.112 for ßHS2019 â†’ sCr/bw2021 (all P < 0.05). CONCLUSIONS: This study indicated mutual causality between sCr/bw and NAFLD. Considering that sCr/bw is a surrogate marker of muscle mass index, the findings emphasize that NAFLD and low muscle mass form a vicious cycle, which should be taken seriously in clinical practice.

Temporal and Bidirectional Association Between Blood Pressure Variability and Arterial Stiffness: Cross-Lagged Cohort Study.

BACKGROUND: The causal relationship between blood pressure variability (BPV) and arterial stiffness remains debated. OBJECTIVE: This study aimed to explore the temporal and bidirectional associations between long-term BPV and arterial stiffness using a cohort design with multiple surveys. METHODS: Participants from the Beijing Health Management Cohort who underwent health examinations from visit 1 (2010-2011) to visit 5 (2018-2019) were enrolled in this study. Long-term BPV was defined as intraindividual variation using the coefficient of variation (CV) and SD. Arterial stiffness was measured by brachial-ankle pulse wave velocity (baPWV). The bidirectional relationship between BPV and arterial stiffness was explored using cross-lagged analysis and linear regression models, with records before and after visit 3 categorized as phase 1 and phase 2, respectively. RESULTS: Of the 1506 participants, who were a mean of 56.11 (SD 8.57) years old, 1148 (76.2%) were male. The cross-lagged analysis indicated that the standardized coefficients of BPV at phase 1 directing to the baPWV level at phase 2 were statistically significant but not vice-versa. The adjusted regression coefficients of the CV were 4.708 (95% CI 0.946-8.470) for systolic blood pressure, 3.119 (95% 0.166-6.073) for diastolic pressure, and 2.205 (95% CI 0.300-4.110) for pulse pressure. The coefficients of the SD were 4.208 (95% CI 0.177-8.239) for diastolic pressure and 4.247 (95% CI 0.448-8.046) for pulse pressure. The associations were predominant in the subgroup with hypertension, but we did not observe any significant association of baPWV level with subsequent BPV indices. CONCLUSIONS: The findings supported a temporal relationship between long-term BPV and arterial stiffness level, especially among people with hypertension.

Association Between Long-Term Exposure to Fine Particulate Matter Constituents and Progression of Cerebral Blood Flow Velocity in Beijing: Modifying Effect of Greenness.

Few studies have explored the effects of fine particulate matter (PM2.5) and its constituents on the progression of cerebral blood flow velocity (BFV) and the potential modifying role of greenness. In this study, we investigated the association of PM2.5 and its constituents, including sulfate (SO4 2-), nitrate (NO3 -), ammonium (NH4 +), organic matter (OM), and black carbon (BC), with the progression of BFV in the middle cerebral artery. Participants from the Beijing Health Management Cohort who underwent at least two transcranial Doppler sonography examinations during 2015-2020 were recruited. BFV change and BFV change rate were used to define the progression of cerebral BFV. Linear mixed effects models were employed to analyze the data, and the weighted quantile sum regression assessed the contribution of PM2.5 constituents. Additionally, greenness was examined as a modifier. Among the examined constituents, OM exhibited the strongest association with BFV progression. An interquartile range increase in PM2.5 and OM exposure concentrations was associated with a decrease of -16.519 cm/s (95% CI: -17.837, -15.201) and -15.403 cm/s (95% CI: -16.681, -14.126) in BFV change, and -10.369 cm/s/year (95% CI: -11.387, -9.352) and -9.615 cm/s/year (95% CI: -10.599, -8.632) in BFV change rate, respectively. Furthermore, stronger associations between PM2.5 and BFV progression were observed in individuals working in areas with lower greenness, those aged under 45 years, and females. In conclusion, reducing PM2.5 levels in the air, particularly the OM constituent, and enhancing greenness could potentially contribute to the protection of cerebrovascular health.

Separate and Joint Associations of Remnant Cholesterol Accumulation and Variability With Carotid Atherosclerosis: A Prospective Cohort Study.

Background We aimed to examine separate and joint associations of remnant cholesterol (RC) accumulation and variability with the risk of carotid atherosclerosis (CAS) in the general population. Methods and Results A total of 6213 participants who underwent 3 sequential health examinations during 2010 to 2015 were enrolled and were followed up until December 31, 2021. Cumulative RC (cumRC) and RC variability among the 3 visits were the exposure of interest in our study. Adjusted Cox models were performed to calculate the hazard ratio (HR) and 95% CI. C-statistics, integrated discrimination improvement, and the net reclassification index were used to estimate the incremental predictive ability. During a median follow-up of 4.00 years, 2613 participants developed CAS. Higher cumRC (HR, 1.33 [95% CI, 1.17-1.52]) and greater RC variability (HR, 1.22 [95% CI, 1.08-1.39]) were significantly associated with elevated risk of CAS, independent of traditional cardiovascular risk factors and low-density lipoprotein cholesterol. Participants were divided into 4 groups according to the median of cumRC and RC variability to assess their joint associations. Compared with "low cumRC and low variability," "high cumRC and high variability" had the highest risk of CAS, followed by "high cumRC and low variability" and "low cumRC and high variability." Finally, joint assessment of RC accumulation and variability had the significantly highest incremental effect on the predictive value of CAS versus single-time-point measures of RC. Conclusions Excessive cumRC levels and greater RC variability were each independently associated with higher incidence of CAS, and their coexistence could further yield significantly higher risks.

Association of impaired sensitivity to thyroid hormones with hyperuricemia through obesity in the euthyroid population.

BACKGROUND: Impaired sensitivity to thyroid hormones is a newly proposed clinical entity associated with hyperuricemia in the subclinical hypothyroid population. However, it is unknown whether the association exists in the euthyroid population. This study aimed to explore the association of impaired sensitivity to thyroid hormones (assessed by the thyroid feedback quantile-based index [TFQI], parametric thyroid feedback quantile-based index [PTFQI], thyrotrophic thyroxine resistance index [TT4RI] and thyroid-stimulating hormone index [TSHI]) with hyperuricemia and quantify the mediating effect of body mass index BMI in the euthyroid population. METHODS: This cross-sectional study enrolled Chinese adults aged ≥ 20 years who participated in the Beijing Health Management Cohort (2008-2019). Adjusted logistic regression models were used to explore the association between indices of sensitivity to thyroid hormones and hyperuricemia. Odds ratios [OR] and absolute risk differences [ARD] were calculated. Mediation analyses were performed to estimate direct and indirect effects through BMI. RESULTS: Of 30,857 participants, 19,031 (61.7%) were male; the mean (SD) age was 47.3 (13.3) years; and 6,515 (21.1%) had hyperuricemia. After adjusting for confounders, individuals in the highest group of thyroid hormone sensitivity indices were associated with an increased prevalence of hyperuricemia compared with the lowest group (TFQI: OR = 1.18, 95% CI 1.04-1.35; PTFQI: OR = 1.20, 95% CI 1.05-1.36; TT4RI: OR = 1.17, 95% CI 1.08-1.27; TSHI: OR = 1.12, 95% CI 1.04-1.21). BMI significantly mediated 32.35%, 32.29%, 39.63%, and 37.68% of the associations of TFQI, PTFQI, TT4RI and TSHI with hyperuricemia, respectively. CONCLUSIONS: Our research revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population. These findings could provide useful evidence for understanding the interaction between impaired sensitivity to thyroid hormone and hyperuricemia in euthyroid individuals and suggest the clinical implications of weight control in terms of impaired thyroid hormones sensitivity.

Deep-Learning Model of ResNet Combined with CBAM for Malignant-Benign Pulmonary Nodules Classification on Computed Tomography Images.

Background and Objectives: Lung cancer remains a leading cause of cancer mortality worldwide. Accurately classifying benign pulmonary nodules and malignant ones is crucial for early diagnosis and improved patient outcomes. The purpose of this study is to explore the deep-learning model of ResNet combined with a convolutional block attention module (CBAM) for the differentiation between benign and malignant lung cancer, based on computed tomography (CT) images, morphological features, and clinical information. Methods and materials: In this study, 8241 CT slices containing pulmonary nodules were retrospectively included. A random sample comprising 20% (n = 1647) of the images was used as the test set, and the remaining data were used as the training set. ResNet combined CBAM (ResNet-CBAM) was used to establish classifiers on the basis of images, morphological features, and clinical information. Nonsubsampled dual-tree complex contourlet transform (NSDTCT) combined with SVM classifier (NSDTCT-SVM) was used as a comparative model. Results: The AUC and the accuracy of the CBAM-ResNet model were 0.940 and 0.867, respectively, in test set when there were only images as inputs. By combining the morphological features and clinical information, CBAM-ResNet shows better performance (AUC: 0.957, accuracy: 0.898). In comparison, a radiomic analysis using NSDTCT-SVM achieved AUC and accuracy values of 0.807 and 0.779, respectively. Conclusions: Our findings demonstrate that deep-learning models, combined with additional information, can enhance the classification performance of pulmonary nodules. This model can assist clinicians in accurately diagnosing pulmonary nodules in clinical practice.