Nonlinear Relationship Research Articles

Acoustic Waves in Axial Crystals and Quasicrystals with Preliminary Finite Strains

The dynamic problem of acoustic wave propagation in elastic bodies with preliminary finite deformations is formulated. Several types of anisotropic elastic materials are considered: hexagonal crystals of class [Formula: see text], transversally isotropic materials and axial quasicrystals with an arbitrary order of the rotary axis. A variant of nonlinear hypoelasticity relations is constructed for these materials. In the constitutive relations, the tensor connecting the rate of change of the stress tensor and the strain rate tensor is a function of deformations. The propagation of acoustic waves in a hypoelastic material with preliminary finite deformations and stresses is described as a process of weak perturbations superimposed on finite strains. The characteristic features of elastic wave propagation in hexagonal crystals and axial quasicrystals are revealed. Within the framework of the constructed models, the most significant differences are found in the phase velocities of a transverse wave with a polarization vector located in the crystallographic plane (110). Unlike hexagonal crystals, in axial quasicrystals, there are such directions of acoustic wave propagation for which the phase velocities of transverse waves are insensitive to the degree of preliminary deformations. Based on the solution of the problem of elastic wave propagation, a program of dynamic experiments with macrosamples, which allows to distinguish axial quasicrystals from hexagonal crystals by the peculiarities of acoustic wave propagation, is proposed.

Neuromechanical Circuits of the Spinal Motor Apparatus.

The evolution of mechanisms for terrestrial locomotion has resulted in multi-segmented limbs that allow navigation on irregular terrains, changing of direction, manipulation of external objects, and control over the mechanical properties of limbs important for interaction with the environment, with corresponding changes in neural pathways in the spinal cord. This article is focused on the organization of these pathways, their interactions with the musculoskeletal system, and the integration of these neuromechanical circuits with supraspinal mechanisms to control limb impedance. It is argued that neural pathways from muscle spindles and Golgi tendon organs form a distributive impedance controller in the spinal cord that controls limb impedance and coordination during responses to external disturbances. These pathways include both monosynaptic and polysynaptic components. Autogenic, monosynaptic pathways serve to control the spring-like properties of muscles preserving the nonlinear relationship between stiffness and force. Intermuscular monosynaptic pathways compensate for inertial disparities between the inertial properties of limb segments and help to control inertial coupling between joints and axes of rotation. Reciprocal inhibition controls joint stiffness in conjunction with feedforward cocontraction commands. Excitatory force feedback becomes operational during locomotion and increases muscular stiffness to accommodate the higher inertial loads. Inhibitory force feedback is widely distributed among muscles. It is integrated with excitatory pathways from muscle spindles and Golgi tendon organs to determine limb stiffness and interjoint coordination during interactions with the environment. The intermuscular distribution of force feedback is variable and serves to modulate limb stiffness to meet the physical demands of different motor tasks. © 2024 American Physiological Society. Compr Physiol 14:5789-5838, 2024.

Association of remnant cholesterol with insulin resistance and type 2 diabetes: mediation analyses from NHANES 1999–2020

BackgroundPrevious studies have established a correlation between elevated levels of remnant cholesterol (RC) and the occurrence of type 2 diabetes mellitus (T2D) as well as insulin resistance (IR); however, the precise nature of these associations remains incompletely elucidated. This study aimed to evaluate the relationships between RC and IR, as well as RC and T2D, and to determine the extent to which IR mediated the relationship between RC and T2D.MethodsThis was an observational study that utilized cross-sectional methods to examine the general population in the National Health and Nutrition Examination Survey (NHANES) 1999–2020. The participants were divided into 4 groups according to the RC quartiles. The outcome was the prevalence of IR and T2D. Survey-weighted binary logistic regression analysis was used to analyze the associations, and the restricted cubic spline (RCS) curve was used to further analyze the nonlinear relationship. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic performance, and the areas under the curves (AUC) of RC, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) were compared using the DeLong test. The mediating effect of IR on the relationship between RC and T2D was evaluated through mediation analysis.ResultsA total of 23,755 participants (46.02 ± 18.48 years, 48.8% male) were included in our study. Higher RC levels were significantly associated with increased prevalence of both IR and T2D. After adjusting for potential confounders, logistic regression analysis showed that higher RC quartiles were associated with the increased prevalence of IR [Quartile 4 vs. Quartile 1: odds ratio (OR) (95% confidence interval, CI): 1.65 (1.41–1.94), p < 0.001] and T2D [Quartile 4 vs. Quartile 1: OR (95% CI): 1.24 (1.03–1.50), p = 0.024]. RCS analysis revealed two distinct nonlinear relationships: one between RC levels and the prevalence of IR (nonlinear p < 0.001), and another between RC levels and the prevalence of T2D (nonlinear p < 0.001). ROC curve analysis demonstrated that RC had the highest discriminative ability, significantly outperforming LDL-C, HDL-C, and TG in predicting both IR and T2D risk (all P < 0.001 by DeLong test). Mediation analysis revealed that IR significantly mediated the relationship between RC and T2D, with approximately 54.1% of the effect of RC on T2D being indirect through IR.ConclusionsHigher RC level was associated with increased prevalence of IR and T2D. IR mediated 54.1% of the association between RC and T2D, suggesting that managing IR could be crucial in reducing the risk of T2D in individuals with elevated RC levels.

Association between urinary arsenic and hearing threshold shifts in adults in the United States, National Health and Nutrition Examination Survey, 2015–2016

BackgroundHearing loss (HL) is a common sensory disorder in humans. Studies on the relationship between arsenic, which is a highly toxic and widely distributed heavy metal with a health risk to humans, and hearing status in humans are contradictory and mostly focused on people living in arsenic-contaminated areas. This study investigated the association between urinary arsenic levels and hearing threshold shifts in the general population in the United States.MethodsOverall, 1,017 adults (aged 20–69 years) from the National Health and Nutrition Examination Survey (2015–2016) were included in this study. HL was defined as pure-tone average (PTA) ≥ 20 dB at frequencies 500, 1,000, 2000, and 4,000 Hz in the better-hearing ear. Total urinary arsenic (uAs) and dimethylarsinic acid (uDMA) levels were analyzed. Multivariate linear regression analyses and smooth curve fitting were performed to evaluate the correlations between uDMA, uAs, and low-, speech-, and high-frequency hearing levels.ResultsThe mean age of the participants was 42.13 ± 13.66 years, including weighted 48.67% men and 12.88% participants with sensorineural HL. After adjusting for potential confounders in the multivariate linear regression model, higher uDMA levels were significantly associated with poor low-, and speech-frequency PTAs, with no differences among participants by age or sex. Smooth curve fitting indicated a nonlinear relationship between uAs and high-frequency PTA hearing threshold shifts. The uAs levels were positively associated with high-frequency PTA until the turning point of 1.54 (adjusted β 4.53, 95% CI 1.16, 7.90; p = 0.0085), beyond which this association was not observed (adjusted β −0.43, 95% CI −1.57, 0.71; p = 0.4600).ConclusionWe found positive associations between urinary arsenic metabolites uDMA, uAs levels and poor hearing threshold shifts in US adults. This study provides new evidence for the association between arsenic exposure and auditory function.

Low-carbohydrate diet score and chronic obstructive pulmonary disease: a machine learning analysis of NHANES data

BackgroundRecent research has identified the Low-Carbohydrate Diet (LCD) score as a novel biomarker, with studies showing that LCDs can reduce carbon dioxide retention, potentially improving lung function. While the link between the LCD score and chronic obstructive pulmonary disease (COPD) has been explored, its relevance in the US population remains uncertain. This study aims to explore the association between the LCD score and the likelihood of COPD prevalence in this population.MethodsData from 16,030 participants in the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2023 were analyzed to examine the relationship between LCD score and COPD. Propensity score matching (PSM) was employed to reduce baseline bias. Weighted multivariable logistic regression models were applied, and restricted cubic spline (RCS) regression was used to explore possible nonlinear relationships. Subgroup analyses were performed to evaluate the robustness of the results. Additionally, we employed eight machine learning methods—Boost Tree, Decision Tree, Logistic Regression, MLP, Naive Bayes, KNN, Random Forest, and SVM RBF—to build predictive models and evaluate their performance. Based on the best-performing model, we further examined variable importance and model accuracy.ResultsUpon controlling for variables, the LCD score demonstrated a strong correlation with the odds of COPD prevalence. In compared to the lowest quartile, the adjusted odds ratios (ORs) for the high quartile were 0.77 (95% CI: 0.63, 0.95), 0.74 (95% CI: 0.59, 0.93), and 0.61 (95% CI: 0.48, 0.78). RCS analysis demonstrated a linear inverse relationship between the LCD score and the odds of COPD prevalence. Furthermore, the random forest model exhibited robust predictive efficacy, with an area under the curve (AUC) of 71.6%.ConclusionOur study of American adults indicates that adherence to the LCD may be linked to lower odds of COPD prevalence. These findings underscore the important role of the LCD score as a tool for enhancing COPD prevention efforts within the general population. Nonetheless, additional prospective cohort studies are required to assess and validate these results.

The impact of firm size on the relationship between leverage and firm performance: evidence from Saudi Arabia

Capital structure and its relationship with firm performance is one of the most debatable topics in corporate finance among both scholars and policy-makers. Using a panel threshold regression model, this study investigates the impact of firm size on the nonlinear relationship between the leverage and performance of Saudi listed firms from 2010 to 2019. The results reveal that firm size is critical in determining the nonlinear relationship between leverage and firm performance. A single threshold level divides the sample into two regimes of small and large firms. Leverage negatively affects performance in both regimes with different debt maturities. However, the negative impact is more pronounced among small firms, especially when long-term debt is employed. This study adds to the evolving literature because the unique setting of the Saudi market is characterized by its illiquid and underdeveloped bond market. Additionally, Saudi firms are not subject to income tax; instead, they are subject to zakat, which is levied at 2.5%. These characteristics impact the relationship between leverage and Saudi firm performance at different firm sizes. This study is important for financial managers, regulators, researchers, and investors to understand how leverage with different maturities affects performance and the role of firm size in this relationship.

Exploring the acceptance of virtual reality training systems among construction workers: a combined structural equation modeling and artificial neural network approach

Virtual Reality Training System (VRTS) has been verified effective in safety training in the construction field. However, in China, it is not widely used as a regular training tool. Among all the reasons, the acceptance level of construction workers (CWs) has the decisive impact on the promotion of VRTS. In view of this, this study is devoted to constructing a training model of CWs’ acceptance level of VRTS training that integrates the technology acceptance level model with the theory of planned behavior. What’s more, this paper innovatively introduces three crucial elements of external influences, namely, risk perception (RP), safety climate (SC) and self-efficacy (SE). In order to more accurately figure out the linear and nonlinear relationship between every structure and the factors of CWs’ acceptance level, 528 participating CWs in this study filled in structured questionnaires, through the data of which the analyzing process uses structural equation model and artificial neural network two-stage analysis method. Based on the analyzing results of the study, this paper put forward a series of specific strategies and suggestions to significantly promote the acceptance level of CWs to VRTS training considering the designment, the enterprises and the government.

Relationship Between A Body Shape Index and Self-Reported Stress Urinary Incontinence Among US Women: A Cross-Sectional Analysis.

Stress urinary incontinence (SUI) is common among women, but its link with A Body Shape Index (ABSI) is not well understood. This study investigates the association between ABSI and SUI risk in women, exploring variations across different subgroups. Data from National Health and Nutrition Examination Survey (2001-2020) were analyzed. A weighted multivariable logistic regression was performed to examine the relationship between ABSI and SUI risk, calculating odds ratios and 95% confidence intervals. A restricted cubic spline (RCS) analysis was used to assess any nonlinear associations. Subgroup analyses and interaction tests were conducted to explore the influence of factors on the ABSI-SUI relationship. Sensitivity analyses were also performed to ensure the robustness of the findings. The analysis, after adjusting for potential confounders, showed a significant association between ABSI and SUI risk (p < 0.001). The RCS analysis indicated a nonlinear relationship (p for nonlinear = 0.02) with a turning point at an ABSI of 0.081. Subgroup analyses revealed that the association between ABSI and SUI was stronger in women with lower BMI, non-Mexican ethnicity, and those without hypertension (p for interaction < 0.05). Sensitivity analyses confirmed the consistency of these findings, supporting their robustness. Higher ABSI is associated with an increased risk of SUI in US women, particularly in specific subgroups. This suggests that ABSI could be a valuable measure for identifying women at higher risk of SUI.

Nonparametric Estimation for Propensity Scores With Misclassified Treatments.

In the framework of causal inference, average treatment effect (ATE) is one of crucial concerns. To estimate it, the propensity score based estimation method and its variants have been widely adopted. However, most existing methods were developed by assuming that binary treatments are precisely measured. In addition, propensity scores are usually formulated as parametric models with respect to confounders. However, in the presence of measurement error in binary treatments and nonlinear relationship between treatments and confounders, existing methods are no longer valid and may yield biased inference results if these features are ignored. In this paper, we first analytically examine the impact of estimation of ATE and derive biases for the estimator of ATE when treatments are contaminated with measurement error. After that, we develop a valid method to address binary treatments with misclassification. Given the corrected treatments, we adopt the random forest method to estimate the propensity score with nonlinear confounders accommodated and then derive the estimator of ATE. Asymptotic properties of the error-eliminated estimator are established. Numerical studies are also conducted to assess the finite sample performance of the proposed estimator, and numerical results verify the importance of correcting for measurement error effects.

Double copy, Kerr–Schild gauges and the effective-one-body formalism

Abstract We look for a classical double-copy-inspired relation between gravity and electrodynamics by connecting the descriptions of the scattering of two point masses, and of two point charges, in terms of perturbative (post-Minkowskian or post-Lorentzian) expansions. We do so by recasting available analytical information within the effective-one-body formalism using Kerr–Schild gauges in both cases. Working at the third perturbative level, we find that the usual linear relation (holding in the probe limit) between the adimensionalized electric potential, ϕ ~ = G M e 1 e 2 ϕ el , and the Schwarzschild-like gravitational one, Φ grav , is deformed, in the comparable-mass, comparable-charge, case, into a nonlinear relation which becomes universal in the high energy limit: Φ grav = 2 ϕ ~ − 5 ϕ ~ 2 + 18 ϕ ~ 3 .

Informeasure: an R/bioconductor package for quantifying nonlinear dependence between variables in biological networks from an information theory perspective

BackgroundUsing information measures to infer biological regulatory networks can capture nonlinear relationships between variables. However, it is computationally challenging, and there is a lack of convenient tools.ResultsWe introduce Informeasure, an R package designed to quantify nonlinear dependencies in biological regulatory networks from an information theory perspective. This package compiles a comprehensive set of information measurements, including mutual information, conditional mutual information, interaction information, partial information decomposition, and part mutual information. Mutual information is used for bivariate network inference, while the other four estimators are dedicated to trivariate network analysis.ConclusionsInformeasure is a turnkey solution, allowing users to utilize these information measures immediately upon installation. Informeasure is available as an R/Bioconductor package at https://bioconductor.org/packages/Informeasure.

The moderating effect of dietary fiber intake on the association between sleep pattern and liver fibrosis in metabolic dysfunction-associated steatotic liver disease: a study from NHANES

BackgroundInsufficient nocturnal sleep was associated with a higher risk of fibrosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Dietary fiber intake may improve the stimulate the secretion of sleep cytokines, inhibit the inflammatory pathway, contribute to regulating sleep disorders and alleviate liver fibrosis. The associations of dietary fiber intake, sleep patterns, with liver fibrosis remain unclear. The study aimed to explore the associations between dietary fiber, sleep, and liver fibrosis, as well as the moderating effect of dietary fiber intake between sleep patterns and liver fibrosis in MASLD patients.MethodsUsing data from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2017 to 2020, a cross-sectional study included participants with MASLD was performed to assess the relationship between sleep patterns, dietary fiber intake, and liver fibrosis. Weighted univariate and multivariate logistic regression models were used to examine the linear connection between sleep pattern, dietary fiber intake, and liver fibrosis. Restricted cubic spline (RCS) method was also performed to describe the nonlinear relationship. A two-part linear regression model was also used to estimate threshold effects. The moderating effect of dietary fiber intake was further investigated in different subgroups. All results were presented as odds ratios (ORs) and 95% confidence intervals (CIs).ResultsTotally, 1343 MASLD patients were included for final analysis. Among them, 207 (15.41%) have liver fibrosis. Dietary fiber intake did not correlate significantly with sleep pattern in patients with MASLD (Spearman’s r = -0.028, P = 0.1678). Poor sleep pattern was related to higher odds of liver fibrosis (OR = 3.23, 95%CI: 1.05–9.90), while dietary fiber intake ≥ 15 gm/day was associated with lower liver fibrosis risk (OR = 0.51, 95%CI: 0.32–0.83). On the association between sleep pattern and liver fibrosis stratified by dietary fiber intake revealed that poor sleep patterns (OR = 15.13, 95%CI: 4.40-52.01) remained associated with increased liver fibrosis risk among individuals with dietary fiber intake < 15 gm/day. No connection was observed between poor sleep patterns and liver fibrosis in MASLD patients with higher dietary fiber intake, with moderate dietary fiber supplementation beneficial in mitigating poor sleep patterns associated with liver fibrosis. The similar findings were also found in patients aged < 50 years old, ≥ 50 years old, females, those with and without CVD groups, hypertension, and dyslipidemia. Particularly, dietary fiber intake also moderates the relationship between sleep patterns and liver fibrosis in the F4 stage (OR = 13.26, 95%CI: 4.08–43.11).ConclusionDietary fiber intake affects the relationship between sleep patterns and liver fibrosis in MASLD patients.

Dispersion and dissipation of shear horizontal wave in magneto-electro-elastic material loaded with complex magnetic viscous fluid

Abstract The present study outlines the theoretical analysis of Shear horizontal (SH) wave propagation on magneto-electro-elastic (MEE) material lying on an elastic half-space and subjected to magnetic fluid loading. Using an exact analytical approach, complex dispersion relations for SH waves are derived under both electric short and electric open boundary conditions. To validate these derived relations, specific cases are considered where the MEE material behaves as piezoelectric and piezomagnetic. The complex dispersion relations are separated into real and imaginary components, revealing nonlinear relationships between phase velocity and attenuation of SH waves in relation to geometric parameters, frequency, and the physical properties of the magnetic fluid. Five different magnetic fluids are examined to illustrate the phase velocity and attenuation characteristics graphically. The effects of geometric and physical parameters of the magnetic fluids, the thickness of the MEE material, and the frequency and density of the elastic half-space on the phase velocity and attenuation of SH waves are discussed. Additionally, the finite element method (FEM) is employed to validate the results, ensuring the accuracy of the analytical findings. The results of this study are fundamental and can be used to design and development of surface acoustic wave (SAW) liquid sensors as well as magnetic field sensors.

Association of altitude with all-cause and cardiovascular mortality among patients with hypertension: a cohort study in Southwest China

BackgroundAvailable evidence falls short in assessing the risk of long-term outcomes among individuals with hypertension residing at various altitudes. We aimed to investigate the association between residential altitude and the risk of all-cause and cardiovascular disease (CVD) mortality among hypertensive patients.MethodsThis cohort study encompassed 67,275 hypertensive patients aged ≥35 years who participated in China’s Basic Public Health Service Program in 2018. Participants were categorized into four groups based on their residence altitude: <500 m, 500-1,499 m, 1,500-2,500 m, and > 2,500 m. The associations between residential altitude and the risks of all-cause and CVD mortality were analyzed using Cox proportional hazards regression models. The dose-response relationship was performed by the restricted cubic spline with multivariable adjusted models.ResultsAmong the 67,275 hypertensive patients included in the study (mean age of 63.9 years, with 45.3% male), 8,768 deaths were recorded, of which 5,666 were attributed to CVD. Following multivariate adjustment, when compared to the group residing at altitudes < 500 m, the groups living at altitudes of 500-1,499 m, 1500-2,500 m, and > 2,500 m exhibited significantly risks of all-cause mortality [HR = 1.45 (95% CI: 1.36–1.54), 1.35 (95% CI: 1.28–1.43), and 1.41 (95% CI: 1.28–1.54), respectively] and CVD mortality [HR = 1.47 (95% CI: 1.35–1.58), 1.42 (95% CI: 1.33–1.52), and 1.46 (95% CI: 1.31–1.62), respectively]. The restricted cubic spline curves revealed a nonlinear relationship between residential altitude and all-cause and CVD mortality. The risk of mortality was higher among participants with poorly controlled blood pressure, aged 65 years and above, and living in rural areas.ConclusionsThis study demonstrated a significant association between long-term residential high-altitude exposure and increased risks of all-cause and CVD mortality among hypertension patients. The implications of the findings call for a prioritization of public health resource allocation and early intervention efforts, especially for those living at high altitudes and in low-income areas where hypertension is prevalent.

N-terminal pro-brain natriuretic peptide and cardiorenal outcome in patients with anaemia in chronic kidney disease.

Blood levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) may be modified by low renal clearance and anaemia. The aim of this study was to investigate the impact of the blood NT-proBNP level on cardiovascular and renal outcomes in patients with these two manifestations. This post hoc analysis stemmed from the oBservational clinical Research In chronic kidney disease patients with renal anemia: renal proGnosis in patients with Hyporesponsive anemia To Erythropoiesis-stimulating agents, darbepoetiN alfa (BRIGHTEN) trial, a large prospective study involving patients with non-dialysis kidney disease experiencing anaemia. The Pearson correlation coefficient was employed to examine the association of baseline NT-proBNP level with renal function or anaemia. Longitudinal assessment of the association of baseline blood NT-proBNP levels with cardiovascular outcomes (cardiac death, acute coronary syndrome, hospitalization due to heart failure or fatal arrhythmia) and renal outcomes [the initiation of maintenance dialysis, kidney transplantation, a 50% decrease in the estimated glomerular filtration rate (eGFR) or an eGFR of ≤6mL/min/1.73m2] was conducted by using restricted cubic spline analysis and Cox proportional hazard model analysis. In total, this study included 1484 patients [mean age, 70.2±11.8years; women, 40.6%; eGFR, 20.3±9.6mL/min/1.73m2; haemoglobin (Hb) level, 9.8±0.9g/dL]. Baseline NT-proBNP levels were a median of 496.0pg/mL [inter-quartile range: 235.0-1090.0pg/mL]. A weak association existed between NT-proBNP levels, on a logarithmic scale, and eGFR (r=-0.131, P<0.001) or Hb levels (r=-0.182, P<0.001) at baseline. During 2.29±0.89years, 92 cardiovascular and 573 renal events were recorded. After adjusting for potential confounders such as eGFR and blood Hb level, a nonlinear relationship existed between blood NT-proBNP levels and cardiorenal outcomes. Patients with a baseline NT-proBNP level ≥1000 and 500-1000pg/mL exhibited a greater risk for cardiovascular outcomes than did patients with an NT-proBNP level <250pg/mL {hazard ratio [HR]=8.10 [95% confidence interval (CI), 2.80-23.40] and 3.35 [95% CI, 1.10-10.18], respectively}. These patients also exhibited a moderate risk for renal outcomes [HR=1.77 (95% CI, 1.36-2.31) and 1.54 (95% CI, 1.19-2.00), respectively]. NT-proBNP provides prognostic insights into cardiovascular and renal outcomes among patients with advanced chronic kidney disease experiencing anaemia.

Association of non-insulin-dependent insulin resistance indices with lower limb artery restenosis after drug-coated balloon angioplasty

BackgroundThis study aimed to investigate the associations between noninsulin-dependent insulin resistance indices (NI-IRIs), including the triglyceride-glucose (TyG) index, TyG-BMI, triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C), and metabolic score for insulin resistance (METS-IR), as well as the occurrence of restenosis in patients with lower extremity atherosclerotic occlusive disease after drug-coated balloon (DCB) treatment.MethodsThe primary endpoint was restenosis within one year after the procedure, which was defined as ≥ 50% stenosis of the treated artery segment. The association between NI-IRIs and restenosis was assessed via multivariable logistic regression analysis. Restricted cubic spline (RCS) analysis was performed to quantify nonlinearity. The consistency of these associations was confirmed through subgroup and interaction analyses. Additionally, the additional predictive value of NI-IRIs beyond established risk factors for restenosis was evaluated via receiver operating characteristic (ROC) curves, the net reclassification improvement (NRI), and integrated discrimination improvement (IDI) indices.ResultsExcept for the TyG index, the other three NI-IRIs demonstrated nonlinear relationships with the probability of postoperative restenosis. Specifically, TG/HDL-C (inflection point: 1.48, P for nonlinearity: 0.003) exhibited a saturating effect, whereas METS-IR (inflection point: 49.30, P for nonlinearity: 0.017) and TyG-BMI (inflection point: 221.53, P for nonlinearity: 0.039) showed threshold effects. Subgroup analysis revealed that the interactions among the subgroups were not statistically significant. Furthermore, among the four NI-IRIs, the addition of the TG/HDL-C index significantly enhanced the predictive power of the base model for restenosis in ASO patients following DCB angioplasty (AUC values: 0.726 vs. 0.760, P = 0.042). The P values for the NRI and IDI were 0.001 and 0.002, respectively.ConclusionTG/HDL-C showed a saturating effect on restenosis within one year after DCB treatment in ASO patients, and METS-IR and TyG-BMI showed threshold effects. The addition of the TG/HDL-C index significantly improved the predictive ability of the base model for restenosis in ASO patients who underwent DCB angioplasty.

Association between bowel movement frequency, stool consistency and MAFLD and advanced fibrosis in US adults: a cross-sectional study of NHANES 2005-2010

BackgroundAlthough previous studies have established associations between specific gut microbiota (GM) and metabolic dysfunction-associated fatty liver disease (MAFLD), research examining the relationship between functional gastrointestinal symptoms and MAFLD, including advanced fibrosis, remains limited. This study aims to investigate the association between stool consistency, bowel movement frequency (BMF), and the occurrence of MAFLD and advanced fibrosis in U.S. adults.MethodsThis population-based study included 9,928 adults from the 2005–2010 National Health and Nutrition Examination Survey (NHANES), with a mean age of 47.19 ± 16.65 years, comprising 47.7% males and 52.3% females. Weighted logistic regression was used to assess the association between stool consistency, BMF, and MAFLD or advanced fibrosis. A linear trend was assessed by treating BMF categories as continuous variables with ordinal values. The dose-response relationship between BMF and MAFLD was analyzed using restricted cubic splines (RCS) regression. Sensitivity and subgroup analyses were performed to confirm the robustness of the findings.ResultsIn the RCS regression, no significant nonlinear relationship was observed between BMF and the risk of MAFLD (p-overall < 0.0001; p-nonlinear = 0.0663). The multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for MAFLD were 0.82 (95% CI 0.69–0.98), 1.31 (95% CI 1.16–1.46), and 1.50 (95% CI 1.14–1.99) for participants with 3–6 BMs/week, 1–2 BMs/day, and > 2 BMs/day, respectively, compared to those with once/day (p-trend < 0.001). For stool consistency, hard stools were associated with a decreased risk of MAFLD (OR 0.77; 95% CI 0.62–0.95), whereas loose stools increased the risk (OR 1.37; 95% CI 1.05–1.80), relative to normal stools. A significant interaction between BMF and age was observed. No significant associations were found between stool consistency or BMF and advanced liver fibrosis. Sensitivity analyses confirmed the robustness of these findings.ConclusionsThis cross-sectional study demonstrates that a BMF of 3–6 BMs/week and hard stools are associated with a reduced risk of MAFLD, whereas a BMF of more than once/day and loose stools are linked to an increased risk of MAFLD. Moreover, no significant associations were observed between stool consistency, BMF, and advanced fibrosis among individuals diagnosed with MAFLD.Clinical trial numberNot applicable.

Association between brominated flame retardants and periodontitis: a large-scale population-based study

BackgroundThe association between brominated flame retardants (BFRs) and periodontitis has remained unclear.MethodsThis research included adult participants from NHANES cycles 2009–2014. Survey-weighted generalized linear regressions were used to explore the associations between BFR exposure and periodontitis. Ln-transformed BFRs were treated as quantitative variables and then divided into four quartiles for qualitative analysis. Restricted cubic splines (RCSs) were utilized to investigate potential nonlinear relationships. Quantile weighted quantile sum (WQS) regression and quantile g-computation (QGC) analysis were performed to assess the overall effect of BFRs on periodontitis.ResultsA total of 2,445 participants were included in this study. In the fully adjusted model, several ln-transformed BFR components were positively correlated with periodontitis: serum PBDE28, PBDE47, PBDE85, PBDE99, PBDE100, PBDE154, and PBB153. When expressed in quartiles, PBDE28, PBDE85, PBDE100, PBDE154, and PBB153 showed increased odds with periodontitis. We found significant nonlinear correlation between PBDE28, PBDE47, PBDE85, PBDE100, PBDE154, and PBB153 with periodontitis in the RCS regression. The WQS index for mixed BFR exposure was positively associated with periodontitis prevalence (OR: 1.52; 95% CI: 1.30–1.79, p &amp;lt; 0.001). Similarly, the QGC analysis showed a positive association between mixed BFR exposure and periodontitis prevalence (β: 1.29; 95% CI: 1.24–1.36, p &amp;lt; 0.001).ConclusionThis study indicates that overall exposure to BFRs is positively associated with the prevalence of periodontitis. Further research is needed to investigate the causal relationship and underlying mechanisms between BFRs and periodontitis.

Association of Physiological Reserve Obtained from Cardiopulmonary Exercise Testing and Frailty with All-Cause Mortality in Hemodialysis Patients.

Potential impairment of exercise capacity is prevalent even in patients undergoing hemodialysis without frailty. Cardiopulmonary exercise testing (CPET) can detect physiological reserves such as cardiopulmonary, muscle, and autonomic function. We hypothesized that these indices could accurately determine the prognosis of patients on hemodialysis and analyzed them based on their relationship to frailty. In this two-center prospective cohort study hemodialysis patients from Japan, participants underwent CPET and physical assessment to evaluate peak oxygen uptake (peak VO2, indicator of exercise capacity), peak work rate (WR, indicator of muscle function), ventilatory equivalent for carbon dioxide (VE/VCO2) slope (indicator of cardiac reserve), heart rate reserve (indicator of chronotropic incompetence), and frailty phenotype. Survival was followed-up for up to 5 years. Data from 189 patients (median [IQR] age: 71 [62, 77] years) were analyzed. All CPET indicators showed a consistent nonlinear relationship with all-cause mortality after adjustment: for peak VO2, hazard ratio [HR] 0.79 [95% CI: 0.71, 0.88], P <0.001; for peak WR, HR 0.95 [95% CI: 0.93, 0.97], P <0.001; for VE/VCO2 slope, HR 1.09 [95% CI: 1.05, 1.13], P <0.001; for heart rate reserve, HR 0.96 [95% CI: 0.93, 0.99], P=0.02). Frailty phenotype was associated with mortality after adjustment (HR 1.73 [95% CI: 1.06, 2.81], P=0.03); however, this association was not statistically significant in the model after adding peak VO2 (P=0.41). Furthermore, in both subgroups with and without frailty, CPET measures were significantly associated with mortality risk (peak VO2, peak WR, and VE/VCO2 slope: P <0.05). The peak VO2 (Δ area under the curve [AUC] 0.09, 95% CI: 0.02, 0.16) or the peak WR (ΔAUC 0.09, 95% CI: 0.02, 0.15) most significantly improved the prognostic accuracy. Results showed the fragile aspect of the frailty phenotype in the hemodialysis population and the superior ability of CPET to indicate death risk complementing that aspect.

Comparing and Optimizing Four Machine Learning Approaches to Radar-Based Quantitative Precipitation Estimation

To improve radar-based quantitative precipitation estimation (QPE) methods, this study investigated the relationship between radar reflectivity (Z) and hourly rainfall intensity (R) using data from 289 precipitation events in Shanghai between September 2020 and March 2024. Two Z-R relationship models were compared in terms of their fitting performance: Z = 270.81 R1.09 (empirically fitted relationship) and Z = 300 R1.4 (standard relationship). The results show that the Z = 270.81 R1.09 model outperforms the Z = 300 R1.4 model in terms of fitting accuracy. Specifically, the Z = 270.81 R1.09 model more effectively captures the nonlinear relationship between radar reflectivity and rainfall intensity, with a higher degree of agreement between the fitted curve and the observed data points. This model demonstrated superior performance across all 289 precipitation events. This study evaluated the performance of four machine learning approaches while incorporating five meteorological features: specific differential phase shift (KDP), echo-top height (ET), vertical liquid water content (VIL), differential reflectivity (ZDR), and correlation coefficient (CC). Nine QPE models were constructed using these inputs. The key findings are as follows: (1) For models with a single-variable input, the KAN deep learning model outperformed Random Forest, Gradient Boosting Decision Trees, Support Vector Machines, and the traditional Z-R relationship. (2) When six features were used as inputs, the accuracy of the machine learning models improved significantly, with the KAN deep learning model outperforming other machine learning methods. Compared to using only radar reflectivity, the KAN deep learning model reduced the MRE by 20.78%, MAE by 4.07%, and RMSE by 12.74%, while increasing the coefficient of determination (R2) by 18.74%. (3) The integration of multiple meteorological features and machine learning optimization significantly enhanced QPE accuracy, with the KAN deep learning model performing best under varying meteorological conditions. This approach offers a promising method for improving radar-based QPE, particularly considering seasonal, weather system, and precipitation stage differentiation.