Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Prognostic Value of Hemoglobin Concentration on Renal Outcomes with Diabetic Kidney Disease: A Retrospective Cohort Study

Objective

Diabetic kidney disease (DKD) patients with anemia face an elevated risk of glomerular filtration rate decline. However, the association between hemoglobin and estimated Glomerular Filtration Rate (eGFR) progression remains to be elucidated.

Methods

A retrospective cohort of 815 subjects with DKD was followed from January 2010 to January 2023. A Cox proportional hazard regression model was utilized to explore the predictive role of hemoglobin in renal outcomes. Renal outcomes were defined as a composite endpoint, including a 50% decline in eGFR from baseline or progression to End-Stage Renal Disease (ESRD). To unveil any nonlinear relationship between hemoglobin and renal outcomes, Cox proportional hazard regression with cubic spline functions and smooth curve fitting was conducted. Additionally, subgroup analyses were performed to identify specific patient populations that might derive greater benefits from higher hemoglobin.

Results

Among the 815 DKD subjects, the mean age was 56.482 ± 9.924 years old, and 533 (65.4%) were male. The mean hemoglobin was 121.521±22.960 g/L. The median follow-up time was 21.103±18.335 months. A total of 182 (22.33%) individuals reached the renal composite endpoint during the study period. After adjusting for covariates, hemoglobin was found to exert a negative impact on the renal composite endpoint in patients with DKD (HR 0.975, 95% CI [0.966, 0.984]). A nonlinear relationship between hemoglobin and the renal composite endpoint was identified with an inflection point at 109 g/L. Subgroup analysis unveiled a more pronounced association between hemoglobin and renal prognosis in males.

Conclusion

Hemoglobin emerges as a predictive indicator for the renal prognosis of diabetic kidney disease in China. This study reveals a negative and non-linear relationship between hemoglobin levels and the renal composite endpoint. A substantial association is noted when hemoglobin surpasses 109 g/L in relation to the renal composite endpoint.

Assessing the relationship between monocyte-to-HDL cholesterol ratio and mortality in patients with hypertrophic cardiomyopathy

OBJECTIVE

A new inflammatory marker, namely monocyte-to-high-density lipoprotein cholesterol ratio (MHR), has emerged as a useful indicator for adverse outcomes in several cardiovascular diseases; however, the relationship between MHR and the prognosis of hypertrophic cardiomyopathy (HCM) remains to be evaluated. We examined the relationship between MHR and all-cause mortality (ACM) in Chinese adult patients with HCM.

METHODS

We retrospectively performed clinical evaluation in 305 patients with HCM (median age: 52.0 years, male: 54.10%).

RESULTS

During a median follow-up of 4.9 years, ACM occurred in 57 (18.7%) patients. Based on the tertiles of baseline MHR, ACM increased with higher tertile. With tertile 1 as reference, adjusted ACM hazard ratios (HRs) were 2.68 for tertile 2 (95% confidence interval [CI]: 1.18-6.11, p = 0.019) and 4.85 for tertile 3 (95% CI: 2.16-10.89, p < 0.001). Stratified analysis and E-value analysis suggested the robustness of the above-mentioned results. Furthermore, adjusted smooth curve fitting exhibited a non-linear relationship between MHR and ACM (inflection point: 0.5), and the risk of ACM increased significantly with higher MHR only the value below the inflection point (HR: 4.37 per one standard deviation, 95% CI: 1.81-10.6, p = 0.001). Finally, sensitivity analysis was similar to the main findings.

CONCLUSION

In Chinese adult patients with HCM, higher MHR is a strong independent predictor of ACM, and a non-linear relationship is also observed between MHR and ACM.

Exploring non-linear effects of walking accessibility on well-being in rural older adults of Jintang County: a random forest analysis

Objective

The global concern surrounding the aging population has brought the well-being of older individuals to the forefront of societal attention. Unfortunately, studies focusing on the well-being of older people residing in rural areas are frequently overshadowed by the developmental disparities between rural and urban regions. Thus, this study aims to delve into the non-linear impact of walking accessibility on the subjective well-being of rural older adults. The goal is to gain a comprehensive understanding of this relationship, ultimately contributing to an improved quality of life and health for older adults in rural areas.

Methods

In this study, the Random Forest algorithm was employed to explore the non-linear effects of demographic variables, perceived safety, subjective built environment (including perceptions and preferences of the built environment), and walking accessibility on the subjective well-being of older adults.

Results

The findings of this study underscore the pivotal role of walking accessibility in influencing the well-being of older adults, particularly in terms of access to bazaars and health centers, where non-linear and threshold effects are evident. Furthermore, community safety, road conditions, and walking preferences were identified as positive influencers on the well-being of older adults. Well-being trends varied with age, revealing noteworthy non-linear relationships for certain variables.

Conclusion

The insights gained from this study provide crucial theoretical guidance for the development of policies tailored to the unique context of rural aging. By taking into account factors such as walking accessibility, community safety, health support, and social interaction, we can create an improved living environment for rural older adults, ultimately enhancing their happiness and overall quality of life.

Defining the threshold: triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio's non-linear impact on tubular atrophy in primary membranous nephropathy

Background

Hyperlipidemia is common in primary membranous nephropathy (PMN) patients, and tubular atrophy (TA) is an unfavorable prognostic factor. However, the correlation between the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and TA is controversial. Therefore, our study aimed to investigate the association between the TG/HDL-C ratio and TA in PMN patients.

Methods

We conducted a cross-sectional study and collected data from 363 PMN patients at Shenzhen Second People's Hospital from January 2008 to April 2023. The primary objective was to evaluate the independent correlation between the TG/HDL-C ratio and TA using binary logistic regression model. We used a generalized additive model along with smooth curve fitting and multiple sensitivity analyses to explore the relationship between these variables. Additionally, subgroup analyses were conducted to delve deeper into the results.

Results

Of the 363 PMN patients, 75 had TA (20.66%). The study population had a mean age of 46.598 ± 14.462 years, with 217 (59.78%) being male. After adjusting for sex, age, BMI, hypertension, history of diabetes, smoking, alcohol consumption, UPRO, eGFR, HB, FPG, and ALB, we found that the TG/HDL-C ratio was an independent risk factor for TA in PMN patients (OR=1.29, 95% CI: 1.04, 1.61, P=0.0213). A non-linear correlation was observed between the TG/HDL-C ratio and TA, with an inflection point at 4.25. The odds ratios (OR) on the left and right sides of this inflection point were 1.56 (95% CI: 1.17, 2.07) and 0.25 (95% CI: 0.04, 1.54), respectively. Sensitivity analysis confirmed these results. Subgroup analysis showed a consistent association between the TG/HDL-C ratio and TA, implying that factors such as gender, BMI, age, UPRO, ALB, hypertension and severe nephrotic syndrome had negligible effects on the link between the TG/HDL-C ratio and TA.

Conclusion

Our study demonstrates a non-linear positive correlation between the TG/HDL-C ratio and the risk of TA in PMN patients, independent of other factors. Specifically, the association is more pronounced when the ratio falls below 4.25. Based on our findings, it would be advisable to decrease the TG/HDL-C ratio below the inflection point in PMN patients as part of treatment strategies.

Bi-sinusoidal light stimulation reveals an enhanced response power and reduced phase coherence at the visual cortex in migraine

Introduction

Migraine is associated with enhanced visual sensitivity during and outside attacks. Processing of visual information is a highly non-linear process involving complex interactions across (sub)cortical networks. In this exploratory study, we combined electroencephalography with bi-sinusoidal light stimulation to assess non-linear features of visual processing in participants with migraine.

Methods

Twenty participants with migraine (10 with aura, 10 without aura) and ten non-headache controls were measured (outside attacks). Participants received bi-sinusoidal 13 + 23 Hz red light visual stimulation. Electroencephalography spectral power and multi-spectral phase coherence were compared between groups at the driving stimulation frequencies together with multiples and combinations of these frequencies (harmonic and intermodulation frequencies) caused by non-linearities.

Results

Only at the driving frequency of 13 Hz higher spectral power was found in migraine with aura participants compared with those with migraine without aura and controls. Differences in phase coherence were present for 2nd, 4th, and 5th-order non-linearities in those with migraine (migraine with and without aura) compared with controls. Bi-sinusoidal light stimulation revealed evident non-linearities in the brain's electroencephalography response up to the 5th order with reduced phase coherence for higher order interactions in interictal participants with migraine.

Discussion

Insight into interictal non-linear visual processing may help understand brain dynamics underlying migraine attack susceptibility. Future research is needed to determine the clinical value of the results.

Non-linear association of triglyceride-glucose index with prevalence of prediabetes and diabetes: a cross-sectional study

Background

The Triglyceride-glucose (TyG) index has been acknowledged as a convenient, cost-effective, and relatively simple marker for insulin resistance (IR). Meanwhile, prediabetes, described as an asymptomatic, moderately hyperglycemic state, tends to be more prevalent than diabetes. Thus, the objective of this study was to explore the relationship between the TyG index and the prevalence of both prediabetes and diabetes within the U.S. population.

Methods

This study utilized a cross-sectional dataset derived from the National Health and Nutrition Survey (NHANES) spanning 1999 to 2018. The subjects were individuals aged 18 years and above, who had available fasting glucose and fasting triglyceride information, permitting a diagnosis of prediabetes or diabetes. The TyG index was computed using laboratory data, and participants were subsequently categorized into quartiles based on this information. The relationship between the TyG index and the prevalence of prediabetes and diabetes was investigated using logistic regression analysis.

Results

Out of the 25,159 participants, 23.88% were found to have prediabetes, while 16.22% were diagnosed with diabetes. After adjusting for confounding factors, a linear increase in relative odds was observed in Q2 (OR: 1.69; 95% CI: 1.52, 1.89), Q3 (OR: 2.57; 95% CI: 2.30, 2.88), and Q4 (OR: 4.88; 95% CI: 4.33, 5.49) groups in comparison to the reference group, Q1. In addition, a non-linear relationship was observed between the TyG index and the prevalence of prediabetes and diabetes. Specifically, patients with a TyG index greater than 8.00 overall exhibited a significantly higher risk of prediabetes and diabetes, confirming that an increase in the TyG index is associated with a corresponding increase in risk. However, this shift showed gender-specific variations; the threshold was observed at 8.00 in males but shifted to 9.00 in females.

Conclusion

The TyG index demonstrated a non-linear positive correlation with both prediabetes and diabetes. This suggests that maintaining the TyG index at a certain, reduced level could potentially aid in preventing the onset of prediabetes and diabetes.

Evaluation of the non-linearity of NA808 in liver not reflected in plasma using a rat pharmacokinetic study and PBPK modelling

When NA808, a potent HCV replication inhibitor, was intravenously administered to rats, it was distributed to the liver. The AUC ratio in the liver of 20 mg/kg to 2 mg/kg was greater than the dose ratio, whereas exposure in plasma was increased in a dose-proportional manner. Saturation of biliary excretion was also shown at 20 mg/kg.NA808 was revealed to be a substrate for both OATP1B and MRP2 transporters by an in vitro study using OATP1B1-MRP2 expressing cells. [14C]NA808 was taken up into the cells by OATP1B1 and excreted from cells by MRP2 efficiently (Papp ratio: 24.2-70.2). The Papp ratio decreased with increasing NA808 concentration.PBPK modelling was constructed to display the blood and liver concentration time profile and biliary excretion of NA808. This model analysis was able to reproduce the pharmacokinetics in rats; the degree of increase in the liver exposure from 2 to 20 mg/kg was more than dose-proportional and was greater than the increase in the blood exposure due to saturation of efflux transporters.In drug development, to avoid unexpected toxicity in tissues, it is important to consider the potential for tissue non-linearity with linear plasma exposure based on pre-clinical data and PBPK modelling.

The systemic immune-inflammation index was non-linear associated with all-cause mortality in individuals with nonalcoholic fatty liver disease

OBJECTIVE

Systemic immune-inflammation index (SII), a novel inflammatory indicator based on platelets, neutrophils and lymphocytes, has been shown to be associated with prognostic value in several solid tumors. However, its prognostic value in nonalcoholic fatty liver disease (NAFLD) has not been reported yet. Therefore, the present study aimed to investigate the prognostic value of SII in individuals with NAFLD.

METHODS

Data was collected from the 2005 to 2014 National Health and Nutrition Examination Survey (NHANES, https://www.cdc.gov/nchs/nhanes/index.htm), and vital status was derived from the National Death Index (NDI) up to 31 December 2015. NAFLD was diagnosed based on Hepatic Steatosis Index (HSI). Multivariate Cox regression and Kaplan-Meier survival curves were performed to measure the hazard ratios (HRs) and 95% confidence interval (CI). Our study investigated the relationship between SII and all-cause mortality by using two-part linear regression models with penalized splines, as well as Cox models with penalized splines.

RESULTS

A total of 10,787 NAFLD participants (44.14% men) aged ≥20 years old were enrolled. There were 776 deaths from all causes after a mean follow-up period of 5.6 years. According to the full adjusted Cox regression analysis, the low log₂-SII group (quartile 1) and the highest log₂-SII group (quartile 4) were significantly associated with increased mortality from all causes (aHR =1.86; 95% CI: 1.47-2.37; p < 0.0001). After controlling for confounders, an increase in log₂-SII was associated with an increased all-cause mortality risk of 41% for every unit raised (aHR = 1.41; 95% CI: 1.26-1.57; p < 0.0001). After adjusting for multiple potential confounders, the association between log₂-SII and all-cause mortality was nonlinear, and the threshold value was 8.8. There was no association between an increase of one unit in log₂-SII and all-cause mortality below the threshold (aHR = 0.90, 95% CI: 0.71-1.15, p = 0.419). However, a higher log₂-SII was associated with a higher risk of death from any cause when it exceeded the threshold (aHR = 1. 73, 95% CI: 1.49-2.02, p < 0.001).

Based on a study of US NAFLD patients, it was found that the baseline log₂-SII is associated with all-cause mortality. Elevated SII is associated with poor survival among NAFLD patients.KEY MESSAGESUsing a large nationally representative survey of individuals among US adults, the study demonstrated that log₂-SII was J-shaped and associated with all-cause death among individuals with NAFLD.Spline analyses demonstrated that the association between log₂-SII and all-cause mortality was non-linear after adjusting for multiple potential confounders, and the threshold value was 8.8.Higher log₂-SII associated with poor survival in NAFLD.

Patient Confidential Data Hiding and Transmission System Using Amplitude Quantization in the Frequency Domain of ECG Signals

The transform domain provides a useful tool in the field of confidential data hiding and protection. In order to protect and transmit patients' information and competence, this study develops an amplitude quantization system in a transform domain by hiding patients' information in an electrocardiogram (ECG). In this system, we first consider a non-linear model with a hiding state switch to enhance the quality of the hidden ECG signals. Next, we utilize particle swarm optimization (PSO) to solve the non-linear model so as to have a good signal-to-noise ratio (SNR), root mean square error (RMSE), and relative root mean square error (rRMSE). Accordingly, the distortion of the shape in each ECG signal is tiny, while the hidden information can fulfill the needs of physiological diagnostics. The extraction of hidden information is reversely similar to a hiding procedure without primary ECG signals. Preliminary outcomes confirm the effectiveness of our proposed method, especially an Amplitude Similarity of almost 1, an Interval RMSE of almost 0, and SNRs all above 30.

Calibration methods to fit parameters within complex biological models

Mathematical and computational models of biological systems are increasingly complex, typically comprised of hybrid multi-scale methods such as ordinary differential equations, partial differential equations, agent-based and rule-based models, etc. These mechanistic models concurrently simulate detail at resolutions of whole host, multi-organ, organ, tissue, cellular, molecular, and genomic dynamics. Lacking analytical and numerical methods, solving complex biological models requires iterative parameter sampling-based approaches to establish appropriate ranges of model parameters that capture corresponding experimental datasets. However, these models typically comprise large numbers of parameters and therefore large degrees of freedom. Thus, fitting these models to multiple experimental datasets over time and space presents significant challenges. In this work we undertake the task of reviewing, testing, and advancing calibration practices across models and dataset types to compare methodologies for model calibration. Evaluating the process of calibrating models includes weighing strengths and applicability of each approach as well as standardizing calibration methods. Our work compares the performance of our model agnostic Calibration Protocol (CaliPro) with approximate Bayesian computing (ABC) to highlight strengths, weaknesses, synergies, and differences among these methods. We also present next-generation updates to CaliPro. We explore several model implementations and suggest a decision tree for selecting calibration approaches to match dataset types and modeling constraints.

A novel non-linear approach for establishing a QSAR model of a class of 2-Phenyl-3-(pyridin-2-yl) thiazolidin-4-one derivatives

In this investigation, we aimed to address the pressing challenge of treating osteosarcoma, a prevalent and difficult-to-treat form of cancer. To achieve this, we developed a quantitative structure-activity relationship (QSAR) model focused on a specific class of compounds called 2-Phenyl-3-(pyridin-2-yl) thiazolidin-4-one derivatives. A set of 39 compounds was thoroughly examined, with 31 compounds assigned to the training set and 8 compounds allocated to the test set randomly. The goal was to predict the IC50 value of these compounds accurately. To optimize the compounds and construct predictive models, we employed a heuristic method of the CODESSA program. In addition to a linear model using four carefully selected descriptors, we also developed a nonlinear model using the gene expression programming method. The heuristic method resulted in correlation coefficients (R 2) of 0.603, 0.482, and 0.107 for R2 cv and S2, respectively. On the other hand, the gene expression programming method achieved higher R 2 and S2 values of 0.839 and 0.037 in the training set, and 0.760 and 0.157 in the test set, respectively. Both methods demonstrated excellent predictive performance, but the gene expression programming method exhibited greater consistency with experimental values. The successful nonlinear model generated through gene expression programming shows promising potential for designing targeted drugs to combat osteosarcoma effectively. This approach offers a valuable tool for optimizing compound selection and guiding future drug discovery efforts in the battle against osteosarcoma.

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy: A Bayesian Approach

Background

Cognitive decline is a key outcome of clinical studies in Alzheimer's disease (AD).

Objective

To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts.

Methods

We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis.

Results

We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases.

Conclusions

We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid.

Association between weight-adjusted-waist index and female infertility: a population-based study

Aims

Obesity is detrimental to infertility. The association between weight-adjusted-waist index (WWI, a recently developed adiposity indicator) and infertility has not previously been confirmed.

Methods

The data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES) 2013-2018. Each participant's WWI was calculated as their waist circumference in centimeters by the square root of weight in kilograms. Multivariable logistic regression and generalized additive model were utilized to investigate the relationship between WWI with infertility. We used smoothed curve fitting to explore the non-linear relationship. Subgroup analysis and interaction tests were also conducted.

Results

A total of 3,526 participants with ages from18 to 45 were enrolled, 364 of whom were infertile. With the higher WWI, infertility was more prevalent (OR = 1.42, 95% CI: 1.22-1.65), and this association was still consistent in subgroups (all P for interaction> 0.05). Smoothed curve fitting showed a positive non-linear relationship between WWI and infertility. Furthermore, we discovered that WWI had a stronger connection with the risk of infertility than other markers of obesity including WC, body mass index (BMI) and a body shape index (ABSI).

Conclusions

Weight-adjusted-waist index levels were positively linked to an increased risk of infertility in American females and showed a stronger association than other markers of obesity. Our research indicated WWI could help identify women with infertility, and managing obesity as determined by WWI may help to reduce the risk of infertility.

Association between selenium intake and migraine: a nationwide cross-sectional study

Background

Dietary interventions for migraine are receiving increasing attention. However, it remains unclear whether there is any relationship between migraine and selenium intake. The aim of this study was to investigate the association between selenium intake and migraine.

Methods

We used multivariate logistic regression equations to explore the association between selenium intake and migraine. Restricted cubic splines were used to examine the presence of non-linear relationships. Upon finding a non-linear relationship, a recursive algorithm was used to calculate the inflection point. Population differences were also explored through stratified analysis.

Results

In the model adjusted for all covariates, the ORs (95% CI) for the association between selenium intake and migraine were 0.96 (0.88, 1.04), which was no statistical significance. However, the result of the linear trend test with quadrilles of selenium intake indicated the association between selenium intake and migraine may be non-linear. The restricted cubic splines confirmed this non-linear relationship, finding an inflection point (93.1 mcg/day), where the odds of migraine decreased with increasing selenium intake before the inflection point, and no statistically significant relationship was found after the inflection point. The association between selenium intake and migraine was non-linear in all strata except the obese.

Conclusion

We found a non-linear association between selenium intake and migraine in the general American population.

Non-linear effects of absolute risk information on individuals'self-evaluation, affective responses, and behavioral intentionsof precautionary actions against skin cancer

OBJECTIVE

The current study explores non-linear effects of absolute risk and effects of comparative risk information about skin cancer on individuals' safety ratings, affective responses and behavioral intentions.

METHOD

An experimental survey was conducted among college students (N = 563) to test the effects of absolute and comparative risk information across a range of risk levels from 3.7% to 60%.

RESULTS

The non-linear model of absolute risk effect was confirmed by the data. Absolute risk information had detectable effects at low levels of risk, but the effects did not change appreciably at the highest absolute risk levels. Regarding comparative risk, the data did not support its effects on individuals' safety ratings, affective responses and behavioral intentions.

CONCLUSION

The study found the non-linear model fits well to the skin cancer related feelings and behavioral intentions. It suggests future research apply non-linear models to a variety of health communication areas.

The nonlinear correlation between the cardiometabolic index and the risk of diabetes: A retrospective Japanese cohort study

BACKGROUND

The cardiometabolic index (CMI) has been proposed as a novel indicator of cardiometabolic status. However, evidence on the relationship between CMI and diabetes mellitus (DM) risk was limited. Our study aimed to explore the relationship between CMI and DM risk among a large cohort of Japanese adults.

METHODS

This retrospective cohort study recruited 15453 Japanese adults without diabetes at baseline who underwent physical examinations at the Murakami Memorial Hospital between 2004 and 2015. Cox proportional-hazards regression was applied to evaluate the independent relationship between CMI and diabetes. Our study performed a generalized smooth curve fitting (penalized spline technique) and an additive model (GAM) to determine the non-linear relationship between CMI and DM risk. In addition, a set of sensitivity analyses and subgroup analyses were employed to evaluate the relationship between CMI and incident DM.

RESULTS

After adjusting for confounding covariates, CMI was positively related to the DM risk in Japanese adults (HR: 1.65, 95%CI: 1.43-1.90, P<0.0001). A series of sensitivity analyses were also employed in this study to guarantee the reliability of the findings. In addition, our study discovered a non-linear association between CMI and diabetes risk. CMI's inflection point was 1.01. A strong positive association between CMI and diabetes incidence was also discovered to the left of the inflection point (HR: 2.96, 95%CI: 1.96-4.46, P<<0.0001). However, their association was not significant when CMI was higher than 1.01 (HR: 1.27, 95%CI: 0.98-1.64, P=0.0702). Interaction analysis showed that gender, BMI, habit of exercise, and smoking status interacted with CMI.

CONCLUSION

Increased CMI level at baseline is associated with incident DM. The association between CMI and incident DM is also non-linear. A high CMI level is associated with an increased risk for DM when CMI is below 1.01.

Continuously changing memories: a framework for proactive and non-linear consolidation

The traditional view of long-term memory is that memory traces mature in a predetermined 'linear' process: their neural substrate shifts from rapidly plastic medial temporal regions towards stable neocortical networks. We propose that memories remain malleable, not by repeated reinstantiations of this linear process but instead via dynamic routes of proactive and non-linear consolidation: memories change, their trajectory is flexible and reversible, and their physical basis develops continuously according to anticipated demands. Studies demonstrating memory updating, increasing hippocampal dependence to support adaptive use, and rapid neocortical plasticity provide evidence for continued non-linear consolidation. Although anticipated demand can affect all stages of memory formation, the extent to which it shapes the physical memory trace repeatedly and proactively will require further dedicated research.

Expectile Neural Networks for Genetic Data Analysis of Complex Diseases

The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. Expectile regression is a generalization of linear regression and provides complete information on the conditional distribution of a phenotype of interest. While expectile regression has many nice properties, it has rarely been used in genetic research. In this paper, we develop an expectile neural network (ENN) method for genetic data analyses of complex diseases. Similar to expectile regression, ENN provides a comprehensive view of relationships between genetic variants and disease phenotypes, which can be used to discover variants predisposing to sub-populations. We further integrate the idea of neural networks into ENN, making it capable of capturing non-linear and non-additive genetic effects (e.g., gene-gene interactions). Through simulations, we showed that the proposed method outperformed an existing expectile regression when there exist complex genotype-phenotype relationships. We also applied the proposed method to the data from the Study of Addiction: Genetics and Environment (SAGE), investigating the relationships of candidate genes with smoking quantity.

The use of non-linear tools to analyze the variability of force production as an index of fatigue: A systematic review

Background: Fatigue is a process that results in a decreased ability to produce force, and which could eventually affect performance and increase the risk of injury. Force variability analysis has been proposed to describe the level of fatigue with the purpose of detecting the development of fatigue. Variability is credited to play a functional and adaptive role through which the components of a system self-organize to solve a motor problem. Non-linear tools have been applied to analyze the variability of physiological signals, revealing that the structure of motor fluctuations provides relevant information about the functional role of variability. It has been suggested that the presence of lower complexity in the variability structure could reveal a less functional and adaptative state (e.g., ageing or illness). In the last years, an increased number of studies have applied these techniques to force variability analysis in relation to fatigue. Objective: To provide an overview of the current knowledge on the use of non-linear tools on force variability as a fatigue index. Methods: Following PRISMA guidelines, a systematic search of SPORTDiscus, Scopus, Web of Science and PubMed was carried out. Studies included were: a) original studies that analyzed the effect of fatigue on humans during an action focused on force production; b) published studies with their title and abstract in English; c) studies that applied non-linear tools on a signal directly related to force production. Results: Twenty-five studies were included in this review. The relationship between fatigue and the complexity of force variability, the type of action and relative intensity, the nature of the signal and the non-linear tools used, and the methods of data acquisition and processing were identified. Conclusion: The articles reviewed suggest that fatigue leads to a decrease in complexity mostly in isometric contractions, but this is not as clear in dynamic contractions. This fatigue-induced loss of complexity seems to be a result of changes in the nervous system at the central level, albeit triggered by peripheral mechanisms. It should be noted that non-linear tools are affected by the relative intensity of contraction, non-stationarity, and the acquisition and treatment of the signal.

Tourism and Green Development: Analysis of Linear and Non-Linear Effects

Clarifying the relationship between tourism and green development is conducive to promoting the harmonious coexistence of tourism industry benefits and economic and environmental systems. The externalities of tourism on economies and the environment have sparked numerous fascinating academic research debates; however, few studies have considered the impact of tourism on green development that balances economic growth and environmental protection. This study selects the green development efficiency measured by the super-efficient SBM model with undesired output as a proxy indicator of green development and adopts the panel data regression model and dynamic panel threshold regression model to investigate the linear impact and non-linear characteristics of tourism on the green development efficiency for 284 cities in mainland China at the prefecture level and above. The main findings are as follows: (1) Although China's green development efficiency showed an upward trend during the study period, the overall level was not high. (2) Tourism has significantly promoted the improvement of China's green development efficiency, indicating that tourism has become an effective driver of China's economic green transformation. (3) This type of positive promotion of green development by tourism has a non-linear threshold characteristic, which means that, with the continuous improvement of the development level of the tourism industry, after crossing a specific threshold value and entering a higher level of development, the tourism industry will have an increasing marginal impact on the green development efficiency.

Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio has a non-linear association with non-alcoholic fatty liver disease: A secondary prospective cohort study in non-obese Chinese adults

OBJECTIVE

The evidence for a relationship between the ratio of gamma-glutamyl transferase (GGT) to high-density lipoprotein cholesterol (HDL-c) and non-alcoholic fatty liver disease (NAFLD) is currently inadequate. This study aimed to investigate the relationship between the GGT/HDL-c ratio and NAFLD.

MATERIALS AND METHODS

This study is a prospective cohort study that recruited a total of 11,891 non-obese volunteers in a Chinese hospital from January 2010 to December 2014 in a non-selective manner. The Cox proportional-hazards regression model was then used to investigate the relationship between baseline GGT/HDL-c ratio and the probability of developing NAFLD. The non-linear link between the GGT/HDL-c ratio and NAFLD was identified using a Cox proportional hazards regression with cubic spline functions and smooth curve fitting (cubic spline smoothing). Furthermore, we conducted several sensitivity and subgroup analyses. Data had been uploaded to the DATADRYAD website.

RESULTS

The mean age of study participants was 43.29 ± 14.95 years old, and 6,502 (54.68%) were male. The median (interquartile ranges) of GGT/HDL-c ratio was 15.56 (10.73-23.84). During a median follow-up of 29.35 months, 2028 (17.05%) participants were diagnosed with NAFLD. After adjusting for covariates, the results showed that GGT/HDL-c ratio was positively associated with incident NAFLD (HR = 1.014, 95% CI 1.011-1.017). There was also a non-linear relationship between GGT/HDL-c ratio and NAFLD, and the inflection point of the GGT/HDL-c ratio was 20.35. The effect sizes (HR) on the left and right sides of the inflection point were 1.113 (95% CI 1.096, 1.130) and 1.003 (95% CI 1.000-1.007), respectively. Moreover, the sensitivity analysis demonstrated the robustness of our results. Subgroup analysis showed that GGT/HDL-c ratio was more strongly associated with incident NAFLD in triglyceride (TG) < 1.7 mmol/L participants. In contrast, the weaker association was probed in those with TG ≥ 1.7 mmol/L.

CONCLUSION

The present study reveals a positive and non-linear relationship between the GGT/HDL-c ratio and NAFLD risk in a non-obese Chinese population. GGT/HDL-c ratio is strongly associated with NAFLD when GGT/HDL-c ratio is less than 20.35. Therefore, maintaining the GGT/HDL-c ratio lower than the inflection point is recommended from a treatment perspective.

Poroelastic plant-inspired structures & materials to sense, regulate flow, and move

Despite their lack of a nervous system and muscles, plants are able to feel, regulate flow, and move. Such abilities are achieved through complex multi-scale couplings between biology, chemistry, and physics, making them difficult to decipher. A promising approach is to decompose plant responses in different blocks that can be modeled independently, and combined later on for a more holistic view. In this perspective, we examine the most recent strategies for designing plant-inspired soft devices that leverage poroelastic principles to sense, manipulate flow, and even generate motion. We will start at the organism scale, and study how plants can use poroelasticity to carry informationin-lieuof a nervous system. Then, we will go down in size and look at how plants manage to passively regulate flow at the microscopic scale using valves with encoded geometric non-linearities. Lastly, we will see at an even smaller scale, at the nanoscopic scale, how fibers orientation in plants' tissues allow them to induce motion using water instead of muscles.

Non-linear association between composite dietary antioxidant index and depression

Background

Growing evidence has shown that the antioxidant diet is a protective factor against depression. However, the relationship between the Composite Dietary Antioxidant Index (CDAI), an important measure of antioxidant diet, and depression has received little attention. Therefore, we investigated the relationship between CDAI and depression through a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018.

Methods

The association between CDAI and depression was investigated using a weighted multiple logistic regression model with subgroup analysis. Non-linear correlations were explored using fitted smoothing curves. And we used a recursive method to figure out the turning point and build a weighted two-piece linear regression model.

Results

In the multivariate logistic regression model with full adjustment for confounding variables, the ORs (95% CI) for the association between CDAI and depression were 0.83 (0.78, 0.88). Moreover, a non-linear association was found, with 0.16 being the inflection point. Before the inflection point, each unit increase in CDAI was associated with a 30% decrease in the risk of depression. After the inflection point, the risk of depression was found to be reduced by 11% for each unit increase. None of the interactions in all subgroup analyses were statistically significant.

Conclusions

Our study highlighted a negative non-linear association between CDAI and depression in a nationally representative sample of US adults. Further clinical and basic research is needed to explore their association better.

Linear and non-linear Mendelian randomization analyses of sex-specific associations between sleep duration and hyperuricemia

Background

Observational studies have suggested a potential non-linear association between sleep duration and hyperuricemia. However, the causal nature and sex-specific differences are poorly understood. We aimed to determine the shape of sex-specific causal associations between sleep duration and hyperuricemia in the UK Biobank.

Methods

Logistic regression was used to investigate the observational association between self-reported sleep duration and hyperuricemia among 387,980 white British participants (mean age: 56.9 years and 46.0% males). Linear and non-linear Mendelian Randomization (MR) analyses were performed to assess the causal association between continuous sleep duration and hyperuricemia. The causal effects of genetically predicted short (<7 h) and long (>8 h) sleep durations on hyperuricemia were further estimated, respectively.

Results

Traditional observational analysis suggested U- and J-shaped associations between sleep duration and hyperuricemia in females and males, respectively. Linear MR did not support the causal effect of sleep duration on hyperuricemia. Non-linear MR demonstrated an approximately U-shaped causal association between continuous sleep duration and hyperuricemia in overall participants and females, but not in males. Genetically predicted short sleep duration was significantly associated with hyperuricemia in females (OR [95% CI]: 1.21 [1.08–1.36]; P = 0.001), but not in males (1.08 [0.98–1.18]; P = 0.137). By contrast, genetically predicted long sleep duration was not significantly associated with the risk of hyperuricemia in either females or males.

Conclusion

Genetically predicted short sleep duration is a potential causal risk factor for hyperuricemia for females but has little effect on males. Long sleep duration does not appear to be causally associated with hyperuricemia.

Modeling multivariate age-related imaging variables with dependencies

Neuroimaging techniques have been increasingly used to understand the neural biology of aging brains. The neuroimaging variables from distinct brain locations and modalities can exhibit age-related patterns that reflect localized neural decline. However, it is a challenge to identify the impacts of risk factors (eg, mental disorders) on multivariate imaging variables while simultaneously accounting for the dependence structure and nonlinear age trajectories using existing tools. We propose a mixed-effects model to address this challenge by building random effects based on the latent brain aging status. We develop computationally efficient algorithms to estimate the parameters of new random effects. The simulations show that our approach provides accurate parameter estimates, improves the inference efficiency, and reduces the root mean square error compared to existing methods. We further apply this method to the UK Biobank data to investigate the effects of tobacco smoking on the white matter integrity of the entire brain during aging and identify the adverse effects on white matter integrity with multiple fiber tracts.

NoLiTiA: An Open-Source Toolbox for Non-linear Time Series Analysis

In many scientific fields including neuroscience, climatology or physics, complex relationships can be described most parsimoniously by non-linear mechanics. Despite their relevance, many neuroscientists still apply linear estimates in order to evaluate complex interactions. This is partially due to the lack of a comprehensive compilation of non-linear methods. Available packages mostly specialize in only one aspect of non-linear time-series analysis and most often require some coding proficiency to use. Here, we introduce NoLiTiA, a free open-source MATLAB toolbox for non-linear time series analysis. In comparison to other currently available non-linear packages, NoLiTiA offers (1) an implementation of a broad range of classic and recently developed methods, (2) an implementation of newly proposed spatially and time-resolved recurrence amplitude analysis and (3) an intuitive environment accessible even to users with little coding experience due to a graphical user interface and batch-editor. The core methodology derives from three distinct fields of complex systems theory, including dynamical systems theory, recurrence quantification analysis and information theory. Besides established methodology including estimation of dynamic invariants like Lyapunov exponents and entropy-based measures, such as active information storage, we include recent developments of quantifying time-resolved aperiodic oscillations. In general, the toolbox will make non-linear methods accessible to the broad neuroscientific community engaged in time series processing.

Dynamic Effects of Immersive Bilingualism on Cortical and Subcortical Grey Matter Volumes

Bilingualism has been shown to induce neuroplasticity in the brain, but conflicting evidence regarding its specific effects in grey matter continues to emerge, probably due to methodological differences between studies, as well as approaches that may miss the variability and dynamicity of bilingual experience. In our study, we devised a continuous score of bilingual experiences and we investigated their non-linear effects on regional GM volume in a sample of young healthy participants from an immersive and naturalistic bilingual environment. We focused our analyses on cortical and subcortical regions that had been previously proposed as part of the bilingual speech pipeline and language control network. Our results showed a non-linear relationship between bilingualism score and grey matter volume of the inferior frontal gyrus. We also found linear increases in volumes of putamen and cerebellum as a function of bilingualism score. These results go in line with predictions for immersive and naturalistic bilingual environments with increased intensity and diversity of language use and provide further evidence supporting the dynamicity of bilingualism’s effects on brain structure.

Non-Linear Association between Serum Folate Concentration and Dyslipidemia: Korea National Health and Nutrition Examination Survey (KNHANES) 2016-2018

Objectives

We aimed to evaluate the association between serum folate concentration and prevalence of dyslipidemia.

Methods

A total of 4,477 adults (2,019 men and 2,458 women) enrolled in the Korea National Health and Nutrition Examination Survey (KNHANES) 2016-2018 were included. Serum samples were used to access folate concentration and total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL)-cholesterol, and high-density lipoprotein (HDL)-cholesterol levels. Multivariate logistic regression with a sampling weight was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs).

Results

Elevated TC, TG, LDL-cholesterol and HDL-cholesterol were observed in 506 (11.3%), 646 (14.4%), 434 (9.7%), and 767 (17.1%) participants, respectively. We found non-linear trends between serum folate concentration and prevalence of hypercholesterolemia and hyper-LDL cholesterolemia from the restricted cubic smoothing spline. A higher prevalence of hypercholesterolemia was observed among participants in the 1st tertile serum folate concentration group (OR [95% CI] = 1.38 [1.05-1.79]) compared to those in the 2nd tertile group. On the other hand, a higher prevalence of hyper-LDL cholesterolemia was identified for both the 1st and 3rd serum folate concentration tertile groups (OR [95% CI]: 1.49 [1.08-2.05] and 1.63 [1.20-2.20], respectively); furthermore, in these tertiles, the prevalence of hyper-LDL cholesterolemia was more pronounced among obese participants.

Conclusion

Non-linear associations may exist between serum folate concentration and the prevalence of hypercholesterolemia and hyper-LDL cholesterolemia in adults. The findings suggest that more accurate recommendations about folate intake and folic acid fortification and supplementation should be provided.

Performance evaluation of regression models for COVID-19: A statistical and predictive perspective

Research is very important in the pandemic situation of COVID-19 to deliver a speedy solution to this problem. COVID-19 has presented governments, corporations and ordinary citizens around the world with technology playing an essential role to tackle the crisis. Moderate and flexible innovation arrangements that can speed up progress towards giving critical well-being ability are proved hourly. Knowledge with the aid of creativity must be obtained, accepted and analysed in a short time frame. In this example, the machine learning model has a major role to play in predicting the number of next positive COVID-19 cases to come. For government departments to take effective and strengthened future COVID-19 planning and innovation. The ongoing global pandemic of COVID-19 has been non-linear and dynamic. Due to the especially perplexing nature of the COVID-19 episode and its diversity from country to country, this study recommends machine learning as a convincing means to demonstrate flare-up. In this linear regression, polynomial regression, ridge regression, polynomial ridgeregression, support vector regression models, the COVID-19 data set from multiple on-line tools have been evaluated. During the work process comprehensive experiments were performed and each test was evaluated with the parameters mean square error (MSE), medium absolute error (MAE), root mean square error (RMSE) and R2 score. This study also offers a path for future research using regression models based on machine learning. Precise validation and data analysis can contribute to strategies for healing and disease prevention at an early stage. A systematic comprehensive strategy is a new philosophy in which statistical data for government agencies and community can be forecast.

Alcohol consumption and risk of Alzheimer's disease: A dose-response meta-analysis

AIM

This study aimed to investigate the association between alcohol consumption and the risk of Alzheimer's disease (AD).

METHODS

PubMed and Web of Science databases were systematically searched as of 1 September 2019. Relative risk and 95% CI were used to evaluate the association between alcohol consumption and AD risk. Subgroup analyses based on the type of alcohol, ethnicity, study design and sex were carried out. An alcohol dose-response meta-analysis was carried out.

RESULTS

A total of 13 studies were included in the quantitative synthesis, and six were used in the dose-response meta-analysis. Compared with non-drinkers, individuals who drank had a lower risk of AD (relative risk 0.68, 95% CI 0.53-0.87; I²  = 87.9%, P < 0.001). In subgroup analyses, drinking wine was found to reduce the occurrence of AD (relative risk 0.71, 95% CI 0.51-0.96). When stratified by ethnicity, sex and study design, no association was seen between AD risk and alcohol use. There was an overall non-linear, but not significant, association between alcohol intake dose and AD risk. A significant non-linear association was observed between excess AD risk and alcohol intake dose in men (overall P = 0.023; P for non-linearity = 0.025) starting from 14.8 drinks per week. Women's alcohol intake dose <16.9 drinks per week showed a significant non-linear association with decreased AD risk (overall P = 0.002; P for non-linearity = 0.019).

CONCLUSIONS

Drinking alcohol could reduce the risk of AD. Alcohol dose had a non-linear, but non-significant, relationship with the development of AD. The amount of alcohol consumption showed significant sex-specific effects on AD. Geriatr Gerontol Int 2022; ••: ••-••.

Using a Network Physiology Approach to Prescribe Exercise for Exercise Oncology

Current American College of Sports Medicine (ACSM) exercise guidelines for exercise oncology survivors are generic one-size fits all recommendations, which assume ideal or prototypic health and fitness state in order to prescribe. Individualization is based on the objective evaluation of the patient's baseline physiological status based on a linear dose response relationship of endpoints. This is only a partial snapshot of both the acute and chronic responses exercise can provide. Each acute exercise session represents a unique challenge to whole-body homeostasis and complex acute and adaptive responses occur at the cellular and systemic levels. Additionally, external factors must be considered when prescribing exercise. Network physiology views the human organism in terms of physiological and organ systems, each with structural organization and functional complexity. This organizational approach leads to complex, transient, fluctuating and nonlinear output dynamics which should be utilized in exercise prescription across health states. Targeting health outcomes requires a multi-system approach as change doesn't happen in only one system at a time or in one direction Utilizing a multi-system or person-centered approach, allows for targeting and personalization and understands and targets non-linear dynamics of change. Therefore, the aims of this review are to propose a paradigm shift towards a Network Physiology approach for exercise prescription for cancer survivors. Cancer treatment affects multiple systems that interact to create symptoms and disruptions across these and therefore, prescribing exercise utilizing both external daily factors and internal physiological networks is of the highest order.

About-Weekly Pattern in the Dynamic Complexity of a Healthy Subject's Cellular Immune Activity: A Biopsychosocial Analysis

In a previous integrative single-case study, we collected biological, psychological and social time-series data on a 25-year-old healthy woman over the course of 126 12-h intervals (63 days) and used urinary neopterin as an indicator of cellular immune activity [Schubert et al. 2012 (1)]. The present re-evaluation introduced Dynamic Complexity (DC) as an additional non-linear and non-stationary measure to further investigate the subject's biopsychosocial dynamics during the study. The new time series dealing with urinary neopterin complexity revealed a cyclic, circaseptan (about-weekly) repeating pattern (6.59 days). The only weekly reoccurring events over the course of the study that were associated with this immunological pattern were the in-depth interviews with the subject (mean distance between interviews: 6.5 days). Superposed epoch analysis (SEA) revealed a U-shaped relation between neopterin complexity and interviews, with a decrease in neopterin complexity before and during interviews and an increase after interviews. Furthermore, the complexity scores for irritation, anxiousness/depressiveness and mental activity were positively correlated with neopterin complexity. The results suggest that the interviews, which had been found to be related to the subject's need for educational and/or social accomplishment, were marked by stress (decrease in psycho-immunological flexibility and adaptability), which was then relieved after the interviews (increase in psycho-immunological flexibility and adaptability). It appears that the subject's cellular immune activity, as indicated by neopterin complexity, functionally mirrored the emotional meaning she ascribed to the in-depth interviews. This re-evaluation is in line with the view that biopsychosocial research requires multimodal analysis of single cases based on qualitative (e.g., in-depth interviews) and quantitative (e.g., time series analysis) data under conditions of "life as it is lived".

Relationship of Noninvasive Assessment of Arterial Stiffness with 10-Year Atherosclerotic Cardiovascular Disease (ASCVD) Risk in a General Middle-Age and Elderly Population

Purpose

As a powerful indicator of arterial stiffening, the brachial-ankle pulse wave velocity (baPWV) has been extensively validated for predicting cardiovascular events. However, whether and how the brachial-ankle pulse wave velocity (baPWV) is correlated with the 10-year atherosclerotic cardiovascular disease (ASCVD) risk is unclear. This study aimed to investigate the association between baPWV and 10-year ASCVD risk in Chinese population.

Methods

A total of 1768 subjects were enrolled from Shanghai, China. They were divided into two groups according to the Pooled Cohorts Equations model made by ACC/AHA as follows: low ASCVD risk (n = 992, 10-year ASCVD risk <7.5%) and high ASCVD risk (n = 776, 10-year ASCVD risk ≥7.5%). The baseline characteristics were obtained via the use of a questionnaire. Measurement of baPWV, laboratory tests, and echocardiography were conducted by trained physicians. The relationship between baPWV and 10-year ASCVD risk was evaluated using multiple logistic regression model and generalized additive model.

Results

The mean age of the subjects was 58.89±8.60 years, 32.69% of which were male. Non-linear relationship analysis revealed threshold effects between baPWV and 10-year ASCVD risk in which a baPWV of approximately 16 m/s might be the threshold effect of 10-year ASCVD risk. After multivariable adjustment, logistic-regression analysis demonstrated that ankle-brachial index (ABI) (OR 5.28, 95% CI 1.20–12.23) and baPWV (OR 9.09, 95% CI 6.84–12.07) were independently correlated with 10-year ASCVD risk. The AUC for baPWV for predicting 10-year ASCVD risk was 0.80 (95% CI 0.78–0.82).

Conclusion

Increased baPWV as an indicator of arterial stiffness correlates strongly with 10-year ASCVD risk in general middle-aged and elderly populations. The association between baPWV and 10-year ASCVD risk is not purely linear but non-linear. Subjects with baPWV above 16 m/s are more likely to encounter a higher 10-year ASCVD risk.

Threshold Effect in the Relationship between Environmental Regulations and Haze Pollution: Empirical Evidence from PSTR Estimation

The impact of environmental regulations (ER) on haze pollution control has been continuously debated in the field of sustainable development. This paper explores the direct and indirect threshold effects of ER on haze pollution, and five underlying mechanisms—technological innovation (TI), industrial structure (IS), foreign direct investment (FDI), urbanization (UR), and electricity consumption (EC)—are adopted to investigate the indirect threshold effects. Panel data, over the period 2008–2018, of 284 Chinese cities were used and the threshold effects were predicted endogenously based on the panel smooth transition regression (PSTR) model. The results showed the following: (1) For the direct threshold effect, there exists a U-shaped relationship between ER and haze pollution. ER significantly reduced haze pollution when ER < 38.86 due to “cost effects”. However, ER increased haze pollution after the threshold owing to the “green paradox”, which was not significant. (2) For the indirect threshold effect, when TI = 0.37, IS = 39.61, FDI = 7.25, and UR = 42.86, the relationships between ER and haze pollution changed. The changes and corresponding reasons for the indirect threshold effects are discussed in detail. (3) After a comprehensive analysis, the threshold effects have obvious regional distribution characteristics and internal connections. Finally, based on the results, it is essential for governments to enact appropriate environmental regulatory policies and enhance inter-regional synergies in environmental governance.

ECG Authentication Based on Non-Linear Normalization under Various Physiological Conditions

The development and use of wearable devices require high levels of security and have sparked interest in biometric authentication research. Among the available approaches, electrocardiogram (ECG) technology is attracting attention because of its strengths in spoofing. However, morphological changes of ECG, which are affected by physical and psychological factors, can make authentication difficult. In this paper, we propose authentication using non-linear normalization of ECG beats that is robust to changes in ECG waveforms according to heart rate fluctuations in various daily activities. We performed a non-linear normalization method through the analysis of ECG alongside heart rate, evaluating similarities and authenticating the performance of our new method compared to existing methods. Compared with beats before normalization, the average similarity of the proposed method increased 23.7% in the resting state and 43% in the non-resting state. After learning in the resting state, authentication performance reached 99.05% accuracy for the resting state and 88.14% for the non-resting state. The proposed method can be applicable to an ECG-based authentication system under various physiological conditions.

Using Restricted Cubic Splines to Study the Trajectory of Systolic Blood Pressure in the Prognosis of Acute Myocardial Infarction

Background: Acute myocardial infarction (AMI) is still the most serious manifestation of coronary artery disease. Systolic blood pressure (SBP) is the best predictor of blood pressure in AMI. Thus, its influence on AMI is necessary to be explored. Methods: A total of 4,277 patients with AMI were extracted from the Medical Information Mart for Intensive Care database. Chi-square test or Student's t-test was used to judge differences between groups, and Cox regression was used to identify factors that affect AMI prognosis. SBP was classified as low (<90 mmHg), normal (90-140 mmHg), or high (>140 mmHg), and a non-linear test was performed. Meaningful variables were incorporated into models for sensitivity analysis. Patient age was classified as low and high for subgroup analysis, and the cutoff value of the trajectory was identified. P < 0.05 indicates statistical significance. Results: The effect of SBP on the prognosis of patients with AMI is non-linear. The risks in models 1-3 with low SBP are 6.717, 4.910, and 3.080 times those of the models with normal SBP, respectively. The risks in models 1-3 with high SBP are 1.483, 1.637, and 2.937 times those of the models with normal SBP, respectively. The cutoff point (95% confidence interval) of the trajectory is 114.489 mmHg (111.275-117.702 mmHg, all P < 0.001). Conclusions: SBP has a non-linear effect on AMI prognosis. Low and high SBP show risks, and the risk of low SBP is obviously greater than that of high SBP.

Non-Linear Effects of the Built Environment and Social Environment on Bus Use among Older Adults in China: An Application of the XGBoost Model

Global aging has raised increasing concerns on the health and well-being of older adults. Public transport is a viable option to improve the mobility and quality of life among older adults. However, policies that promote the public transport use among older adults are rare. This study utilizes the eXtreme Gradient Boosting (XGBoost) decision tree to explore the non-linear associations of the built and social environment with bus use among older adults in China. The bus use of older adults was obtained from the Zhongshan Household Travel Survey (ZHTS) in 2012. Results show that non-linear relationships exist among all built environment and social environment characteristics. Within certain thresholds, the percentage of green space land use, land use mixture, bus-stop density, and dwelling unit density are positively related to bus use among older adults. Likewise, one social environment variable, the proportion of older adults in a neighborhood, is the key social environment variable. Furthermore, the dwelling unit density and proportion of older adults appear to have an inverse U-shaped relationship. Additionally, age, ownership of motorcycles, and distance from home to the nearest bus stop also show non-linearity. The findings presented in this paper facilitate effective planning interventions to promote bus use among older adults.

Longitudinal Plasma Metabolomics Profile in Pregnancy-A Study in an Ethnically Diverse U.S. Pregnancy Cohort

Amino acids, fatty acids, and acylcarnitine metabolites play a pivotal role in maternal and fetal health, but profiles of these metabolites over pregnancy are not completely established. We described longitudinal trajectories of targeted amino acids, fatty acids, and acylcarnitines in pregnancy. We quantified 102 metabolites and combinations (37 fatty acids, 37 amino acids, and 28 acylcarnitines) in plasma samples from pregnant women in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies—Singletons cohort (n = 214 women at 10–14 and 15–26 weeks, 107 at 26–31 weeks, and 103 at 33–39 weeks). We used linear mixed models to estimate metabolite trajectories and examined variation by body mass index (BMI), race/ethnicity, and fetal sex. After excluding largely undetected metabolites, we analyzed 77 metabolites and combinations. Levels of 13 of 15 acylcarnitines, 7 of 25 amino acids, and 18 of 37 fatty acids significantly declined over gestation, while 8 of 25 amino acids and 10 of 37 fatty acids significantly increased. Several trajectories appeared to differ by BMI, race/ethnicity, and fetal sex although no tests for interactions remained significant after multiple testing correction. Future studies merit longitudinal measurements to capture metabolite changes in pregnancy, and larger samples to examine modifying effects of maternal and fetal characteristics.

Non-linear Relationships Between the Built Environment and Walking Frequency Among Older Adults in Zhongshan, China

Aim: Promoting walking activity is an effective way to improve the health of older adults. Walking frequency is a critical component of walking behavior and an essential determinant of daily walking levels. To decipher the association between the built environment and walking frequency among older adults, this study's aims are as follows: (1) to empirically test whether non-linear relationships between the two exist, and (2) to identify the thresholds of the built environment characteristics that promote walking.

Methods: The walking frequency of old adults was derived from the Zhongshan Household Travel Survey (ZHTS) in 2012. The sample size of old adults aged 60 or over was 4784 from 274 urban and rural neighborhoods. A semi-parametric generalized additive model (GAMM) is used to analyze the non-linear or non-monotonic relationships between the built environment and the walking frequency among older adults.

Results: We found that non-linear relationships exist among five out of the six built environment characteristics. Within certain thresholds, the population density, sidewalk density, bus stop density, land use mixture, and the percentage of green space are positively related to older adults' walking trips. Furthermore, the land use mixture and the percentage of green space show an inverse “V”-shaped relationship.

Conclusions: Built environment features can either support or hinder the walking frequency among older adults. The findings in the current study contribute to effective land use and transport policies for promoting active travel among older adults.

Socio-demographic factors in relation to habitual sodium and potassium intakes among adults in Trinidad and Tobago

BACKGROUND

Approximately one-third of adults in Trinidad and Tobago have high blood pressure (hypertension). Excessive consumption of sodium (Na⁺) is a known risk factor for hypertension.

AIM

We investigated Na⁺ and potassium (K⁺) intakes and their correlates in a multi-ethnic Caribbean population.

METHOD

Volunteers completed a self-administered questionnaire comprising socio-demographic items, physical activity (PA) and a semiquantitative food frequency questionnaire. Foods eaten were classified by level of processing using the NOVA classification system and analysed for Na⁺ and K⁺ levels using appropriate dietary analysis software. The study was approved by the University of the West Indies at Saint Augustine Ethics Committee.

RESULTS

11,783 adults participated in the study. Approximately 83.2% of total calories, 79% of Na⁺ and 40% of K⁺ was derived from the consumption of highly processed foods. Median daily Na⁺ and K⁺ intakes were 2759 mg and 2853 mg, respectively. Na⁺ intakes showed significant nonlinear increases with age (p < 0.001) and body mass index (BMI) (p < 0.001), and non-linear decreases with educational attainment (p < 0.001). K⁺ intakes showed significant nonlinear decreases with age (p < 0.001) and BMI (p < 0.001), and linear increases with educational attainment (p < 0.001). Males had higher intakes of Na⁺ and K⁺ than females. Na⁺: K⁺ was lower among persons participating in moderate to high intensity PA ≥ 150 minutes/week compared to those participating in such activities < 150 minutes/week.

CONCLUSION

Socio-demographic factors were significantly correlated with Na⁺ and K⁺ intakes among participants and must be considered in strategies aimed at achieving healthy intakes of these nutrients.

Regular-Type Liesegang Pattern of AgCl in a One-Dimensional System

The Liesegang phenomenon can be used for micro- and nanofabrication processes to yield materials with periodic precipitation of diverse types of materials. Although there have been several attempts to control the periodicity of the Liesegang patterns, it remains unclear whether the periodic precipitation of AgCl in gel medium causes regular- or revert-type patterns. To confirm the periodicity of the AgCl pattern, we conduct one-dimensional experiments under various ion concentration conditions. From microscopic observations, three different precipitation modes were observed, i.e., continuous precipitation with a sharp front, periodic precipitation and continuous precipitation with a gradual front. For these three modes, numerical analyses of the pattern geometry are performed for the periodic precipitation. It was confirmed that the regular-type pattern appeared for all concentration conditions conducted in the present experiments. Furthermore, the pattern was found to obey the spacing law and the Matalon–Packter law. From our experiments, we concluded that AgCl forms regular-type Liesegang patterns, regardless of the dimension of diffusion.

The impacts of ICTs on tourism development: International evidence based on a panel quantile approach

Information and communication technologies (ICTs) have transformed the travel and leisure sector worldwide, yet until now there are no studies presenting international evidence of the different impacts of ICTs (i.e., Internet usage, secure Internet servers, mobile cellular subscriptions, high-technology export, communications as well as computer, and fixed broadband subscriptions) on tourism development (i.e., international traveler arrivals, increased international tourism receipts, and travel and leisure sector returns) by considering countries with different tourism development processes (e.g., high or low tourism development quantile). It is possible that ICTs have diverse or non-linear impacts on countries undergoing varying tourism development processes. Using international data based on a new panel quantile approach, this research thus aims to explore whether ICTs affect tourism development and looks into the possible asymmetric and non-linear relationships among the many variables. Results show that increasing mobile cellular subscriptions, secure Internet servers, and fixed broadband subscriptions have greater positive effects on traveler arrivals. ICTs also asymmetrically and non-linearly influence tourism across different quantiles. Non-global financial sub-periods and developing nations gain benefits from ICTs’ establishment. Lastly, there are geographic differences in the ICTs-tourism nexus.

Improving on the Adrogué-Madias Formula

The Adrogué-Madias (A-M) formula is correct as written, but technically, it only works when adding 1 L of an intravenous (IV) fluid. For all other volumes, the A-M algorithm gives an approximate answer, one that diverges further from the truth as the IV volume is increased. If 1 L of an IV fluid is calculated to change the serum sodium by some amount, then it was long assumed that giving a fraction of the liter would change the serum sodium by a proportional amount. We challenged that assumption and now prove that the A-M change in [sodium] ([Na]) is not scalable in a linear way. Rather, the Δ[Na] needs to be scaled in a way that accounts for the actual volume of IV fluid being given. This is accomplished by our improved version of the A-M formula in a mathematically rigorous way. Our equation accepts any IV fluid volume, eliminates the illogical infinities, and most importantly, incorporates the scaling step so that it cannot be forgotten. However, the nonlinear scaling makes it harder to obtain a desired Δ[Na]. Therefore, we reversed the equation so that clinicians can enter the desired Δ[Na], keeping the rate of sodium correction safe, and then get an answer in terms of the volume of IV fluid to infuse. The improved equation can also unify the A-M formula with the corollary A-M loss equation wherein 1 L of urine is lost. The method is to treat loss as a negative volume. Because the new equation is just as straightforward as the original formula, we believe that the improved form of A-M is ready for immediate use, alongside frequent [Na] monitoring.

Investigating Passive Muscle Mechanics With Biaxial Stretch

Introduction

The passive stiffness of skeletal muscle can drastically affect muscle function in vivo, such as the case for fibrotic tissue or patients with cerebral palsy. The two constituents of skeletal muscle that dominate passive stiffness are the intracellular protein titin and the collagenous extracellular matrix (ECM). However, efforts to correlate stiffness and measurements of specific muscle constituents have been mixed, and thus the complete mechanisms for changes to muscle stiffness remain unknown. We hypothesize that biaxial stretch can provide an improved approach to evaluating passive muscle stiffness.

Methods

We performed planar biaxial materials testing of passively stretched skeletal muscle and identified three previously published datasets of uniaxial materials testing. We developed and employed a constitutive model of passive skeletal muscle that includes aligned muscle fibers and dispersed ECM collagen fibers with a bimodal von Mises distribution. Parametric modeling studies and fits to experimental data (both biaxial and previously published) were completed.

Results

Biaxial data exhibited differences in time dependent behavior based on orientation (p < 0.0001), suggesting different mechanisms supporting load in the direction of muscle fibers (longitudinal) and in the perpendicular (transverse) directions. Model parametric studies and fits to experimental data exhibited the robustness of the model (<20% error) and how differences in tissue stiffness may not be observed in uniaxial longitudinal stretch, but are apparent in biaxial stretch.

Conclusion

This work presents novel materials testing data of passively stretched skeletal muscle and use of constitutive modeling and finite element analysis to explore the interaction between stiffness, constituent variability, and applied deformation in passive skeletal muscle. The results highlight the importance of biaxial stretch in evaluating muscle stiffness and in further considering the role of ECM collagen in modulating passive muscle stiffness.

Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults

Gait variability observed in step duration is predictive of impending adverse health outcomes among apparently healthy older adults and could potentially be evaluated using wearable sensors (inertial measurement units, IMU). The purpose of the present study was to establish the reliability and concurrent validity of gait variability and complexity evaluated with a waist and an ankle-worn IMU. Seventeen women (age 74.8 (SD 44) years) and 10 men (73.7 (4.1) years) attended two laboratory measurement sessions a week apart. Their stride duration variability was concurrently evaluated based on a continuous 3 min walk using a force plate and a waist- and an ankle-worn IMU. Their gait complexity (multiscale sample entropy) was evaluated from the waist-worn IMU. The force plate indicated excellent stride duration variability reliability (intra-class correlation coefficient, ICC = 0.90), whereas fair to good reliability (ICC = 0.47 to 0.66) was observed from the IMUs. The IMUs exhibited poor to excellent concurrent validity in stride duration variability compared to the force plate (ICC = 0.22 to 0.93). A good to excellent reliability was observed for gait complexity in most coarseness scales (ICC = 0.60 to 0.82). A reasonable congruence with the force plate-measured stride duration variability was observed on many coarseness scales (correlation coefficient = 0.38 to 0.83). In conclusion, waist-worn IMU entropy estimates may provide a feasible indicator of gait variability among community-dwelling ambulatory older adults.

A Study on Non-Linear DPL Model for Describing Heat Transfer in Skin Tissue during Hyperthermia Treatment

The article studies the simulation-based mathematical modeling of bioheat transfer under the Dirichlet boundary condition. We used complex non-linear dual-phase-lag bioheat transfer (DPLBHT) for analyzing the temperature distribution in skin tissues during hyperthermia treatment of infected cells. The perfusion term, metabolic heat source, and external heat source were the three parts of the volumetric heat source that were used in the model. The non-linear DPLBHT model predicted a more accurate temperature within skin tissues. The finite element Runge–Kutta (4,5) (FERK (4,5)) method, which was based on two techniques, finite difference and Runge–Kutta (4,5), was applied for calculating the result in the case of our typical non-linear problem. The paper studies and presents the non-dimensional unit. Thermal damage of normal tissue was observed near zero during hyperthermia treatment. The effects of the non-dimensional time, non-dimensional space coordinate, location parameter, regional parameter, relaxation and thermalization time, metabolic heat source, associated metabolic heat source parameter, perfusion rate, associated perfusion heat source parameter, and external heat source coefficient on the dimensionless temperature profile were studied in detail during the hyperthermia treatment process.

Beat-to-Beat Patterning of Sinus Rhythm Reveals Non-linear Rhythm in the Dog Compared to the Human

The human and dog have sinus arrhythmia; however, the beat-to-beat interval changes were hypothesized to be different. Geometric analyses (R–R interval tachograms, dynamic Poincaré plots) to examine rate changes on a beat-to-beat basis were analyzed along with time and frequency domain heart rate variability from 40 human and 130 canine 24-h electrocardiographic recordings. Humans had bell-shaped beat-interval distributions, narrow interval bands across time with continuous interval change and linear changes in rate. In contrast, dogs had skewed non-singular beat distributions, wide interval bands {despite faster average heart rate of dogs [mean (range); 81 (64–119)] bpm compared to humans [74.5 (59–103) p = 0.005]} with regions displaying a paucity of intervals (zone of avoidance) and linear plus non-linear rate changes. In the dog, dynamic Poincaré plots showed linear rate changes as intervals prolonged until a point of divergence from the line of identity at a mean interval of 598.5 (95% CI: 583.5–613.5) ms (bifurcation interval). The dog had bimodal beat distribution during sleep with slower rates and greater variability than during active hours that showed singular interval distributions, higher rates and less variability. During sleep, Poincaré plots of the dog had clustered or branched patterns of intervals. A slower rate supported greater parasympathetic modulation with a branched compared to the clustered distribution. Treatment with atropine eliminated the non-linear patterns, while hydromorphone shifted the bifurcated branching and beat clustering to longer intervals. These results demonstrate the unique non-linear nature of beat-to-beat variability in the dog compared to humans with increases in interval duration (decrease heart rate). These results provoke the possibility that changes are linear with a dominant sympathetic modulation and non-linear with a dominant parasympathetic modulation. The abrupt bifurcation, zone of avoidance and beat-to-beat patterning are concordant with other studies demonstrating the development of exit block from the sinus node with parasympathetic modulation influencing not only the oscillation of the pacing cells, but conduction to the atria. Studies are required to associate the in vivo sinus node beat patterns identified in this study to the mapping of sinus impulse origin and exit from the sinus node.

Vitamin D Concentration during Early Pregnancy and Adverse Outcomes among HIV-Negative Women in Dar-es-Salaam, Tanzania: A Case-Control Study

We examined the associations of plasma vitamin D concentration and adverse pregnancy outcomes among HIV-negative women in Dar-es-Salaam, Tanzania. We used an unmatched case-control study design, with 25-hydroxyvitamin D [25(OH)D] concentration assessed in the first trimester. Cases were individuals with adverse pregnancy outcomes, including stillbirth, premature birth, or small for gestational age births (SGA). Unconditional logistic regression and weighted logistic regression models were used to describe the associations of 25(OH)D concentration with the composite of adverse pregnancy outcome and individual adverse pregnancy outcomes, respectively. We included 310 cases and 321 controls. In controls, 5(2%) were vitamin D deficient (25(OH)D < 20 ng/mL), and 17(5%) had insufficient 25(OH)D concentration (20.0–29.9 ng/mL). Women with 25(OH)D < 20 ng/mL had 1.82 times the odds of occurrence of the composite adverse pregnancy outcome (OR = 1.82, 95% CI: 0.56–5.93; p = 0.32), however we noted a non-linear association between 25(OH)D concentration and adverse pregnancy outcome (p = 0.02). We found a 3-fold increased odds of stillbirth in women with low 25(OH)D concentration (OR = 3.11, 95% CI: 1.18–8.23, p = 0.02). Vitamin D concentration in early pregnancy may be an important factor in determining the course of pregnancy. Further research is needed to investigate whether the association of maternal 25(OH)D concentration in early pregnancy and stillbirth is causal.

Deep Learning Enables Accurate Prediction of Interplay Between lncRNA and Disease

Many studies have suggested that lncRNAs are involved in distinct and diverse biological processes. The mutation of lncRNAs plays a major role in a wide range of diseases. A comprehensive information of lncRNA-disease associations would improve our understanding of the underlying molecular mechanism that can explain the development of disease. However, the discovery of the relationship between lncRNA and disease in biological experiment is costly and time-consuming. Although many computational algorithms have been proposed in the last decade, there still exists much room to improve because of diverse computational limitations. In this paper, we proposed a deep-learning framework, NNLDA, to predict potential lncRNA-disease associations. We compared it with other two widely-used algorithms on a network with 205,959 interactions between 19,166 lncRNAs and 529 diseases. Results show that NNLDA outperforms other existing algorithm in the prediction of lncRNA-disease association. Additionally, NNLDA can be easily applied to large-scale datasets using the technique of mini-batch stochastic gradient descent. To our best knowledge, NNLDA is the first algorithm that uses deep neural networks to predict lncRNA-disease association. The source code of NNLDA can be freely accessed at https://github.com/gao793583308/NNLDA.