Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning.

Advancements in deep learning algorithms over the past decade have led to extensive developments in brain-computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging technique. The present study developed a MEG sensor-based BCI neural network to decode Rock-Paper-scissors gestures (MEG-RPSnet). Unique preprocessing pipelines in tandem with convolutional neural network deep-learning models accurately classified gestures. On a single-trial basis, we found an average of 85.56% classification accuracy in 12 subjects. Our MEG-RPSnet model outperformed two state-of-the-art neural network architectures for electroencephalogram-based BCI as well as a traditional machine learning method, and demonstrated equivalent and/or better performance than machine learning methods that have employed invasive, electrocorticography-based BCI using the same task. In addition, MEG-RPSnet classification performance using an intra-subject approach outperformed a model that used a cross-subject approach. Remarkably, we also found that when using only central-parietal-occipital regional sensors or occipitotemporal regional sensors, the deep learning model achieved classification performances that were similar to the whole-brain sensor model. The MEG-RSPnet model also distinguished neuronal features of individual hand gestures with very good accuracy. Altogether, these results show that noninvasive MEG-based BCI applications hold promise for future BCI developments in hand-gesture decoding.

GABA promotes interstitial fluid clearance in an AQP4-dependent manner by activating the GABAA R.

The glymphatic system is a newly discovered perivascular network where cerebrospinal fluid mixes with interstitial fluid, facilitating clearance of protein solutes and metabolic waste from the parenchyma. The process is strictly dependent on water channel aquaporin-4 (AQP4) expressed on the perivascular astrocytic end-feet. Various factors, such as noradrenaline levels related to the arousal state, influence clearance efficiency, highlighting the possibility that other neurotransmitters additionally modulate this process. To date, the specific role of γ-aminobutyric acid (GABA) in the glymphatic system remains unknown. We used C57BL/6J mice to observe the regulatory effect of GABA on glymphatic pathway by administering a cerebrospinal fluid tracer containing GABA or its GABAA receptor (GABAA R) antagonist through cisterna magna injection. Then, we employed an AQP4 knockout mouse model to explore the regulatory effects of GABA on glymphatic drainage and further study whether transcranial magnetic stimulation-continuous theta burst stimulation (cTBS) could regulate the glymphatic pathway through the GABA system. Our data showed that GABA promotes glymphatic clearance in an AQP4-dependent manner by activating the GABAA R. Furthermore, cTBS was found to modulate the glymphatic pathway by activating the GABA system. Accordingly, we propose that regulating the GABA system by cTBS could modulate glymphatic clearance and provide new insight for clinical prevention and treatment of abnormal protein deposition-related diseases.

Modeling homophily in dynamic networks with application to HIV molecular surveillance.

BACKGROUND: Efforts to control the HIV epidemic can benefit from knowledge of the relationships between the characteristics of people who have transmitted HIV and those who became infected by them. Investigation of this relationship is facilitated by the use of HIV genetic linkage analyses, which allows inference about possible transmission events among people with HIV infection. Two persons with HIV (PWH) are considered linked if the genetic distance between their HIV sequences is less than a given threshold, which implies proximity in a transmission network. The tendency of pairs of nodes (in our case PWH) that share (or differ in) certain attributes to be linked is denoted homophily. Below, we describe a novel approach to modeling homophily with application to analyses of HIV viral genetic sequences from clinical series of participants followed in San Diego. Over the 22-year period of follow-up, increases in cluster size results from HIV transmissions to new people from those already in the cluster-either directly or through intermediaries. METHODS: Our analytical approach makes use of a logistic model to describe homophily with regard to demographic, clinical, and behavioral characteristics-that is we investigate whether similarities (or differences) between PWH in these characteristics are associated with their sequences being linked. To investigate the performance of our methods, we conducted on a simulation study for which data sets were generated in a way that reproduced the structure of the observed database. RESULTS: Our results demonstrated strong positive homophily associated with hispanic ethnicity, and strong negative homophily, with birth year difference. The second result implies that the larger the difference between the age of a newly-infected PWH and the average age for an available cluster, the lower the odds of a newly infected person joining that cluster. We did not observe homophily associated with prior diagnosis of sexually transmitted diseases. Our simulation studies demonstrated the validity of our approach for modeling homophily, by showing that the estimates it produced matched the specified values of the statistical network generating model. CONCLUSIONS: Our novel methods provide a simple and flexible statistical network-based approach for modeling the growth of viral (or other microbial) genetic clusters from linkage to new infections based on genetic distance.

Head-to-head comparison between MEFIB, MAST, and FAST for detecting stage 2 fibrosis or higher among patients with NAFLD.

BACKGROUND & AIMS: Patients with non-alcoholic fatty liver disease (NAFLD) and significant fibrosis (fibrosis stage ≥2) are candidates for pharmacological trials. The aim of this study was to perform a head-to-head comparison of the diagnostic test characteristics of three non-invasive stiffness-based models including MEFIB (magnetic resonance elastography [MRE] plus FIB-4), MAST (magnetic resonance imaging [MRI]-aspartate aminotransferase [AST]), and FAST (FibroScan-AST) for detecting significant fibrosis. METHODS: This prospective study included 563 patients with biopsy-proven NAFLD undergoing contemporaneous MRE, MRI proton density fat fraction (MRI-PDFF) and FibroScan from two prospective cohorts derived from Southern California and Japan. Diagnostic performances of models were evaluated by area under the receiver-operating characteristic curve (AUC). RESULTS: The mean age of the cohort was 56.5 years (51% were women). Significant fibrosis was observed in 51.2%. To detect significant fibrosis, MEFIB outperformed both MAST and FAST (both p <0.001); AUCs for MEFIB, MAST, and FAST were 0.901 (95% CI 0.875-0.928), 0.770 (95% CI 0.730-0.810), and 0.725 (95% CI 0.683-0.767), respectively. Using rule-in criteria, the positive predictive value of MEFIB (95.3%) was significantly higher than that of FAST (83.5%, p = 0.001) and numerically but not statistically greater than that of MAST (90.0%, p = 0.056). Notably, MEFIB's rule-in criteria covered more of the study population than MAST (34.1% vs. 26.6%; p = 0.006). Using rule-out criteria, the negative predictive value of MEFIB (90.1%) was significantly higher than that of either MAST (69.6%) or FAST (71.8%) (both p <0.001). Furthermore, to diagnose "at risk" non-alcoholic steatohepatitis defined as NAFLD activity score ≥4 and fibrosis stage ≥2, MEFIB outperformed both MAST and FAST (both p <0.05); AUCs for MEFIB, MAST, and FAST were 0.768 (95% CI 0.728-0.808), 0.719 (95% CI 0.671-0.766), and 0.687 (95% CI 0.640-0.733), respectively. CONCLUSIONS: MEFIB was better than MAST and FAST for detection of significant fibrosis as well as "at risk" NASH. All three models provide utility for the risk stratification of NAFLD. LAY SUMMARY: Non-alcoholic fatty liver disease (NAFLD) affects over 25% of the general population worldwide and is one of the main causes of chronic liver disease. Because so many individuals have NAFLD, it is not practical to perform liver biopsies to identify those with more severe disease who may require pharmacological interventions. Therefore, accurate non-invasive tests are crucial. Herein, we compared three such tests and found that a test called MEFIB was the best at detecting patients who might require treatment.

Continuous Theta-Burst Stimulation Promotes Paravascular CSF-Interstitial Fluid Exchange through Regulation of Aquaporin-4 Polarization in APP/PS1 Mice.

Amyloid-ß (Aß) deposition plays a crucial role in the occurrence and development of Alzheimer's disease (AD), and impaired Aß clearance is the leading cause of Aß deposition. Recently, studies have found that the glymphatic system performs similar functions to the peripheral lymphatic system. Glymphatic fluid transport mainly consists of cerebrospinal fluid (CSF) entering the brain from the paravascular space (PVS) by penetrating arteries and CSF and interstitial fluid exchanging mediated by aquaporin-4 (AQP4). This system promotes the drainage of interstitial fluid (ISF) in the parenchyma and removes metabolic waste, including Aß, in the brain. Glymphatic system dysfunction plays an essential role in the occurrence and progression of AD. Regulation of glymphatic fluid transport may be a critical target for AD therapy. This study explored the regulatory effects of continuous theta-burst stimulation (CTBS) on the glymphatic system in APPswe/PS1dE9 (APP/PS1) mice with two-photon imaging. The results demonstrated that CTBS could increase glymphatic fluid transport, especially CSF and ISF exchange, mediated by improved AQP4 polarization. In addition, the accelerated glymphatic pathway reduced Aß deposition and enhanced spatial memory cognition. It provided new insight into the clinical prevention and treatment of Aß deposition-related diseases.

Extending the Mann-Whitney-Wilcoxon rank sum test to survey data for comparing mean ranks.

Statistical methods for analysis of survey data have been developed to facilitate research. More recently, Lumley and Scott (2013) developed an approach to extend the Mann-Whitney-Wilcoxon (MWW) rank sum test to survey data. Their approach focuses on the null of equal distribution. In many studies, the MWW test is called for when two-sample t-tests (with or without equal variance assumed) fail to provide meaningful results, as they are highly sensitive to outliers. In such situations, the null of equal distribution is too restrictive, as interest lies in comparing centers of groups. In this article, we develop an approach to extend the MWW test to survey data to test the null of equal mean rank. Although not as popular as the mean and median, the mean rank is also a meaningful measure of the center of a distribution and is the same as the median for a symmetric distribution. We illustrate the proposed approach and show major differences with Lumley and Scott's alternative using both real and simulated data.

Prevalence of Dysphagia in China: An Epidemiological Survey of 5943 Participants.

OBJECTIVE: To determine the prevalence of dysphagia among an older population and patients with stroke, head and neck cancers (HNCs) or neurodegenerative diseases (NDDs) in China, to identify the factors associated with this condition, and to explore the relationship between dysphagia and nutritional status. METHODS: This study included participants 65 years and older living in the community or in nursing homes and patients who had sustained a stroke, HNC, or NDD also recruited in hospitals from 14 provinces of China. The presence of dysphagia was determined by use of a questionnaire, water swallowing test, and/or a videofluoroscopic swallowing study. Logistic regression analysis was used to assess the possible associated risk factors. Body mass index was assessed as an indicator of malnutrition. RESULTS: A total of 5943 persons met the inclusion criteria and 2341 (39.4%) were identified with dysphagia, including the following: 51.14% of patients with stroke, 34.4% in HNCs, 48.3% in NDDs, and 19.2% of otherwise healthy older adults. The elderly with comorbidity (OR = 2.90, p < 0.01) and stroke patients (OR = 2.27, p < 0.01) were significantly more likely to exhibit signs of dysphagia. Dysphagic participants were at significantly greater risk of malnutrition (OR = 1.91, p < 0.01) compared to those without dysphagia. CONCLUSION: Dysphagia is prevalent in China among older individuals and people who have suffered a stroke, HNCs, or NDDs. The prevalence of dysphagia increases steadily with increasing age and presence of comorbid disease. People with dysphagia are more likely to suffer from malnutrition.

Isoflurane Impacts Murine Melanoma Growth in a Sex-Specific, Immune-Dependent Manner: A Brief Report.

The impact of volatile anesthetics on cancer progression has been observed for decades, but sex differences have not been described. Male and female immune systems vary considerably, and the immune system plays an important role in limiting cancer growth. Currently, mouse models describing the impact of volatile anesthetics on cancer growth are limited to same-sex models. In this brief report, we describe a sex-specific impact of isoflurane on melanoma growth observed in wild-type but not in immune-deficient mice. Future experimental designs related to anesthesia and cancer should evaluate the biological variable of sex in a systematic manner.

The correlation between manometric and videofluoroscopic measurements of the swallowing function in brainstem stroke patients with Dysphagia.

GOALS: The objective of the current study was to examine the correlation between high-resolution manometric and videofluoroscopic measurements of the swallowing function. BACKGROUND: In such cases in which manometric analysis is not feasible, it would be ideal if information regarding pressure during swallowing could be inferred from a videofluoroscopic swallowing study (VFSS) evaluation alone. STUDY: The swallowing function was examined using simultaneous VFSS and high-resolution manometry (HRM) in 24 brainstem stroke survivors with dysphagia. The pharyngeal constriction ratio (PCR) and upper esophageal sphincter (UES) maximum opening diameter were measured using VFSS digital analysis. The pharyngeal maximum pressure and UES residual pressure were measured using HRM. The correlation coefficients between the PCR and pharyngeal maximum pressure and between the UES maximum opening diameter and UES residual pressure were calculated. The Spearman analyses were used to calculate the correlation coefficients between manometric and fluoroscopic parameters. RESULTS: The increase in the pharyngeal maximum pressure wave amplitude was significantly correlated with a decrease in the PCR (r=-0.849, P<0.001). The increase in the UES opening diameter was significantly correlated with a decrease in the UES residual pressure (r=-0.705, P<0.001). High space-time correlations between the pressure and kinematics of swallowing-related structures were obtained using simultaneous manometric and videofluoroscopic measurements. CONCLUSIONS: Certain VFSS measures are significantly correlated with measures of pressure assessed using HRM. The measures may be used as indicators of possible pressure deficits of swallowing.

Assessing Interest in a Peer Support Person for Patients Experiencing Early Pregnancy Loss: Results from a National Survey.

Introduction: The use of a peer support person as an intervention for early pregnancy loss (EPL) is not well studied. In addition, limited literature exists regarding the type of support patients need when experiencing EPL. The objective of this study is to quantify interest in a peer EPL support person intervention, to assess the types of support desired following EPL, and to investigate if there is an association between self-compassion or resilience and coping ability post-EPL. Methods: We conducted a cross-sectional, web-based survey with 110 individuals who experienced EPL in the past 2 years. Questions explored interest in a peer EPL support person and different types of support, as well as perceived self-compassion and resilience. Analyses of variance were used to test if interest in the peer support intervention and in different types of support varied by demographics, while linear regression modeling was used to test the relationship between self-compassion, resilience, and coping ability. Results: Nearly all participants (98.2%, n = 108) were interested in peer support. The majority (31.8%, n = 35) of participants prioritized informational and educational support at the time of their EPL and in the months following. There was a positive relationship between self-compassion scores and ability to cope with EPL (p = 0.2) and between resilience scores and coping ability (p < 0.05). Conclusions: Almost all participants were interested in a peer support person for coping with EPL. Given the types of support participants identified in this study, a peer support person may provide emotional and informational support as well as resilience training.

Electroencephalography oscillations can predict the cortical response following theta burst stimulation.

BACKGROUND: Continuous theta burst stimulation and intermittent theta burst stimulation are clinically popular models of repetitive transcranial magnetic stimulation. However, they are limited by high variability between individuals in cortical excitability changes following stimulation. Although electroencephalography oscillations have been reported to modulate the cortical response to transcranial magnetic stimulation, their association remains unclear. This study aims to explore whether machine learning models based on EEG oscillation features can predict the cortical response to transcranial magnetic stimulation. METHOD: Twenty-three young, healthy adults attended two randomly assigned sessions for continuous and intermittent theta burst stimulation. In each session, ten minutes of resting-state electroencephalography were recorded before delivering brain stimulation. Participants were classified as responders or non-responders based on changes in resting motor thresholds. Support vector machines and multi-layer perceptrons were used to establish predictive models of individual responses to transcranial magnetic stimulation. RESULT: Among the evaluated algorithms, support vector machines achieved the best performance in discriminating responders from non-responders for intermittent theta burst stimulation (accuracy: 91.30%) and continuous theta burst stimulation (accuracy: 95.66%). The global clustering coefficient and global characteristic path length in the beta band had the greatest impact on model output. CONCLUSION: These findings suggest that EEG features can serve as markers of cortical response to transcranial magnetic stimulation. They offer insights into the association between neural oscillations and variability in individuals' responses to transcranial magnetic stimulation, aiding in the optimization of individualized protocols.

Age-related changes in meningeal lymphatic function are closely associated with vascular endothelial growth factor-C expression.

Meningeal lymphatic vessels (MLVs) have crucial roles in removing metabolic waste and toxic proteins from the brain and transporting them to the periphery. Aged mice show impaired meningeal lymphatic function. Nevertheless, as the disease progresses, and significant pathological changes manifest in the brain, treating the condition becomes increasingly challenging. Therefore, investigating the alterations in the structure and function of MLVs in the early stages of aging is critical for preventing age-related central nervous system degenerative diseases. We detected the structure and function of MLVs in young, middle-aged, and aged mice. Middle-aged mice, compared with young and aged mice, showed enhanced meningeal lymphatic function along with MLV expansion and performed better in the Y maze test. Moreover, age-related changes in meningeal lymphatic function were closely associated with vascular endothelial growth factor-C (VEGF-C) expression in the brain cortex. Our data suggested that the cerebral cortex may serve as a target for VEGF-C supplementation to ameliorate meningeal lymphatic dysfunction, thus providing a new strategy for preventing age-related central nervous system diseases.

A New Paradigm for High-dimensional Data: Distance-Based Semiparametric Feature Aggregation Framework via Between-Subject Attributes.

This article proposes a distance-based framework incentivized by the paradigm shift towards feature aggregation for high-dimensional data, which does not rely on the sparse-feature assumption or the permutation-based inference. Focusing on distance-based outcomes that preserve information without truncating any features, a class of semiparametric regression has been developed, which encapsulates multiple sources of high-dimensional variables using pairwise outcomes of between-subject attributes. Further, we propose a strategy to address the interlocking correlations among pairs via the U-statistics-based estimating equations (UGEE), which correspond to their unique efficient influence function (EIF). Hence, the resulting semiparametric estimators are robust to distributional misspecification while enjoying root-n consistency and asymptotic optimality to facilitate inference. In essence, the proposed approach not only circumvents information loss due to feature selection but also improves the model's interpretability and computational feasibility. Simulation studies and applications to the human microbiome and wearables data are provided, where the feature dimensions are tens of thousands.

Individual differences in beta-band oscillations predict motor-inhibitory control.

Objective: The ability of motor-inhibitory control is critical in daily life. The physiological mechanisms underlying motor inhibitory control deficits remain to be elucidated. Beta band oscillations have been suggested to be related to motor performance, but whether they relate to motor-inhibitory control remains unclear. This study is aimed at systematically investigating the relationship between beta band oscillations and motor-inhibitory control to determine whether beta band oscillations were related to the ability of motor-inhibitory control. Methods: We studied 30 healthy young adults (age: 21.6 ± 1.5 years). Stop-signal reaction time (SSRT) was derived from stop signal task, indicating the ability of motor-inhibitory control. Resting-state electroencephalography (EEG) was recorded for 12 min. Beta band power and functional connectivity (including global efficiency) were calculated. Correlations between beta band oscillations and SSRT were performed. Results: Beta band EEG power in left and right motor cortex (MC), right somatosensory cortex (SC), and right inferior frontal cortex (IFC) was positively correlated with SSRT (P's = 0.031, 0.021, 0.045, and 0.015, respectively). Beta band coherence between bilateral MC, SC, and IFC was also positively correlated with SSRT (P's < 0.05). Beta band global efficiency was positively correlated with SSRT (P = 0.01). Conclusion: This is the first study to investigate the relationship between resting-state cortical beta oscillations and response inhibition. Our findings revealed that individuals with better ability of motor inhibitory control tend to have less cortical beta band power and functional connectivity. This study has clinical significance on the underlying mechanisms of motor inhibitory control deficits.

On modelling relative risks for longitudinal binomial responses: implications from two dueling paradigms.

Although logistic regression is the most popular for modelling regression relationships with binary responses, many find relative risk (RR), or risk ratio, easier to interpret and prefer to use this measure of risk in regression analysis. Indeed, since Zou published his modified Poisson regression approach for modelling RR for cross-sectional data, his paper has been cited over 7 000 times, demonstrating the popularity of this alternative measure of risk in regression analysis involving binary responses. As longitudinal studies have become increasingly popular in clinical trials and observational studies, it is imperative to extend Zou's approach for longitudinal data. The two most popular approaches for longitudinal data analysis are the generalised linear mixed-effects model (GLMM) and generalised estimating equations (GEE). However, the parametric GLMM cannot be used for the extension within the current context, because Zou's approach treats the binary response as a Poisson variable, which is at odds with the Bernoulli distribution for the binary response. On the other hand, as it imposes no mathematical model on data distributions, the semiparametric GEE is coherent with Zou's modified Poisson regression. In this paper, we develop a GEE-based longitudinal model for binary responses to provide inference about RR.

Exploring the Effect of Adding an Interactive Lecture to a Standardized Patient Curriculum on the Attitudes of Third-Year Medical Students About Patients With Obesity: A Quasi-Experimental Study.

OBJECTIVES: Anti-obesity bias is pervasive among medical professionals, students, and trainees. Stigmatization of patients leads to suboptimal care and clinical outcomes. Educational strategies in medical training are needed to reverse these attitudes. The aim of this study was to evaluate the effect of an innovative didactic intervention and a standardized patient (SP) exercise on attitudes towards patients with obesity among medical students. METHODS: In 2016, a quasi-experimental study design was used at a US medical school. The class was divided into 2 groups according to a pre-determined protocol based on their clinical schedule, one assessed after exposure to a SP group and the other after exposure to the SP and an interactive lecture (IL + SP group) with real patients. The Attitudes about Treating Patients with Obesity and The Perceived Causes of Obesity questionnaires measured changes in several domains. A generalized estimating equations model was used to estimate the effect of the interventions both within and between groups. RESULTS: Both groups showed improvements in negative and positive attitudes, although the reduction in scores for the negative attitude domain did not reach statistical significance in the IL + SP group (for the SP group, P = .01 and < .001, respectively; for the IL + SP group, P = .15 and .01, respectively). For perceived causes of obesity, there were no statistically significant changes for pre-post survey measures within each group, except for the physiologic causes domain in the SP group (P = .03). The addition of an IL to a SP curriculum did not result in any changes for any domain in between-group analyses. CONCLUSIONS: Although adding a novel intervention utilizing real patients to a SP curriculum failed to show an additional educational benefit, our study showed that it is possible to influence attitudes of medical students regarding patients with obesity.

Optimizing campus-wide COVID-19 test notifications with interpretable wastewater time-series features using machine learning models.

During the COVID-19 pandemic, wastewater surveillance of the SARS CoV-2 virus has been demonstrated to be effective for population surveillance at the county level down to the building level. At the University of California, San Diego, daily high-resolution wastewater surveillance conducted at the building level is being used to identify potential undiagnosed infections and trigger notification of residents and responsive testing, but the optimal determinants for notifications are unknown. To fill this gap, we propose a pipeline for data processing and identifying features of a series of wastewater test results that can predict the presence of COVID-19 in residences associated with the test sites. Using time series of wastewater results and individual testing results during periods of routine asymptomatic testing among UCSD students from 11/2020 to 11/2021, we develop hierarchical classification/decision tree models to select the most informative wastewater features (patterns of results) which predict individual infections. We find that the best predictor of positive individual level tests in residence buildings is whether or not the wastewater samples were positive in at least 3 of the past 7 days. We also demonstrate that the tree models outperform a wide range of other statistical and machine models in predicting the individual COVID-19 infections while preserving interpretability. Results of this study have been used to refine campus-wide guidelines and email notification systems to alert residents of potential infections.

Causal Association of Cytokines and Growth Factors with Stroke and Its Subtypes: a Mendelian Randomization Study.

Cytokines and growth factors contribute to nerve growth and angiogenesis and are associated with the development of vascular disease. This Mendelian randomization (MR) study was designed to examine the causal relationship between factors associated with stem cell paracrine mechanisms and with stroke and its subtypes. We used pooled statistics on cytokine levels from three studies (INTERIAL, Olink Proseek CVD array, and KORA) encompassing 7795 participants in Europe. Data for stroke and its subtypes were pooled from these European populations (40,585 cases and 406,111 controls) in a multiprogenitor genome-wide association study (GWAS). MR was performed using established analytical methods, including inverse variance weighting (IVW), weighted median (WM), and MR-Egger. Genetically determined high IGF-1 levels were found to associate negatively with risk of stroke, ischemic stroke (large-artery atherosclerosis), and ischemic stroke (cardiogenic embolism). Meanwhile, high IL-13 levels had a positive causal relationship with ischemic stroke (large-artery atherosclerosis). An additional 27 cytokines were found to have a causal association with stroke or its subtypes. However, these results should be interpreted with caution given that the power efficacy was <80%. This MR study supports the concept of a causal relationship of 29 cytokines with stroke or its subtypes. Our genetic analysis provides new insights into stroke prevention and treatment by demonstrating an association of stem cell paracrine-related cytokines with stroke risk.

Urinary Glyphosate, 2,4-D and DEET Biomarkers in Relation to Neurobehavioral Performance in Ecuadorian Adolescents in the ESPINA Cohort.

BACKGROUND: Herbicides are the most used class of pesticides worldwide, and insect repellents are widely used globally. Yet, there is a dearth of studies characterizing the associations between these chemical groups and human neurobehavior. Experimental studies suggest that glyphosate and 2,4-dichlorophenoxyacetic acid (2,4-D) herbicides can affect neurobehavior and the cholinergic and glutamatergic pathways in the brain. We aim to assess whether herbicides and insect repellents are associated with neurobehavioral performance in adolescents. METHODS: We assessed 519 participants (11-17 years of age) living in agricultural communities in Ecuador. We quantified urinary concentrations of glyphosate, 2,4-D, and two N,N-diethyl-meta-toluamide (DEET) insect repellent metabolites [3-(diethylcarbamoyl)benzoic acid (DCBA) and 3-(ethylcarbamoyl)benzoic acid (ECBA)] using isotope-dilution mass spectrometry. We assessed neurobehavioral performance using 9 subtests across 5 domains (attention/inhibitory control, memory/learning, language, visuospatial processing, and social perception). We characterized the associations using generalized estimating equations and multiple imputation for metabolites below detection limits. Models were adjusted for demographic and anthropometric characteristics, urinary creatinine, and sexual maturation. Mediation by salivary cortisol, dehydroepiandrosterone, 17ß-estradiol, and testosterone was assessed using structural equation modeling. RESULTS: The mean of each neurobehavioral domain score was between 7.0 and 8.7 [standard deviation (SD) range: 2.0-2.3]. Glyphosate was detected in 98.3% of participants, 2,4-D in 66.2%, DCBA in 63.3%, and ECBA in 33.4%. 2,4-D was negatively associated with all neurobehavioral domains, but statistically significant associations were observed with attention/inhibition [score difference per 50% higher metabolite concentration (ß)=-0.19 95% confidence interval (CI): -0.31, -0.07], language [ß=-0.12 (95% CI: -0.23, -0.01)], and memory/learning [ß=-0.11 (95% CI: -0.22, 0.01)]. Glyphosate had a statistically significant negative association only with social perception [ß=-0.08 (95% CI: -0.14, -0.01)]. DEET metabolites were not associated with neurobehavioral performance. Mediation by gender and adrenal hormones was not observed. CONCLUSION: This study describes worse neurobehavioral performance associated with herbicide exposures in adolescents, particularly with 2,4-D. Replication of these findings among other pediatric and adult populations is needed. https://doi.org/10.1289/EHP11383.

A RIEMANN MANIFOLD MODEL FRAMEWORK FOR LONGITUDINAL CHANGES IN PHYSICAL ACTIVITY PATTERNS.

Physical activity (PA) is significantly associated with many health outcomes. The wide usage of wearable accelerometer-based activity trackers in recent years has provided a unique opportunity for in-depth research on PA and its relations with health outcomes and interventions. Past analysis of activity tracker data relies heavily on aggregating minute-level PA records into day-level summary statistics in which important information of PA temporal/diurnal patterns is lost. In this paper we propose a novel functional data analysis approach based on Riemann manifolds for modeling PA and its longitudinal changes. We model smoothed minute-level PA of a day as one-dimensional Riemann manifolds and longitudinal changes in PA in different visits as deformations between manifolds. The variability in changes of PA among a cohort of subjects is characterized via variability in the deformation. Functional principal component analysis is further adopted to model the deformations, and PC scores are used as a proxy in modeling the relation between changes in PA and health outcomes and/or interventions. We conduct comprehensive analyses on data from two clinical trials: Reach for Health (RfH) and Metabolism, Exercise and Nutrition at UCSD (MENU), focusing on the effect of interventions on longitudinal changes in PA patterns and how different modes of changes in PA influence weight loss, respectively. The proposed approach reveals unique modes of changes, including overall enhanced PA, boosted morning PA, and shifts of active hours specific to each study cohort. The results bring new insights into the study of longitudinal changes in PA and health and have the potential to facilitate designing of effective health interventions and guidelines.