Effects of mini-basketball training program on social communication impairments and regional homogeneity of brain functions in preschool children with autism spectrum disorder.

BACKGROUND: Social communication impairments (SCI) is a core symptom of autism spectrum disorder (ASD) and is marked by challenges in social interaction. Although physical exercise has been shown to improve SCI, this finding has not been supported by comprehensive scientific evidence. Existing research has established a strong link between the SCI in children with ASD and abnormalities in regional homogeneity (ReHo). Therefore, investigating the effects of physical exercise on SCI and Reho in patients with ASD may help to elucidate the neurological mechanisms involved. METHODS: The present study included 30 preschool children diagnosed with ASD, with 15 participants in each group (experimental and control). The experimental group underwent a 12-week mini-basketball training program (MBTP) based on routine behavioral rehabilitation, while the control group only received routine behavioral rehabilitation. The Social Responsiveness Scale-Second Edition (SRS-2) was employed to assess SCI in both groups. Resting-state functional magnetic resonance imaging technology was used to evaluate ReHo in both groups. RESULTS: After 12-week of MBTP, significant group × time interactions were observed between the experimental and control groups in total SRS-2 scores (F = 14.514, p < 0.001, ηp2 = 0.341), as well as in the domains of social cognition (F = 15.620, p < 0.001, ηp2 = 0.358), social communication (F = 12.460, p < 0.01, ηp2 = 0.308), and autistic mannerisms (F = 9.970, p < 0.01, ηp2 = 0.263). No statistical difference was found in the scores for the social awareness subscale and social motivation subscale in the group × time interaction (all p > 0.05). The experimental group exhibited increased ReHo in the right Cerebellum_Crus1 and right parahippocampal gyrus, coupled with decreased ReHo in the left middle frontal gyrus (orbital part), left superior frontal gyrus (dorsolateral), left postcentral gyrus, and right superior parietal gyrus. Furthermore, a decrease in ReHo in the left postcentral gyrus positively correlated with changes in social communication scores in SCI behaviors (p < 0.05). CONCLUSIONS: Our study underscores the effectiveness of a 12-week MBTP in ameliorating SCI and abnormalities in ReHo among preschool children with ASD. TRIAL REGISTRATION: The trial is retrospectively registered on the Chinese Clinical Trial Registry (ChiCTR1900024973; August 5, 2019).

Effects on brain structural and functional in deaf children after aerobic exercise training: a pilot cluster randomized controlled study.

Purpose: To examine effects of aerobic exercise interventions on brain via the structural Magnetic Resonance Imaging (MRI), as well as functional change during working memory (WM) task using fMRI in deaf children.Method: The study applied a cluster randomized controlled design. Twelve deaf children in the intervention group were required to complete an eleven-week aerobic exercise intervention, while other twelve age and gender matched deaf children in the control group were required to keep their normal daily life. Task fMRI images of each participant were acquired in the baseline and post intervention period. The surface-based morphometry (SBM) analysis and functional activation analysis were employed to probe the effects of 11-week aerobic exercise on cerebral structural and functional in deaf children, respectively.Results: The 11-week aerobic exercise intervention did not change brain structure in deaf children. However, behavior performance (reaction time and mean accuracy rate) presented significant improvements after the 11-week aerobic exercise intervention. Compared to the control group, the intervention group showed decreased reaction time in the 2-back (p < 0.001) and 2-0 back (p < 0.001), and increased mean accuracy rate during 2-back (p = 0.034). Furthermore, enhanced brain activations in the left supplementary motor cortex (p < 0.05, FDR-corrected) and left paracentral lobule (p < 0.05, FDR-corrected) were observed in the intervention group.Conclusion: 11-week aerobic exercise intervention may not be able to modulate brain structure in deaf children, but may have significantly positive effects on behavior performance and brain functional activation during WM task.

The effects of football juggling learning on executive function and brain functional connectivity.

This study aimed to explore the relationship between motor skill learning and executive function (EF), with an emphasis on the potential effects of football juggling learning. A randomized controlled trial involving 111 participants aged 17-19 years was conducted. Participants were randomly assigned to either the football juggling learning (FJL) group or a control group. The FJL group underwent 70 sessions of football juggling learning, while the control group engaged in their normal daily activities without any exercise intervention during the same time frame. Both groups were assessed for EF performance and underwent functional magnetic resonance imaging (fMRI) scans before and after the experiment. The executive function test included three tasks, namely, inhibition, working memory, and shifting. The results showed significant improvement in inhibition and shifting in both groups, and the FJL group showed greater improvement in these aspects of EF compared to the control group. Additionally, in comparison to the control group, the FJL group exhibited increased functional connectivity within the frontal, temporal, and cerebellar regions from the pre-test to the post-test. Notably, enhanced functional connectivity between the right superior temporal gyrus (posterior division) and left cerebellum 6 was identified in the FJL group and was associated with improved EF performance induced by football juggling learning. These findings shed light on the potential causal relationship between motor skill learning, EF, and brain plasticity. Importantly, our study provides preliminary evidence supporting the use of motor skill learning, such as football juggling, as a potential avenue for cognitive enhancement.

Predicting academic achievement from the collaborative influences of executive function, physical fitness, and demographic factors among primary school students in China: ensemble learning methods.

BACKGROUND: Elevated levels of executive function and physical fitness play a pivotal role in shaping future quality of life. However, few studies have examined the collaborative influences of physical and mental health on academic achievement. This study aims to investigate the key factors that collaboratively influence primary school students' academic achievement from executive function, physical fitness, and demographic factors. Additionally, ensemble learning methods are employed to predict academic achievement, and their predictive performance is compared with individual learners. METHODS: A cluster sampling method was utilized to select 353 primary school students from Huai'an, China, who underwent assessments for executive function, physical fitness, and academic achievement. The recursive feature elimination cross-validation method was employed to identify key factors that collaboratively influence academic achievement. Ensemble learning models, utilizing eXtreme Gradient Boosting and Random Forest algorithms, were constructed based on Bagging and Boosting methods. Individual learners were developed using Support Vector Machine, Decision Tree, Logistic Regression, and Linear Discriminant Analysis algorithms, followed by the establishment of a Stacking ensemble learning model. RESULTS: Our findings revealed that sex, body mass index, muscle strength, cardiorespiratory function, inhibition, working memory, and shifting were key factors influencing the academic achievement of primary school students. Moreover, ensemble learning models demonstrated superior predictive performance compared to individual learners in predicting academic achievement among primary school students. CONCLUSIONS: Our results suggest that recognizing sex differences and emphasizing the simultaneous development of cognition and physical well-being can positively impact the academic development of primary school students. Ensemble learning methods warrant further attention, as they enable the establishment of an accurate academic early warning system for primary school students.

Diagnosing autism severity associated with physical fitness and gray matter volume in children with autism spectrum disorder: Explainable machine learning method.

PURPOSE: This study aimed to investigate the relationship between physical fitness, gray matter volume (GMV), and autism severity in children with autism spectrum disorder (ASD). Besides, we sought to diagnose autism severity associated with physical fitness and GMV using machine learning methods. METHODS: Ninety children diagnosed with ASD underwent physical fitness tests, magnetic resonance imaging scans, and autism severity assessments. Diagnosis models were established using extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), and decision tree (DT) algorithms. Hyperparameters were optimized through the grid search cross-validation method. The shapley additive explanation (SHAP) method was employed to explain the diagnosis results. RESULTS: Our study revealed associations between muscular strength in physical fitness and GMV in specific brain regions (left paracentral lobule, bilateral thalamus, left inferior temporal gyrus, and cerebellar vermis I-II) with autism severity in children with ASD. The accuracy (95 % confidence interval) of the XGB, RF, SVM, and DT models were 77.9 % (77.3, 78.6 %), 72.4 % (71.7, 73.2 %), 71.9 % (71.1, 72.6 %), and 66.9 % (66.2, 67.7 %), respectively. SHAP analysis revealed that muscular strength and thalamic GMV significantly influenced the decision-making process of the XGB model. CONCLUSION: Machine learning methods can effectively diagnose autism severity associated with physical fitness and GMV in children with ASD. In this respect, the XGB model demonstrated excellent performance across various indicators, suggesting its potential for diagnosing autism severity.

Supervised machine learning: A new method to predict the outcomes following exercise intervention in children with autism spectrum disorder

The individual differences among children with autism spectrum disorder (ASD) may make it challenging to achieve comparable benefits from a specific exercise intervention program. A new method for predicting the possible outcomes and maximizing the benefits of exercise intervention for children with ASD needs further exploration. Using the mini-basketball training program (MBTP) studies to improve the symptom performance of children with ASD as an example, we used the supervised machine learning method to predict the possible intervention outcomes based on the individual differences of children with ASD, investigated and validated the efficacy of this method. In a long-term study, we included 41 ASD children who received the MBTP. Before the intervention, we collected their clinical information, behavioral factors, and brain structural indicators as candidate factors. To perform the regression and classification tasks, the random forest algorithm from the supervised machine learning method was selected, and the cross validation method was used to determine the reliability of the prediction results. The regression task was used to predict the social communication impairment outcome following the MBTP in children with ASD, and explainable variance was used to evaluate the predictive performance. The classification task was used to distinguish the core symptom outcome groups of ASD children, and predictive performance was assessed based on accuracy. We discovered that random forest models could predict the outcome of social communication impairment (average explained variance was 30.58%) and core symptom (average accuracy was 66.12%) following the MBTP, confirming that the supervised machine learning method can predict exercise intervention outcomes for children with ASD. (AU)

Decreased Functional and Structural Connectivity is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder After Mini-basketball Training Program.

Exercise intervention has been proven helpful to ameliorate core symptoms of Autism Spectrum Disorder (ASD). However, the underlying mechanisms are not fully understood. In this study, we carried out a 12-week mini-basketball training program (MBTP) on ASD children and examined the changes of brain functional and structural networks before and after exercise intervention. We applied individual-based method to construct functional network and structural morphological network, and investigated their alterations following MBTP as well as their associations with the change in core symptom. Structural MRI and resting-state functional MRI data were obtained from 58 ASD children aged 3-12 years (experiment group: n = 32, control group: n = 26). ASD children who received MBTP intervention showed several distinguishable alternations compared to the control without special intervention. These included decreased functional connectivity within the sensorimotor network (SM) and between SM and the salience network, decreased morphological connectivity strength in a cortical-cortical network centered on the left inferior temporal gyrus, and a subcortical-cortical network centered on the left caudate. Particularly, the aforementioned functional and structural changes induced by MBTP were associated with core symptoms of ASD. Our findings suggested that MBTP intervention could be an effective approach to improve core symptoms in ASD children, decrease connectivity in both structure and function networks, and may drive the brain change towards normal-like neuroanatomy.

Supervised machine learning: A new method to predict the outcomes following exercise intervention in children with autism spectrum disorder.

The individual differences among children with autism spectrum disorder (ASD) may make it challenging to achieve comparable benefits from a specific exercise intervention program. A new method for predicting the possible outcomes and maximizing the benefits of exercise intervention for children with ASD needs further exploration. Using the mini-basketball training program (MBTP) studies to improve the symptom performance of children with ASD as an example, we used the supervised machine learning method to predict the possible intervention outcomes based on the individual differences of children with ASD, investigated and validated the efficacy of this method. In a long-term study, we included 41 ASD children who received the MBTP. Before the intervention, we collected their clinical information, behavioral factors, and brain structural indicators as candidate factors. To perform the regression and classification tasks, the random forest algorithm from the supervised machine learning method was selected, and the cross validation method was used to determine the reliability of the prediction results. The regression task was used to predict the social communication impairment outcome following the MBTP in children with ASD, and explainable variance was used to evaluate the predictive performance. The classification task was used to distinguish the core symptom outcome groups of ASD children, and predictive performance was assessed based on accuracy. We discovered that random forest models could predict the outcome of social communication impairment (average explained variance was 30.58%) and core symptom (average accuracy was 66.12%) following the MBTP, confirming that the supervised machine learning method can predict exercise intervention outcomes for children with ASD. Our findings provide a novel and reliable method for identifying ASD children most likely to benefit from a specific exercise intervention program in advance and a solid foundation for establishing a personalized exercise intervention program recommendation system for ASD children.

Effectiveness of physical activity interventions for core symptoms of autism spectrum disorder: A systematic review and meta-analysis.

In this paper, systematic review and meta-analysis were used to demonstrate the effectiveness of physical activity intervention on core symptoms of autism spectrum disorder (ASD). Physical activity intervention for core symptoms of ASD were retrieved by computer from the PubMed Cochrane Library, Web of Science, APA PsycNet, and CNKI database during December 1, 2022. Two researchers evaluated the quality of the included literature and extracted the data. Sixteen studies were eventually included, with a total of 587 patients with ASD. Meta-analysis showed that the core symptoms of ASD patients decreased after physical activity intervention, ES(g) = 0.681(95% CI: 0.380-0.982, p = 0.000), specifically, physical activity improved the reduction of social disorder ES(g) = 0.749(95% CI: 0.524-0.973) and repeated rigid behavior ES(g) = 0.553 (95% CI: -0.079 to 1.186). Subgroup analysis showed that preschool children with ASD who were 3-6 years old, exercised for more than 12 weeks, more than 3 times a week, and exercised for more than 90 min per session had better improvement in core symptoms after participating in physical activity. The conclusion of this paper is that physical activity intervention can improve the core symptoms of ASD, especially the reduction of social disorders and repetitive behaviors.

Relationship between Overweight/Obesity and Social Communication in Autism Spectrum Disorder Children: Mediating Effect of Gray Matter Volume.

With advances in medical diagnostic technology, the healthy development of children with autism spectrum disorder (ASD) is receiving more and more attention. In this article, the mediating effect of brain gray matter volume (GMV) between overweight/obesity and social communication (SC) was investigated through the analysis of the relationship between overweight/obesity and SC in autism spectrum disorder children. In total, 101 children with ASD aged 3-12 years were recruited from three special educational centers (Yangzhou, China). Overweight/obesity in children with ASD was indicated by their body mass index (BMI); the Social Responsiveness Scale, Second Edition (SRS-2) was used to assess their social interaction ability, and structural Magnetic Resonance Imaging (sMRI) was used to measure GMV. A mediation model was constructed using the Process plug-in to analyze the mediating effect of GMV between overweight/obesity and SC in children with ASD. The results revealed that: overweight/obesity positively correlated with SRS-2 total points (p = 0.01); gray matter volume in the left dorsolateral superior frontal gyrus (Frontal_Sup_L GMV) negatively correlated with SRS-2 total points (p = 0.001); and overweight/obesity negatively correlated with Frontal_Sup_L GMV (p = 0.001). The Frontal_Sup_L GMV played a partial mediating role in the relationship between overweight/obesity and SC, accounting for 36.6% of total effect values. These findings indicate the significant positive correlation between overweight/obesity and SC; GMV in the left dorsolateral superior frontal gyrus plays a mediating role in the relationship between overweight/obesity and SC. The study may provide new evidence toward comprehensively revealing the overweight/obesity and SC relationship.

Associations between meeting 24-hour movement guidelines and quality of life among children and adolescents with autism spectrum disorder.

BACKGROUND: The Canadian 24-hour movement behavior (24-HMB) guidelines suggest that a limited amount of screen time use, an adequate level of physical activity (PA), and sufficient sleep duration are beneficial for ensuring and optimizing the health and quality of life (QoL) of children and adolescents. However, this topic has yet to be examined for children and adolescents with autism spectrum disorder (ASD) specifically. The aim of this cross-sectional observational study was to examine the associations between meeting 24-HMB guidelines and several QoL-related indicators among a national sample of American children and adolescents with ASD. METHODS: Data were taken from the 2020 U.S. National Survey of Children's Health dataset. Participants (n = 956) aged 6-17 years and currently diagnosed with ASD were included. The exposure of interest was adherence to the 24-HMB guidelines. Outcomes were QoL indicators, including learning interest/curiosity, repeating grades, adaptive ability, victimization by bullying, and behavioral problems. Categorical variables were described with unweighted sample counts and weighted percentages. Age, sex, race, preterm birth status, medication, behavioral treatment, household poverty level, and the educational level of the primary caregivers were included as covariates. Odds ratio (OR) and 95% confidence interval (95%CI) were used to present the strength of association between adherence to 24-HMB guidelines and QoL-related indicators. RESULTS: Overall, 452 participants (45.34%) met 1 of the 3 recommendations, 216 (22.65%) met 2 recommendations, whereas only 39 participants (5.04%) met all 3 recommendations. Compared with meeting none of the recommendations, meeting both sleep duration and PA recommendations (OR = 3.92, 95%CI: 1.63-9.48, p < 0.001) or all 3 recommendations (OR = 2.11, 95%CI: 1.03-4.35, p = 0.04) was associated with higher odds of showing learning interest/curiosity. Meeting both screen time and PA recommendations (OR = 0.15, 95%CI: 0.04-0.61, p < 0.05) or both sleep duration and PA recommendations (OR = 0.24, 95%CI: 0.07-0.87, p < 0.05) was associated with lower odds of repeating any grades. With respect to adaptive ability, participants who met only the PA recommendation of the 24-HMB were less likely to have difficulties dressing or bathing (OR = 0.11, 95%CI: 0.02-0.66, p < 0.05) than those who did not. For participants who met all 3 recommendations (OR = 0.38, 95%CI: 0.15-0.99, p = 0.05), the odds of being victimized by bullying was lower. Participants who adhered to both sleep duration and PA recommendations were less likely to present with severe behavioral problems (OR = 0.17, 95%CI: 0.04-0.71, p < 0.05) than those who did not meet those guidelines. CONCLUSION: Significant associations were found between adhering to 24-HMB guidelines and selected QoL indicators. These findings highlight the importance of maintaining a healthy lifestyle as a key factor in promoting and preserving the QoL of children with ASD.

Cardiorespiratory fitness as a mediator between body fat rate and executive function in college students.

Purpose: To examine whether body fat rate (BF%) is associated with cardiorespiratory fitness (CRF) and whether cardiorespiratory fitness (CRF) mediates the association between BF% and Executive function (EF) in young adults. Methods: In this cross-sectional study, 226 college students were recruited from an university. Flanker, 2-back, and odder and shifting tasks were used to assess EF. The incremental cardiopulmonary exercise tests were performed, and maximal oxygen consumption was recorded during test. The body composition measuring instrument was used to evaluate the participants' BF%. Results: The BF% of college students was negatively correlated with each EF, BF% was negatively correlated with CRF, and CRF was negatively correlated with EF (P< 0.001). Structural equation modeling (SEM) and simultaneous analysis of several groups were used to construct mediator model. The CRF of college students plays a partial mediating role between BF% and EF, and the mediating effect accounts for 48.8% of the total effect value. Sex has no moderate effect on the relationship between BF%, CRF, and EF. Conclusions: College students with high BF% can improve their CRF by strengthening physical exercise, thereby indirectly improving their EF. Therefore, college students who have a higher body fat percentage should be compensated for engaging in physical exercise in order to enhance their CRF and mitigate the detrimental effects of obesity and overweight on EF.

Effects of exercise types on white matter microstructure in late midlife adults: Preliminary results from a diffusion tensor imaging study.

Higher aerobic fitness during late midlife is associated with higher white matter (WM) microstructure. Compared with individuals engaged in irregular exercise, those who engage in regular aerobic exercise show higher fractional anisotropy (FA), a diffusion tenor imaging (DTI) measure that provides an index of WM microstructural integrity. However, whether other types of exercise, such as Tai Chi, can also facilitate WM changes in adults during late midlife remains unknown. The present study compares two types of exercise, Tai Chi and walking, with a sedentary control group, in order to examine the effects of exercise on WM microstructure and determine the regional specificity of WM differences. Thirty-six healthy adults between the ages of 55 and 65 years participated in the study. Based on the participants' exercise habits, they were allocated into three groups: Tai Chi, walking, or sedentary control. All participants were required to complete physical fitness measurements and completed magnetic reasoning imaging (MRI) scans. Our results revealed that the Tai Chi group exhibited a higher FA value in the left cerebral peduncle, compared to the sedentary control group. We also observed that both the Tai Chi and walking groups exhibited higher FA values in the right uncinate fasciculus and the left external capsule, in comparison to the sedentary control group. Increased FA values in these regions was positively correlated with higher levels of physical fitness measurements (i.e., peak oxygen uptake [VO2peak], muscular endurance/number of push-up, agility, power). These findings collectively suggest that regular exercise is associated with improved WM microstructural integrity, regardless of the exercise type, which could guide the development and application of future prevention and intervention strategies designed to address age-related cognitive impairments during late midlife.

DWFed: A statistical- heterogeneity-based dynamic weighted model aggregation algorithm for federated learning.

Federated Learning is a distributed machine learning framework that aims to train a global shared model while keeping their data locally, and previous researches have empirically proven the ideal performance of federated learning methods. However, recent researches found the challenge of statistical heterogeneity caused by the non-independent and identically distributed (non-IID), which leads to a significant decline in the performance of federated learning because of the model divergence caused by non-IID data. This statistical heterogeneity is dramatically restricts the application of federated learning and has become one of the critical challenges in federated learning. In this paper, a dynamic weighted model aggregation algorithm based on statistical heterogeneity for federated learning called DWFed is proposed, in which the index of statistical heterogeneity is firstly quantitatively defined through derivation. Then the index is used to calculate the weights of each local model for aggregating federated model, which is to constrain the model divergence caused by non-IID data. Multiple experiments on public benchmark data set reveal the improvements in performance and robustness of the federated models in heterogeneous settings.

Relationship between Cardiorespiratory Fitness and Executive Function in Young Adults: Mediating Effects of Gray Matter Volume.

We evaluated the association between cardiorespiratory fitness (CRF) and executive function (EF) in young adults and the mediating effects of GMV on this relationship. This study involved 217 college students. An incremental load exercise program was used to evaluate VO2max. EF was estimated by the Flanker task, the 2-back task, and the more-odd shifting task, while structural magnetic resonance and region-based morphometry (RBM) were used to analyze GMV. The high CRF group had a shorter updating reaction time (RT) (p ≤ 0.05). CRF was positively correlated with the right orbital part of the middle frontal gyrus (ORBmid.R) GMV (p ≤ 0.05). ORBmid.R GMV was negatively correlated with updating RT (p ≤ 0.05). Model 4 in SPSS was used to assess the mediating effects of ORBmid.R GMV between CRF and updating RT. ORBmid.R GMV was established to have a partially mediating role between CRF and updating RT, which accounted for 19.6% of the total effect value. These findings indicate that the negative correlation between CRF and EF was significant, and ORBmid.R GMV played a mediating role in the relationship between CRF and EF, providing new evidence toward comprehensively revealing that CRF promotes EF performance.

Relationship between Physical Activity and Emotional Regulation Strategies in Early Adulthood: Mediating Effects of Cortical Thickness.

We investigated the relationship between physical activity (PA) and emotional regulation strategies among college students to establish the mediating role of cortical thickness. A total of 60 university students (18−20 years old) were enrolled in this study. The International Physical Activity Questionnaire (IPAQ-L) was used to estimate PA levels. Based on the International Physical Activity Working Group standards, PA levels were divided into low, medium, and high PA groups; emotional regulation strategies were determined by the Emotion Regulation Questionnaire (ERQ), including the Cognitive Reappraisal Scale (CR) and the Expressive Suppression Scale (ES). Structural magnetic resonance imaging (MRI) was used to measure cortical thickness. Differences in use of the ES strategy among high, medium, and low PA groups were not marked. However, compared to the low PA group, the CR strategy was frequently used in the high PA group, with a thicker right hemisphere rostral anterior cingulate cortex (rrACC). PA levels were positively correlated with thickness of the rrACC cortex (r = 0.398, p = 0.002 < 0.05) and CR strategy (r = 0.398, p = 0.002 < 0.05), and negatively correlated with the ES strategy (r = −0.348, p = 0.007 < 0.05). The rrACC cortical thickness played a partial mediating role in the relationship between PA and CR strategy, accounting for 33.1% of total effect values. These findings indicate that although the negative correlation between PA and ES was not significant, the positive correlation between PA with CR was significant, and rrACC thickness played a partial mediating role in the relationship between PA and CR, providing new evidence toward comprehensively revealing the relationship between PA, rrACC cortical thickness, and emotion regulation strategies.

Bibliometric analysis of research trends of physical activity intervention for autism spectrum disorders.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social impairment, restricted interests, and repetitive stereotyped behaviors. At present, its pathogenesis has not been fully understood. Various methods are used for clinical treatment and intervention, among which physical activity (PA) intervention also has an obvious effect. This study has used bibliometric methods and visual analysis methods to analyze 885 studies of PA intervention in ASD from 2003 to 2022 in the Web of Science (WoS) database in order to provide theoretical support for the follow-up research on the effect of PA with ASD. The main findings of this study are as follows. First, the literature on PA interventions in ASD research showed a growing trend. The leading institution in this field is the University of Delaware, forming a core group of authors represented by authors such as Sean Healy and Carol Curtin et al. Second, the research focus of this research area mainly includes PA interventions for children and adolescents with ASD. PA can improve symptoms such as stereotyped behaviors and motor function in patients with ASD as well as can reduce childhood obesity rates and improve quality of life. Third, skill, youth, prevalence, and meta-analysis systematic reviews were found. It is the long-term concern and focus of researchers. In conclusion, the current research is only a short-term analysis, and it is not possible to verify the long-term effect; thus, future data analysis should evaluate and explore the long-term effects of PA interventions on ASD including cohort and longitudinal study types focused on the rehabilitation of patients with ASD. Moreover, testing the sustainability of benefits for children with ASD and constructing a multidimensional exercise integrated intervention model are the main directions for future research in this field.

An EMD-Based Adaptive Client Selection Algorithm for Federated Learning in Heterogeneous Data Scenarios.

Federated learning is a distributed machine learning framework that enables distributed nodes with computation and storage capabilities to train a global model while keeping distributed-stored data locally. This process can promote the efficiency of modeling while preserving data privacy. Therefore, federated learning can be widely applied in distributed conjoint analysis scenarios, such as smart plant protection systems, in which widely networked IoT devices are used to monitor the critical data of plant production to improve crop production. However, the data collected by different IoT devices can be dependent and identically distributed (non-IID), causing the challenge of statistical heterogeneity. Studies have also shown that statistical heterogeneity can lead to a marked decline in the efficiency of federated learning, making it challenging to apply in practice. To promote the efficiency of federated learning in statistical heterogeneity scenarios, an adaptive client selection algorithm for federated learning in statistical heterogeneous scenarios called ACSFed is proposed in this paper. ACSFed can dynamically calculate the possibility of clients being selected to train the model for each communication round based on their local statistical heterogeneity and previous training performance instead of randomly selected clients, and clients with heavier statistical heterogeneity or bad training performance would be more likely selected to participate in the later training. This client selection strategy can enable the federated model to learn the global statistical knowledge faster and thereby promote the convergence of the federated model. Multiple experiments on public benchmark datasets demonstrate these improvements in the efficiency of the models in heterogeneous settings.

The Association of Obesity and Cardiorespiratory Fitness in Relation to Cognitive Flexibility: An Event-Related Potential Study.

This study investigates an association between obesity and cardiorespiratory fitness concerning their potential effects on cognitive flexibility in young adults from behavioral and neuroelectrical perspectives. Eligible young adults (N = 140, 18-25 years) were assigned into one of four groups, according to their status of obesity (i.e., body mass index) and cardiorespiratory fitness levels (i.e., estimated maximal oxygen uptake), namely, normal weight with high cardiorespiratory fitness (NH), obese with high cardiorespiratory fitness (OH), normal weight with low cardiorespiratory fitness (NL), and obese with low cardiorespiratory fitness (OL). The task-switching test was utilized, and its induced endogenous (P3) and exogenous (N1) event-related potential components were recorded. Concerning behavioral indices, the NH demonstrated superior behavioral performance across global switching and local switching of the task-switching test compared to individuals with lower cardiorespiratory fitness and obesity (i.e., NL, OH, and OL). Additionally, the OH demonstrated better performance than the OL during the heterogeneous condition. For neuroelectrical indices, the NH had larger mean P3 amplitudes during global and local switching than the other three groups. A larger N1 amplitude was also observed in the NH during local switching than in the OH group. The findings suggest that cardiorespiratory fitness has beneficial effects on cognitive flexibility, attentional resource allocation, and sensory evaluation in young adults. Furthermore, our research provided novel evidence showing that cardiorespiratory fitness might potentially alleviate the adverse effects of obesity on cognitive flexibility in young adults.

Key molecular events involved in root exudates-mediated replanted disease of Rehmannia glutinosa.

The perennial herbaceous plant, Rehmannia glutinosa Libosch, is one of traditional Chinese medicines with a long history of cultivation. However, replanted disease severely affects its yield and quality in production. In this study, a specific culture device was designed to accurately isolate the root exudates of R. glutinosa. In addition, the formation mechanism of replanted diseases mediated by root exudates was deeply studied in R. glutinosa. The results indicated that root exudates have obvious allelopathic activity, furthermore, metagenomics analysis found that the exudates were found to significantly induce the proliferation of harmful pathogenic fungal and the reduction of probiotics in rhizosphere of R. glutinosa. Further analysis found that, 8,758 genes were differentially expressed in root exudate-treated R. glutinosa plants. These genes mainly involved in critical cellular processes including immune response, hormone metabolism, signaling transduction and cell membrane transport. Of which, numerous genes were found to involve in immune response, such as PR (Pathogenesis-related protein), were highly expressed in root exudate-treated plants. Transiently overexpression experiments found that a PR1 could enhance the resistance of R. glutinosa to root exudates treatment. These results indicated that the interaction between root exudates and microbes altered the expression pattern of the genes related to immune pathway and signaling transduction mediated by it. These disordered genes finally severely affected the growth and development of R. glutinosa, and eventually formed the replanted disease. This study provides a novel approach to collect root exudates and a new data basis for revealing the molecular events occurring in replanted plants.