EFFECT OF 12 WEEKS OF FUNCTIONAL TRAINING ON COLLEGE SOCCER PLAYERS

ABSTRACT Introduction Soccer is a sport with intense rivalry, where physical strength is a prerequisite to ensure high level of playability. Objective Explore the application of functional training in soccer training and its influence on soccer players’ specific physical fitness. Methods 24 s and divided into experimental and control groups into an experimental group and a control group. The control group underwent the intervention according to the normal program, while the experimental group used a functional training program protocol. The subjects’ FMS scores and special fitness and ss were tested before and after the experiment, the results were statistically analyzed and discussed in the light of up-to-date scientific literature. Results Before the experiment, the overall functional action screening scores of the two groups of players were low, and there was a high risk of sports injuries. After 12 weeks of training intervention, the experimental and control groups’ FMS scores were significantly elevated, indicating that traditional physical and functional training can effectively improve functional movement screening performance. Conclusion The 12 weeks suggested functional training protocol can significantly improve the physical fitness of soccer players. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.</div

IMPROVEMENT OF THE HEALTH OF PEOPLE WITH AUTISM SPECTRUM DISORDER BY EXERCISE

ABSTRACT Introduction Autism Spectrum Disorder (ASD) is a typical neurological development disorder of the brain, exhibiting social communication and communication disorders, narrow interests, and repetitive, stereotyped behaviors. Movement development is an important evaluation index for the development of early motor function in children, so exercise intervention in children with ASD is of great significance. Objective This article conducts exercise intervention on children with ASD to stimulate their exercise ability and improve their self-care ability. Methods The article randomly grouped 24 children with an autism spectrum disorder. The experimental group received exercise intervention, and the control group had regular classes. After the experiment is completed, the influence of exercise intervention on children with autism is analyzed. Results The motor skills of the two groups of children were different after the intervention. The motor skills of the experimental group improved more significantly. Conclusion Exercise intervention can significantly improve the motor skills of children with an autism spectrum disorder. To evaluate whether the large-muscle motor skill learning of children with ASD and its influence on basic motor skills can be transferred to provide a reference for related motor intervention. Level of evidence II; Therapeutic studies - investigation of treatment results.</div

Supplementary_Material – Supplemental material for Nitrogen-doped carbon dots as a probe for the detection of Cu2+ and its cellular imaging

Supplemental material, Supplementary_Material for Nitrogen-doped carbon dots as a probe for the detection of Cu2+ and its cellular imaging by Ning Wang, Xuebing Li, Xuefang Yang, Zenglian Tian, Wei Bian and Weihua Jia in Journal of Chemical Research</p

Numbers of eligible patients in TIMS-China.

<p>Numbers of eligible patients in TIMS-China.</p

Comparison of function in different subtype of AHT at 7-day and at 90-day in TIMS-china.

<p>AHT: asymptomatic hemorrhagic transformation; mRS, modified Rankin Scale; HI1:hemorrhagic infarcts type 1; HI2: hemorrhagic infarcts type 2; PH1: parenchymal hematomas type 1; PH2: parenchymal hematomas type 2.</p

Table_1_Metabolomics-based investigation of SARS-CoV-2 vaccination (Sinovac) reveals an immune-dependent metabolite biomarker.xlsx

SARS-CoV-2 and its mutant strains continue to rapidly spread with high infection and fatality. Large-scale SARS-CoV-2 vaccination provides an important guarantee for effective resistance to existing or mutated SARS-CoV-2 virus infection. However, whether the host metabolite levels respond to SARS-CoV-2 vaccine-influenced host immunity remains unclear. To help delineate the serum metabolome profile of SARS-CoV-2 vaccinated volunteers and determine that the metabolites tightly respond to host immune antibodies and cytokines, in this study, a total of 59 sera samples were collected from 30 individuals before SARS-CoV-2 vaccination and from 29 COVID-19 vaccines 2 weeks after the two-dose vaccination. Next, untargeted metabolomics was performed and a distinct metabolic composition was revealed between the pre-vaccination (VB) group and two-dose vaccination (SV) group by partial least squares-discriminant and principal component analyses. Based on the criteria: FDR 1, we found that L-glutamic acid, gamma-aminobutyric acid (GABA), succinic acid, and taurine showed increasing trends from SV to VB. Furthermore, SV-associated metabolites were mainly annotated to butanoate metabolism and glutamate metabolism pathways. Moreover, two metabolite biomarkers classified SV from VB individuals with an area under the curve (AUC) of 0.96. Correlation analysis identified a positive association between four metabolites enriched in glutamate metabolism and serum antibodies in relation to IgG, IgM, and IgA. These results suggest that the contents of gamma-aminobutyric acid and indole in serum could be applied as biomarkers in distinguishing vaccinated volunteers from the unvaccinated. What’s more, metabolites such as GABA and taurine may serve as a metabolic target for adjuvant vaccines to boost the ability of the individuals to improve immunity.</p

Table_4_Metabolomics-based investigation of SARS-CoV-2 vaccination (Sinovac) reveals an immune-dependent metabolite biomarker.xlsx

SARS-CoV-2 and its mutant strains continue to rapidly spread with high infection and fatality. Large-scale SARS-CoV-2 vaccination provides an important guarantee for effective resistance to existing or mutated SARS-CoV-2 virus infection. However, whether the host metabolite levels respond to SARS-CoV-2 vaccine-influenced host immunity remains unclear. To help delineate the serum metabolome profile of SARS-CoV-2 vaccinated volunteers and determine that the metabolites tightly respond to host immune antibodies and cytokines, in this study, a total of 59 sera samples were collected from 30 individuals before SARS-CoV-2 vaccination and from 29 COVID-19 vaccines 2 weeks after the two-dose vaccination. Next, untargeted metabolomics was performed and a distinct metabolic composition was revealed between the pre-vaccination (VB) group and two-dose vaccination (SV) group by partial least squares-discriminant and principal component analyses. Based on the criteria: FDR 1, we found that L-glutamic acid, gamma-aminobutyric acid (GABA), succinic acid, and taurine showed increasing trends from SV to VB. Furthermore, SV-associated metabolites were mainly annotated to butanoate metabolism and glutamate metabolism pathways. Moreover, two metabolite biomarkers classified SV from VB individuals with an area under the curve (AUC) of 0.96. Correlation analysis identified a positive association between four metabolites enriched in glutamate metabolism and serum antibodies in relation to IgG, IgM, and IgA. These results suggest that the contents of gamma-aminobutyric acid and indole in serum could be applied as biomarkers in distinguishing vaccinated volunteers from the unvaccinated. What’s more, metabolites such as GABA and taurine may serve as a metabolic target for adjuvant vaccines to boost the ability of the individuals to improve immunity.</p

Additional file 14 of Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Additional file 14: Fig. S4. Validation of the models in the training set with only the 9 SNPs as inputs. a, b The picture shows the AU-ROC and AU-PRC curves of all models in the test set

Additional file 2 of Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Additional file 2: Table S2. Demographics of COPD patients and control subjectsin the training set

Additional file 10 of Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Additional file 10: Table S8. The efficacy of KNN, LR, SVM, DT, MLP and XGboost in the training set of 5 Clinical features