ANALYSIS OF CARDIOPULMONARY RESISTANCE UNDER DIFFERENT LOADS IN AEROBIC EXERCISES

ABSTRACT Introduction The key objective of aerobic exercise is enhancing cardiorespiratory endurance. On the national gymnastics plan implementation, the idea of lifelong sports was gradually accepted by the masses, and the aerobic gymnastics concept was sweeping the world. Objective Analyze the cardiorespiratory endurance responses in female college students under different frequencies in aerobic exercise. Methods 20 female professors and civilian women were randomly selected and divided into two groups. The experimental group performed 45 and 90 minutes of aerobic exercise to analyze changes in cardiopulmonary function before and after each exercise. Results After 16 weeks of aerobic exercise with different loads, all young women who had participated in the program training showed a significant increase in vital capacity and maximal oxygen uptake capacity. The vital capacity of the 90-min aerobic exercise group was significantly higher than that of the 45-min aerobic exercise group (P</div

Data_Sheet_1_Emotion recognition based on microstate analysis from temporal and spatial patterns of electroencephalogram.PDF

IntroductionRecently, the microstate analysis method has been widely used to investigate the temporal and spatial dynamics of electroencephalogram (EEG) signals. However, most studies have focused on EEG at resting state, and few use microstate analysis to study emotional EEG. This paper aims to investigate the temporal and spatial patterns of EEG in emotional states, and the specific neurophysiological significance of microstates during the emotion cognitive process, and further explore the feasibility and effectiveness of applying the microstate analysis to emotion recognition.MethodsWe proposed a KLGEV-criterion-based microstate analysis method, which can automatically and adaptively identify the optimal number of microstates in emotional EEG. The extracted temporal and spatial microstate features then served as novel feature sets to improve the performance of EEG emotion recognition. We evaluated the proposed method on two publicly available emotional EEG datasets: the SJTU Emotion EEG Dataset (SEED) and the Database for Emotion Analysis using Physiological Signals (DEAP).ResultsFor the SEED dataset, 10 microstates were identified using the proposed method. These temporal and spatial features were fed into AutoGluon, an open-source automatic machine learning model, yielding an average three-class accuracy of 70.38% (±8.03%) in subject-dependent emotion recognition. For the DEAP dataset, the method identified 9 microstates. The average accuracy in the arousal dimension was 74.33% (±5.17%) and 75.49% (±5.70%) in the valence dimension, which were competitive performance compared to some previous machine-learning-based studies. Based on these results, we further discussed the neurophysiological relationship between specific microstates and emotions, which broaden our knowledge of the interpretability of EEG microstates. In particular, we found that arousal ratings were positively correlated with the activity of microstate C (anterior regions of default mode network) and negatively correlated with the activity of microstate D (dorsal attention network), while valence ratings were positively correlated with the activity of microstate B (visual network) and negatively correlated with the activity of microstate D (dorsal attention network).DiscussionIn summary, the findings in this paper indicate that the proposed KLGEV-criterion-based method can be employed to research emotional EEG signals effectively, and the microstate features are promising feature sets for EEG-based emotion recognition.</p

Data for: Dual process management of coal miners’ unsafe behaviour in the Chinese context: Evidence from a meta-analysis and inspired by the JD-R model

Data for: Dual process management of coal miners’ unsafe behaviour in the Chinese context: Evidence from a meta-analysis and inspired by the JD-R mode

Additional file 3 of scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

Additional file 3 Review history

Distribution of the d_N/<i>d_S</i> ratios of proteins containing polyQ tracts and regions flanking the tracts.

<p>The <i>d_N</i>/<i>d_S</i> ratios for more than 80% of the proteins containing polyQ tracts and more than 60% of the regions flanking the tracts are under 0.2.</p

Additional file 1 of scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

Additional file 1 Supplementary figures S1–S21 and table S1

Image_1_Revealing brain’s cognitive process deeply: a study of the consistent EEG patterns of audio-visual perceptual holistic.PDF

IntroductionTo investigate the brain’s cognitive process and perceptual holistic, we have developed a novel method that focuses on the informational attributes of stimuli.MethodsWe recorded EEG signals during visual and auditory perceptual cognition experiments and conducted ERP analyses to observe specific positive and negative components occurring after 400ms during both visual and auditory perceptual processes. These ERP components represent the brain’s perceptual holistic processing activities, which we have named Information-Related Potentials (IRPs). We combined IRPs with machine learning methods to decode cognitive processes in the brain.ResultsOur experimental results indicate that IRPs can better characterize information processing, particularly perceptual holism. Additionally, we conducted a brain network analysis and found that visual and auditory perceptual holistic processing share consistent neural pathways.DiscussionOur efforts not only demonstrate the specificity, significance, and reliability of IRPs but also reveal their great potential for future brain mechanism research and BCI applications.</p

The Top-10 performance of all algorithms on FilmTrust and Yelp.

The Top-10 performance of all algorithms on FilmTrust and Yelp.</p

Table_1_Body Mass Index and Long-Term Follow-Up Outcomes in Patients With Acute Myocardial Infarction by the Median of Non-HDL Cholesterol: Results From an Observational Cohort Study in China.DOCX

Background: The association between obesity, non-HDL cholesterol, and clinical outcomes in subjects with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI) is incompletely understood. The aim of this investigation was to explore the association between body mass index (BMI), non-high density lipoprotein (non-HDL) cholesterol, and long-term follow-up prognosis.Methods: This present study used data obtained by the Cardiovascular Center of Beijing Friendship Hospital Database Bank. We identified 3,780 consecutive AMI populations aged 25–93 years from 2013 to 2020. Participants were categorized as normal weight (18.5 ≤ BMI 2), overweight (23.0 ≤ BMI 2), obese class I (25.0 ≤ BMI 2), and obese class II (BMI ≥ 30.0 kg/m2). The endpoint of interest was cardiovascular (CV) death, all-cause death, myocardial infarction (MI), stroke, unplanned revascularization, and cardiac hospitalization.Results:Participants with higher BMI were younger and more likely to be males compared with lower BMI groups. Elevated non-HDL cholesterol was present in 8.7, 11.0, 24.3, and 5.9% of the normal, overweight, obese class I, and obese class II groups, respectively. After multivariate adjustment, compared to normal-weight participants with decreased non-HDL cholesterol (reference group), obese participants with and without elevated non-HDL cholesterol had a lower risk of mortality (with obese class I and elevated non-HDL cholesterol: hazard ratio [HR] 0.44, 95% confidence interval [CI] 0.28–0.67; with obese class I and decreased non-HDL cholesterol: HR, 0.68, 95% CI, 0.47–0.98; with obese class II and elevated non-HDL cholesterol: HR, 0.42, 95% CI, 0.20–0.87; with obese class II and decreased non-HDL cholesterol: HR, 0.35, 95% CI, 0.16–0.72).Conclusion: In AMI participants performing with PCI, obesity had a better long-term prognosis which probably unaffected by the level of non-HDL cholesterol.</p

Image_1_Prognostic Value of Global Longitudinal Strain in Asymptomatic Aortic Stenosis: A Systematic Review and Meta-Analysis.TIF

BackgroundsThe presence of impaired global longitudinal strain (GLS) may be a valuable bio-marker in the early diagnosis for left ventricle (LV) impairment, which would help scrutinize asymptomatic aortic stenosis (AS) patients with high risk of adverse outcomes, such as major adverse cardiovascular events (MACE).MethodsThe study was prospectively registered in PROPSERO (CRD 42021223472). Databases, such as Pubmed, Embase, Cochrane Library, Web of science, and Scopus were searched for studies evaluating the impact of impaired GLS on MACE, all-cause mortality, and aortic valve replacement (AVR) in asymptomatic AS. Hazard ratios (HRs) with 95% CIs were calculated with meta-analysis for binary variants. Meta-regression, subgroup analysis, and sensitivity analyses were applied as needed to explore the heterogeneity.ResultsEventually, a total of nine studies reporting 1,512 patients were enrolled. Compared with the normal GLS group, impaired GLS significantly increased MACE (HR = 1.20, 95% CI: 1.10–1.30, I2 = 79%) with evident heterogeneity, all-cause mortality (HR = 1.42, 95% CI: 1.24–1.63), and AVR (HR = 1.17, 95% CI: 1.07–1.28). Subgroup analyses stratified by left ventricular ejection fraction (LVEF) > 50% or LVEF without precise cut-off point found that compared with the normal GLS group, impaired GLS remarkably increased MACE both in two subgroups (LVEF > 50%: HR: 1.22, 95% CI: 1.05–1.50; LVEF without cutpoint: HR: 1.25, 95% CI: 1.05–1.50). The results stratified by AS severity (mild/moderate and severe) or follow-up time resembled those stratified by LVEF. In addition, when subgroup analysis was stratified by mean aortic valve pressure gradient (MG ≥ 40 mm Hg and MG ConclusionsThe presence of impaired GLS substantially worsens the outcomes for adverse cardiovascular events in asymptomatic patients with AS regardless of LVEF or AS severity or follow-up time or mean aortic valve pressure gradient, which highlights the importance of incorporating impaired GLS into risk algorithms in asymptomatic AS.Systematic Review RegistrationPROSPERO (registration number: CRD42021223472).</p