Effects of Personalized Aerobic-Exercise and Resistance-Training Prescriptions on College Students with Anxiety During the COVID-19

The COVID-19 pandemic has seriously increased anxiety prevalence among the public, including Chinese college students. However, many exercises cannot be performed as usual under the stay-at-home order. The purpose of this study was to evaluate and compare the effect of personalized individual aerobic-exercise and resistance-training prescriptions on anxiety in college students during the COVID-19. This was a 12-week three-arm randomized control trial using the intention-to-treat principle. Sixty-six college students with anxiety were recruited and randomized into aerobic-exercise (AE), resistance-training (RT), and health-education group (HE). AE and RT groups also received health education. Measures on anxiety and physical activity included Zung Self-Rating Anxiety Scale (SAS), Chinese College Students Mental Health Scale - Anxiety Subscale (CCSMHS-AS) and International Physical Activity Questionnaire-Short Form (IPAQ-SF). All data were collected at the baseline, 4, 8, 12 weeks and 4-week post-intervention. All participants completed the intervention and measurements. The mean (SD) of SAS, CCSMHS-AS score and physical activity was 56.36 (5.63), 19.27 (4.56), 1306.57 (1421.19) (met-min/week). After the intervention, 78.79% of anxiety participants improved from anxiety to “normal”. Participants in all groups showed a statistically and clinically significant improvement after 12-week intervention (p \u3c 0.001). Moreover, such improvement was well-maintained in RT and HE group as there were no significant differences in SAS and CCSMHS-AS at 4-week post-intervention compared to 12 weeks (p \u3e 0.05). However, the SAS score of participants in AE group showed a significant increase during the 4 weeks after intervention (p \u3c 0.05). No significant differences were observed in the effect of AE and RT on anxiety at each time-point (p \u3e 0.05). PA of participants in AE and RT group represented a significant improvement at 4-week post-intervention compared to baseline (p \u3c 0.01). Personalized individual aerobic-exercise and resistance-training combined with health-education resulted in a similar effect on reducing anxiety and improving physical activity, and the effect was better than health education alone. Furthermore, the effect of resistance-training and health-education on reducing anxiety was more stable than that of aerobic-exercise. We recommended 45- to 60-minute home-based individual exercise (including 30- to 40-minute main exercise) with progressive moderate-to-high intensity, 3 times/week for at least 12 weeks for those students with anxiety during the COVID-19 pandemic

Worldwide productivity and research trend of publications concerning electroactive materials and spinal cord injury: A bibliometric study

Purpose: We investigated the current state and trends in the area during the previous 10 years using bibliometric approaches to evaluate the global scientific output of research on electroactive materials and spinal cord injury.Methods: Studies on spinal cord injury in electroactive materials that were published between 2012 and 2022 were located using the Web of science (WOS) datebase. The software programs bibliometrix R-package and CiteSpace were used to do quantitative analyses of annual publications, nation, author, institution, journal source, co-cited references, and keywords. The studies were categorized by the research’s main points using a qualitative analysis, and publications having more than 10 citations each year.Results: In the final analysis, 1,330 relevant papers or reviews were included. There is an increased tendency in both the average annual citation rate and the number of publications in the discipline. The United States and the University of Toronto are the countries and institutions that have contributed the most to this discipline, respectively. The majority of authors are from the China and United States. Zhang Y is the author with the most published articles and holds the top position in the cited author h-index species. The journal with the highest number of published articles is “Disability and rehabilitation”; the journal is divided into four main areas including physics, materials, chemistry, molecular, and biology. The keyword analysis revealed a shift in research hotspots from schwann cell, fracture, and urinary disorders to carbon-based materials, functional recovery, and surgery. Analysis of qualitative data revealed that the role and mechanism of injectable conductive hydrogels in spinal cord healing after damage is a hot topic of current study, with the mechanism primarily focusing on the inhibition of oxidative stress (Nrf2) and apoptosis (Casepase 3).Conclusion: Our bibliometric analysis indicates that research on electroactive materials for spinal cord injury remains an active field of study. Moreover, contemporary research is concentrated on carbon-based materials, functional rehabilitation, and surgery

Effects of replication domains on genome-wide UV-induced DNA damage and repair

Nucleotide excision repair is the primary repair mechanism that removes UV-induced DNA lesions in placentals. Unrepaired UV-induced lesions could result in mutations during DNA replication. Although the mutagenesis of pyrimidine dimers is reasonably well understood, the direct effects of replication fork progression on nucleotide excision repair are yet to be clarified. Here, we applied Damage-seq and XR-seq techniques and generated replication maps in synchronized UV-treated HeLa cells. The results suggest that ongoing replication stimulates local repair in both early and late replication domains. Additionally, it was revealed that lesions on lagging strand templates are repaired slower in late replication domains, which is probably due to the imbalanced sequence context. Asymmetric relative repair is in line with the strand bias of melanoma mutations, suggesting a role of exogenous damage, repair, and replication in mutational strand asymmetry

Visualization of textual content from social media and online communities

In this thesis, I explore design principles for interactive visualizations that facilitate analysis of large quantities of text documents from social media and online communities. I summarize characteristics of such text documents, including their huge volume, short and informal expressions, high density of repeated language patterns, high noise-to-information ratio, and the prevalence of conflicting opinions. All of these characteristics pose challenges for analyzing the data, in addition to the difficulties of processing natural language. I focus on two domains of text, consumer reviews and social media posts, and show that analytical tasks in both domains share three common steps: 1) gaining an overall impression of the dataset by learning the major topics, 2) finding interesting facets of the dataset that are worth exploration, 3) reading the original documents to gain insights. I introduce two visualization systems that address these tasks for the two domains I study. OpinionBlocks presents a novel visualization interface for reading consumer reviews and enables crowd-correction of text analysis errors. SentenTree is a new visualization technique uniquely suited for social media text analysis by providing the key benefits of both word-based (a variation of word cloud) and sentence-based (as represented by Word Tree) visual metaphors while overcoming some of the limitations of each.Ph.D

Research on the Relationship between Data Empowerment and Service Innovation Capability of Logistics Platform Enterprise

Based on the application of big data, this paper constructed a theoretical model focusing on the mechanism of data empowerment on the service innovation capability of logistics platform enterprises, with value cocreation as the mediating variable and environmental dynamism as the moderating variable. The research hypothesis was empirically tested based on the results obtained from the questionnaire survey. The results demonstrate that data empowerment can promote the value co-creation between logistics platform enterprises and users, and value co-creation is an important factor to promote the service innovation capability of logistics platform enterprises. Meanwhile, the moderating variable of environmental dynamism is found to inhibit the interaction between cooperation and service innovation capability. The findings expand the theoretical research on data empowerment and raise important inspiration for practical activities of logistics platform enterprises

Efficacy and Safety of Eplerenone for Treating Chronic Kidney Disease: A Meta-Analysis

Background. In recent years, a large amount of clinical evidence and animal experiments have demonstrated the unique advantages of mineralocorticoid receptor antagonists (MRA) for treating chronic kidney disease (CKD). Aims. Accordingly, the present study aimed to systematically assess the second-generation selective MRAs eplerenone’s safety and effectiveness for treating CKD. Methods. Four databases (PubMed, The Cochrane Library, Embase, and Web of Science) were searched for randomized controlled trials (RCT) correlated with eplerenone for treating CKD up to September 21, 2022. By complying with the inclusion and exclusion criteria, literature screening, and data extraction were conducted. Results. A total of 19 randomized controlled articles involving 4501 cases were covered. As suggested from the meta-analysis, significant differences were reported with the 24-h urine protein (MD = −42.23, 95% confidence interval [CI] = -76.72 to −7.73, P = 0.02), urinary albumin-creatinine ratio (UACR) (MD = −23.57, 95% CI = −29.28 to −17.86, P < 0.00001), the systolic blood pressure (SBP) (MD = −2.73, 95% CI = −4.86 to −0.59, P = 0.01), and eGFR (MD = −1.56, 95% CI = −2.78 to −0.34, P = 0.01) in the subgroup of eplerenone vs placebo. The subgroups of eplerenone vs placebo (MD = 0.13, 95% CI = 0.07 to 0.18, P < 0.00001) and eplerenone vs thiazide diuretic (MD = 0.18, 95% CI = 0.13 to 0.23, P < 0.00001) showed the significantly increased potassium levels. However, no statistical significance was reported between the eplerenone treatment groups and the control in the effect exerted by serum creatinine (MD=0.03, 95% CI = −0.01 to 0.07, P = 0.12) and diastolic blood pressure (DBP) (MD = 0.11, 95% CI = −0.41 to 0.63, P = 0.68). Furthermore, significant risks of hyperkalemia were reported in the eplerenone group (K+ ≥ 5.5 mmol/l, RR = 1.70, 95%CI = 1.35 to 2.13, P =< 0.00001; K+ ≥ 6.0 mmol/l, RR = 1.61, 95% CIs = 1.06 to 2.44, P = 0.02), respectively. Conclusions. Eplerenone has beneficial effects on CKD by reducing urinary protein and the systolic blood pressure, but it also elevates the risk of hyperkalemia

Predicting mortality of patients with acute kidney injury in the ICU using XGBoost model.

PurposeThe goal of this study is to construct a mortality prediction model using the XGBoot (eXtreme Gradient Boosting) decision tree model for AKI (acute kidney injury) patients in the ICU (intensive care unit), and to compare its performance with that of three other machine learning models.MethodsWe used the eICU Collaborative Research Database (eICU-CRD) for model development and performance comparison. The prediction performance of the XGBoot model was compared with the other three machine learning models. These models included LR (logistic regression), SVM (support vector machines), and RF (random forest). In the model comparison, the AUROC (area under receiver operating curve), accuracy, precision, recall, and F1 score were used to evaluate the predictive performance of each model.ResultsA total of 7548 AKI patients were analyzed in this study. The overall in-hospital mortality of AKI patients was 16.35%. The best performing algorithm in this study was XGBoost with the highest AUROC (0.796, p ConclusionXGBoot model had obvious advantages of performance compared to the other machine learning models. This will be helpful for risk identification and early intervention for AKI patients at risk of death