Optimization of train formation plan based on technical station under railcar demand fluctuation

Train formation planning (TFP) is essential for rail freight logistics services. The fluctuation of railcar flows dramatically compared with before the outbreak of COVID-19. This paper studies train formation planning, considering three types of train services provided for railcar flow between pairs of technical stations (TS), including direct trains, district trains, and pickup trains. This paper introduces an optimization model with average railcars flow data (OMAD) and an optimization model with dynamic railcars flow data (OMDD) for the train formation planning based on TS under railcar demand fluctuation while minimizing railcar-hour consumption. The OMAD is a deterministic model, and the OMDD is a probability constraint model. To solve the OMDD, an approach for transforming probability constraints into deterministic constraints is presented. Various groups of scenarios are given to verify the effectiveness of the proposed models. [ FROM AUTHOR] Copyright of Journal of Industrial & Production Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Proteomic profiling of single extracellular vesicles reveals colocalization of SARS-CoV-2 with a CD81/integrin-rich EV subpopulation in sputum from COVID-19 severe patients.

Background: The global outbreak of COVID-19, and the limited availability of clinical treatments, forced researchers around the world to search for the pathogenesis and potential treatments. Understanding the pathogenesis of SARS-CoV-2 is crucial to respond better to the current coronavirus disease 2019 (COVID-19) pandemic. Methods: We collected sputum samples from 20 COVID-19 patients and healthy controls. Transmission electron microscopy was used to observe the morphology of SARS-CoV-2. Extracellular vesicles (EVs) were isolated from sputum and the supernatant of VeroE6 cells, and were characterized by transmission electron microscopy, nanoparticle tracking analysis and Western-Blotting. Furthermore, a proximity barcoding assay was used to investigate immune-related proteins in single EV, and the relationship between EVs and SARS-CoV-2. Result: Transmission electron microscopy images of SARS-COV-2 virus reveal EV-like vesicles around the virion, and western blot analysis of EVs extracted from the supernatant of SARS-COV-2-infected VeroE6 cells showed that they expressed SARS-COV-2 protein. These EVs have the infectivity of SARS-COV-2, and the addition can cause the infection and damage of normal VeroE6 cells. In addition, EVs derived from the sputum of patients infected with SARS-COV-2 expressed high levels of IL6 and TGF-ß, which correlated strongly with expression of the SARS-CoV-2 N protein. Among 40 EV subpopulations identified, 18 differed significantly between patients and controls. The EV subpopulation regulated by CD81 was the most likely to correlate with changes in the pulmonary microenvironment after SARS-CoV-2 infection. Single extracellular vesicles in the sputum of COVID-19 patients harbor infection-mediated alterations in host and virus-derived proteins. Conclusions: These results demonstrate that EVs derived from the sputum of patients participate in virus infection and immune responses. This study provides evidence of an association between EVs and SARS-CoV-2, providing insight into the possible pathogenesis of SARS-CoV-2 infection and the possibility of developing nanoparticle-based antiviral drugs.

Heparan sulfate promotes ACE2 super-cluster assembly to enhance SARS-CoV-2-associated syncytium formation.

The mechanism of syncytium formation, caused by spike-induced cell-cell fusion in severe COVID-19, is largely unclear. Here we combine chemical genetics with 4D confocal imaging to establish the cell surface heparan sulfate (HS) as a critical host factor exploited by SARS-CoV-2 to enhance spike’s fusogenic activity. HS binds spike to facilitate ACE2 clustering, generating synapse-like cell-cell contacts to promote fusion pore formation. ACE2 clustering, and thus, syncytium formation is significantly mitigated by chemical or genetic elimination of cell surface HS, while in a cell-free system consisting of purified HS, spike, and lipid-anchored ACE2, HS directly induces ACE2 clustering. Importantly, the interaction of HS with spike allosterically enables a conserved ACE2 linker in receptor clustering, which concentrates spike at the fusion site to overcome fusion-associated activity loss. This fusion-boosting mechanism can be effectively targeted by an investigational HS-binding drug, which reduces syncytium formation in vitro and viral infection in mice.

Stability of SARS-CoV-2 in cold-chain transportation environments and the efficacy of disinfection measures.

Background: Low temperature is conducive to the survival of COVID-19. Some studies suggest that cold-chain environment may prolong the survival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increase the risk of transmission. However, the effect of cold-chain environmental factors and packaging materials on SARS-CoV-2 stability remains unclear. Methods: This study aimed to reveal cold-chain environmental factors that preserve the stability of SARS-CoV-2 and further explore effective disinfection measures for SARS-CoV-2 in the cold-chain environment. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, on various types of packaging material surfaces, i.e., polyethylene plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of visible light (wavelength 450 nm-780 nm) and airflow on the stability of SARS-CoV-2 pseudovirus at -18°C was subsequently assessed. Results: Experimental data show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surfaces than on nonporous surfaces, including polyethylene (PE) plastic, stainless steel, and Teflon. Compared with that at 25°C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperatures. Seawater preserved viral stability both at -18°C and with repeated freeze-thaw cycles compared with that in deionized water. Visible light from light-emitting diode (LED) illumination and airflow at -18°C reduced SARS-CoV-2 pseudovirus stability. Conclusion: Our studies indicate that temperature and seawater in the cold chain are risk factors for SARS-CoV-2 transmission, and LED visible light irradiation and increased airflow may be used as disinfection measures for SARS-CoV-2 in the cold-chain environment.

A dynamic model for elevator operation-induced spread of a respiratory infectious disease in an apartment building.

Residents have to use elevators to leave and enter their high-rise apartments frequently. An elevator car can easily spread respiratory infectious diseases, as it has a confined and small space. Therefore, studying how elevator operations promote epidemic transmission is of importance to public health. We developed an infectious disease dynamics model. First, we used homemade codes to simulate the operating state of an elevator and the dynamic process of infectious disease transmission in an apartment building due to elevator operations. Second, we analysed the temporal distribution patterns of infected individuals and patients. Finally, we validated the reliability of the model by performing continuous-time sensitivity analysis on important model parameters. We found that elevator operations can cause rapid spread of infectious diseases within an apartment building. Therefore, it is necessary to enhance elevator ventilation and disinfection mechanisms to prevent the outbreak of respiratory infections. Moreover, residents should reduce elevator use and wear masks.

Microbial and human transcriptional profiling of coronavirus disease 2019 patients: Potential predictors of disease severity.

The high morbidity of patients with coronavirus disease 2019 (COVID-19) brings on a panic around the world. COVID-19 is associated with sex bias, immune system, and preexisting chronic diseases. We analyzed the gene expression in patients with COVID-19 and in their microbiota in order to identify potential biomarkers to aid in disease management. A total of 129 RNA samples from nasopharyngeal, oropharyngeal, and anal swabs were collected and sequenced in a high-throughput manner. Several microbial strains differed in abundance between patients with mild or severe COVID-19. Microbial genera were more abundant in oropharyngeal swabs than in nasopharyngeal or anal swabs. Oropharyngeal swabs allowed more sensitive detection of the causative SARS-CoV-2. Microbial and human transcriptomes in swabs from patients with mild disease showed enrichment of genes involved in amino acid metabolism, or protein modification via small protein removal, and antibacterial defense responses, respectively, whereas swabs from patients with severe disease showed enrichment of genes involved in drug metabolism, or negative regulation of apoptosis execution, spermatogenesis, and immune system, respectively. Microbial abundance and diversity did not differ significantly between males and females. The expression of several host genes on the X chromosome correlated negatively with disease severity. In this way, our analyses identify host genes whose differential expression could aid in the diagnosis of COVID-19 and prediction of its severity via non-invasive assay.

The primary care COVID-19 integrated pathway: a rapid response to health and social impacts of COVID-19.

BACKGROUND: The first wave of COVID-19 in Calgary, Alberta accelerated the integration of primary care with the province's centrally managed health system. This integration aimed to deliver wraparound in-community patient care through two interventions that combined to create the COVID-19 Integrated Pathway (CIP). The CIP's interventions were: 1) a data sharing platform that ensured COVID-19 test results were directly available to family physicians (FPs), and 2) a clinical algorithm that supported FPs in delivering in-community follow up to improve patient outcomes. We describe the CIP function and its capacity to facilitate FP follow-up with COVID-19 patients and evaluate its impact on Emergency Department (ED) visits and hospitalization. METHOD: We generated descriptive statistics by analyzing data from a Calgary Zone hub clinic called the Calgary COVID-19 Care Clinic (C4), provincially maintained records of hospitalization, ED visits, and physician claims. RESULTS: Between Apr. 16 and Sep. 27, 2020, 7289 patients were referred by the Calgary Public Health team to the C4 clinic. Of those, 48.6% were female, the median age was 37.4 y. 97% of patients had at least one visit with a healthcare professional, where follow-up was conducted using the CIP's algorithm. 5.1% of patients visited an ED and 1.9% were hospitalized within 30 days of diagnosis. 75% of patients had a median of 4 visits with their FP. DISCUSSION: Our data suggest that information exchange between Primary Care (PC) and central systems facilitates primary care-based management of patients with COVID-19 in the community and has potential to reduce acute care visits.

Radiomics-Based Detection of COVID-19 from Chest X-ray Using Interpretable Soft Label-Driven TSK Fuzzy Classifier.

The COVID-19 pandemic has posed a significant global public health threat with an escalating number of new cases and death toll daily. The early detection of COVID-related CXR abnormality potentially allows the early isolation of suspected cases. Chest X-Ray (CXR) is a fast and highly accessible imaging modality. Recently, a number of CXR-based AI models have been developed for the automated detection of COVID-19. However, most existing models are difficult to interpret due to the use of incomprehensible deep features in their models. Confronted with this, we developed an interpretable TSK fuzzy system in this study for COVID-19 detection using radiomics features extracted from CXR images. There are two main contributions. (1) When TSK fuzzy systems are applied to classification tasks, the commonly used binary label matrix of training samples is transformed into a soft one in order to learn a more discriminant transformation matrix and hence improve classification accuracy. (2) Based on the assumption that the samples in the same class should be kept as close as possible when they are transformed into the label space, the compactness class graph is introduced to avoid overfitting caused by label matrix relaxation. Our proposed model for a multi-categorical classification task (COVID-19 vs. No-Findings vs. Pneumonia) was evaluated using 600 CXR images from publicly available datasets and compared against five state-of-the-art AI models in aspects of classification accuracy. Experimental findings showed that our model achieved classification accuracy of over 83%, which is better than the state-of-the-art models, while maintaining high interpretability.

Fully Automatic Dual-probe Lung Ultrasound Scanning Robot for Screening Triage.

Two-dimensional lung ultrasound (LUS) has widely emerged as a rapid and non-invasive imaging tool for the detection and diagnosis of coronavirus disease 2019 (COVID-19). However, image differences will be magnified due to changes in ultrasound imaging experience, such as ultrasound probe attitude control and force control, which will directly affect the diagnosis results. In addition, the risk of virus transmission between sonographer and patients is increased due to frequent physical contact. In this study, a fully automatic dual-probe ultrasound scanning robot for the acquisition of lung ultrasound images is proposed and developd. Furthermore, the trajectory was optimized based on the velocity look-ahead strategy, the stability of contact force of the system and the scanning efficiency were improved by 24.13% and 29.46%, respectively. And the control ability of the contact force of robotic automatic scanning was 34.14 times higher than that of traditional manual scanning, which significantly improves the smoothness of scanning. Importantly, there was no significant difference in image quality obtained by robotic automatic scanning and manual scanning. Furthermore, the scanning time for a single person is less than 4 minutes, which greatly improves the efficiency of screening triage of group COVID-19 diagnosis and suspected patients, and reduces the risk of virus exposure and spread.

Microbial and human transcriptional profiling of coronavirus disease 2019 patients: Potential predictors of disease severity

The high morbidity of patients with coronavirus disease 2019 (COVID-19) brings on a panic around the world. COVID-19 is associated with sex bias, immune system, and preexisting chronic diseases. We analyzed the gene expression in patients with COVID-19 and in their microbiota in order to identify potential biomarkers to aid in disease management. A total of 129 RNA samples from nasopharyngeal, oropharyngeal, and anal swabs were collected and sequenced in a high-throughput manner. Several microbial strains differed in abundance between patients with mild or severe COVID-19. Microbial genera were more abundant in oropharyngeal swabs than in nasopharyngeal or anal swabs. Oropharyngeal swabs allowed more sensitive detection of the causative SARS-CoV-2. Microbial and human transcriptomes in swabs from patients with mild disease showed enrichment of genes involved in amino acid metabolism, or protein modification via small protein removal, and antibacterial defense responses, respectively, whereas swabs from patients with severe disease showed enrichment of genes involved in drug metabolism, or negative regulation of apoptosis execution, spermatogenesis, and immune system, respectively. Microbial abundance and diversity did not differ significantly between males and females. The expression of several host genes on the X chromosome correlated negatively with disease severity. In this way, our analyses identify host genes whose differential expression could aid in the diagnosis of COVID-19 and prediction of its severity via non-invasive assay.

Study of the Water Environment Risk Assessment of the Upper Reaches of the Baiyangdian Lake, China

The risk assessment of water environments provides important references for water environment risk management. In this paper, the water environment risk of the upper rivers of the Baiyangdian Lake is assessed, considering both cumulative and sudden environmental risk. For the cumulative environmental risk assessment of the rivers, the characteristics of pollution transmissibility and accumulation in rivers was considered firstly. Furthermore, suggestions for the control of water environment pollution in the Baiyangdian Basin are given. The results indicate that the cumulative water environment risks of the Xiaoyi River—Dingzhou County, Xiaoyi River—Anguo County, Xiaoyi River—Boye County, and Xiaoyi River—Li County are high. The amount of fertilizer applied per unit of cultivated area, water quality, rate of water quality above the standard in water function zoning, and the ratio of environmental investment to gross domestic product (GDP) are important factors influencing the cumulative water environment risk. For sudden water environment assessments, the Xiaoyi River—Boye County is high. In the future, reducing the intensity of fertilizer application, strengthening the water quality control of the rivers, as well as upgrading the industry, should be carried out to protect the water environment in the Baiyangdian Basin.

On-chip integrated graphene aptasensor with portable readout for fast and label-free COVID-19 detection in virus transport medium.

Graphene field-effect transistor (GFET) biosensors exhibit high sensitivity due to a large surface-to-volume ratio and the high sensitivity of the Fermi level to the presence of charged biomolecules near the surface. For most reported GFET biosensors, bulky external reference electrodes are used which prevent their full-scale chip integration and contribute to higher costs per test. In this study, GFET arrays with on-chip integrated liquid electrodes were employed for COVID-19 detection and functionalized with either antibody or aptamer to selectively bind the spike proteins of SARS-CoV-2. In the case of the aptamer-functionalized GFET (aptasensor, Apt-GFET), the limit-of-detection (LOD) achieved was about 103 particles per mL for virus-like particles (VLPs) in clinical transport medium, outperforming the Ab-GFET biosensor counterpart. In addition, the aptasensor achieved a LOD of 160 aM for COVID-19 neutralizing antibodies in serum. The sensors were found to be highly selective, fast (sample-to-result within minutes), and stable (low device-to-device signal variation; relative standard deviations below 0.5%). A home-built portable readout electronic unit was employed for simultaneous real-time measurements of 12 GFETs per chip. Our successful demonstration of a portable GFET biosensing platform has high potential for infectious disease detection and other health-care applications.

On-chip integrated graphene aptasensor with portable readout for fast and label-free COVID-19 detection in virus transport medium† † Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2sd00076h

Graphene field-effect transistor (GFET) biosensors exhibit high sensitivity due to a large surface-to-volume ratio and the high sensitivity of the Fermi level to the presence of charged biomolecules near the surface. For most reported GFET biosensors, bulky external reference electrodes are used which prevent their full-scale chip integration and contribute to higher costs per test. In this study, GFET arrays with on-chip integrated liquid electrodes were employed for COVID-19 detection and functionalized with either antibody or aptamer to selectively bind the spike proteins of SARS-CoV-2. In the case of the aptamer-functionalized GFET (aptasensor, Apt-GFET), the limit-of-detection (LOD) achieved was about 103 particles per mL for virus-like particles (VLPs) in clinical transport medium, outperforming the Ab-GFET biosensor counterpart. In addition, the aptasensor achieved a LOD of 160 aM for COVID-19 neutralizing antibodies in serum. The sensors were found to be highly selective, fast (sample-to-result within minutes), and stable (low device-to-device signal variation;relative standard deviations below 0.5%). A home-built portable readout electronic unit was employed for simultaneous real-time measurements of 12 GFETs per chip. Our successful demonstration of a portable GFET biosensing platform has high potential for infectious disease detection and other health-care applications. On-chip integrated graphene field-effect transistor (GFET)-based aptasensor was developed with portable readouts for sensitive and specific virus detection.

International Trade of Masks and COVID-19 Pandemic Containment.

This study analyzes the impact of the exports of China's masks and other antivirus supplies on the people from the importing countries who are subject to the severe pandemic during the coronavirus disease 2019 (COVID-19) pandemic. Our main data include the COVID-19 cases data of countries around the world published by Johns Hopkins University and the data of China's exports of masks or other antivirus supplies to these countries from the Chinese Customs Database. Using cross-sectional data of about 180 countries and multiple regression analysis, we find that the antivirus supplies from China have played an important role in combating the COVID-19 pandemic. Specifically, China's masks are shipped to countries around the world, and these masks can improve the recovery rate and protect people against the COVID-19 pandemic. Our findings are relevant to global efforts in the COVID-19 pandemic containment.

Quantitative methods and modeling to assess COVID-19-interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches.

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a "batch" effect to the mixed effects model may be used when a significant "batch" effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.

Risk Factors for Death Among the First 80 543 Coronavirus Disease 2019 (COVID-19) Cases in China: Relationships Between Age, Underlying Disease, Case Severity, and Region.

BACKGROUND: Knowledge of COVID-19 epidemiology remains incomplete and crucial questions persist. We aimed to examine risk factors for COVID-19 death. METHODS: A total of 80 543 COVID-19 cases reported in China, nationwide, through 8 April 2020 were included. Risk factors for death were investigated by Cox proportional hazards regression and stratified analyses. RESULTS: Overall national case-fatality ratio (CFR) was 5.64%. Risk factors for death were older age (≥80: adjusted hazard ratio, 12.58; 95% confidence interval, 6.78-23.33), presence of underlying disease (1.33; 1.19-1.49), worse case severity (severe: 3.86; 3.15-4.73; critical: 11.34; 9.22-13.95), and near-epicenter region (Hubei: 2.64; 2.11-3.30; Wuhan: 6.35; 5.04-8.00). CFR increased from 0.35% (30-39 years) to 18.21% (≥70 years) without underlying disease. Regardless of age, CFR increased from 2.50% for no underlying disease to 7.72% for 1, 13.99% for 2, and 21.99% for ≥3 underlying diseases. CFR increased with worse case severity from 2.80% (mild) to 12.51% (severe) and 48.60% (critical), regardless of region. Compared with other regions, CFR was much higher in Wuhan regardless of case severity (mild: 3.83% vs 0.14% in Hubei and 0.03% elsewhere; moderate: 4.60% vs 0.21% and 0.06%; severe: 15.92% vs 5.84% and 1.86%; and critical: 58.57% vs 49.80% and 18.39%). CONCLUSIONS: Older patients regardless of underlying disease and patients with underlying disease regardless of age were at elevated risk of death. Higher death rates near the outbreak epicenter and during the surge of cases reflect the deleterious effects of allowing health systems to become overwhelmed.

Environmental risks of disposable face masks during the pandemic of COVID-19: Challenges and management.

Since the COVID-19 outbreak in early 2020, face mask (FM) has been recognized as an effective measure to reduce the infection, increasing its consumption across the world. However, the large amount of at-home FM usage changed traditional medical waste management practices, lack of improper management. Currently, few studies estimate FM consumption at a global scale, not to say a comprehensive investigation on the environmental risks of FM from a life cycle perspective. Therefore, global FM consumption and its associated environmental risks are clarified in the present study. Our result shows that 449.5 billion FMs were consumed from January 2020 to March 2021, with an average of 59.4 FMs per person worldwide. This review also provides a basis to understand the environmental risk of randomly disposed of FM and highlights the urgent requirement for the attention of FMs waste management to prevent pollution in the near future.

Correlation of Sexual Behavior Change, Family Function, and Male-Female Intimacy Among Adults Aged 18-44 Years During COVID-19 Epidemic.

INTRODUCTION: Coronavirus disease (COVID-19) has been declared a global pandemic. In this unprecedented situation, the intimate relationship, sexual behavior, and family functions of partners have also undergone unique changes. There are few reports on whether sexual behavior and family function affect intimate relationships between partners, especially among people aged 18 to 44 years. AIM: To analyze the influence of sociodemographic characteristics, family function, and changes in sexual behavior on male-female intimacy, the independent contributions of the aforementioned factors in this population group are required to be further investigated. METHODS: In the present study, 284 Chinese citizens aged 18-44 years completed the online questionnaire. The univariate analysis and cluster multiple linear regression were used to analyze the associations between sociodemographic factors, sexual-behavior changes, family function, and male-female intimacy. MAIN OUTCOME MEASURE: Family adaptation, partnership, growth, affection, resolve (APGAR) Scale and Relationship Assessment Scale were used to evaluate participants' family function and their intimacy. Details of the participants (sociodemographic and sexual factors) were obtained. RESULTS: The summary scores, with Relationship Assessment Scale and APGAR scales, were 27.19 ± 4.49 and 6.76 ± 2.28, respectively. About 43.3% of participants reported a decrease in sexual frequency. There were considerable differences among age, education level, sexual desire, sexual satisfaction, quality of sexual life, family function with male-female intimacy (P < .05). The sexual satisfaction and intimacy demonstrated a significant positive correlation (P < .05) by cluster multiple linear regression analysis. Compared with those who had a sexual life of mediocre quality, respondents who experienced a good quality sexual life had relatively higher scores in intimacy. The independent contributions of sociodemographic factors, sexual behavior factors, and family function in male-female intimacy were 13.0%, 38.2%, and 48.8%, respectively. CONCLUSIONS: Sexual behavior factors and family function were important independent determinants of partner intimacy among people aged 18-44 years. It can provide supportive information for health care to develop intervention plans and services to promote the harmonious development of intimate relationship. Feng Y-J, Fan Y-J, Su Z-Z, et al. Correlation of Sexual Behavior Change, Family Function, and Male-Female Intimacy Among Adults Aged 18-44 Years During COVID-19 Epidemic. Sex Med 2021;9:100301.

Quality of and Recommendations for Relevant Clinical Practice Guidelines for COVID-19 Management: A Systematic Review and Critical Appraisal.

Background: The morbidity and mortality of coronavirus disease 2019 (COVID-19) are still increasing. This study aimed to assess the quality of relevant COVID-19 clinical practice guidelines (CPGs) and to compare the similarities and differences between recommendations. Methods: A comprehensive search was conducted using electronic databases (PubMed, Embase, and Web of Science) and representative guidelines repositories from December 1, 2019, to August 11, 2020 (updated to April 5, 2021), to obtain eligible CPGs. The Appraisal of Guidelines for Research and Evaluation (AGREE II) tool was used to evaluate the quality of CPGs. Four authors extracted relevant information and completed data extraction forms. All data were analyzed using R version 3.6.0 software. Results: In total, 39 CPGs were identified and the quality was not encouragingly high. The median score (interquartile range, IQR) of every domain from AGREE II for evidence-based CPGs (EB-CPGs) versus (vs.) consensus-based CPG (CB-CPGs) was 81.94% (75.00-84.72) vs. 58.33% (52.78-68.06) in scope and purpose, 59.72% (38.89-75.00) vs. 36.11% (33.33-36.11) in stakeholder involvement, 64.58% (32.29-71.88) vs. 22.92% (16.67-26.56) in rigor of development, 75.00% (52.78-86.81) vs. 52.78% (50.00-63.89) in clarity of presentation, 40.63% (22.40-62.50) vs. 20.83% (13.54-25.00) in applicability, and 58.33% (50.00-100.00) vs. 50.00% (50.00-77.08) in editorial independence, respectively. The methodological quality of EB-CPGs were significantly superior to the CB-CPGs in the majority of domains (P < 0.05). There was no agreement on diagnosis criteria of COVID-19. But a few guidelines show Remdesivir may be beneficial for the patients, hydroxychloroquine +/- azithromycin may not, and there were more consistent suggestions regarding discharge management. For instance, after discharge, isolation management and health status monitoring may be continued. Conclusions: In general, the methodological quality of EB-CPGs is greater than CB-CPGs. However, it is still required to be further improved. Besides, the consistency of COVID-19 recommendations on topics such as diagnosis criteria is different. Of them, hydroxychloroquine +/- azithromycin may be not beneficial to treat patients with COVID-19, but remdesivir may be a favorable risk-benefit in severe COVID-19 infection; isolation management and health status monitoring after discharge may be still necessary. Chemoprophylaxis, including SARS-CoV 2 vaccines and antiviral drugs of COVID-19, still require more trials to confirm this.

The Impact of Intolerance of Uncertainty on Test Anxiety: Student Athletes During the COVID-19 Pandemic.

Test anxiety caused by intolerance of uncertainty has a negative impact on the physical and mental health of student athletes, especially in the context of the coronavirus disease 2019 (COVID-19) pandemic. A total of 556 grade three high school student athletes in Chongqing, China, were investigated using the Test Anxiety Scale (TAS), Intolerance of Uncertainty Scale-12 (IUS-12), Perceived Social Support Scale, and Coping Style Scale for Middle School Students. Results reveal that more than half the student athletes experienced test anxiety, and the severity was above average during the COVID-19 pandemic. There was a significant correlation between intolerance of uncertainty, perceived social support, coping style, and test anxiety. A positive correlation was found between test anxiety, intolerance of uncertainty, and coping style toward emotions, and a negative correlation between test anxiety, perceived social support, and coping style toward problems. Intolerance of uncertainty has a direct predictive effect on test anxiety, and perceived social support and coping style play a chain mediator role between intolerance of uncertainty and test anxiety. By constructing the mediating effect model, we can, to some extent, reveal the mechanism of the influence of intolerance of uncertainty on test anxiety. This study has a certain reference value for the prevention of test anxiety in student athletes in the context of the COVID-19 pandemic.