Aspirin is associated with lower risks of severe covid-19 disease: a population-based study

IntroductionThe use of aspirin has been hypothesized to improve severe clinical outcomes in COVID-19 infection. The present study aims to evaluate the effect of both antecedent and inpatient aspirin use, individually and concomitant with other medications, on severe disease outcomes in COVID-19 positive patients treated with steroids/antiviral therapy.MethodsConsecutive patients who attended Hong Kong's public hospitals or outpatient clinics between 1st January and 8th December 2020 for COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) and received steroids/antiviral therapy were included. Propensity score matching (1:1) between aspirin users and non-users was performed. The primary endpoint was the composite outcome of the need for intubation and 30-day all-cause mortality.ResultsA total of 2664 RT-PCR positive and hospitalized COVID-19 patients receiving steroids/antiviral therapy were included (male= 50.7%, baseline age= 52.3 [35.2-64.6] years old). Over follow-up, 2.96% suffered from 30-day all-cause mortality. Univariable logistic regression showed that aspirin use was associated with lower odds of severe COVID-19 in the propensity score-matched cohort (odds ratio [OR]: 0.33, 95% confidence interval [CI]: [0.18, 0.6];P=0.0003). This association remained significant following adjustment for significant confounders (OR= 0.33, 95% CI= [0.18, 0.59], P= 0002).ConclusionAspirin use was associated with lower odds of severe outcomes in COVID-19.Conflict of InterestNone

Ensemble learning-based feature selection for phosphorylation site detection.

SARS-COV-2 is prevalent all over the world, causing more than six million deaths and seriously affecting human health. At present, there is no specific drug against SARS-COV-2. Protein phosphorylation is an important way to understand the mechanism of SARS -COV-2 infection. It is often expensive and time-consuming to identify phosphorylation sites with specific modified residues through experiments. A method that uses machine learning to make predictions about them is proposed. As all the methods of extracting protein sequence features are knowledge-driven, these features may not be effective for detecting phosphorylation sites without a complete understanding of the mechanism of protein. Moreover, redundant features also have a great impact on the fitting degree of the model. To solve these problems, we propose a feature selection method based on ensemble learning, which firstly extracts protein sequence features based on knowledge, then quantifies the importance score of each feature based on data, and finally uses the subset of important features as the final features to predict phosphorylation sites.

A New Role for Old Friends: Effects of Helminth Infections on Vaccine Efficacy.

Vaccines are one of the most successful medical inventions to enable the eradication or control of common and fatal diseases. Environmental exposure of hosts, including helminth infections, plays an important role in immune responses to vaccines. Given that helminth infections are among the most common infectious diseases in the world, evaluating vaccine efficiency in helminth-infected populations may provide critical information for selecting optimal vaccination programs. Here, we reviewed the effects of helminth infections on vaccination and its underlying immunological mechanisms, based on findings from human studies and animal models. Moreover, the potential influence of helminth infections on SARS-CoV-2 vaccine was also discussed. Based on these findings, there is an urgent need for anthelmintic treatments to eliminate helminth suppressive impacts on vaccination effectiveness during implementing mass vaccination in parasite endemic areas.

Impact of waste of COVID-19 protective equipment on the environment, animals and human health: a review.

During the Corona Virus Disease 2019 (COVID-19) pandemic, protective equipment, such as masks, gloves and shields, has become mandatory to prevent person-to-person transmission of coronavirus. However, the excessive use and abandoned protective equipment is aggravating the world's growing plastic problem. Moreover, above protective equipment can eventually break down into microplastics and enter the environment. Here we review the threat of protective equipment associated plastic and microplastic wastes to environments, animals and human health, and reveal the protective equipment associated microplastic cycle. The major points are the following:1) COVID-19 protective equipment is the emerging source of plastic and microplastic wastes in the environment. 2) protective equipment associated plastic and microplastic wastes are polluting aquatic, terrestrial, and atmospheric environments. 3) Discarded protective equipment can harm animals by entrapment, entanglement and ingestion, and derived microplastics can also cause adverse implications on animals and human health. 4) We also provide several recommendations and future research priority for the sustainable environment. Therefore, much importance should be attached to potential protective equipment associated plastic and microplastic pollution to protect the environment, animals and humans.

The Double-Edged Sword of Safety Training for Safety Behavior: The Critical Role of Psychological Factors during COVID-19.

Safety training (ST) is the primary means of avoiding unsafe behaviors, but it has not achieved the expected impact on improving workplace safety because of the high psychological stress it brings to workers. The coronavirus disease 2019 (COVID-19) further threatens workers' psychological conditions, thereby diminishing the effectiveness of ST. However, the existing literature has mainly laid emphasis on the bright side of ST and neglected examining its impact on safety behavior (SB) from detrimental psychological factors. Drawing from the conservation of resources theory, a novel two-staged model was established to understand how these psychological factors mediate and moderate the association between ST and SB. We incorporated resource consumption (e.g., role overload (RO) and COVID-19-related task setbacks) and resource generation (e.g., psychological resilience) into the model to consider both detrimental and protective psychological factors against ST. We then implemented a time-separated, three-wave data collection on a sample of frontline workers to validate this hypothetical model. Consistent with our hypothesis, RO played a significant mediating role between ST and SB, that is, ST leads to RO, and in turn, holds up SB. Surprisingly, contrary to our hypothesis, COVID-19-related task setbacks weakened the negative and indirect impact of ST on SB via RO. This is one of the first empirical studies to highlight how detrimental psychological factors caused by ST constrict or amplify SB. In practice, the efficacy of ST can be enhanced by cultivating psychological resilience and clarifying employees' job responsibilities to reduce the ambiguity of roles.

Forecasting Crude Oil Future Volatilities with a Threshold Zero-Drift GARCH Model

The recent price crash of the New York Mercantile Exchange (NYMEX) crude oil futures contract, which occurred on 20 April 2020, has caused history-writing movements of relative prices. For instance, the West Texas Intermediate (WTI) experienced a negative price. Explosive heteroskedasticity is also evidenced in associated products, such as the Intercontinental Exchange Brent (BRE) and Shanghai International Energy Exchange (INE) crude oil futures. Those movements indicate potential non-stationarity in the conditional volatility with an asymmetric influence of negative shocks. To incorporate those features, which cannot be accommodated by the existing generalized autoregressive conditional heteroskedasticity (GARCH) models, we propose a threshold zero-drift GARCH (TZD-GARCH) model. Our empirical studies of the daily INE returns from March 2018 to April 2020 demonstrate the usefulness of the TZD-GARCH model in understanding the empirical features and in precisely forecasting the volatility of INE. Robust checks based on BRE and WTI over various periods further lead to highly consistent results. Applications of news impact curves and Value-at-Risk (VaR) analyses indicate the usefulness of the proposed TZD-GARCH model in practice. Implications include more effectively hedging risks of crude oil futures for policymakers and market participants, as well as the potential market inefficiency of INE relative to WTI and BRE.

COVID-19 vaccination and carditis in children and adolescents: a systematic review and meta-analysis.

BACKGROUND: Coronavirus Disease-2019 (COVID-19) vaccination has been associated with the development of carditis, especially in children and adolescent males. However, the rates of these events in the global setting have not been explored in a systematic manner. The aim of this systematic review and meta-analysis is to investigate the rates of carditis in children and adolescents receiving COVID-19 vaccines. METHODS: PubMed, Embase and several Latin American databases were searched for studies. The number of events, and where available, at-risk populations were extracted. Rate ratios were calculated and expressed as a rate per million doses received. Subgroup analysis based on the dose administered was performed. Subjects ≤ 19 years old who developed pericarditis or myocarditis following COVID-19 vaccination were included. RESULTS: A total of 369 entries were retrieved. After screening, 39 articles were included. Our meta-analysis found that 343 patients developed carditis after the administration of 12,602,625 COVID-19 vaccination doses (pooled rate per million: 37.76; 95% confidence interval [CI] 23.57, 59.19). The rate of carditis was higher amongst male patients (pooled rate ratio: 5.04; 95% CI 1.40, 18.19) and after the second vaccination dose (pooled rate ratio: 5.60; 95% CI 1.97, 15.89). In 301 cases of carditis (281 male; mean age: 15.90 (standard deviation [SD] 1.52) years old) reported amongst the case series/reports, 261 patients were reported to have received treatment. 97.34% of the patients presented with chest pain. The common findings include ST elevation and T wave abnormalities on electrocardiography. Oedema and late gadolinium enhancement in the myocardium were frequently observed in cardiac magnetic resonance imaging (CMR). The mean length of hospital stay was 3.91 days (SD 1.75). In 298 out of 299 patients (99.67%) the carditis resolved with or without treatment. CONCLUSIONS: Carditis is a rare complication after COVID-19 vaccination across the globe, but the vast majority of episodes are self-limiting with rapid resolution of symptoms within days. Central illustration. Balancing the benefits of vaccines on COVID-19-caused carditis and post-vaccination carditis.

Meeting in the metaverse - a new paradigm for scientific mentorship

81 Figure 1A photograph of our co-author, Mr. Teddy Tai Loy Lee, a pharmacy student using a virtual reality head-mounted display during the metaverse meeting. Informed consent was provided for the publication of identifiable information[Figure omitted. See PDF] 81 Figure 2A screenshot of the virtual experience during the mentorship sessions and research meetings taken using the selfie function. All participants consented to the publication of their avatars[Figure omitted. See PDF]ConclusionThe metaverse is an effective system for facilitating and enabling interactions amongst international colleagues, breaking down barriers between colleagues from different countries and across traditional hierarchies.Conflict of InterestN/A

Exploring the Relationship among Human Activities, COVID-19 Morbidity, and At-Risk Areas Using Location-Based Social Media Data: Knowledge about the Early Pandemic Stage in Wuhan.

It is significant to explore the morbidity patterns and at-risk areas of the COVID-19 outbreak in megacities. In this paper, we studied the relationship among human activities, morbidity patterns, and at-risk areas in Wuhan City. First, we excavated the activity patterns from Sina Weibo check-in data during the early COVID-19 pandemic stage (December 2019~January 2020) in Wuhan. We considered human-activity patterns and related demographic information as the COVID-19 influencing determinants, and we used spatial regression models to evaluate the relationships between COVID-19 morbidity and the related factors. Furthermore, we traced Weibo users' check-in trajectories to characterize the spatial interaction between high-morbidity residential areas and activity venues with POI (point of interest) sites, and we located a series of potential at-risk places in Wuhan. The results provide statistical evidence regarding the utility of human activity and demographic factors for the determination of COVID-19 morbidity patterns in the early pandemic stage in Wuhan. The spatial interaction revealed a general transmission pattern in Wuhan and determined the high-risk areas of COVID-19 transmission. This article explores the human-activity characteristics from social media check-in data and studies how human activities played a role in COVID-19 transmission in Wuhan. From that, we provide new insights for scientific prevention and control of COVID-19.

Promising Role of Emodin as Therapeutics to Against Viral Infections.

Emodin is an anthraquinone derivative that is widely present in natural plants and has a wide spectrum of pharmacological effects, such as antibacterial, anti-inflammatory, anti-fibrotic and anticancer and so on. Through reviewing studies on antiviral effect of emodin in the past decades, we found that emodin exhibits ability of inhibiting the infection and replication of more than 10 viruses in vitro and in vivo, including herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2), human cytomegalovirus (HCMV), Epstein-Barr virus (EBV), coxsackievirus B (CVB), hepatitis B virus (HBV), influenza A virus (IAV), SARS-CoV, viral haemorrhagic septicaemia rhabdovirus (VHSV), enterovirus 71 (EV71), dengue virus serotype 2 (DENV-2) and Zika virus (ZIKV). Therefore, this review aims to summarize the antiviral effect of emodin, in order to provide reference and hopes to support the further investigations.

Comparisons of the risk of myopericarditis between COVID-19 patients and individuals receiving COVID-19 vaccines: a population-based study.

BACKGROUND: Both COVID-19 infection and COVID-19 vaccines have been associated with the development of myopericarditis. The objective of this study is to (1) analyse the rates of myopericarditis after COVID-19 infection and COVID-19 vaccination in Hong Kong, (2) compared to the background rates, and (3) compare the rates of myopericarditis after COVID-19 vaccination to those reported in other countries. METHODS: This was a population-based cohort study from Hong Kong, China. Patients with positive RT-PCR test for COVID-19 between 1st January 2020 and 30th June 2021 or individuals who received COVID-19 vaccination until 31st August were included. The main exposures were COVID-19 positivity or COVID-19 vaccination. The primary outcome was myopericarditis. RESULTS: This study included 11,441 COVID-19 patients from Hong Kong, four of whom suffered from myopericarditis (rate per million: 326; 95% confidence interval [CI] 127-838). The rate was higher than the pre-COVID-19 background rate in 2019 (rate per million: 5.5, 95% CI 4.1-7.4) with a rate ratio of 55.0 (95% CI 21.4-141). Compared to the background rate, the rate of myopericarditis among vaccinated subjects in Hong Kong was similar (rate per million: 5.5; 95% CI 4.1-7.4) with a rate ratio of 0.93 (95% CI 0.69-1.26). The rates of myocarditis after vaccination in Hong Kong were comparable to those vaccinated in the United States, Israel, and the United Kingdom. CONCLUSIONS: COVID-19 infection was associated with significantly higher rate of myopericarditis compared to the vaccine-associated myopericarditis.

Straw burning, PM2.5, and death: evidence from China

This study uses satellite data to detect agricultural straw burning and estimates its impact on air pollution and health in China. We find that straw burning increases particulate matter pollution and causes people to die from cardiorespiratory diseases. We estimate that a 10 g/m3 increase in PM2.5 increases mortality by 3.25%. Middle-aged and old people in rural areas are particularly sensitive to straw burning pollution. Exploratory analysis of China's programs to subsidize straw recycling suggests that extending these programs to all the straw burning regions would bring about a health benefit that is an order of magnitude larger than the cost.

Changes in alcohol consumption during the COVID-19 pandemic: exploring gender differences and the role of emotional distress. / Modifications de la consommation d'alcool pendant la pandémie de COVID-19 : exploration des différences selon le genre et du rôle de la détresse émotionnelle.

INTRODUCTION: Restrictions to do with the COVID-19 pandemic have had substantial unintended consequences on Canadians' alcohol consumption patterns, including increased emotional distress and its potential impact on alcohol use. This study examines 1) changes in adults' alcohol consumption during the COVID-19 pandemic in New Brunswick and Nova Scotia; 2) whether drinking more frequently during the pandemic is associated with increased feelings of stress, loneliness and hopelessness; and 3) whether gender moderates this relationship. METHODS: Participants were drawn from a cross-sectional survey of 2000 adults. Adjusted multinomial regression models were used to assess the association between drinking frequency and increased feelings of stress, loneliness and hopelessness. Additional analyses were stratified by gender. RESULTS: About 12% of respondents reported drinking more frequently after the start of the COVID-19 pandemic, and 25%-40% reported increased emotional distress. Increased feelings of stress (odds ratio [OR] = 1.99; 95% confidence interval [CI]: 1.35-2.93), loneliness (OR = 1.79; 95% CI: 1.22-2.61) and hopelessness (OR = 1.98; 95% CI: 1.21-3.23) were all associated with drinking more frequently during the pandemic. While women respondents reported higher rates of emotional distress, significant associations with increased drinking frequency were only observed among men in gender-stratified analyses. CONCLUSION: Individuals who report increased feelings of stress, loneliness and hopelessness during the COVID-19 pandemic were more likely to report increased drinking frequency; however, these associations were only significant for men in stratified analyses. Understanding how the pandemic is associated with mental health and drinking may inform alcohol control policies and public health interventions to minimize alcohol-related harm.

Alcohol access and purchasing behaviour during COVID-19 pandemic restrictions: An exploration of sociodemographic, health and psychosocial correlates in two Canadian provinces.

INTRODUCTION: Alcohol access has changed in Canada during the COVID-19 pandemic. This study compares the use of two novel purchasing modes (via delivery and in excess/stockpiling) to traditional, in-person purchasing to determine if their use is associated with sociodemographic and psychosocial characteristics, perceived COVID-19 health risk or consumption frequency. METHODS: We draw on cross-sectional survey data from 2000 residents of the Canadian provinces of Nova Scotia and New Brunswick, ages 19 years and older that were administered online and by telephone. Associations between purchasing modes and sociodemographic and psychosocial characteristics, perceived COVID-19 health risk or consumption frequency were assessed using logistic regression. RESULTS: About 70% of people who drink purchased in-person, 17% used delivery and 30% purchased in excess/stockpiled. Sociodemographic and psychosocial attributes varied among those at increased odds of using each purchasing mode. Those at higher COVID-19 health risk were at higher odds of getting alcohol delivered. Increased drinking frequency was associated with alcohol delivery and purchasing in excess/stockpiling. DISCUSSION AND CONCLUSIONS: This study highlights the need for increased public health considerations regarding changes to alcohol regulations. Alcohol delivery and purchasing in excess/stockpiling is positively associated with heavier drinking. Drinkers at higher COVID-19 health risk were more likely to purchase online for delivery, which suggests novel purchasing modes may serve a partial public health function.

Interferon-α2b induced anemia in severe coronavirus disease 2019 patients: a single centered, retrospective study.

BACKGROUND: The current outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread throughout the world. During treatment, we found that the majority of patients had a decrease in hemoglobin (Hb). Interferon-α2b (IFN-α2b) was the primary suspected drug that was related to Hb reduction. Thus, the study aimed to investigate whether IFN-α2b could induce Hb reduction in severe patients with COVID-19 and its potential mechanism. MATERIAL AND METHODS: A total of 50 patients who were admitted to the First Affiliated Hospital of Harbin Medical University with severe COVID-19 infection were enrolled from February 12th to 24th, 2020. The demographics, baseline characteristics, clinical data, and therapeutic regimen were collected retrospectively. The patients were divided into two groups according to the declined use of IFN-α2b on day 14. The Hb levels on admission, day 7, day14, and day 21 were collected and analyzed. The primary endpoint was the level of Hb on day 21. RESULTS: A total of 31 patients in the IFN-stop group and 19 patients in the non-IFN-stop group were reviewed. The age, gender, comorbidities, clinical symptoms, nutritional status, disease severity, complications, and other factors of the patients were compared, no difference was found between the IFN-stop group and the non-IFN-stop group. The Hb levels of all patients significantly decreased on day 7 compared with that on admission (p < .0001). In the IFN-stop group, the Hb level was increased in 7 days after IFN-α2b was stopped (p = .0008), whereas no difference was found between day 14 and day 21 in the non-IFN-stop group (p = .3152). CONCLUSIONS: IFN-α2b was associated with Hb reduction in the treatment of severe patients of COVID-19. Clinicians should be aware of the high incidence of Hb reduction for patients treated by IFN-α2b.

Structural Basis of a Human Neutralizing Antibody Specific to the SARS-CoV-2 Spike Protein Receptor-Binding Domain.

The emerging new lineages of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have marked a new phase of coronavirus disease 2019 (COVID-19). Understanding the recognition mechanisms of potent neutralizing monoclonal antibodies (NAbs) against the spike protein is pivotal for developing new vaccines and antibody drugs. Here, we isolated several monoclonal antibodies (MAbs) against the SARS-CoV-2 spike protein receptor-binding domain (S-RBD) from the B cell receptor repertoires of a SARS-CoV-2 convalescent. Among these MAbs, the antibody nCoV617 demonstrates the most potent neutralizing activity against authentic SARS-CoV-2 infection, as well as prophylactic and therapeutic efficacies against the human angiotensin-converting enzyme 2 (ACE2) transgenic mouse model in vivo. The crystal structure of S-RBD in complex with nCoV617 reveals that nCoV617 mainly binds to the back of the "ridge" of RBD and shares limited binding residues with ACE2. Under the background of the S-trimer model, it potentially binds to both "up" and "down" conformations of S-RBD. In vitro mutagenesis assays show that mutant residues found in the emerging new lineage B.1.1.7 of SARS-CoV-2 do not affect nCoV617 binding to the S-RBD. These results provide a new human-sourced neutralizing antibody against the S-RBD and assist vaccine development. IMPORTANCE COVID-19 is a respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic has posed a serious threat to global health and the economy, so it is necessary to find safe and effective antibody drugs and treatments. The receptor-binding domain (RBD) in the SARS-CoV-2 spike protein is responsible for binding to the angiotensin-converting enzyme 2 (ACE2) receptor. It contains a variety of dominant neutralizing epitopes and is an important antigen for the development of new coronavirus antibodies. The significance of our research lies in the determination of new epitopes, the discovery of antibodies against RBD, and the evaluation of the antibodies' neutralizing effect. The identified antibodies here may be drug candidates for the development of clinical interventions for SARS-CoV-2.

Comparison of the Characteristics of Cytokine Storm and Immune Response Induced by SARS-CoV, MERS-CoV, and SARS-CoV-2 Infections.

Cytokine storm (CS) is a significant cause of death in patients with severe coronavirus pneumonia. Excessive immune-inflammatory reaction, many inflammatory cell infiltration, and extreme increase of proinflammatory cytokines and chemokines lead to acute lung injury and acute respiratory distress syndrome (ARDS). This review compares the characters of cytokine storms and immune responses caused by three highly pathogenic and infectious coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome-coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and analyzes the possible mechanisms to guide clinical treatment in the future.

Multi-task multi-modality SVM for early COVID-19 Diagnosis using chest CT data.

In the early diagnosis of the Coronavirus disease (COVID-19), it is of great importance for either distinguishing severe cases from mild cases or predicting the conversion time that mild cases would possibly convert to severe cases. This study investigates both of them in a unified framework by exploring the problems such as slight appearance difference between mild cases and severe cases, the interpretability, the High Dimension and Low Sample Size (HDLSS) data, and the class imbalance. To this end, the proposed framework includes three steps: (1) feature extraction which first conducts the hierarchical segmentation on the chest Computed Tomography (CT) image data and then extracts multi-modality handcrafted features for each segment, aiming at capturing the slight appearance difference from different perspectives; (2) data augmentation which employs the over-sampling technique to augment the number of samples corresponding to the minority classes, aiming at investigating the class imbalance problem; and (3) joint construction of classification and regression by proposing a novel Multi-task Multi-modality Support Vector Machine (MM-SVM) method to solve the issue of the HDLSS data and achieve the interpretability. Experimental analysis on two synthetic and one real COVID-19 data set demonstrated that our proposed framework outperformed six state-of-the-art methods in terms of binary classification and regression performance.