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The pandemic of coronavirus disease (COVID)-19 is a global threat, causing high mortality, especially in the elderly. The main symptoms and the primary cause of death are related to interstitial pneumonia. Viral entry also into myocardial cells mainly via the angiotensin converting enzyme type 2 (ACE2) receptor and excessive production of pro-inflammatory cytokines, however, also make the heart susceptible to injury. In addition to the immediate damage caused by the acute inflammatory response, the heart may also suffer from long-term consequences of COVID-19, potentially causing a post-pandemic increase in cardiac complications. Although the main cause of cardiac damage in COVID-19 remains coagulopathy with micro- (and to a lesser extent macro-) vascular occlusion, open questions remain about other possible modalities of cardiac dysfunction, such as direct infection of myocardial cells, effects of cytokines storm, and mechanisms related to enhanced coagulopathy. In this opinion paper, we focus on these lesser appreciated possibilities and propose experimental approaches that could provide a more comprehensive understanding of the cellular and molecular bases of cardiac injury in COVID-19 patients. We first discuss approaches to characterize cardiac damage caused by possible direct viral infection of cardiac cells, followed by formulating hypotheses on how to reproduce and investigate the hyperinflammatory and pro-thrombotic conditions observed in the heart of COVID-19 patients using experimental in vitro systems. Finally, we elaborate on strategies to discover novel pathology biomarkers using omics platforms. [ABSTRACT FROM AUTHOR]

The cardiovascular system is significantly affected in coronavirus disease-19 (COVID-19). Microvascular injury, endothelial dysfunction, and thrombosis resulting from viral infection or indirectly related to the intense systemic inflammatory and immune responses are characteristic features of severe COVID-19. Pre-existing cardiovascular disease and viral load are linked to myocardial injury and worse outcomes. The vascular response to cytokine production and the interaction between severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and angiotensin-converting enzyme 2 receptor may lead to a significant reduction in cardiac contractility and subsequent myocardial dysfunction. In addition, a considerable proportion of patients who have been infected with SARS-CoV-2 do not fully recover and continue to experience a large number of symptoms and post-acute complications in the absence of a detectable viral infection. This conditions often referred to as 'post-acute COVID-19' may have multiple causes. Viral reservoirs or lingering fragments of viral RNA or proteins contribute to the condition. Systemic inflammatory response to COVID-19 has the potential to increase myocardial fibrosis which in turn may impair cardiac remodelling. Here, we summarize the current knowledge of cardiovascular injury and post-acute sequelae of COVID-19. As the pandemic continues and new variants emerge, we can advance our knowledge of the underlying mechanisms only by integrating our understanding of the pathophysiology with the corresponding clinical findings. Identification of new biomarkers of cardiovascular complications, and development of effective treatments for COVID-19 infection are of crucial importance. [ABSTRACT FROM AUTHOR]

Background The National Institutes of Health (NIH) mobilized more than $4 billion in extramural funding for the COVID-19 pandemic. Assessing the research output from this effort is crucial to understanding how the scientific community leveraged federal funding and responded to this public health crisis. Methods NIH-funded COVID-19 grants awarded between January 2020 and December 2021 were identified from NIH Research Portfolio Online Reporting Tools Expenditures and Results using the "COVID-19 Response" filter. PubMed identifications of publications under these grants were collected and the NIH iCite tool was used to determine citation counts and focus (eg, clinical, animal). iCite and the NIH's LitCOVID database were used to identify publications directly related to COVID-19. Publication titles and Medical Subject Heading terms were used as inputs to a machine learning–based model built to identify common topics/themes within the publications. Results and Conclusions We evaluated 2401 grants that resulted in 14 654 publications. The majority of these papers were published in peer-reviewed journals, though 483 were published to preprint servers. In total, 2764 (19%) papers were directly related to COVID-19 and generated 252 029 citations. These papers were mostly clinically focused (62%), followed by cell/molecular (32%), and animal focused (6%). Roughly 60% of preprint publications were cell/molecular-focused, compared with 26% of nonpreprint publications. The machine learning–based model identified the top 3 research topics to be clinical trials and outcomes research (8.5% of papers), coronavirus-related heart and lung damage (7.3%), and COVID-19 transmission/epidemiology (7.2%). This study provides key insights regarding how researchers leveraged federal funding to study the COVID-19 pandemic during its initial phase. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 virus has, up to the time of this article, resulted in >770 million cases of COVID-19 illness worldwide, and approximately 7 million deaths, including >1.1 million in the United States. Although defined as a respiratory virus, early in the pandemic, it became apparent that considerable numbers of people recovering from COVID-19 illness experienced persistence or new onset of multi-system health problems, including neurologic and cognitive and behavioral health concerns. Persistent multi-system health problems are defined as Post-COVID-19 Condition (PCC), Post-Acute Sequelae of COVID-19, or Long COVID. A significant number of those with PCC report cognitive problems. This paper reviews the current state of scientific knowledge on persisting cognitive symptoms in adults following COVID-19 illness. A brief history is provided of the emergence of concerns about persisting cognitive problems following COVID-19 illness and the definition of PCC. Methodologic factors that complicate clear understanding of PCC are reviewed. The review then examines research on patterns of cognitive impairment that have been found, factors that may contribute to increased risk, behavioral health variables, and interventions being used to ameliorate persisting symptoms. Finally, recommendations are made about ways neuropsychologists can improve the quality of existing research. [ABSTRACT FROM AUTHOR]

The identification of viruses from negative staining transmission electron microscopy (TEM) images has mainly depended on experienced experts. Recent advances in artificial intelligence have enabled virus recognition using deep learning techniques. However, most of the existing methods only perform virus classification or semantic segmentation, and few studies have addressed the challenge of virus instance segmentation in TEM images. In this paper, we focus on the instance segmentation of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) and other respiratory viruses and provide experts with more effective information about viruses. We propose an effective virus instance segmentation network based on the You Only Look At CoefficienTs backbone, which integrates the Swin Transformer, dense connections and the coordinate-spatial attention mechanism, to identify SARS-CoV-2, H1N1 influenza virus, respiratory syncytial virus, Herpes simplex virus-1, Human adenovirus type 5 and Vaccinia virus. We also provide a public TEM virus dataset and conduct extensive comparative experiments. Our method achieves a mean average precision score of 83.8 and F1 score of 0.920, outperforming other state-of-the-art instance segmentation algorithms. The proposed automated method provides virologists with an effective approach for recognizing and identifying SARS-CoV-2 and assisting in the diagnosis of viruses. Our dataset and code are accessible at https://github.com/xiaochiHNU/Virus-Instance-Segmentation-Transformer-Network. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic saw unprecedented resources and funds driven into research for the development, and subsequent rapid distribution, of vaccines, diagnostics and directly acting antivirals (DAAs). DAAs have undeniably prevented progression and life-threatening conditions in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, there are concerns of antimicrobial resistance (AMR), antiviral resistance specifically, for DAAs. To preserve activity of DAAs for COVID-19 therapy, as well as detect possible mutations conferring resistance, antimicrobial stewardship and surveillance were rapidly implemented in England. This paper expands on the ubiquitous ongoing public health activities carried out in England, including epidemiologic, virologic and genomic surveillance, to support the stewardship of DAAs and assess the deployment, safety, effectiveness and resistance potential of these novel and repurposed therapeutics. [ABSTRACT FROM AUTHOR]

Background: In 2020, SARS-CoV-2 and the COVID-19 pandemic had a huge impact on the access to and provision of ART treatments. Gradually, knowledge of the virus and its transmission has become available, allowing ART activities to resume. Still, questions on the impact of the virus on human gametes and fertility remain.Objective and Rationale: This article summarizes published data, aiming to clarify the impact of SARS-CoV-2 and the COVID-19 disease on human fertility and assisted reproduction, as well as the impact of vaccination, and from this, provide answers to questions that are relevant for people contemplating pregnancy and for health care professionals.Search Methods: PUBMED/MEDLINE and the WHO COVID-19 database were searched from inception to 5 October 2022 with search terms focusing on 'SARS-CoV-2' and gametes, embryos, reproductive function, fertility and ART. Non-English studies and papers published prior to 2020 were excluded, as well as reviews and non-peer reviewed publications. Full papers were assessed for relevance and quality, where feasible.Outcomes: From the 148 papers included, the following observations were made. The SARS-CoV-2-binding proteins, angiotensin-converting enzyme 2 (ACE2) and type II transmembrane serine protease (TMPRSS2), are expressed in the testis, but co-expression remains to be proven. There is some evidence of SARS-CoV-2 RNA in the ejaculate of COVID-19 patients with severe disease, but not in those with mild/moderate disease. SARS-CoV-2 infection can impair spermatogenesis, but this seems to resolve after one spermatogenic cycle. Testosterone levels seem to be lower during and after COVID-19, but long-term data are lacking; disease severity may be associated with testosterone levels. COVID-19 cannot be considered a sexually transmitted disease. There is no co-expression of ACE2 and TMPRSS2 in the myometrium, uterus, ovaries or fallopian tubes. Oocytes seem to have the receptors and protease machinery to be susceptible to SARS-CoV-2 infection; however, viral RNA in oocytes has not been detected so far. Women contemplating pregnancy following COVID-19 may benefit from screening for thyroid dysfunction. There is a possible (transient) impact of COVID-19 on menstrual patterns. Embryos, and particularly late blastocysts, seem to have the machinery to be susceptible to SARS-CoV-2 infection. Most studies have not reported a significant impact of COVID-19 on ovarian reserve, ovarian function or follicular fluid parameters. Previous asymptomatic or mild SARS-CoV-2 infection in females does not seem to negatively affect laboratory and clinical outcomes of ART. There are no data on the minimum required interval, if any, between COVID-19 recovery and ART. There is no evidence of a negative effect of SARS-CoV-2 vaccination on semen parameters or spermatogenesis, ovarian function, ovarian reserve or folliculogenesis. A transient effect on the menstrual cycle has been documented. Despite concerns, cross reactivity between anti-SARS-CoV-2 spike protein antibodies and Syncytin-1, an essential protein in human implantation, is absent. There is no influence of mRNA SARS-CoV-2 vaccine on patients' performance during their immediate subsequent ART cycle. Pregnancy rates post-vaccination are similar to those in unvaccinated patients.Wider Implications: This review highlights existing knowledge on the impact of SARS-CoV-2 infection or COVID-19 on fertility and assisted reproduction, but also identifies gaps and offers suggestions for future research. The knowledge presented should help to provide evidence-based advice for practitioners and couples contemplating pregnancy alike, facilitating informed decision-making in an environment of significant emotional turmoil. [ABSTRACT FROM AUTHOR]

Background: There has been a large influx of COVID-19 seroprevalence studies, but comparability between the seroprevalence estimates has been an issue because of heterogeneities in testing platforms and study methodology. One potential source of heterogeneity is the response or participation rate.Methods: We conducted a review of participation rates (PR) in SARS-CoV-2 seroprevalence studies collected by SeroTracker and examined their effect on the validity of study conclusions. PR was calculated as the count of participants for whom the investigators had collected a valid sample, divided by the number of people invited to participate in the study. A multivariable beta generalized linear model with logit link was fitted to determine if the PR of international household and community-based seroprevalence studies was associated with the factors of interest, from 1 December 2019 to 10 March 2021.Results: We identified 90 papers based on screening and were able to calculate the PR for 35 out of 90 papers (39%), with a median PR of 70% and an interquartile range of 40.92; 61% of the studies did not report PR.Conclusions: Many SARS-CoV-2 seroprevalence studies do not report PR. It is unclear what the median PR rate would be had a larger portion not had limitations in reporting. Low participation rates indicate limited representativeness of results. Non-probabilistic sampling frames were associated with higher participation rates but may be less representative. Standardized definitions of participation rate and data reporting necessary for the PR calculations are essential for understanding the representativeness of seroprevalence estimates in the population of interest. [ABSTRACT FROM AUTHOR]

Summary: The occurrence of antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) has been reported since the coronavirus disease 2019 (COVID-19) vaccination, but whether there is a causal relationship or coincidence remains to be verified. We combined the term COVID-19 vaccination with each word of AAV to search for case reports and case series published in PubMed, EMBASE, and Web of Science databases before 13 March 2023. A total of 56 patients who developed AAV after COVID-19 vaccination were identified from 44 research centers. Of the 56 subjects, 43 (76.7%) were vaccinated with the mRNA vaccine, followed by the adenovirus vaccine (14.3%) and inactivated vaccine (9.0%) (P = 0.015). Compared with relapsed AAV, new-onset AAV patients had at least two other diseases previously (P < 0.001). Twenty-five (44.6%) patients presented symptoms after the first injection, and the medium onset time was 12 (1–77) days, while Twenty-eight (50.0%) patients developed symptoms after the second dose, and their medium period was 14 (1–60) days. Forty-four (78.5%) patients achieved remission after immunosuppressive agents, plasma exchange, and hemodialysis. One (1.8%) patient died from progressive respiratory failure and nine (16.1%) did not recover, leaving five patients permanently dependent on hemodialysis. Pathogenic ANCA may be activated by enhanced immune response and epitope spreading after COVID-19 vaccination and induced the occurrence of AAV, especially in genetically susceptible populations. The occurrence of antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) has been reported since the coronavirus disease 2019 (COVID-19) vaccination, but whether there is a causal relationship or coincidence remains to be verified. This paper explores the occurrence of AAV, especially in genetically susceptible populations. [ABSTRACT FROM AUTHOR]

Massive-scale SARS-CoV-2 testing using the SwabSeq diagnostic platform came with quality assurance challenges due to the novelty and scale of sequencing-based testing. The SwabSeq platform relies on accurate mapping between specimen identifiers and molecular barcodes to match a result back to a patient specimen. To identify and mitigate mapping errors, we instituted quality control using placement of negative controls within a rack of patient samples. We designed 2-dimensional paper templates to fit over a 96-position rack of specimens with holes to show the control tube placements. We designed and 3-dimensionally printed plastic templates that fit onto 4 racks of patient specimens and provide accurate indications of the correct control tube placements. The final plastic templates dramatically reduced plate mapping errors from 22.55% in January 2021 to less than 1% after implementation and training in January 2021. We show how 3D printing can be a cost-effective quality assurance tool to mitigate human error in the clinical laboratory. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic led to rapid vaccine development and large global vaccination schemes. However, patients with immune-mediated kidney disease, chronic kidney diseases and kidney transplant recipients show high non-response rates to vaccination despite more than three vaccinations and, consequently, reduced viral clearance capacity when infected while receiving certain immunosuppressants, carrying an elevated risk for coronavirus disease 2019 (COVID-19)-related morbidity and mortality. SARS-CoV-2 evolution has been characterized by the emergence of novel variants and spike mutations contributing to waning efficacy of neutralizing antibodies. To this end, the therapeutic field expands from vaccination towards a combined approach of immunization, pre-exposure prophylaxis and early post-exposure treatment using direct-acting antivirals and neutralizing monoclonal antibodies to treat early in the disease course and avoid hospitalization. This expert opinion paper from the Immunonephrology Working Group of the European Renal Association (ERA-IWG) summarizes available prophylactic and/or early treatment options (i.e. neutralizing monoclonal antibodies and direct-acting antivirals) of SARS-CoV-2-infected patients with immune-mediated kidney disease, chronic kidney disease and kidney transplant recipients. [ABSTRACT FROM AUTHOR]

Motivation Virus mutation is one of the most important research issues which plays a critical role in disease progression and has prompted substantial scientific publications. Mutation extraction from published literature has become an increasingly important task, benefiting many downstream applications such as vaccine design and drug usage. However, most existing approaches have low performances in extracting virus mutation due to both lack of precise virus mutation information and their development based on human gene mutations. Results We developed ViMRT, a text-mining tool and search engine for automated virus mutation recognition using natural language processing. ViMRT mainly developed 8 optimized rules and 12 regular expressions based on a development dataset comprising 830 papers of 5 human severe disease-related viruses. It achieved higher performance than other tools in a test dataset (1662 papers, 99.17% in F1-score) and has been applied well to two other viruses, influenza virus and severe acute respiratory syndrome coronavirus-2 (212 papers, 96.99% in F1-score). These results indicate that ViMRT is a high-performance method for the extraction of virus mutation from the biomedical literature. Besides, we present a search engine for researchers to quickly find and accurately search virus mutation-related information including virus genes and related diseases. Availability and implementation ViMRT software is freely available at http://bmtongji.cn:1225/mutation/index. [ABSTRACT FROM AUTHOR]

While research into drug–target interaction (DTI) prediction is fairly mature, generalizability and interpretability are not always addressed in the existing works in this field. In this paper, we propose a deep learning (DL)-based framework, called BindingSite-AugmentedDTA, which improves drug–target affinity (DTA) predictions by reducing the search space of potential-binding sites of the protein, thus making the binding affinity prediction more efficient and accurate. Our BindingSite-AugmentedDTA is highly generalizable as it can be integrated with any DL-based regression model, while it significantly improves their prediction performance. Also, unlike many existing models, our model is highly interpretable due to its architecture and self-attention mechanism, which can provide a deeper understanding of its underlying prediction mechanism by mapping attention weights back to protein-binding sites. The computational results confirm that our framework can enhance the prediction performance of seven state-of-the-art DTA prediction algorithms in terms of four widely used evaluation metrics, including concordance index, mean squared error, modified squared correlation coefficient (⁠|$r^2_m$|⁠) and the area under the precision curve. We also contribute to three benchmark drug–traget interaction datasets by including additional information on 3D structure of all proteins contained in those datasets, which include the two most commonly used datasets, namely Kiba and Davis, as well as the data from IDG-DREAM drug-kinase binding prediction challenge. Furthermore, we experimentally validate the practical potential of our proposed framework through in-lab experiments. The relatively high agreement between computationally predicted and experimentally observed binding interactions supports the potential of our framework as the next-generation pipeline for prediction models in drug repurposing. [ABSTRACT FROM AUTHOR]

Aims: The purpose of this study was to evaluate the effects of ambient or altered environmental conditions on the inactivation of SARS‐CoV‐2 applied to materials common in libraries, archives and museums. Methods and Results: Porous and non‐porous materials (e.g. paper, plastic protective book cover) were inoculated with approximately 1 × 105 TCID50 SARS CoV‐2 (USA‐WA1/2020), dried, placed within test chamber in either a stacked or unstacked configuration, and exposed to environmental conditions ranging from 4 to 29°C at 40 ± 10% relative humidity. The amount of infectious SARS‐CoV‐2 was then assessed at various timepoints from 0 to 10 days. Ambient conditions resulted in varying inactivation rates per material type. Virus inactivation rate decreased when materials were stacked or at colder temperatures. Virus inactivation rate increased when materials were unstacked or at warmer temperatures. Conclusions: SARS‐CoV‐2 at ambient conditions resulted in the inactivation of virus below limit of quantitation (LOQ) for all materials by Day 8. Warmer temperatures, for a subset of materials, increased SARS‐CoV‐2 inactivation, and all were

Background Early reports on the pandemic nature of coronavirus disease 2019 (COVID-19) directed the nephrology community to develop infection prevention and control (IPC) guidance. We aimed to make an inventory of strategies that dialysis centres followed to prevent infection with COVID-19 in the first pandemic wave. Methods We analyzed IPC measures taken by hemodialysis centres treating patients presenting with COVID-19 between 1 March 2020 and 31 July 2020 and that completed the European Renal Association COVID-19 Database centre questionnaire. Additionally, we made an inventory of guidelines published in European countries to prevent spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in dialysis centres. Results Data from 73 dialysis units located in and bordering Europe were analyzed. All participating centres implemented IPC measures to mitigate the impact of SARS-CoV-2 during the first pandemic wave. Measures mentioned most often included triage with questions before entering the dialysis ward, measuring body temperature, hand disinfection, masking for all patients and staff, and personal protective equipment for staff members. These measures were also recommended in most of the 14 guidelines that were identified in the inventory of national guidelines and were also scored as being among the most important measures by the authors of this paper. Heterogeneity existed between centres and national guidelines regarding the minimal distance between dialysis chairs and recommendations regarding isolation and cohorting. Conclusions Although variation existed, measures to prevent transmission of SARS-CoV-2 were relatively similar across centres and national guidelines. Further research is needed to assess causal relationships between measures taken and spread of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination has decreasing protection from acquiring any infection with emergence of new variants; however, vaccination continues to protect against progression to severe coronavirus disease 2019 (COVID-19). The impact of vaccination status on symptoms over time is less clear. Methods Within a randomized trial on early outpatient COVID-19 therapy testing metformin, ivermectin, and/or fluvoxamine, participants recorded symptoms daily for 14 days. Participants were given a paper symptom diary allowing them to circle the severity of 14 symptoms as none (0), mild (1), moderate (2), or severe (3). This is a secondary analysis of clinical trial data on symptom severity over time using generalized estimating equations comparing those unvaccinated, SARS-CoV-2 vaccinated with primary vaccine series only, or vaccine-boosted. Results The parent clinical trial prospectively enrolled 1323 participants, of whom 1062 (80%) prospectively recorded some daily symptom data. Of these, 480 (45%) were unvaccinated, 530 (50%) were vaccinated with primary series only, and 52 (5%) vaccine-boosted. Overall symptom severity was least for the vaccine-boosted group and most severe for unvaccinated at baseline and over the 14 days (P <.001). Individual symptoms were least severe in the vaccine-boosted group including cough, chills, fever, nausea, fatigue, myalgia, headache, and diarrhea, as well as smell and taste abnormalities. Results were consistent over Delta and Omicron variant time periods. Conclusions SARS-CoV-2 vaccine-boosted participants had the least severe symptoms during COVID-19, which abated the quickest over time. Clinical Trial Registration. NCT04510194. [ABSTRACT FROM AUTHOR]

Aims Assess the persistence of infectious SARS-CoV-2 virus and virus genomic material on three common food coverings. Methods and Results The stability of infectious virus and genomic material on plastic wrap, fruit wax, and cardboard takeout containers was measured. SARS-CoV-2 in simulated saliva was applied to the surface of these materials and allowed to dry. Samples were stored at 4°C or 20°C and a relative humidity of 30%, 50%, 65%, or 70% for up to 7 days. Viability was measured by TCID50 and the half-life for infectious virus was determined to be ~24 hours and ~8 hours at 4°C and 20°C, respectively, on all surfaces and RH tested. There was no loss of virus genomic material as measured by qRT-PCR at all conditions evaluated. Conclusions SARS-CoV-2 virus remains infectious on food coverings for hours to days. It is estimated that a 99.9% reduction in titer requires 10 days at 4°C and 3 days at 20°C for all RH tested. SARS-CoV-2 genomic material showed no loss when assayed by qRT-PCR. Significance and Impact of Study: SARS-CoV-2 virus on food coverings loses infectivity over a certain period, but PCR assays can still detect virus genomic material throughout the same time. Thus, testing and controls may need to consider the fact that virus genomic material may still be detected when no infectious virus is present. [ABSTRACT FROM AUTHOR]

Background Age-standardized mortality rates for taxi drivers, chauffeurs, bus and coach drivers show that public transport workers were at high risk at the beginning of the COVID-19 pandemic. Nevertheless, the public transport sector was required to continue services throughout the pandemic. Objectives This paper aims to develop a better understanding of the experiences of organizational leaders and workers within the UK public transport sector (bus, rail, and tram). Specifically, it aims to explore the perceived balance of risk and mitigation of SARS-CoV-2 transmission, report on their perceptions of safety in public transport during the pandemic and in the future, and consider how these perceptions and changes impact on long-term worker health and wellbeing. Methods This study formed part of a larger stakeholder engagement with the public transport sector. Organizational leaders and workers were recruited (n = 18) and semi-structured interviews carried out between January and May 2021. Data were analysed thematically. Results Overarching and subthemes were identified. Themes relating to perceptions and impacts of risk of COVID-19 for employees included: acceptability of risk for workers, perceptions of risk mitigation effectiveness, changes to working practices and their impact on morale and wellbeing, issues with compliance to mitigations such as social distancing and face coverings in passenger and co-worker groups alongside a lack of power to challenge behaviour effectively, and the roles of leadership and messaging. Themes related to long-lasting impacts of COVID-19 on working practices and effects on health and wellbeing included: continuing mitigations, impact of increasing passenger numbers, impact of vaccination programme, and impact of changes to business structure. Conclusions Most public transport employees reported feeling safe, related to the extent to which their role was public-facing. However, data were collected during a time of very low passenger numbers. Current mitigation measures were thought effective in reducing the risk of viral transmission, although measures may have a detrimental effect on worker morale and wellbeing. Issues relating to non-compliance with guidance and 'in-group' behaviour were identified. Impacts on wider business sustainability and individual wellbeing of staff should be considered when developing responses to any future pandemics. Recommendations are made for prioritizing employee engagement with colleagues, and the importance of strong leadership and clear messaging in promoting adherence to behavioural mitigations. [ABSTRACT FROM AUTHOR]

Cannabis is a plant notorious for its psychoactive effect, but when used correctly, it provides a plethora of medicinal benefits. With more than 400 active compounds that have therapeutic properties, cannabis has been accepted widely as a medical treatment and for recreational purposes in several countries. The compounds exhibit various clinical benefits, which include, but are not limited to, anticancer, antimicrobial, and antioxidant properties. Among the vast range of compounds, multiple research papers have shown that cannabinoids, such as cannabidiol and delta-9-tetrahydrocannabinol, have antiviral effects. Recently, scientists found that both compounds can reduce severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) viral infection by downregulating ACE2 transcript levels and by exerting anti-inflammatory properties. These compounds also act as the SARS-CoV-2 main protease inhibitors that block viral replication. Apart from cannabinoids, terpenes in cannabis plants have also been widely explored for their antiviral properties. With particular emphasis on four different viruses, SARS-CoV-2, human immunodeficiency virus, hepatitis C virus, and herpes simplex virus-1, this review discussed the role of cannabis compounds in combating viral infections and the potential of both cannabinoids and terpenes as novel antiviral therapeutics. [ABSTRACT FROM AUTHOR]

A novel Corona virus disease 2019 (COVID-19) outbreak is declared as the international public health emergency concern by the World Health Organization in the month of March 2020. This viral disease invented from China in the month of December 2019 has previously caused havoc around the world, including India. In this paper, efficient mathematical models using Gustafson–Kessel fuzzy clustering approach for the transmission of the COVID-19 are developed by considering the actual reported cases in the state of Tamil Nadu, India. The results proved a good concord between the reported data and the estimated data given by the proposed models. Moreover, the developed models are also capable to predict the requirements of beds in hospitals on the month of August 2020 in Tamil Nadu, India. Also, this work suggests strictly implementing/extending the complete lockdown for at least 21 days in the month of August 2020 and immediate separation of infected cases are the positive steps to reduce the spread of novel corona virus in Tamil Nadu state, India. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 pandemic has alerted people of the threat caused by viruses. Vaccine is the most effective way to prevent the disease from spreading. The interaction between antibodies and antigens will clear the infectious organisms from the host. Identifying B-cell epitopes is critical in vaccine design, development of disease diagnostics and antibody production. However, traditional experimental methods to determine epitopes are time-consuming and expensive, and the predictive performance using the existing in silico methods is not satisfactory. This paper develops a general framework to predict variable-length linear B-cell epitopes specific for human-adapted viruses with machine learning approaches based on Protvec representation of peptides and physicochemical properties of amino acids. QR decomposition is incorporated during the embedding process that enables our models to handle variable-length sequences. Experimental results on large immune epitope datasets validate that our proposed model's performance is superior to the state-of-the-art methods in terms of AUROC (0.827) and AUPR (0.831) on the testing set. Moreover, sequence analysis also provides the results of the viral category for the corresponding predicted epitopes with high precision. Therefore, this framework is shown to reliably identify linear B-cell epitopes of human-adapted viruses given protein sequences and could provide assistance for potential future pandemics and epidemics. [ABSTRACT FROM AUTHOR]

Predicting protein properties from amino acid sequences is an important problem in biology and pharmacology. Protein–protein interactions among SARS-CoV-2 spike protein, human receptors and antibodies are key determinants of the potency of this virus and its ability to evade the human immune response. As a rapidly evolving virus, SARS-CoV-2 has already developed into many variants with considerable variation in virulence among these variants. Utilizing the proteomic data of SARS-CoV-2 to predict its viral characteristics will, therefore, greatly aid in disease control and prevention. In this paper, we review and compare recent successful prediction methods based on long short-term memory (LSTM), transformer, convolutional neural network (CNN) and a similarity-based topological regression (TR) model and offer recommendations about appropriate predictive methodology depending on the similarity between training and test datasets. We compare the effectiveness of these models in predicting the binding affinity and expression of SARS-CoV-2 spike protein sequences. We also explore how effective these predictive methods are when trained on laboratory-created data and are tasked with predicting the binding affinity of the in-the-wild SARS-CoV-2 spike protein sequences obtained from the GISAID datasets. We observe that TR is a better method when the sample size is small and test protein sequences are sufficiently similar to the training sequence. However, when the training sample size is sufficiently large and prediction requires extrapolation, LSTM embedding and CNN-based predictive model show superior performance. [ABSTRACT FROM AUTHOR]

Understanding the T-cell response to SARS-CoV-2 is key in patients who lack antibody production. We demonstrate the applicability of a functional assay to measure the T-cell response in a cohort of patients with immunodeficiency. T-cell responses to COVID are now linked to improved outcomes. This paper demonstrates a method to robustly test responses for routine diagnostic use in healthy controls and those unable to make a detectable antibody response due to underlying immune deficiency (primary or acquired). [ABSTRACT FROM AUTHOR]

We read with interest the paper by Lee I et al i .[1] in which they describe widespread microvascular damage marked by endothelial cell damage/activation, microthrombi, complement activation, and disruption of the blood-brain barrier (BBB). Endothelial cell damage is the central part of COVID-19 and a mouse model induced by injection of the S1 subunit of the spike protein. [Extracted from the article]

Coronavirus disease 2019 (COVID-19) has attracted research interests from all fields. Phylogenetic and social network analyses based on connectivity between either COVID-19 patients or geographic regions and similarity between syndrome coronavirus 2 (SARS-CoV-2) sequences provide unique angles to answer public health and pharmaco-biological questions such as relationships between various SARS-CoV-2 mutants, the transmission pathways in a community and the effectiveness of prevention policies. This paper serves as a systematic review of current phylogenetic and social network analyses with applications in COVID-19 research. Challenges in current phylogenetic network analysis on SARS-CoV-2 such as unreliable inferences, sampling bias and batch effects are discussed as well as potential solutions. Social network analysis combined with epidemiology models helps to identify key transmission characteristics and measure the effectiveness of prevention and control strategies. Finally, future new directions of network analysis motivated by COVID-19 data are summarized. [ABSTRACT FROM AUTHOR]

The haemagglutination test (HAT)-field protocol described here is an optimization of the recently published HAT, for the detection of antibodies directed against the receptor binding domain (RBD) of the SARS-Cov-2 virus. HAT and HAT-field are both based on haemagglutination triggered by a single reagent, the IH4-RBD recombinant protein. A sample of IH4-RBD sufficient for several thousand tests or a plasmid encoding IH4-RBD can be obtained from the authors of our first paper. Using titration of IH4-RBD, HAT-field now allows a quantitative assessment of antibody levels in a single step, using a few microliters of whole blood, such as can be obtained by finger prick, and requires only very simple disposable equipment. Because it is based on a single soluble reagent, the test can be adapted very simply and rapidly to detect antibodies against variants of the SARS-CoV-2, or conceivably against different pathogens. HAT-field appears well suited to provide quantitative assessments of the serological protection of populations as well as individuals, and given its very low cost, the stability of the IH4-RBD reagent in the adapted buffer and the simplicity of the procedure, could be deployed pretty much anywhere, including in the poorest countries and the most remote corners of the globe. [ABSTRACT FROM AUTHOR]

Background We aimed to review the evidence from studies relating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) culture with the results of reverse-transcription polymerase chain reaction (RT-PCR) and other variables that may influence the interpretation of the test, such as time from symptom onset. Methods We searched LitCovid, medRxiv, Google Scholar, and the World Health Organization coronavirus disease 2019 (COVID-19) database for COVID-19 up to 10 September 2020. We included studies attempting to culture or observe SARS-CoV-2 in specimens with RT-PCR positivity. Studies were dual-extracted and the data summarized narratively by specimen type. Where necessary, we contacted corresponding authors of included papers for additional information. We assessed quality using a modified Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) risk-of-bias tool. Results We included 29 studies reporting attempts at culturing, or observing tissue infection by, SARS-CoV-2 in sputum, nasopharyngeal or oropharyngeal, urine, stool, blood, and environmental specimens. The quality of the studies was moderate with lack of standardized reporting. The data suggest a relationship between the time from onset of symptom to the timing of the specimen test, cycle threshold (Ct), and symptom severity. Twelve studies reported that Ct values were significantly lower and log copies higher in specimens producing live virus culture. Two studies reported that the odds of live virus culture were reduced by approximately 33% for every 1-unit increase in Ct. Six of 8 studies reported detectable RNA for >14 days, but infectious potential declined after day 8 even among cases with ongoing high viral loads. Four studies reported viral culture from stool specimens. Conclusions Complete live viruses are necessary for transmission, not the fragments identified by PCR. Prospective routine testing of reference and culture specimens and their relationship to symptoms, signs, and patient co-factors should be used to define the reliability of PCR for assessing infectious potential. Those with high Ct are unlikely to have infectious potential. [ABSTRACT FROM AUTHOR]

The psychological and sexual health of different populations are negatively affected during the coronavirus disease 2019 (COVID-19) pandemic. However, little is known about psychological distress and erectile function of male recovered patients with COVID-19 in the long term. We aimed to evaluate psychological distress and erectile function of male recovered patients with COVID-19 in the mid-to-long terms. We recruited 67 eligible male recovered patients with COVID-19 and followed them up twice within approximately 6 months of recovery time. The psychological distress and erectile function were assessed by validated Chinese version of paper questionnaires. The primary outcomes were Symptom Checklist 90 questionnaire for psychological distress and International Index of Erectile Function-5 for erectile function. In the first visit, COVID-19 patients with a median recovery time of 80 days mainly presented the following positive symptoms: Obsessive-Compulsive, additional items (ADD), Hostility, Interpersonal Sensitivity, Depression, and Somatization; while the dimension scores in Somatization, Anxiety, ADD, and Phobia were higher than Chinese male norms. Besides, the prevalence of erectile dysfunction (ED) in the first-visit patients was significantly higher than Chinese controls. In the second visit, the primary psychological symptoms of COVID-19 patients with a median recovery time of 174 days were Obsessive-Compulsive, ADD, Interpersonal Sensitivity, and Hostility, while all dimensions scores of Symptom Checklist 90 were lower than Chinese male norms. Moreover, second-visit patients had no significant difference with Chinese controls in ED prevalence. In addition, it suggested that GSI was the independent risk factor for ED in the regression analysis for the first-visit patients. The study showed the changes of psychological symptoms and erectile function in COVID-19 recovered patients, and provided reference on whether psychological and sexual supports are needed after a period of recovery. To our knowledge, it is the first study to comprehensively evaluate the psychological distress and erectile function of COVID-19 recovered patients in the mid-to-long terms. The main limitations were the low number of analyzed participants, and the psychological distress and erectile function of healthy Chinese men over the same period were not evaluated, and the psychological and sexual related data of participants prior to COVID-19 were not available. Additionally, there was a selection bias in comparing COVID-19 patients with healthy controls. With less impact of COVID-19 event, the impaired erectile function and psychological distress improved in COVID-19 recovered patients with a recovery time of nearly half a year. Hu B, Ruan Y, Liu K, et al. A Mid-to-Long Term Comprehensive Evaluation of Psychological Distress and Erectile Function in COVID-19 Recovered Patients. J Sex Med 2021;18:1863–1871. [ABSTRACT FROM AUTHOR]

The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide. Despite many efforts, the development of effective drugs and vaccines for this novel virus will take considerable time. Artificial intelligence (AI) and machine learning (ML) offer promising solutions that could accelerate the discovery and optimization of new antivirals. Motivated by this, in this paper, we present an extensive survey on the application of AI and ML for combating COVID-19 based on the rapidly emerging literature. Particularly, we point out the challenges and future directions associated with state-of-the-art solutions to effectively control the COVID-19 pandemic. We hope that this review provides researchers with new insights into the ways AI and ML fight and have fought the COVID-19 outbreak. [ABSTRACT FROM AUTHOR]

Two thousand nineteen novel coronavirus SARS-CoV-2, the pathogen of COVID-19, has caused a catastrophic pandemic, which has a profound and widespread impact on human lives and social economy globally. However, the molecular perturbations induced by the SARS-CoV-2 infection remain unknown. In this paper, from the perspective of omnigenic, we analyze the properties of the neighborhood perturbed by SARS-CoV-2 in the human interactome and disclose the peripheral and core regions of virus-host network (VHN). We find that the virus-host proteins (VHPs) form a significantly connected VHN, among which highly perturbed proteins aggregate into an observable core region. The non-core region of VHN forms a large scale but relatively low perturbed periphery. We further validate that the periphery is non-negligible and conducive to identifying comorbidities and detecting drug repurposing candidates for COVID-19. We particularly put forward a flower model for COVID-19, SARS and H1N1 based on their peripheral regions, and the flower model shows more correlations between COVID-19 and other two similar diseases in common functional pathways and candidate drugs. Overall, our periphery-core pattern can not only offer insights into interconnectivity of SARS-CoV-2 VHPs but also facilitate the research on therapeutic drugs. [ABSTRACT FROM AUTHOR]

Discovering drug–target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug–target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences. [ABSTRACT FROM AUTHOR]

: Biological, Clinical, and Technical Considerations These considerations are important when performing serology studies, with anti-S1/S2 serology tests preferably used to assess true seroprevalence; anti-RBD-specific serology immunoassays may be better suited to reflecting the presence of neutralizing antibodies. We read with interest the report by Geisler et al[1] and commend the authors for their efforts to address the important need to evaluate the clinical performance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic assays in pediatric populations, especially with respect to serology, given the noted differences in immune responses between children and adults.[2] We do feel, however, that the title of this paper may be misleading. This behavior would make it challenging to define whether anti-RBD antibodies are false negatives or if anti-S1 antibodies are false positives. [Extracted from the article]

We read with interest the paper by Molero-Salinas I et al i . on coronavirus disease of 2019 (COVID-19) false negative travellers arriving to Spain in 2021.[1] This study challenges the effectiveness of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing prior to flight departure to control COVID-19 spread. The authors report 196 COVID-19 false negative passengers with an average PCR Ct value of 20.3, meaning a high viral load. [Extracted from the article]