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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
337 Research products, page 1 of 34

  • COVID-19
  • Publications
  • Research data
  • Research software
  • 2017-2021
  • 03 medical and health sciences
  • Natural Sciences and Engineering Research Council of Canada

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  • Open Access English
    Authors: 
    Juan Carlos Abrego-Martinez; Maziar Jafari; Siham Chergui; Catalin Pavel; Diping Che; Mohamed Siaj;
    Publisher: Published by Elsevier B.V.
    Project: NSERC

    Rapid, mass diagnosis of the coronavirus disease 2019 (COVID-19) is critical to stop the ongoing infection spread. The two standard screening methods to confirm the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are polymerase chain reaction (PCR), through the RNA of the virus, and serology by detecting antibodies produced as a response to the viral infection. However, given the detection complexity, cost and relatively long analysis times of these techniques, novel technologies are urgently needed. Here, we report an aptamer-based biosensor developed on a screen-printed carbon electrode platform for rapid, sensitive, and user-friendly detection of SARS-CoV-2. The aptasensor relies on an aptamer targeting the receptor-binding domain (RBD) in the spike protein (S-protein) of the SARS-CoV-2. The aptamer immobilization on gold nanoparticles, and the presence of S-protein in the aptamer-target complex, investigated for the first time by photo-induced force microscopy mapping between 770 and 1910 cm-1 of the electromagnetic spectrum, revealed abundant S-protein homogeneously distributed on the sensing probe. The detection of SARS-CoV-2 S-protein was achieved by electrochemical impedance spectroscopy after 40 min incubation with several analyte concentrations, yielding a limit of detection of 1.30 pM (66 pg/mL). Moreover, the aptasensor was successfully applied for the detection of a SARS-CoV-2 pseudovirus, thus suggesting it is a promising tool for the diagnosis of COVID-19.

  • Open Access
    Authors: 
    Alisha Geldert; Alison Su; Allison W. Roberts; Guillaume Golovkine; Samantha M. Grist; Sarah A. Stanley; Amy E. Herr;
    Publisher: eScholarship, University of California
    Country: United States
    Project: NSERC

    AbstractDuring public health crises like the COVID-19 pandemic, ultraviolet-C (UV-C) decontamination of N95 respirators for emergency reuse has been implemented to mitigate shortages. Pathogen photoinactivation efficacy depends critically on UV-C dose, which is distance- and angle-dependent and thus varies substantially across N95 surfaces within a decontamination system. Due to nonuniform and system-dependent UV-C dose distributions, characterizing UV-C dose and resulting pathogen inactivation with sufficient spatial resolution on-N95 is key to designing and validating UV-C decontamination protocols. However, robust quantification of UV-C dose across N95 facepieces presents challenges, as few UV-C measurement tools have sufficient (1) small, flexible form factor, and (2) angular response. To address this gap, we combine optical modeling and quantitative photochromic indicator (PCI) dosimetry with viral inactivation assays to generate high-resolution maps of “on-N95” UV-C dose and concomitant SARS-CoV-2 viral inactivation across N95 facepieces within a commercial decontamination chamber. Using modeling to rapidly identify on-N95 locations of interest, in-situ measurements report a 17.4 ± 5.0-fold dose difference across N95 facepieces in the chamber, yielding 2.9 ± 0.2-log variation in SARS-CoV-2 inactivation. UV-C dose at several on-N95 locations was lower than the lowest-dose locations on the chamber floor, highlighting the importance of on-N95 dose validation. Overall, we integrate optical simulation with in-situ PCI dosimetry to relate UV-C dose and viral inactivation at specific on-N95 locations, establishing a versatile approach to characterize UV-C photoinactivation of pathogens contaminating complex substrates such as N95s.

  • Open Access
    Authors: 
    Winston T Wang; Charlotte L Zhang; Kang Wei; Ye Sang; Jun Shen; Guangyu Wang; Alexander X. Lozano;
    Publisher: Oxford University Press (OUP)
    Project: NSERC

    Abstract Within COVID-19 there is an urgent unmet need to predict at the time of hospital admission which COVID-19 patients will recover from the disease, and how fast they recover to deliver personalized treatments and to properly allocate hospital resources so that healthcare systems do not become overwhelmed. To this end, we have combined clinically salient CT imaging data synergistically with laboratory testing data in an integrative machine learning model to predict organ-specific recovery of patients from COVID-19. We trained and validated our model in 285 patients on each separate major organ system impacted by COVID-19 including the renal, pulmonary, immune, cardiac, and hepatic systems. To greatly enhance the speed and utility of our model, we applied an artificial intelligence method to segment and classify regions on CT imaging, from which interpretable data could be directly fed into the predictive machine learning model for overall recovery. Across all organ systems we achieved validation set area under the receiver operator characteristic curve (AUC) values for organ-specific recovery ranging from 0.80 to 0.89, and significant overall recovery prediction in Kaplan-Meier analyses. This demonstrates that the synergistic use of an artificial intelligence (AI) framework applied to CT lung imaging and a machine learning model that integrates laboratory test data with imaging data can accurately predict the overall recovery of COVID-19 patients from baseline characteristics.

  • Open Access
    Authors: 
    Kailyn J. Wanhella; Carlos Fernandez-Patron;
    Publisher: Elsevier BV
    Project: NSERC

    Coronavirus Disease 2019 (COVID-19) is caused by the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) - the culprit of an ongoing pandemic responsible for the loss of over 3 million lives worldwide within a year and a half. While the majority of SARS-CoV-2 infected people develop no or mild symptoms, some become severely ill and may die from COVID-19-related complications. In this review, we compile and comment on a number of biomarkers that have been identified and are expected to enhance the detection, protection and treatment of individuals at high risk of developing severe illnesses, as well as enable the monitoring of COVID-19 prognosis and responsiveness to therapeutic interventions. Consistent with the emerging notion that the majority of COVID-19 deaths occur in older and frail individuals, we researched the scientific literature and report the identification of a subset of COVID-19 biomarkers indicative of increased vulnerability to developing severe COVID-19 in older and frail patients. Mechanistically, increased frailty results from reduced disease tolerance, a phenomenon aggravated by ageing and comorbidities. While biomarkers of ageing and frailty may predict COVID-19 severity, biomarkers of disease tolerance may predict resistance to COVID-19 with socio-economic factors such as access to adequate health care remaining as major non-biomolecular influencers of COVID-19 outcomes. Graphical Abstract Figure: Biomarkers of ageing and frailty may predict COVID-19 severity as both conditions are associated with reduced disease tolerance - the host’s defense mechanisms to limit tissue damage or reduce immunopathology induced by the infection with a pathogen. While these biomolecular markers inform about the baseline ground for exacerbated viral infection, inflammaging and pre-existing comorbidities, which are common at advanced ages, as well as socio-economic conditions that affect people in underdeveloped nations and underserved communities of developed nations appear to be strong influencers of COVID-19 trajectory - particularly in older and frail individuals.ga1

  • Open Access
    Authors: 
    Wayne Vuong; Conrad Fischer; Muhammad Bashir Khan; Marco J. van Belkum; Tess Lamer; Kurtis D. Willoughby; Jimmy Lu; Elena Arutyunova; Michael A. Joyce; Holly A. Saffran; +6 more
    Publisher: Elsevier BV
    Project: NSERC , CIHR

    Replication of SARS-CoV-2, the coronavirus causing COVID-19, requires a main protease (Mpro) to cleave viral proteins. Consequently, Mpro is a target for antiviral agents. We and others previously demonstrated that GC376, a bisulfite prodrug with efficacy as an anti-coronaviral agent in animals, is an effective inhibitor of Mpro in SARS-CoV-2. Here, we report structure-activity studies of improved GC376 derivatives with nanomolar affinities and therapeutic indices >200. Crystallographic structures of inhibitor-Mpro complexes reveal that an alternative binding pocket in Mpro, S4, accommodates the P3 position. Alternative binding is induced by polar P3 groups or a nearby methyl. NMR and solubility studies with GC376 show that it exists as a mixture of stereoisomers and forms colloids in aqueous media at higher concentrations, a property not previously reported. Replacement of its Na+ counter ion with choline greatly increases solubility. The physical, biochemical, crystallographic, and cellular data reveal new avenues for Mpro inhibitor design. Graphical abstract Image 1

  • Open Access English
    Authors: 
    Sabateeshan Mathavarajah; Graham Dellaire;
    Publisher: Oxford University Press
    Project: NSERC

    Abstract SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2) has been reported to infect domesticated animals in a species-specific manner, where cats were susceptible but not dogs. Using the recently published crystal structure of the SARS-CoV-2 spike protein complexed with the human host cell receptor ACE2, we characterized the structure and evolution of ACE2 in several of these species and identify a single interacting amino acid residue conserved between human and Felidae ACE2 but not in Canidae that correlates with virus susceptibility. Using computational analyses we describe how this site likely affects ACE2 targeting by the virus. Thus, we highlight how evolution-based approaches can be used to form hypotheses and study animal transmission of such viruses in the future. Lay summary: Recently, the virus that causes COVID-19 was shown to transmit to companion animals. A single genetic change in the host receptor for the virus inherited in cats, but not dogs, correlates with feline susceptibility. With human-to-cat transmission of COVID-19 confirmed, such information can inform public health policy regarding companion animals.

  • Open Access
    Authors: 
    Sandra Isabel; Lucía Graña-Miraglia; Jahir M. Gutierrez; Cedoljub Bundalovic-Torma; Helen E. Groves; Marc R. Isabel; Ali Reza Eshaghi; Samir N. Patel; Jonathan B. Gubbay; Tomi Poutanen; +2 more
    Publisher: Cold Spring Harbor Laboratory
    Country: United Kingdom
    Project: CIHR , NSERC

    The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), was declared on March 11, 2020 by the World Health Organization. As of the 31st of May, 2020, there have been more than 6 million COVID-19 cases diagnosed worldwide and over 370,000 deaths, according to Johns Hopkins. Thousands of SARS-CoV-2 strains have been sequenced to date, providing a valuable opportunity to investigate the evolution of the virus on a global scale. We performed a phylogenetic analysis of over 1,225 SARS-CoV-2 genomes spanning from late December 2019 to mid-March 2020. We identified a missense mutation, D614G, in the spike protein of SARS-CoV-2, which has emerged as a predominant clade in Europe (954 of 1,449 (66%) sequences) and is spreading worldwide (1,237 of 2,795 (44%) sequences). Molecular dating analysis estimated the emergence of this clade around mid-to-late January (10 - 25 January) 2020. We also applied structural bioinformatics to assess D614G potential impact on the virulence and epidemiology of SARS-CoV-2. In silico analyses on the spike protein structure suggests that the mutation is most likely neutral to protein function as it relates to its interaction with the human ACE2 receptor. The lack of clinical metadata available prevented our investigation of association between viral clade and disease severity phenotype. Future work that can leverage clinical outcome data with both viral and human genomic diversity is needed to monitor the pandemic.

  • Open Access
    Authors: 
    Vitor Serrão; Jeffrey E. Lee;
    Publisher: Elsevier BV
    Project: CIHR , NSERC

    In this issue of Cell Host & Microbe, Lu et al. utilize single-molecule FRET to reveal the conformation dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, showing transitions from a closed ground state to the open receptor-accessible conformation via an on-path intermediate. These insights into spike conformations will facilitate rational immunogen design.

  • Open Access English
    Authors: 
    Timothy J. Tse; Sarah Purdy; Jianheng Shen; Fina B Nelson; Rana Mustafa; Daniel J. Wiens; Martin J. T. Reaney;
    Publisher: Elsevier
    Project: NSERC

    Alcohol-based hand rubs (ABHRs) formulated with technical-grade ethanol were temporarily permitted in Canada and the U.S beginning April 2020 to meet the current demand due to COVID-19. ABHRs formulated with technical-grade ethanol are low risk for general use. In this review, we discuss the toxicity of common contaminants found in technical-grade ethanol, as well as contaminants that may have been introduced into the products during formulation and packaging of ABHRs. Although primary route of exposure is via dermal absorption and inhalation, there have been reported elevated concerns regarding to ingestion of ABHRs. Overall, the highest risks were associated with methanol (for its toxicity), ethyl acetate (skin defattening), and acetaldehyde (carcinogenic and teratogenic). For these reasons Health Canada and the United States Food and Drug Administration have issued recalls on products containing some of these contaminants. More vigilant policing by regulatory agencies and general product users are required to ensure compliance, safety, and efficacy of these new products, as demand continue to rise during this unprecedented pandemic. Highlights • Alcohol-based hand rubs formulated with technical-grade ethanol can increase exposure to alcoholic impurities. • Inexperienced manufacturers may introduce additional contaminants into the product. • More vigilant policing should be employed to ensure compliancy, safety and efficacy. Graphical abstract

  • Open Access
    Authors: 
    Andrew W. Park; Maxwell J. Farrell; John Paul Schmidt; Shan Huang; Tad A. Dallas; Paula Pappalardo; John M. Drake; Patrick R. Stephens; Robert Poulin; Charles L. Nunn; +1 more
    Publisher: The Royal Society
    Project: NSERC

    The distribution of parasites across mammalian hosts is complex and represents a differential ability or opportunity to infect different host species. Here, we take a macroecological approach to investigate factors influencing why some parasites show a tendency to infect species widely distributed in the host phylogeny (phylogenetic generalism) while others infect only closely related hosts. Using a database on over 1400 parasite species that have been documented to infect up to 69 terrestrial mammal host species, we characterize the phylogenetic generalism of parasites using standard effect sizes for three metrics: mean pairwise phylogenetic distance (PD), maximum PD and phylogenetic aggregation. We identify a trend towards phylogenetic specialism, though statistically host relatedness is most often equivalent to that expected from a random sample of host species. Bacteria and arthropod parasites are typically the most generalist, viruses and helminths exhibit intermediate generalism, and protozoa are on average the most specialist. While viruses and helminths have similar mean pairwise PD on average, the viruses exhibit higher variation as a group. Close-contact transmission is the transmission mode most associated with specialism. Most parasites exhibiting phylogenetic aggregation (associating with discrete groups of species dispersed across the host phylogeny) are helminths and viruses.