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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.

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

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.

High-throughput detection strategies for antibodies against SARS-CoV-2 in patients recovering from COVID-19, or in vaccinated individuals, are urgently required during this ongoing pandemic. Serological assays are the most widely used method to measure antibody responses in patients. However, most of the current methods lack the speed, stability, sensitivity, and specificity to be selected as a test for worldwide serosurveys. Here, we demonstrate a novel NanoBiT-based serological assay for fast and sensitive detection of SARS-CoV-2 RBD-specific antibodies in sera of COVID-19 patients. This assay can be done in high-throughput manner at 384 samples per hour and only requires a minimum of 5 μL of serum or 10 ng of antibody. The stability of our NanoBiT reporter in various temperatures (4–42 °C) and pH (4–12) settings suggests the assay will be able to withstand imperfect shipping and handling conditions for worldwide seroepidemiologic surveillance in the post-vaccination period of the pandemic. Our newly developed rapid assay is highly accessible and may facilitate a more cost-effective solution for seroconversion screening as vaccination efforts progress.

A slowdown in global trade activity due to COVID-19 has led to a reduction in commercial shipping traffic into the Port of Vancouver. The Ocean Networks Canada observatory system provides researchers real-time access to oceanographic data from a wide range of instruments including hydrophones located along the offshore and inshore approaches to Vancouver. Measurements of power spectral density at 100 Hz from four of these bottom mounted hydrophones are presented, along with AIS data and shipping and trade statistics to assess to what extent the economic impact of COVID-19 can be observed acoustically and in near real-time. The quarterly trend in median weekly noise power in the shipping band of frequencies shows that a reduction in noise commensurate with the economic slowdown has been observed at three of the four hydrophone stations.

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.

AbstractThe COVID-19 pandemic has impacted the mental health, physical activity, and sedentary behavior of citizens worldwide. Using an online survey with 1669 respondents, we sought to understand why and how by querying about perceived barriers and motivators to physical activity that changed because of the pandemic, and how those changes impacted mental health. Consistent with prior reports, our respondents were less physically active (aerobic activity, −11%, p <0.05; strength-based activity, −30%, p<0.01) and more sedentary (+11%, p<0.01) during the pandemic as compared to 6-months before. The pandemic also increased psychological stress (+22%, p <0.01) and brought on moderate symptoms of anxiety and depression. Respondents’ whose mental health deteriorated the most were also the ones who were least active (depression r = −.21, p<0.01; anxiety r = −.12, p<0.01). The majority of respondents were unmotivated to exercise because they were too anxious (+8%, p <0.01), lacked social support (+6%, p =<0.01), or had limited access to equipment (+23%, p <0.01) or space (+41%, p <0.01). The respondents who were able to stay active reported feeling less motivated by physical health outcomes such as weight loss (−7%, p<0.01) or strength (−14%, p<0.01) and instead more motivated by mental health outcomes such as anxiety relief (+14%, p <0.01). Coupled with previous work demonstrating a direct relationship between mental health and physical activity, these results highlight the potential protective effect of physical activity on mental health and point to the need for psychological support to overcome perceived barriers so that people can continue to be physically active during stressful times like the pandemic.

Intending to shield front-liners who are currently exposed to COVID-19, and because of the lack of proper powered air-purifying respirator, this study shows the design and development of an open-source ergonomic respirator with a washable filter. This device has an estimated working time of 12 h, and the tests' airflow always showed a value over 4.5 cubic feet per minute, a higher value than the national institute for occupational safety and health specification for full-face closed respirators. The proposal relies on 3D printing technology for all the custom-design parts and usages easy-to-access components for the rest of the material. The mask for the APRPAPR in the article has a defogging feature, 180 degrees of viewing angle, an ergonomic profile, and no obstruction on the mouth to show the user's full face. This respirator has an estimated cost of 318 USD, approximately one-third of the market's price of well-known brands. Graphical abstract

Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 2 million lives, since its emergence in late 2019. This highly contagious disease can easily spread, and if not controlled in a timely fashion, can rapidly incapacitate healthcare systems. The current standard diagnosis method, the Reverse Transcription Polymerase Chain Reaction (RT- PCR), is time consuming, and subject to low sensitivity. Chest Radiograph (CXR), the first imaging modality to be used, is readily available and gives immediate results. However, it has notoriously lower sensitivity than Computed Tomography (CT), which can be used efficiently to complement other diagnostic methods. This paper introduces a new COVID-19 CT scan dataset, referred to as COVID-CT-MD, consisting of not only COVID-19 cases, but also healthy and participants infected by Community Acquired Pneumonia (CAP). COVID-CT-MD dataset, which is accompanied with lobe-level, slice-level and patient-level labels, has the potential to facilitate the COVID-19 research, in particular COVID-CT-MD can assist in development of advanced Machine Learning (ML) and Deep Neural Network (DNN) based solutions. Measurement(s) Low Dose Computed Tomography of the Chest • viral infectious disease Technology Type(s) digital curation • image processing technique Factor Type(s) sex • gender • age group • weight • clinical characteristics • covid-19 RT-PCR result • follow-up data Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13583015

Abstract Background Single stranded ribonucleic acid (ssRNA) binds to toll-like receptor (TLR)7 leading to recruitment of immune cells and production of pro-inflammatory cytokines, which has been shown in mammals. In chickens, synthetic ssRNA analog, resiquimod, has been shown to elicit antiviral response against infectious bursal disease virus infection. The objective of this study was to determine the innate host responses activated by the pre-hatch in ovo administration of resiquimod against infectious laryngotracheitis virus (ILTV) infection in chickens post-hatch. Results First, we observed that in ovo treatment of resiquimod at embryo day (ED) 18 increases macrophage recruitment in respiratory and gastrointestinal tissues of chicken day 1 post-hatch in addition to interleukin (IL)-1β in lungs. Second, we observed that in ovo treatment of resiquimod reduces ILTV cloacal shedding at 7 days post-infection (dpi) when challenged at day 1 post-hatch coinciding with higher macrophage recruitment. In vitro, we found that resiquimod enhances production of nitric oxide (NO) and IL-1β and not type 1 interferon (IFN) activity in avian macrophages. Although, the antiviral response against ILTV is associated with the enhanced innate immune response, it is not dependent on any of the innate immune mediators observed as has been shown in vitro using avian macrophage. Conclusion This study provides insights into the mechanisms of antiviral response mediated by resiquimod, particularly against ILTV infection in chicken.