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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

AbstractDue to frequent and often severe lung affections caused by COVID-19, murine models of acute respiratory distress syndrome (ARDS) are increasingly used in experimental lung research. The one induced by a single lipopolysaccharide (LPS) exposure is practical. However, whether it is preferable to administer LPS intranasally or intratracheally remains an open question. Herein, female C57Bl/6 J mice were exposed intranasally or intratracheally to one dose of either saline or 3 mg/kg of LPS. They were studied 24 h later. The groups treated with LPS, either intranasally or intratracheally, exhibited a pronounced neutrophilic inflammation, signs of lung tissue damage and protein extravasation into the alveoli, and mild lung dysfunction. The magnitude of the response was generally not different between groups exposed intranasally versus intratracheally. However, the variability of some the responses was smaller in the LPS-treated groups exposed intranasally versus intratracheally. Notably, the saline-treated mice exposed intratracheally demonstrated a mild neutrophilic inflammation and alterations of the airway epithelium. We conclude that an intranasal exposure is as effective as an intratracheal exposure in a murine model of ARDS induced by LPS. Additionally, the groups exposed intranasally demonstrated less variability in the responses to LPS and less complications associated with the sham procedure.

Abstract Background Human rhinovirus (HRV) infections are the primary cause of the common cold and are a major trigger for exacerbations of lower airway diseases, such as asthma and chronic obstructive pulmonary diseases. Although human bronchial epithelial cells (HBE) are the natural host for HRV infections, much of our understanding of how HRV replicates and induces host antiviral responses is based on studies using non-airway cell lines (e.g. HeLa cells). The current study examines the replication cycle of HRV, and host cell responses, in highly differentiated cultures of HBE. Methods Highly differentiated cultures of HBE were exposed to initial infectious doses ranging from 104 to 101 50% tissue culture-infective dose (TCID50) of purified HRV-16, and responses were monitored up to 144 h after infection. Viral genomic RNA and negative strand RNA template levels were monitored, along with levels of type I and II interferons and selected antivirals. Results Regardless of initial infectious dose, relatively constant levels of both genomic and negative strand RNA are generated during replication, with negative strand copy numbers being10,000-fold lower than those of genomic strands. Infections were limited to a small percentage of ciliated cells and did not result in any overt signs of epithelial death. Importantly, regardless of infectious dose, HRV-16 infections were cleared by HBE in the absence of immune cells. Levels of type I and type III interferons (IFNs) varied with initial infectious dose, implying that factors other than levels of double-stranded RNA regulate IFN induction, but the time-course of HRV-16 clearance HBE was the same regardless of levels of IFNs produced. Patterns of antiviral viperin and ISG15 expression suggest they may be generated in an IFN-independent manner during HRV-16 infections. Conclusions These data challenge a number of aspects of dogma generated from studies in HeLa cells and emphasize the importance of appropriate cell context when studying HRV infections.

Abstract The world is still struggling in controlling and containing the spread of the COVID-19 pandemic caused by the SARS-CoV-2 virus. The medical conditions associated with SARS-CoV-2 infections have resulted in a surge in the number of patients at clinics and hospitals, leading to a significantly increased strain on healthcare resources. As such, an important part of managing patients with SARS-CoV-2 infections within the clinical workflow is severity assessment, which is often conducted with the use of chest x-ray (CXR) images. In this work, we introduce COVID-Net CXR-S, a convolutional neural network for predicting the airspace severity of a SARS-CoV-2 positive patient based on a CXR image of the patient's chest. More specifically, we leveraged transfer learning to transfer representational knowledge gained from over 16,000 CXR images from a multinational cohort of over 15,000 patient cases into a custom network architecture for severity assessment. Experimental results with a multi-national patient cohort curated by the Radiological Society of North America (RSNA) RICORD initiative showed that the proposed COVID-Net CXR-S has potential to be a powerful tool for computer-aided severity assessment of CXR images of COVID-19 positive patients. Furthermore, radiologist validation on select cases by two board-certified radiologists with over 10 and 19 years of experience, respectively, showed consistency between radiologist interpretation and critical factors leveraged by COVID-Net CXR-S for severity assessment. While not a production-ready solution, the ultimate goal for the open source release of COVID-Net CXR-S is to act as a catalyst for clinical scientists, machine learning researchers, as well as citizen scientists to develop innovative new clinical decision support solutions for helping clinicians around the world manage the continuing pandemic.

Abstract A considerable number of individuals infected by COVID-19 died in self-isolation. This paper uses a graphical inference method to examine if patients were endogenously assigned to self-isolation during the early phase of COVID-19 epidemic in Ontario. The endogeneity of patient assignment is evaluated from a dependence measure revealing relationships between patients’ characteristics and their location at the time of death. We test for absence of assignment endogeneity in daily samples and study the dynamic of endogeneity. This methodology is applied to patients’ characteristics, such as age, gender, location of the diagnosing health unit, presence of symptoms, and underlying health conditions.