COMING SOON

1.  Persistence of viral RNA, pneumocyte syncytia and thrombosis are hallmarks of advanced COVID-19 pathology (Bussani et al., 2020; EBioMedicine)

This interesting clinical report look at post-mortem tissues of 41 individuals that died from COVID19, which serves as valuable information on better understanding the pathology of the disease.

The authors observed alveolar damage i.e. damage to the air sacs of the lungs in all individuals, which is unsurprisingly. But nonetheless, it is still important to see the physical damage the SARS-CoV-2 virus can do to the lungs. The damaged lungs showed a tan-grey colour-ed solid parenchyma filled with hemorrhagic areas and loss of air spaces.

What is interesting is that more than half of the individuals had blood clot formation in the lung micro and marovasculature (thrombosis) with presence of viral RNA in both the pneumocytes (cells lining the air sacs) and endothelial cells. This thrombosis caused extensive lung infarction (death of lung tissues due to lack of blood flow).

 The authors also observed the presence of many dysmorphic pneumocytes often forming syncytial elements indicative of abnormal fusion of damaged cells. The authors did not find clear signs of viral infections in the heart, liver and kidney.  

 2. Inflammatory Biomarker Trends Predict Respiratory Decline in COVID-19 Patients (Mueller et al., 2020; Cell Rep Medicine)

This article describes the use of a plausible biomarker C-reactive protein (CRP) to predict respiratory deterioration in COVID19 patients. CRP is produced in the liver and acts as a marker of inflammation. Therefore, CRP test is routinely used in bloodwork to detect presence of infections or other medical conditions such as heart attacks.

The authors found that CRP levels in COVID19 patients correlates with disease severity which is determined by the severity of acute hypoxemic respiratory failure. This means that the higher CRP levels COVID19 patients present at admission, the more severe the acute hypoxemic respiratory failure.

CRP levels in patients were found to be dynamic; with CRP levels peaking within 10 days of onset of symptoms (to around 300mg/L). Severe patients showed sharp early rise in CRP levels while mild patients had a low plateau which decreases steadily.

The authors show that the admission CRP levels (D0) and change in CRP from day 0 and 1 are able to predict the need for respiratory support in COVID19 patients.

This has important relevance in stratifying the risk of patients suffering from severe respiratory failure that requires intubation. That way, at risk patients can perhaps be prioritized for care and treatment.

1. Human lung stem cell-based alveolospheres provide insights into SARS-CoV-2 mediated interferon responses and pneumocyte dysfunction (Katsura et al., 2020; Cell Stem Cell)

This paper describes the utilization of a novel cellular model called alveolospheres to study SARS-CoV-2 infection. These 3D alveolospheres were derived from human type 2 alveolar epithelial cells (AT2) isolated from a healthy lung and cultured in a chemically-defined condition. These alveolospheres can then be induced to differentiate into type 1 alveolar epithelial cells (AT1).

Alveolospheres-derived AT2 cells express viral receptors and can be infected by SARS-CoV-2 viruses. After being infected for 2 days, genome-wide transcriptome. Unsurprisingly, interferon (IFN) and inflammatory pathways were observed to be upregulated in infected cells.

In addition, genes coding for surfactant proteins (produced by alveolar cells to reduce surface tension during breathing) were found to be significantly reduced in infected cells. Infected cells were also observed to undergo apoptosis.

The authors went on to compare their data with publicly available single-cell RNA sequencing data of COVID19 patients. They were able to show striking similarities between their data and those of COVID19 patients indicating that their alveolospheres model is able to recapture COVID19 pathogenesis in the lungs.

This paper shows the tremendous potential of cell-based models for studying SARS-CoV-2 infection and COVID19 pathogenesis. Of course, this model also serves as a good platform to treat different drugs and therapeutics.

2.    Seasonality and uncertainty in global COVID-19 growth rates (Merow & Urban, PNAS)

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This epidemiology paper describes a prediction model for rates of COVID19 based on the weather. The prediction is largely based on data from the first four months of the global pandemic (Jan to April 2020).

They predicted that COVID19 growth rate will peak at low or intermediate temperatures. High humidity may also lower COVID19 growth rate by limiting transmission of virus through aerosols.

One interesting factor considered is UV light, which was found to have the strongest effect on COVID19 growth. UV light could serve to irradiate (destroy by strong UV light) virus particles or could boost human immunity by encouraging production of vitamin D. This means that sunny days might decrease outdoor transmission of SARS-CoV-2.

Based on their model, they predict that COVID19 spread will decline across the Northern Hemisphere in the summer, remain the same in the tropics and increase in the Southern Hemisphere due to shorter days (lesser overall UV light). By September, they predicted that the declining daylight will lead to increase COVID19 spread in the Northern Hemisphere until a peak in Winter (Dec to Jan).