Evidence map›Paper›PMID 33398280›Full record

ArticlebioRxiv : the preprint server for biology2020

Cell-type apoptosis in lung during SARS-CoV-2 infection.

Yakun Liu, Tania M Garron, Qing Chang, Zhengchen Su, Changcheng Zhou, Eric C Gong, Junying Zheng, Yw Yin, Thomas Ksiazek, Trevor Brasel and 4 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. The role of 5-lipoxygenase in the pathophysiology of COVID-19 and its therapeutic implications.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2021
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Yakun Liu
Tania M Garron
Qing Chang
Zhengchen Su
Changcheng Zhou
Eric C Gong
Junying Zheng
Yw Yin
Thomas Ksiazek
Trevor Brasel
Yang Jin
Paul Boor
Jason E Comer
Bin Gong

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 pandemic has inspired renewed interest in understanding the fundamental pathology of acute respiratory distress syndrome (ARDS) following infection because fatal COVID-19 cases are commonly linked to respiratory failure due to ARDS. The pathologic alteration known as diffuse alveolar damage in endothelial and epithelial cells is a critical feature of acute lung injury in ARDS. However, the pathogenesis of ARDS following SRAS-CoV-2 infection remains largely unknown. In the present study, we examined apoptosis in post-mortem lung sections from COVID-19 patients and lung tissues from a non-human primate model of SARS-CoV-2 infection, in a cell-type manner, including type 1 and 2 alveolar cells and vascular endothelial cells (ECs), macrophages, and T cells. Multiple-target immunofluorescence (IF) assays and western blotting suggest both intrinsic and extrinsic apoptotic pathways are activated during SARS-CoV-2 infection. Furthermore, we observed that SARS-CoV-2 fails to induce apoptosis in human bronchial epithelial cells (i.e., BEAS2B cells) and primary human umbilical vein endothelial cells (HUVECs), which are refractory to SARS-CoV-2 infection. However, infection of co-cultured Vero cells and HUVECs or Vero cells and BEAS2B cells with SARS-CoV-2 induced apoptosis in both Vero cells and HUVECs/BEAS2B cells, but did not alter the permissiveness of HUVECs or BEAS2B cells to the virus. Post-exposure treatment of the co-culture of Vero cells and HUVECs with an EPAC1-specific activator ameliorated apoptosis in HUVECs. These findings may help to delineate a novel insight into the pathogenesis of ARDS following SARS-CoV-2 infection.

Identifiers

PMID33398280
PMCPMC7781315

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.