Neutrophils as a pallbearer for SARS-CoV-2 disease burden
Notice bibliographique
Résumé
We read the Article by Bernadette Schurink and colleagues,1Schurink B Roos E Radonic T et al.Viral presence and immunopathology in patients with lethal COVID-19: a prospective autopsy cohort study.Lancet Microbe. 2020; 1: e290-e299Summary Full Text Full Text PDF PubMed Scopus (364) Google Scholar and were impressed, similar to the authors, with the heterogeneity of the invasion of end organs by neutrophils, despite a severe and systemic COVID-19 disease burden among the study sample. In other words, it is unclear why some organ systems among patients with COVID-19 are affected more extensively compared with others, despite the assertion of this Article that organ damage is predicated by a reactive infiltrate, perhaps independently of the presence of the replication of active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the specific tissue. Because there is evidence to suggest that the SARS-CoV-2 entry receptor,2Li G He X Zhang L et al.Assessing ACE2 expression patterns in lung tissues in the pathogenesis of COVID-19.J Autoimmune. 2020; 112102463Crossref PubMed Scopus (214) Google Scholar ACE2, also has a role in mediating immune cell activity,3Tomar B Anders H-J Desai J Mulay SR Neutrophils and neutrophil extracellular traps drive necroinflammation in COVID-19.Cells. 2020; 91383Crossref Scopus (201) Google Scholar with the use of RNAseq data from GSE1503164Desai N Neyaz A Szabolcs A et al.Temporal and spatial heterogeneity of host response to SARS-CoV-2 pulmonary infection.medRxiv. 2020; (published online Aug 2.) (preprint)https://doi.org/10.1101/2020.07.30.20165241Google Scholar we correlated ACE2 expression from 17 lung specimens from autopsies of patients with SARS-CoV-2 normalised, and derived the ontology of the top 1% of differentially expressed genes. We found a significant correlation of ACE2 expression with neutrophil activation (p<0·0001; appendix).5Zhou Y Zhou B Pache L et al.Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.Nat Commun. 2019; 101523Crossref PubMed Scopus (6942) Google Scholar This finding provides support for the work by Schurink and colleagues, but does not conclusively establish this association. Accordingly, we wondered if Schurink and colleagues have any histological evidence within their data to suggest that variation in ACE2 might serve as a crucial intermediary to end-organ infiltration by inflammatory cells, and consequent disease severity, in response to a SARS-CoV-2 infection. We declare no competing interests. Download .pdf (.36 MB) Help with pdf files Supplementary appendix Viral presence and immunopathology in patients with lethal COVID-19: a prospective autopsy cohort studyIn patients with lethal COVID-19, an extensive systemic inflammatory response was present, with a continued presence of neutrophils and NETs. However, SARS-CoV-2-infected cells were only sporadically present at late stages of COVID-19. This suggests a maladaptive immune response and substantiates the evidence for immunomodulation as a target in the treatment of severe COVID-19. Full-Text PDF Open AccessNeutrophils as a pallbearer for SARS-CoV-2 disease burden – Authors’ replyWe thank David Twa and colleagues for their interest in our findings and agree that it is intriguing that, despite the apparent systemic responses, some organs from patients who died of COVID-19 are more affected than others by neutrophilic extracellular traps (NETs). Although to the best of our knowledge, NETs have never been studied in much detail for other respiratory viral infections, there is strong evidence from respiratory viral infections that are virulent (influenza),1,2 and also those that are less virulent (rhinovirus),3 that NETs are formed locally and even that markers of NETs can be detected systemically. Full-Text PDF Open Access
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».