SynthesismSphere2023
Cell-intrinsic and -extrinsic effects of SARS-CoV-2 RNA on pathogenesis: single-cell meta-analysis.
Synthesis in mSphere, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- HMGB1-mediated formation of IL-33-abundant NETs drives lung-to-kidney injury in severe pneumonia-associated acute kidney injury.JCI insight · 2026Article
- Think Locally, Act Globally: Resolving the Peripheral Immune Milieu in Bacterial Pneumonia.American journal of respiratory and critical care medicine · 2025Article
- Applications and techniques of single-cell RNA sequencing across diverse species.Briefings in bioinformatics · 2025Review
- SARS-CoV-2 variants mediated tissue-specific metabolic reprogramming determines the disease pathophysiology in a hamster model.Brain, behavior, and immunity · 2025Article
- Article
- Emerging role of complement in COVID-19 and other respiratory virus diseases.Cellular and molecular life sciences : CMLS · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Single-cell RNA-seq has been used to characterize human COVID-19. To determine if preclinical models successfully mimic the cell-intrinsic and -extrinsic effects of severe disease, we conducted a meta-analysis of single-cell data across five model species. To assess whether dissemination of viral RNA in lung cells tracks pathology and results in cell-intrinsic and -extrinsic transcriptomic changes in COVID-19. We conducted a meta-analysis by analyzing six publicly available, scRNA-seq data sets. We used dual mapping (host and virus) and differential gene expression analyses to compare viral
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.