ArticlebioRxiv : the preprint server for biology2020
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 5 papers, 1 of them a synthesis that pooled 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.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Evaluation of the Suitability of RNAscope as a Technique to Measure Gene Expression in Clinical Diagnostics: A Systematic Review.Molecular diagnosis & therapy · 2022Pooled it
- Potent SARS-CoV-2 3C-like protease inhibitor ( +)-eupenoxide-3,6-diketone (ICJournal of natural medicines · 2025Article
- Draft genome of neotropical Bacillus thuringiensis UFT038 and its potential against lepidopteran soybean pests.Folia microbiologica · 2024Article
- Related neural networks underlie suppression of emotion, memory, motor processes as identified by data-driven analysis.BMC neuroscience · 2023Article
- i6mA-VC: A Multi-Classifier Voting Method for the Computational Identification of DNA N6-methyladenine Sites.Interdisciplinary sciences, computational life sciences · 2021Article
Corrections and comments
- Updated by
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Treatment of the cytokine release syndrome (CRS) has become an important part of rescuing hospitalized COVID-19 patients. Here, we systematically explored the transcriptional regulators of inflammatory cytokines involved in the COVID-19 CRS to identify candidate transcription factors (TFs) for therapeutic targeting using approved drugs. We integrated a resource of TF-cytokine gene interactions with single-cell RNA-seq expression data from bronchoalveolar lavage fluid cells of COVID-19 patients. We found 581 significantly correlated interactions, between 95 TFs and 16 cytokines upregulated in the COVID-19 patients, that may contribute to pathogenesis of the disease. Among these, we identified 19 TFs that are targets of FDA approved drugs. We investigated the potential therapeutic effect of 10 drugs and 25 drug combinations on inflammatory cytokine production in peripheral blood mononuclear cells, which revealed two drugs that inhibited cytokine production and numerous combinations that show synergistic efficacy in downregulating cytokine production. Further studies of these candidate repurposable drugs could lead to a therapeutic regimen to treat the CRS in COVID-19 patients.
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.