Evidence map›Paper›PMID 19375457›Full record

ReviewAntiviral research2009

Applications of high-throughput genomics to antiviral research: evasion of antiviral responses and activation of inflammation during fulminant RNA virus infection.

John C Kash

Abstract readReview
In one paragraph

Review in Antiviral research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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  6. Review
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  10. Transcriptomics and proteomics in the study of H1N1 2009.Genomics, proteomics & bioinformatics · 2010
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

John C KashViral Pathogenesis and Evolution Section, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD 20892-3203, USA. kashj@niaid.nih.gov
National Institutes of Health · US

Funding

Influenza Viral PathogenesisZIAAI000986 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI TAUBENBERGER, JEFFERY · 2009 to 2025
$30.0M
Intramural NIH HHS Z99 AI999999
6 · The paper itself

Abstract

Host responses can contribute to the severity of viral infection, through the failure of innate antiviral mechanisms to recognize and restrict the pathogen, the development of intense systemic inflammation leading to circulatory failure or through tissue injury resulting from overly exuberant cell-mediated immune responses. High-throughput genomics methods are now being used to identify the biochemical pathways underlying ineffective or damaging host responses in a number of acute and chronic viral infections. This article reviews recent gene expression studies of 1918 H1N1 influenza and Ebola hemorrhagic fever in cell culture and animal models, focusing on how genomics experiments can be used to increase our understanding of the mechanisms that permit those viruses to cause rapidly overwhelming infection. Particular attention is paid to how evasion of type I IFN responses in infected cells might contribute to over-activation of inflammatory responses. Reviewing recent research and describing how future studies might be tailored to understand the relationship between the infected cell and its environment, this article discusses how the rapidly growing field of high-throughput genomics can contribute to a more complete understanding of severe, acute viral infections and identify novel targets for therapeutic intervention.

Indexed as

Gene Expression ProfilingHost-Pathogen InteractionsAnimalsCell LineDisease Models, AnimalEbolavirusHumansInfluenza A Virus, H1N1 SubtypeRNA Virus Infections

Identifiers

PMID19375457
PMCPMC3457704
OpenAlexW2089467424

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.