Evidence map›Paper›PMID 30372120›Full record

ReviewAmerican journal of respiratory cell and molecular biology2019

How the Respiratory Epithelium Senses and Reacts to Influenza Virus.

Kambez H Benam, Laura Denney, Ling-Pei Ho

Abstract readReview
In one paragraph

Review in American journal of respiratory cell and molecular biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Activation of TREK-1 (American journal of physiology. Lung cellular and molecular physiology · 2023
    Article
  9. Review
  10. Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  11. Pharmaceuticals (Basel, Switzerland) · 2021
    Article
  12. Review
  13. Toll-Interacting Protein in Pulmonary Diseases. Abiding by the Goldilocks Principle.American journal of respiratory cell and molecular biology · 2021
    Review
  14. Article
  15. Age-Dependent Differences in T-Cell Responses to Influenza A Virus.American journal of respiratory cell and molecular biology · 2020
    Review
  16. Article
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

3 authors.

Kambez H Benam1 Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado - Anschutz Medical Campus, Aurora, Colorado.ORCID 0000-0001-9117-3959
Laura Denney3 Translational Lung Immunology Programme, MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.
Ling-Pei Ho3 Translational Lung Immunology Programme, MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.

Funding

Tissue Bank and Biomarkers CoreP50CA058187 · NCI · UNIVERSITY OF COLORADO DENVER · PI NEMENOFF, RAPHAEL A. · 1992 to 2018
$43.8M
Medical Research Council G0600371NCI NIH HHS P50 CA058187
6 · The paper itself

Abstract

The human lung is constantly exposed to the environment and potential pathogens. As the interface between host and environment, the respiratory epithelium has evolved sophisticated sensing mechanisms as part of its defense against pathogens. In this review, we examine how the respiratory epithelium senses and responds to influenza A virus, the biggest cause of respiratory viral deaths worldwide.

Indexed as

HumansInfluenza A virusInfluenza, HumanLungRespiratory Mucosainfluenza A virusrespiratory epitheliumviral sensing

Identifiers

PMID30372120
PMCPMC6943877

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.