Evidence map›Paper›PMID 32623064›Full record

ReviewCurrent opinion in microbiology2020

Perspectives in lung microbiome research.

Imran Sulaiman, Sheeja Schuster, Leopoldo N Segal

Abstract readReview
In one paragraph

Review in Current opinion in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions-a pilot study.International microbiology : the official journal of the Spanish Society for Microbiology · 2023
    Article
  10. Article
  11. Review
  12. Article
  13. 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

3 authors.

Imran SulaimanDivision of Pulmonary, Critical Care, & Sleep Medicine, Department of Medicine, New York University School of Medicine, NY, United States.
Sheeja SchusterDivision of Pulmonary, Critical Care, & Sleep Medicine, Department of Medicine, New York University School of Medicine, NY, United States.
Leopoldo N SegalDivision of Pulmonary, Critical Care, & Sleep Medicine, Department of Medicine, New York University School of Medicine, NY, United States. Electronic address: Leopoldo.Segal@nyumc.org.

Funding

Local microbiota signatures of pro-tumor immunity and checkpoint inhibition susceptibility in lung cancerR37CA244775 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Leopoldo Nicolas Segal · 2020 to 2026
$4.7M
Microbial triggers and molecular mechanisms of Th17 mediated airway inflammation-Resubmission-1R01HL125816 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI KORALOV, SERGEI BORISOVICH · 2015 to 2019
$3.3M
NCI NIH HHS R37 CA244775NHLBI NIH HHS R01 HL125816
6 · The paper itself

Abstract

Our understanding of the existence and role of the lung microbiome has grown at a slower pace than other microbiome research areas. This is likely a consequence of the original dogma that the lung was a sterile environment although there are other barriers that are worth discussing. Here we will not be conducting an exhaustive review of the current literature on the lung microbiome, but rather we will focus on what we see as some important challenges that the field needs to face in order to improve our mechanistic understanding of the lung microbiome and its role on human health.

Indexed as

MicrobiotaAnimalsBacteriaBiomedical ResearchHumansLung

Identifiers

PMID32623064
PMCPMC7744389

What OpenQuestion holds

Textmetadata
LicenceTDM
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.