Evidence map›Paper›PMID 22017959›Full record

ArticleStem cell research & therapy2011

Lung stem cells--from an evolving understanding to a paradigm shift?

Mairéad Hayes, Gerard F Curley, John G Laffey

Open access · goldAbstract read
In one paragraph

Article in Stem cell research & therapy, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. 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 at 2 institutions in 1 country.

Mairéad HayesLung Biology Group, Regenerative Medicine Institute, National Centre for Biomedical Engineering Science, National University of Ireland, University Road, Galway, Ireland.
Gerard F Curley
John G Laffey
National University of Ireland · IEUniversity Hospital Galway · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ideal cell type to regenerate an acutely injured or chronically diseased lung would be a stem cell population from the patient's own lung. Consequently, extensive research efforts have focused on identifying and characterizing endogenous lung stem cells. Advances in techniques to facilitate cell isolation, labelling and tracking in vivo to determine their fate have led to the identification of several putative stem cell niches. Recently, convincing evidence has emerged for a novel stem/progenitor cell population in the submucous glands of the cartilaginous airways. These findings support the concept that there is no classical stem cell 'hierarchy' but that different progenitor populations within spatially distinct lung regions regenerate the lung epithelium adjacent to its niche. Intriguingly, recent findings challenge this concept; it was reported that the human lung may contain a primitive stem cell capable of differentiating into multiple cells of both endodermal and mesodermal lineage and of regenerating the injured lung. This suggests that a classical stem cell hierarchy may, in fact, exist in the lung. Although caution is needed in interpreting these emerging findings, the implications for our current concepts regarding lung stem cells, the insights into lung repair and regeneration, and the potential therapeutic implications are considerable.

Indexed as

AnimalsCell DifferentiationCell LineageDisease Models, AnimalEndodermHumansLungLung InjuryMesodermMiceRegenerationStem CellsTranscription FactorsTranscription Factors

Identifiers

PMID22017959
PMCPMC3308038
OpenAlexW2157187758

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.