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Record W1973112307 · doi:10.1586/ers.10.72

Mesenchymal stem cells for repair of the airway epithelium in asthma

2010· review· en· W1973112307 on OpenAlexafffund
Darryl A. Knight, Fábio Rossi, Tillie‐Louise Hackett

Bibliographic record

VenueExpert Review of Respiratory Medicine · 2010
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMesenchymal stem cellStem cellRespiratory epitheliumParacrine signallingMedicineProgenitor cellRegeneration (biology)ImmunologyEpitheliumAirwayCell biologyCancer researchPathologyBiologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

The airway epithelium is constantly faced with inflammatory and potentially injurious stimuli. Following damage, rapid repair mechanisms involving proliferation and differentiation of resident progenitor and stem cell pools are necessary in order to maintain a protective barrier. In asthma, evidence pointing to a compromised ability of the epithelium to properly repair and regenerate is rapidly accumulating. The consequences of this are presently unknown but are likely to have a significant impact on lung function. Mesenchymal stem cells have the potential to serve as a universal source for replacement of specific cells in several diseases and thus offer hope as a potential therapeutic intervention for the treatment of the chronic remodeling changes that occur in the asthmatic epithelium. However, controversy exists regarding whether these cells can actually home to and engraft within the airways and contribute to tissue function or whether this mechanism is necessary, since they can have potent paracrine immunomodulatory effects. This article focuses on the current knowledge about specific stem cell populations that may contribute to airway epithelial regeneration and discusses the use of mesenchymal stem cells as a potential therapeutic intervention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.454
Teacher spread0.353 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2010
Admission routes2
Has abstractyes

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