MétaCan
Menu
Back to cohort
Record W3043660593 · doi:10.3390/cells9071694

What Have In Vitro Co-Culture Models Taught Us about the Contribution of Epithelial-Mesenchymal Interactions to Airway Inflammation and Remodeling in Asthma?

2020· review· en· W3043660593 on OpenAlexafffund
Emmanuel T. Osei, Steven Booth, Tillie‐Louise Hackett

Bibliographic record

VenueCells · 2020
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMitacsMichael Smith Health Research BC
KeywordsMesenchymal stem cellInflammationCrosstalkExtracellular matrixImmunologyAsthmaLungPathogenesisBiologyCell biologyMedicinePathology

Abstract

fetched live from OpenAlex

As the lung develops, epithelial-mesenchymal crosstalk is essential for the developmental processes that drive cell proliferation, differentiation, and extracellular matrix (ECM) production within the lung epithelial-mesenchymal trophic unit (EMTU). In asthma, a number of the lung EMTU developmental signals have been associated with airway inflammation and remodeling, which has led to the hypothesis that aberrant activation of the asthmatic EMTU may lead to disease pathogenesis. Monoculture studies have aided in the understanding of the altered phenotype of airway epithelial and mesenchymal cells and their contribution to the pathogenesis of asthma. However, 3-dimensional (3D) co-culture models are needed to enable the study of epithelial-mesenchymal crosstalk in the setting of the in vivo environment. In this review, we summarize studies using 3D co-culture models to assess how defective epithelial-mesenchymal communication contributes to chronic airway inflammation and remodeling within the asthmatic EMTU.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.058
GPT teacher head0.400
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations46
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCellsSame topicNeonatal Respiratory Health ResearchFrench-language works237,207