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Record W2089103717 · doi:10.1007/s12079-014-0221-2

Activation of latent TGFβ by αvβ1 integrin: of potential importance in myofibroblast activation in fibrosis

2014· article· en· W2089103717 on OpenAlexaff
Andrew Leask, James Hutchenreuther

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2014
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsMyofibroblastIntegrinFibrosisIn vivoMedicineEx vivoTransforming growth factorCancer researchImmunologyCell biologyPathologyBiologyReceptorInternal medicine

Abstract

fetched live from OpenAlex

Cell-mediated activation of latent TGF-β1 is intimately involved with tissue repair and fibrosis in all organs. Previously, it was shown that the integrin β1 subunit was required for activation of latent TGF-β1 and skin fibrosis. A recent study by Henderson and colleagues (Nature Medicine 19,1617-1624, 2013) used three different in vivo models of fibrosis to show that integrin αv subunit was required for fibrogenesis. Through a process of elimination, the authors conclude that in vivo, the little-studied αvβ1 could be the major integrin responsible for TGF-β activation by myofibroblasts. Thus targeting this integrin might be a useful therapy for fibrosis.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.262
Teacher spread0.247 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations8
Published2014
Admission routes1
Has abstractyes

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