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Record W3159924470 · doi:10.1111/wrr.12923

Keloid tissue analysis discredits a role for myofibroblasts in disease pathogenesis

2021· article· en· W3159924470 on OpenAlexfundno aff
Rachel E. Bell, Tanya J. Shaw

Bibliographic record

VenueWound Repair and Regeneration · 2021
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
FundersMedical Research CouncilMedical Research Council CanadaBritish Skin Foundation
KeywordsKeloidMyofibroblastPathogenesisMedicineDiseasePathologyFibrosis

Abstract

fetched live from OpenAlex

Myofibroblasts, renowned for their contractility and extracellular matrix production, are widely considered the key effector cells for nearly all scars resulting from tissue repair processes, ranging from normal scars to extreme fibrosis. For example, it is often assumed that myofibroblasts underpin the characteristics of keloid scars, which are debilitating pathological skin scars lacking effective treatments because of a poor understanding of the disease mechanisms. Here, we present primary and published transcriptional and histological evidence that myofibroblasts are not consistently present in primary keloid lesions, and when alpha-smooth muscle actin (αSMA)-positive cells are detected, they are not greater in number or expressing more αSMA than in normal or hypertrophic scars. In conclusion, keloid scars do not appear to require αSMA-positive myofibroblasts; continuing to consider keloids on a quantitative spectrum with normal or hypertrophic scars, with αSMA serving as a biomarker of disease severity, is hindering advancement of understanding and therapy development.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.301
Teacher spread0.286 · 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.

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

Citations21
Published2021
Admission routes1
Has abstractyes

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