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Record W2911757824 · doi:10.1002/jbm4.10177

EGFR Signaling: Friend or Foe for Cartilage?

2019· review· en· W2911757824 on OpenAlexaff
Ling Qin, Frank Beier

Bibliographic record

VenueJBMR Plus · 2019
Typereview
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsWestern University
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsEndochondral ossificationOsteoarthritisCartilageMedicineSignal transductionEpidermal growth factor receptorNeuroscienceBioinformaticsReceptorCancer researchCell biologyBiologyPathologyInternal medicineAnatomy

Abstract

fetched live from OpenAlex

ABSTRACT Recent studies using genetically modified mice, pharmacological approaches, and human samples have highlighted an important role for the epidermal growth factor receptor (EGFR), selected ligands, and downstream components in endochondral bone formation and joint homeostasis. Although most data demonstrate an important function of this pathway in endochondral ossification and articular cartilage growth, conflicting results on its role in osteoarthritis have been reported. In some contexts, inactivation of EGFR signaling has been shown to protect joints from surgically induced osteoarthritis, whereas in others, similar manipulations worsened joint pathology. The current review summarizes recent studies of cartilage EGFR signaling in long bone development and diseases, provides potential explanations for the reported discrepancies, and suggests directions for future work to clarify the potential of this pathway as target for osteoarthritis treatment. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

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)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.389
GPT teacher head0.528
Teacher spread0.139 · 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

Citations51
Published2019
Admission routes1
Has abstractyes

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