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Record W1513609258 · doi:10.36253/ijae-3263

Mechanisms for Relaxin’s Modulation of MMPs and Matrix Loss in Fibrocartilages

2014· article· en· W1513609258 on OpenAlexaff
Sunil Kapila, Young Joo Park, Nisar Ahmad, Jun Hosomichi, Takayuki Hayami, Claire E. Tacon

Bibliographic record

VenueItalian Journal of Anatomy and Embryology · 2014
Typearticle
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRelaxinMatrix metalloproteinaseModulation (music)Matrix (chemical analysis)ChemistryCell biologyBiologyPhysicsHormoneBiochemistry

Abstract

fetched live from OpenAlex

shown that the fibrocartilaginous temporomandibular joint (TMJ) disc and pubic sym-physis respond to relaxin by upregulation of MMPs and loss of key matrix molecules. These responses to relaxin are enhanced by estrogen, and are also modulated by estro-gen alone. Since these fibrocartilaginous tissue are heterogeneous containing fibroblastic, chondrocytic and intermediate cell types, the responses of specific cell types to relaxin are not known. Also the direct effect of specific MMPs induced by relaxin to the loss carti-lage matrix in vivo has not been demonstrated. Our purpose was to (1) characterize cell type-specific response(s) to relaxin and estrogen; (2) identify the relaxin receptor and downstream signaling involved in relaxin’s induction of specific MMPs; (3) develop a mouse model for in vivo manipulation of hormones; and (4) identify the contribution of each of these hormones and the MMPs they regulate to in vivo matrix loss. Two each of fibroblastic and chondrocytic female mouse TMJ disc cell clones immortalized by human telomerase reverse transcriptase were isolated and charac-terized on the basis of phenotype, growth curves, and fibroblastic and chondroctytic markers, respectively. Chondrocytic cell clones had higher mRNA and protein expres-

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.011
GPT teacher head0.318
Teacher spread0.306 · 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 designTheoretical or conceptual
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

Citations2
Published2014
Admission routes1
Has abstractyes

Explore more

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