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EARLY PATHOLOGICAL REMODELLING EVENTS, ACTORS AND REGULATORS IN OVERUSED SUPRASPINATUS TENDON

2013· article· en· W2064428870 on OpenAlexaff
Mohamed Attia, Alex Scott, Suzanne Ménashi, Dulce Papy-García, Isabelle Martelly, Marie‐Claude Tassoni

Bibliographic record

VenueBritish Journal of Sports Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTendinopathyAggrecanRotator cuffZymographyMedicineExtracellular matrixTendonGlycosaminoglycanMatrix metalloproteinasePathologyContext (archaeology)Keratan sulfateWestern blotChemistryBiochemistryInternal medicineOsteoarthritisChondroitin sulfateAnatomyBiology

Abstract

fetched live from OpenAlex

Introduction Tendon disorders due to overuse during professional activity, sport or ageing are a common cause of rheumatologic consultation and frequently affect the supraspinatus of the rotator cuff.1 Medical care comes often when tendinopathy has reached a chronic pain level or when rupture has occurred. Despite high social and financial cost of this pathology, the early pathological mechanism is not well known. Using a rat model of supraspinatus overuse,2 we aimed at deciphering the early events involved in extracellular matrix (ECM) remodelling in the tendon announcing a deleterious pathology in relationship with the inflammatory context. Methods Anabolic and catabolic biochemical analyses were performed on supraspinatus tendons from male Sprague-Dawley rats subjected to daily downhill treadmill running and control rats. Transcripts were measured by semi-quantitative RT-PCR and proteins determined by Western Blot. Total GAGs (glycosaminoglycans) were quantified using a DiMethyl Methylene blue (DMMB) based assay and specific amounts of Chondroïtin Sulfate (CS), Dermatan Sulfate (DS) and Heparan Sulfate (HS) were determined by DMMB assay after combined pre-treatments of GAG extracts with nitrous acid and/or chondroitinase B. Immunohistochemistry on tendon sections allowed localising total GAGs by DMMB staining or specific PGs (proteoglycans) and GAGs with antibodies. Gelatinase activity of metalloproteinases (MMPs) was assayed by zymography and MMP inhibitors TIMP-1, TIMP-2 and TIMP-3 were detected with reverse gelatin zymography. MMP-2 and EMMPRIN/CD147 were detected in situ by immunolabelling. Inflammatory status was studied using a cytokine array and by immunodetection of pro-inflammatory an anti-inflammatory macrophages. Results After as soon as 2 weeks of tendon overuse, anabolic studies have shown collagen quantitative and qualitative alterations, increases in specific PGs and GAGs including aggrecan and CS, associated with an increase in the chondrogenic transcription factor sox9. These results proved that a precocious shift towards fibrocartilage occurs in the pure fibrous median zone of the tendon. Results also suggested that the cytokine HARP (Heparin Affine Regulatory Peptide) was implicated in this chondroid phenotypic change. In a catabolic study, MMP-2 and MMP-14/MT1-MMP appeared to be the sole enzyme candidates, among several MMPs tested, responsible for the observed matrix remodelling at 2 weeks. Whereas it appeared that remodelling events were not associated with inflammation in overused tendon, results suggested that the MMPs inducer EMMPRIN/CD147, which increased at 2 weeks of overuse and co-localized with MMP-2, is involved in MMP-14/MT1-MMP and MMP-2 up-regulation. Discussion This is the first report which shows specific GAGs (CS, DS, HS), together with PGs (decorin, versican, aggrecan), proteins alterations and localisation, complete with activation of specific MMPs and cytokines in early tendon overuse. These anabolic and catabolic alterations may temporarily interfere with the tendon's tensile load-bearing capacity, which could lead to more deleterious damage. Anticipated detection of these early events, some of which may be reversible, could help to develop injury prevention strategies.

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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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.267
Teacher spread0.251 · 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 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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