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Early voluntary exercise does not promote healing in a rat model of Achilles tendon injury

2006· article· en· W1995080334 on OpenAlexaff
Charles Godbout, Oliver Ang, Jérôme Frenette

Bibliographic record

VenueJournal of Applied Physiology · 2006
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsAchilles tendonMedicineTendonConnective tissueTendinopathyFibrosisSurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Mechanical stress is an important modulator of connective tissue repair. However, the effects on tendon healing are very poorly defined, preventing optimal use of mechanical stress. We hypothesized that early voluntary exercise initially retards tendon repair but results in a faster recovery rate at longer term. Male Wistar rats were injured by a collagenase injection in the Achilles tendon, and exercise was voluntarily performed on a running wheel. We observed the persistent presence of neutrophils in injured tendons of rats that began exercise immediately after the trauma [injured + early exercise (Inj+EEx)]. Early exercise also increased the concentration of ED1(+) macrophages in injured tendons after 3 and 7 days compared with ambulatory injured rats (Inj). Similar results were obtained with the subset of ED2(+) macrophages in the tendon core 3 days after the collagenase injection. Furthermore, collagen content returned to normal values more rapidly in the Inj+EEx tendons than in the Inj group, but this was not associated with an increase in cell proliferation. Surprisingly, Inj+EEx tendons roughly displayed lower stiffness and force at rupture point relative to Inj tendons at day 28. Injured tendons of rats that began exercise only from day 7 had better mechanical properties than those of early-exercised rats 28 days postinjury. We speculate that the persistence of the inflammatory response and undue mechanical loading in the Inj+EEx tendons led to fibrosis and a loss of tendon function.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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 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

Citations36
Published2006
Admission routes1
Has abstractyes

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