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Record W2026410358 · doi:10.1002/jor.20546

Histological analysis of achilles tendons in an overuse rat model

2008· article· en· W2026410358 on OpenAlexaff
Mark Glazebrook, James R. Wright, Maxine Langman, William D. Stanish, J. Michael Lee

Bibliographic record

VenueJournal of Orthopaedic Research® · 2008
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversity of CalgaryQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsAchilles tendonTendonImmunohistochemistryCollagen fiberStainingMedicineTreadmillPathologyRat modelAnatomyInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to design an animal model that induces histological changes in Achilles tendons consistent with those cited in the literature for human Achilles tendon disease. Sprague-Dawley rats were subjected to 10 degrees uphill treadmill running on a custom-designed rodent treadmill and at a speed of 17 meters per minute for 1 h, five times per week, over a 12-week treatment period. Subsequent histological analysis revealed alterations in the rat Achilles tendon that were generally consistent with those described in the literature for diseased human tendon tissues. These features include: decreased collagen fiber organization, more intense collagen staining, and increased cell nuclei numbers. Interestingly, though, immunohistochemical cell typing suggests that the observed increased cellularity does not include a significant inflammatory component but is secondary to increased numbers of endothelial cells (i.e., vascularization) and fibroblasts. These histological features likely represent a biological repair/remodeling response resulting from overuse running.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.414
Teacher spread0.263 · 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 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

Citations124
Published2008
Admission routes1
Has abstractyes

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