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Record W2021059909 · doi:10.1016/s0736-0266(01)00031-6

Neutrophils and macrophages accumulate sequentially following Achilles tendon injury

2001· article· en· W2021059909 on OpenAlexafffund
David Marsolais, Claude H. Côt́e, Jérôme Frenette

Bibliographic record

VenueJournal of Orthopaedic Research® · 2001
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAchilles tendonCollagenaseTendinopathyTendonInflammationMedicineMacrophagePathologyAndrologyInternal medicineChemistryEnzyme

Abstract

fetched live from OpenAlex

Structural damage and inflammation occur following tendon injury. The purpose of this study was to determine the time course of inflammatory cell accumulation in two animal models of acute tendinopathy. In the first model, rat Achilles tendons were exposed by blunt dissection, injected with collagenase and sacrificed at 1, 3, 7, 14 and 28 days. In the second model, collagenase was injected percutaneously and rats were sacrificed after 1 and 3 days. Sham animals were sacrificed at 1 and 3 days in both models. Neutrophil and ED1 macrophage populations increased by 46- and 18-fold, respectively, after 1 day in surgically exposed Achilles tendons (EAT) injected with collagenase. Neutrophils dropped by 70% while the concentration of ED1 macrophages remained constant at day 3 post-injury. Neutrophils and ED1+ macrophages returned to control values after 7 and 14 days, respectively. ED2+ macrophages showed a tendency to increase at day 28 although no significant difference was observed relative to ambulatory controls. Collagenase injected percutaneously reduced the extent of inflammation compared with operated animals. Thus, injured tendons exhibited a specific sequence of inflammatory cell accumulation which varied in intensity according to the modality used for collagenase injection.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.061
GPT teacher head0.408
Teacher spread0.347 · 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".

Quick stats

Citations157
Published2001
Admission routes2
Has abstractyes

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