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Thrombocytopenia alters early but not late repair in a mouse model of Achilles tendon injury

2009· article· en· W1987638402 on OpenAlexaff
Charles Godbout, Rosalie Bilodeau, Patrice Bouchard, Jérôme Frenette

Bibliographic record

VenueWound Repair and Regeneration · 2009
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversité LavalCentre hospitalier de l'Université LavalCentre de Recherche Industrielle du QuébecCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsPlateletAchilles tendonTendonPlaceboMedicineAngiogenesisSurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Besides their hemostatic function, platelets can express key factors involved in tissue healing. However, the role of platelets in tendon healing following acute injury is poorly understood. We investigated this role by injecting male C57BL/6 mice with an antiplatelet antibody to induce thrombocytopenia. Placebo animals received serum only. The right Achilles tendon was sectioned and sutured using the 8-strand technique that allows immediate weight bearing. Platelet depletion did not alter the accumulation of neutrophils and macrophages or cell proliferation. A slight increase in vascularization was observed 7 days postinjury in tendons from thrombocytopenic mice relative to placebo animals, but the effect had disappeared by day 14. Furthermore, collagen content had a tendency to decrease in Achilles tendons under thrombocytopenia when compared with placebo treatment at 7 days posttrauma. This was correlated with a decline in maximal stress sustained by tendons at day 14 but not after 28 days. The impact of thrombocytopenia was otherwise negligible, as force relaxation and stiffness were similar in the two groups. Our findings demonstrate that platelets modulate early tendon repair following rupture, although the effect is limited over time. Nevertheless, platelets are not essential for the recruitment of inflammatory cells, proliferation, angiogenesis, and tendon maturation.

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 score0.156
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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