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Record W2021067536 · doi:10.3791/2176

Preparation of Rat Tail Tendons for Biomechanical and Mechanobiological Studies

2010· article· en· W2021067536 on OpenAlexafffund
Amélie Bruneau, Nadia Champagne, Paule Cousineau‐Pelletier, Gabriel Parent, Ève Langelier

Bibliographic record

VenueJournal of Visualized Experiments · 2010
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsBiomedical engineeringTendonComputer scienceStructural integrityBiologyAnatomyMedicineStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Rat tail tendons (RTTs) are a common biological model used in experimental in vitro studies in the fields of tendon physiology and tendinopathy. Working with those tissues is challenging because they are very fragile, and until now there was no rigorously detailed protocol for their isolation. Faced with these challenges, we have developed methods and instruments to facilitate manipulation of RTTs and control tissue viability, sterility and integrity. This article describes the experimental procedures used to prepare RTTs for biomechanical and mechanobiological studies. Our work is divided into four main steps: extraction, cross-sectional area measurement, rinsing and loading into the bioreactor chamber. At each step, all procedures, materials and manipulations are presented in detail so that they can be easily reproduced. Moreover, the specific instruments developed are presented: a manipulation plate used to segregate RTTs, an optic micrometer to position the tissue during the cross-sectional area measurement and an anchoring system to attach the RTTs onto a bioreactor. Finally, we describe the results obtained after multiple tests to validate our methods. The viability, sterility and integrity evaluations demonstrate that our procedures are sufficiently rigorous for manipulations of fragile tissues such as rat tail tendons.

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 score0.014
Threshold uncertainty score0.269

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 head0.068
GPT teacher head0.516
Teacher spread0.448 · 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

Citations21
Published2010
Admission routes2
Has abstractyes

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