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Record W2739354198

DEVELOPMENT OF A LOADING DEVICE FOR IMAGING RABBIT MCL ENTHESES WITH SECOND HARMONIC GENERATION MICROSCOPY

2015· article· en· W2739354198 on OpenAlexaffvenue
Minjia Xu, Johnathan L. Sevick, May Chung, Nigel Graham Shrive

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2015
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of Calgary
Fundersnot available
KeywordsEnthesisMaterials scienceFemtosecondFibrocartilageBiomedical engineeringOpticsAnatomyEngineeringTendonBiologyLaserMedicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION Entheses are transitional structures in the body between a flexible material and a much stiffer material: ligament and bone, respectively. A gradual transition of mineral content and collagen fibre organization enables the enthesis to dissipate stress concentrations and transfer load between the adjoining elements, contributing to normal joint function [1]. Damage to this small region is associated with conditions like tennis elbow and jumper’s knee. Enthesis tears do not repair well, causing long term weakness. To date, the challenge of observing entheses under applied load has inhibited understanding of their mechanical behaviour. Second Harmonic Generation (SHG) microscopy is a technology that can be used to image highly polarizable proteins like collagen without the need for section fixation or molecular excitation [2]. Given that collagen fibre structure affects load transfer at entheses, SHG microscopy is an ideal tool to elucidate the fibre structure at MCL entheses. The purpose of the project described was to develop a custom device to allow observation of the collagen fibre network of the rabbit medial collateral ligament (MCL) enthesis in the SHG microscope as tensile load is applied. METHODS After generating a morphological chart of alternative solutions, the optimal option was chosen based on project requirements. The design was created with CAD software (SolidWorks 2015) and where possible, the proposed design was modified to optimize objectives— minimizing cost and maximizing movement accuracy. With CAD, it is easy to modify components of a model while assessing its impact on the model as a whole. RESULTS In the final design, the rabbit bones can be secured to bone pots at a physiological angle of 70°, with the MCL in the line of action of the applied force. One bone pot remains stationary as the other, sliding on rail guides which constrain pot movement, is pulled by a linear actuator. A custom load cell will collect force data as the load is applied. For its light-weight property and potential to be scanned using MRI, Perspex is the material of choice for the device. The completed design, shown in Figure 1, satisfies all the requirements previously established and requires only one hand for operation. This model allows for a testing procedure simulating physiological conditions while maximizing accuracy of the recorded data through incorporating rail guides and making use of a linear actuator. DISCUSSION AND CONCLUSIONS With some minor modifications to the bone pots, this device can be used as a reference product for the study of other tissues under load. However, it would be worthwhile to consider interchanging the bone pots between uses since the bone cement is difficult to remove. The small size of entheses has stymied researchers’ efforts to characterize their inhomogeneous material behavior. However, this device will enable the observation of collagen fibre behaviour under load, which will provide insight into mechanisms of load transfer in the enthesis and in time, contribute to improved surgical attachment procedures.

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)0.002
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 score0.067
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.119
GPT teacher head0.406
Teacher spread0.287 · 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".

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Citations0
Published2015
Admission routes2
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