Fibril deformation under load of the rabbit Achilles tendon and medial collateral ligament femoral entheses
Bibliographic record
Abstract
Microscopic visualization under load of the region connecting ligaments/tendons to bone, the enthesis, has been performed previously; however, specific investigation of individual fibril deformation may add insight to such studies. Detailed visualization of fibril deformation would inform on the mechanical strategies employed by this tissue in connecting two mechanically disparate materials. Clinically, an improved understanding of enthesis mechanics may help guide future restorative efforts for torn or injured ligaments/tendons, where the enthesis is often a point of weakness. In this study, a custom ligament/tendon enthesis loading device was designed and built, a unique method of sample preparation was devised, and second harmonic and two-photon fluorescence microscopy were used to capture the fibril-level load response of the rabbit Achilles tendon and medial collateral ligament femoral entheses. A focus was given to investigation of the mechanical problem of fibril embedment. Resultant images indicate a rapid (occurring over approximately 60 μm) change in fibril orientation at the interface of ligament/tendon and calcified fibrocartilage early in the loading regime, before becoming relatively constant. Such a change in fibril angle helps confirm the materially graded region demonstrated by others, while, in this case, providing additional insight into fibril bending. We speculate that the scale of the mechanical problem (i.e., fibril diameters being on the order of 250 nm) allows fibrils to bend over the small (relative to the imaging field of view, but large relative to fibril diameter) distances observed; thus, potentially lessening required embedment lengths. Nevertheless, this behavior merits further investigation to be confirmed. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:2506-2515, 2018.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".