Development of overuse tendinopathy: A new descriptive model for the initiation of tendon damage during cyclic loading
Bibliographic record
Abstract
Tendinopathic tissue has long been characterized by changes to collagen microstructure. However, initial tendon damage from excessive mechanical loading-a hallmark of tendinopathy development-could occur at the nanoscale level of collagen fibrils. Indeed, it is on this scale that tenocytes interact directly with tendon matrix, and excessive collagen fibril damage not visible at the microscale could trigger a degenerative cascade. In this study, we explored whether initiation of tendon damage during cyclic loading occurs via a longitudinal compression-induced buckling mechanism of collagen fibrils leading to nanoscale kinkband development. Two groups of tendons were cyclically loaded to equivalent peak stresses. In each loading cycle, tendons in one group were unloaded to the zero displacement mark, while those in the other group were unloaded to a nominal level of tension, minimizing the potential for fibril buckling. Tendons that were unloaded to the zero displacement mark ruptured significantly sooner during cyclic loading (1,446 ± 737 vs. 4,069 ± 1,129 cycles), indicating that significant fatigue damage is accrued in the low stress, toe region of the load-deformation response. Ultrastructural analysis using scanning electron microscopy of tendons stopped after 1,000 cycles showed that maintaining a nominal tension slowed the accumulation of kinkbands, supporting a longitudinal compression-induced buckling mechanism as the basis for kinkband development. Based on our results, we present a new descriptive model for the initiation of tendon damage during cyclic loading. The so-called Compression of Unrecovered Elongation or CUE Model may provide useful insight into the development of tendinopathy. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:467-476, 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".