Single collagen fibrils isolated from high stress and low stress tendons show differing susceptibility to enzymatic degradation by the interstitial collagenase matrix metalloproteinase-1 (MMP-1)
Bibliographic record
Abstract
Bovine forelimb flexor and extensor tendons serve as a model for examining high stress, energy storing and low stress, positional tendons, respectively. Previous research has shown structural differences between the collagen fibrils of these tissues. The nanoscale collagen fibrils of flexor tendons are smaller in size, more heavily crosslinked, and respond differently to mechanical loading. Meanwhile, energy storing tendons undergo less collagen turnover compared to positional tendons and are more commonly injured. These observations raise the question of whether collagen fibril structure influences the collagen degradation processes necessary for remodelling. Atomic force microscopy was used to image dry collagen fibrils before and after 5-hour exposure to matrix metalloproteinase-1 (MMP-1) to detect changes in fibril size. Collagen fibrils from three tissue types were studied: bovine superficial digital flexor tendons, matched-pair bovine lateral digital extensor tendons, and rat tail tendons. Compared to control fibrils exposed only to buffer, a significant decrease in fibril cross-sectional area (CSA) following MMP-1 exposure was observed for bovine extensor and rat tail fibrils, with larger fibrils experiencing a greater magnitude of CSA decrease in both fibril types. Fibrils from bovine flexor tendons, on the other hand, showed no decrease in CSA when exposed to MMP-1. The result did not appear to be linked to the small size of flexor fibrils, as equivalently sized extensor fibrils were readily degraded by the enzyme. Increased proteolytic resistance of collagen fibrils from high stress tendons may help to explain the longevity of collagen within these tissues in vivo.
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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".