Mechanically overloading collagen fibrils uncoils collagen molecules, placing them in a stable, denatured state
Bibliographic record
Abstract
Due to the high occurrence rate of overextension injuries to tendons and ligaments, it is important to understand the fundamental mechanisms of damage to these tissues' primary load-bearing elements: collagen fibrils and their constituent molecules. Based on our recent observations of a new subrupture, overload-induced mode of fibril disruption that we call discrete plasticity, we have sought in the current study to re-explore whether the tensile overload of collagen fibrils can alter the helical conformation of collagen molecules. In order to accomplish this, we have analyzed the conformation of collagen molecules within repeatedly overloaded tendons in relation to their undamaged matched-pair controls using both differential scanning calorimetry and variable temperature trypsin digestion susceptibility. We find that tensile overload reduces the specific enthalpy of denaturation of tendons, and increases their susceptibility to trypsin digestion, even when the digestion is carried out at temperatures as low as 4 °C. Our results indicate that the tensile overload of collagen fibrils can uncoil the helix of collagen molecules, placing them in a stable, denatured state.
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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".