Mechanical overload decreases the thermal stability of collagen in an in vitro tensile overload tendon model
Bibliographic record
Abstract
Musculoskeletal soft tissue injuries are very common, yet poorly understood. We investigated molecular-level changes in collagen caused by tensile overload of bovine tail tendons in vitro. Previous investigators concluded that tensile tendon rupture resulted in collagen denaturation, but our study suggests otherwise. Based on contemporary collagen biophysics, we hypothesized that tensile overload would lead to reduced thermal stability without change in the nativity of the molecular conformation. The thermal behavior of collagen from tail tendons ruptured in vitro at two strain rates (0.01 s(-1) and 10 s(-1)) was measured by differential scanning calorimetry (DSC). The 1,000-fold difference in strain rate was used since molecular mechanisms that determine mechanical behavior are thought to be strain rate-dependent. DSC revealed that the collagen in tensile overloaded tendons was less thermally stable by 3 degrees to 5 degrees C relative to undamaged controls and was not denatured since there was no change in enthalpy of denaturation. The decrease in thermal stability occurred throughout the overloaded regions, independent of rupture site, and was greater in specimens ruptured at the lower strain rate. The deformation mechanism apparently involves disruption of the lattice structure of the collagen fibrils and greatly increases the molecular freedom of the collagen molecules, leading to reduced thermal molecular stability and the previously reported increased proteolysis. This has important implications for understanding soft tissue injuries, disease etiology and treatment, and for developing tissue engineered products with improved durability.
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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".