Investigation of the composition, turnover, and thermal properties of ruptured cranial cruciate ligaments of dogs
Bibliographic record
Abstract
OBJECTIVE: To assess different components of the extracellular matrix with regard to their thermal properties, composition, and turnover in ruptured cranial cruciate ligaments (CCLs) of dogs, compared with components of intact CCLs from a breed predisposed to CCL failure. SAMPLE POPULATION: Ruptured CCLs obtained from 8 dogs of breeds predisposed to ruptured CCLs and intact CCLs from 12 cadaveric Labrador Retrievers. PROCEDURE: Ruptured and intact CCLs were analyzed for water content; collagen content and collagen cross-links were evaluated via hydroxyproline and amino-acid analyses, respectively. Glycosaminoglycan (GAG) content was analyzed via dimethylmethylene blue and uronic acid assays. Matrix metalloproteinases (MMPs)-2 and -9 and the tissue inhibitors of metalloproteinases (TIMPs)-1 and -2 were detected via gelatin SDS-PAGE zymography and reverse gelatin zymography. Thermal analysis of ligaments was performed by use of differential scanning calorimetry. RESULTS: Ruptured CCLs had significantly higher lamounts of immature cross-links, total and sulfated GAGs, and water content, compared with that of the intact ligaments. Compared with intact CCLs, concentration of pro-MMP-2 was significantly higher in ruptured CCLs; the maximum temperature of collagen denaturation was significantly lower in the ruptured CCLs. CONCLUSIONS AND CLINICAL RELEVANCE: The extracellular matrix of ruptured CCLs had an increased matrix turnover indicated by increased collagen and GAG synthesis, compared with that of intact CCLs. Although the extracellular matrix changes may have occurred before ligament rupture, it is possible that these observed changes may be part of a reparative process after rupture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".