The impact of mild hypercholesterolemia on injury repair in the rat patellar tendon
Bibliographic record
Abstract
Abstract Hypercholesterolemia is associated with tendon pathology and injury prevalence. Lipids can accumulate in the tendon's extracellular spaces, which may disrupt its hierarchical structure and the tenocytes physicochemical environment. We hypothesized that the tendon's ability to repair after injury would be attenuated with elevated cholesterol levels, leading to inferior mechanical properties. Fifty wild‐type (sSD) and 50 apolipoprotein E knock‐out rats ( ApoE −/ − ) were given a unilateral patellar tendon (PT) injury at 12 weeks old; the uninjured limb served as a control. Animals were euthanized at 3‐, 14,‐ or 42‐days postinjury and PT healing was investigated. ApoE −/ − serum cholesterol was double that of SD rats (mean: 2.12 vs. 0.99 mg/mL, p < 0.001) and cholesterol level was related to the expression of several genes after injury; notably rats with higher cholesterol demonstrated a blunted inflammatory response. There was little physical evidence of tendon lipid content or differences in injury repair between groups, therefore we were not surprised that tendon mechanical or material properties did not differ between strains. The young age and the mild phenotype of our ApoE −/ − rats might explain these findings. Hydroxyproline content was positively related to total blood cholesterol, but this result did not translate to observable biomechanical differences, perhaps due to the narrow range of cholesterol levels observed. Tendon inflammatory and healing activity is modulated at the mRNA level even with a mild hypercholesterolemia. These important initial impacts need to be investigated as they may contribute to the known consequences of cholesterol on tendons in humans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".