Compressive compared with tensile loading of medial collateral ligament scar <i>in vitro</i> uniquely influences mRNA levels for aggrecan, collagen type II, and collagenase
Bibliographic record
Abstract
To test the hypothesis that loading conditions can be used to engineer early ligament scar behaviors, we used an in vitro system to examine the effect that cyclic hydrostatic compression and cyclic tension applied to 6-week rabbit medial collateral ligament scars had on mRNA levels for matrix molecules, collagenase, and the proto-oncogenes c-fos and c-jun. Our specific hypothesis was that tensile stress would promote more normal mRNA expression in ligament whereas compression would lead to higher levels of mRNA for cartilage-like molecules. Femur (injured medial collateral ligament)-tibia complexes were subjected to a hydrostatic pressure of 1 MPa or a tensile stress of 1 MPa of 0.5 Hz for 1 minute followed by 14 minutes of rest. On the basis of a preliminary optimization experiment, this 15-minute testing cycle was repeated for 4 hours. Semiquantitative reverse transcription-polymerase chain reaction analysis was performed for mechanically treated medial collateral ligament scars with use of rabbit specific primer sets for types I, II, and III collagen, decorin, biglycan, fibromodulin, versican, aggrecan, collagenase, c-fos, c-jun, and a housekeeping gene, glyceraldehyde-3-phosphate dehydrogenase. Cyclic hydrostatic compression resulted in a statistically significant increase in mRNA levels of type-II collagen (171% of nonloaded values) and aggrecan (313% of nonloaded values) but statistically significant decreases in collagenase mRNA levels (35% of nonloaded values). Cyclic tension also resulted in a statistically significant decrease in collagenase mRNA levels (66% of nonloaded values) and an increase in aggrecan mRNA levels (458% of nonloaded values) but no significant change in the mRNA levels for the other molecules. The results show that it is possible to alter mRNA levels for a subset of genes in scar tissue by supplying unique mechanical stimuli in vitro and thus that further investigation of scar engineering for potential reimplantation appears feasible.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".