Effects of combined administration of transforming growth factor‐β1 and epidermal growth factor on properties of the in situ frozen anterior cruciate ligament in rabbits
Bibliographic record
Abstract
The mechanical properties of tendon autografts used in reconstruction of the anterior cruciate ligament (ACL) are reduced after surgery. Previous studies showed that growth factors such as transforming growth factor-beta1 (TGF-beta1) and epidermal growth factor (EGF) can stimulate fibroblast proliferation and increase collagen and noncollagenous protein synthesis by these cells. These factors might be useful, therefore, in preventing graft deterioration after transplantation or accelerating mechanical restoration of the deteriorated graft. The purpose of our study, therefore, was to clarify the effects of TGF-beta1 and EGF on biomechanical properties using an in situ freeze-thaw ACL model in the rabbit. A total of 142 rabbits underwent the freeze-thaw treatment in the right ACL and were then divided into four groups. Group I served as a freeze-thaw, but otherwise untreated control. In Group II. a delivery vehicle (fibrin sealant) alone was applied. In Group III, 4-ng TGF-beta1 and 100-ng EGF mixed with the vehicle were applied. In Group IV, higher doses (2-microg TGF-beta1 and 50-microg EGF) of growth factors were mixed with the vehicle. The groups were compared at 6 and 12 weeks on the basis of mechanical properties, water content, and histological and ultrastructural observations. The cross-sectional area of Group III (average, 7.1 mm2) was significantly less than that of Groups I, II, and IV (9.0. 8.2. and 9.4 mm2. respectively) at 12 weeks. The tensile strength of Group lII (62.2 MPa) was significantly greater than that of Groups I, II, and IV (35.6, 43.7, and 36.9 MPa, respectively) at 12 weeks, while the water content of Group III (70.7%) was significantly lower than that of Group I (75.2%). No other significant differences occurred among Groups I, II, and IV. A unimodal distribution of collagen fibril diameters was noted in Groups I and II, while a bimodal pattern was found in Group III. This study demonstrated that low-dose application of TGFbeta1 and EGF significantly inhibited not only the increased water content and cross-sectional area, but also the decreased tensile strength caused by the freeze-thaw treatment, while a high dose of TGF-beta1 and EGF does not have the same beneficial effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".