Decoding the mechanical characteristics of the human anterior cruciate ligament entheses through graduated mineralization interfaces
Bibliographic record
Abstract
The anterior cruciate ligament is anchored to the femur and tibia via specialized interfaces known as entheses. These play a critical role in ligament homeostasis and joint stability by transferring forces, varying in magnitude and direction between structurally and functionally dissimilar tissues. However, the precise structural and mechanical characteristics underlying the femoral and tibial entheses and their intricate interplay remain elusive. In this study, two thin-graduated mineralization regions in the femoral enthesis (~21 μm) and tibial enthesis (~14 μm) are identified, both exhibiting distinct biomolecular compositions and mineral assembly patterns. Notably, the femoral enthesis interface exhibits progressively maturing hydroxyapatites, whereas the mineral at the tibial enthesis interface region transitions from amorphous calcium phosphate to hydroxyapatites with increasing crystallinity. Proteomics results reveal that Matrix Gla protein uniquely enriched at the tibial enthesis interface, may stabilize amorphous calcium phosphate, while C-type lectin domain containing 11 A, enriched at the femoral enthesis interface, could facilitate the interface mineralization. Moreover, the finite element analysis indicates that the femoral enthesis model exhibited higher resistance to shearing, whereas the tibial enthesis model contributes to tensile resistance, suggesting that the discrepancy in biomolecular expression and the corresponding mineral assembly heterogeneities collectively contribute to the superior mechanical properties of both the femoral enthesis and tibial enthesis models. These findings provide novel perspectives on the structure-function relationships of anterior cruciate ligament entheses, paving the way for improved management of anterior cruciate ligament injury and regeneration.
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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 | 0.000 | 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 | 0.001 | 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".