Biomechanics of changes in ACL and PCL material properties or prestrains in flexion under muscle force-implications in ligament reconstruction
Bibliographic record
Abstract
The effects of changes in cruciate ligament material and prestrain on knee joint biomechanics following ligament reconstruction surgery by a tendon are not adequately known. A 3D nonlinear finite element model of the entire knee joint was used to investigate the joint response at different flexion angles under a quadriceps force while varying ACL and PCL initial strains or material properties. The ACL and PCL forces as well as tibiofemoral contact forces/areas substantially increased with greater ACL or PCL initial strains or stiffness. The patellofemoral contact force slightly increased whereas the tibial extensor moment slightly decreased with tenser or stiffer ACL. Reverse trends were predicted with slacker ACL. Results confirm the hypotheses that changes in the prestrain of one cruciate ligament substantially influence the force in the other cruciate ligament and the entire joint and that the use of the patellar tendon (PT) as a replacement for cruciate ligaments markedly alters the joint biomechanics with trends similar to those predicted when increasing prestrains. Forces in both ACL and PCL ligaments increased as one of them became tenser or stiffer and diminished as it became slacker. These results have important consequences in joint biomechanics following ligament injuries or replacement and tend to recommend the use of grafts with smaller prestrains (i.e. slacker than intact) when using the PT as the replacement material with stiffness greater than that of replaced ligament itself.
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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 | 0.000 | 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".