Endothelial dysfunction and decreased vascular responsiveness in the anterior cruciate ligament-deficient model of osteoarthritis
Bibliographic record
Abstract
Chronic inflammation associated with osteoarthritis (OA) may alter normal vascular responses and contribute to joint degradation. Vascular responses to vasoactive mediators were evaluated in the medial collateral ligament (MCL) of the anterior cruciate ligament (ACL)-deficient knee. Chronic joint instability and progressive OA were induced in rabbit knees by surgical transection of the ACL. Under halothane anesthesia, laser speckle perfusion imaging (LSPI) was used to measure MCL blood flow in unoperated control (n = 12) and 6-wk ACL-transected knees (n = 12). ACh, bradykinin, histamine, substance P (SP), and prostaglandin E(2) (PGE(2)) were applied to the MCL vasculature in topical boluses of 100 microl (dose range 10(-14) to 10(-8) mol). In normal joints, ACh, bradykinin, histamine, and PGE(2) evoked a dilatory response. Substance P caused a biphasic response that was dilatory from 10(-14) to 10(-11) mol and constricting at higher doses. In ACL-deficient knees, ACh, bradykinin, histamine, and SP decreased perfusion, whereas PGE(2) had a biphasic response that decreased perfusion at 10(-14) to 10(-11) mol and was dilatory at higher concentrations. Sodium nitroprusside increased perfusion in resting and phenylephrine-precontracted vessels with no significant differences between ACL-transected and control knees. Femoral artery occlusion and release increased perfusion by 74.3 +/- 11.1% in control knees but only by 25.8 +/- 4.4% in ACL-deficient knees. The altered responsiveness of the MCL vasculature to these inflammatory mediators may indicate endothelial dysfunction in the MCL, which may contribute to the progression and severity of OA and to the adaptation of the joint in an altered mechanical environment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".