Loss of vasomotor responsiveness to the μ-opioid receptor ligand endomorphin-1 in adjuvant monoarthritic rat knee joints
Bibliographic record
Abstract
Endomorphin-1 is a short-chain neuropeptide with a high affinity fo the mu-opioid receptor and has recently been localized in acutely inflamed knee joints where it was found to reduce inflammation. The present study examined the propensity of endomorphin-1 to modulate synovial blood flow in normal and adjuvant-inflamed at knee joints. Under deep urethane anesthesia, endomorphin-1 was topically applied to exposed normal and 1 wk adjuvant monoarthritic knee joints (0.1 ml bolus; 10(-12)-10(-9) mol). Relative changes in articular blood flow were measured by laser Doppler perfusion imaging and vascular resistances in response to the opioid were calculated. In normal knees, endomorphin-1 caused a dose-dependent increase in synovial vascular resistance and this effect was significantly inhibited by the specific mu-opioid receptor antagonist d-Phe-Cys-Tyr-d-Trp-O n-Thr-Pen-Th amide (CTOP) (P < 0.0001, 2-factor ANOVA, n = 5-7). One week after adjuvant inflammation, the hypoaemic effect of endomorphin-1 was completely abolished (P < 0.0001, 2-factor ANOVA, n = 5-7). Immunohistochemical analysis of normal and adjuvant-inflamed joints showed a ninefold increase in endomorphin-1 levels in the monoarthritic knee compared with normal control. Western blotting and immunohistochemistry revealed a moderate number of mu-opioid receptors in normal knees; however, mu-opioid receptors were almost undetectable in arthritic joints. These findings demonstrate that peripheral administration of endomorphin-1 reduces knee joint blood flow and this effect is not sustainable during advanced inflammation. The loss of this hypoaemic response appears to be due to down regulation of mu-opioid receptors as a consequence of endomorphin-1 accumulation within the arthritic joint.
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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 | 0.000 |
| 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 | 0.000 | 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".