Leukotriene and prostaglandin synthesis pathways in osteoarthritic synovial membranes: regulating factors for interleukin 1beta synthesis.
Bibliographic record
Abstract
OBJECTIVE: To study the mechanisms responsible for the cross-talk between lipoxygenase (LOX) and cyclooxygenase (COX) pathways in human osteoarthritic (OA) synovial explants, and to confirm the arachidonic acid (AA) shunting phenomenon and its influence on interleukin 1beta (IL-1beta) synthesis. METHODS: Synovial membrane explants were cultured in the absence or presence of different drugs that inhibit COX and/or LOX activities. Concentrations of prostaglandin E2 (PGE2), leukotriene B4 (LTB4), lipoxin A4 (LXA4), and IL-1beta were measured. RESULTS: When membrane explants were incubated with naproxen (COX inhibitor) under unstimulated conditions, the production of LTB4 was dose-dependently enhanced, reaching a 5-fold increase over the control. This shunt could be partially reversed by the addition of exogenous PGE2. Under lipopolysaccharide (LPS) stimulation, both licofelone (COX/LOX inhibitor) at therapeutic concentrations and NDGA (LOX inhibitor) inhibited LTB4 production, whereas naproxen did not amplify the LPS-induced LTB4 production. Conversely, using NDGA, it was found that a shunt of AA from the LOX to the COX pathway did not occur. Under LPS conditions, both naproxen and licofelone inhibited LXA4, inducing an increase in the LTB4/LXA4 ratio with naproxen treatment but not with licofelone. Under these conditions, naproxen treatment induced a higher level of IL-1beta production. CONCLUSION: We demonstrated in OA synovium that a shunt from AA to the LOX pathway occurred and that treatment with a nonselective COX inhibitor could increase the production of LTB4 and secondarily the synthesis of IL-1beta. Therefore treatment with licofelone, which can act on both COX and LOX pathways, may have some interesting properties in the treatment of OA.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".