Nitric oxide (NO) and cartilage metabolism: NO effects are modulated by superoxide in response to IL‐1
Bibliographic record
Abstract
Nitric oxide (NO) is thought to mediate most effects of interleukin-1 (IL-1) on cartilage. In vitro evidence includes the decreased synthesis of extracellular matrix components, the abnormal cell renewal, the decreased production of IL-1 receptor antagonist, the induction of apoptosis and the enhanced sensitivity of chondrocytes to oxidative stress. Studies in NOS2(-/-) mice or administration of NO synthase inhibitors in animal models of joint disorders have confirmed its potent pathophysiological role in cartilage. Using L-NMMA (1 mM), as a NO synthase inhibitor, and CuDips (10 microM), as a SOD mimetic, we provide evidence that the inhibitory potency of IL-1beta on proteoglycan synthesis and its stimulating effect on COX-2 activity depend both on NO and O2-* production. Peroxynitrite formation is further demonstrated by the occurrence of 3-nitrotyrosines in chondrocytes stimulated in vitro with 2.5 ng/ml IL-1 and in femoral condyles of rats injected locally with 1 microg IL-1. Preliminary data suggest that such contribution of reactive oxygen species is not shared in common by IL-17, another NO-producing cytokine. We conclude that superoxide is a key modulator of NO-mediated effects in chondrocyte stimulated with IL-1 and that a combined therapy with NO synthase inhibitors and antioxidants may be promising for a full cartilage protection.
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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) | 0.000 | 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".