Inhibition of inducible nitric oxide synthase prevents lipid peroxidation in osteoarthritic chondrocytes
Bibliographic record
Abstract
Nitric oxide (NO) and the lipid peroxidation (LPO) product 4-hydroxynonenal (HNE) are considered to be key mediators of cartilage destruction in osteoarthritis (OA). NO is also known to be an important intermediary in LPO initiation through peroxynitrite formation. The aim of the present study was to assess the ability of the inducible NO synthase (iNOS) inhibitor N-iminoethyl-L-lysine (L-NIL) to prevent HNE generation via NO suppression in human OA chondrocytes and cartilage explants. Human OA chondrocytes and cartilage explants were treated with L-NIL and thereafter with or without interleukin-1beta (IL-1β) or HNE at cytotoxic or non-cytotoxic concentrations. Parameters related to oxidative stress, apoptosis, inflammation, and catabolism were investigated. L-NIL stifled IL-1β-induced NO release, iNOS activity, nitrated proteins, and HNE generation in a dose-dependent manner. It also blocked IL-1β-induced inactivation of the HNE-metabolizing glutathione-s-transferase (GST). L-NIL restored both HNE and GSTA4-4 levels in OA cartilage explants. Interestingly, it also abolished IL-1β-evoked reactive oxygen species (ROS) generation and p47 NADPH oxidase activation. Furthermore, L-NIL significantly attenuated cell death and markers of apoptosis elicited by exposure to a cytotoxic dose of HNE as well as the release of prostaglandin E(2) and metalloproteinase-13 induced by a non-cytotoxic dose of HNE. Altogether, our findings support a beneficial effect of L-NIL in OA by (i) preventing the LPO process and ROS production via NO-dependent and/or independent mechanisms and (ii) attenuating HNE-induced cell death and different mediators of cartilage damage.
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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".