<i>S</i>-allylcysteine inhibits chondrocyte inflammation to reduce human osteoarthritis via targeting RAGE, TLR4, JNK, and Nrf2 signaling: comparison with colchicine
Bibliographic record
Abstract
-allylcysteine (SAC), a sulfur-containing amino acid derivative, or colchicine, an ancient anti-inflammatory therapeutic, for 24 h. SAC or colchicine did not change viability at 1 nM-10 µM but inhibited p-JNK/pan-JNK. While SAC seems to be more effective, both agents inhibited reactive oxygen species (ROS), 3-nitrotyrosine (3-NT), lipid hydroperoxides (LPO), advanced lipoxidation end-products (ALEs as 4-hydroxy-2-nonenal, HNE), advanced glycation end-products (AGEs), and increased glutathione peroxidase (GPx) and type-II-collagen (COL2). IL-1β, IL-6, and osteopontin (OPN) were more strongly inhibited by SAC than by colchicine. In contrast, TNF-α was inhibited only by SAC, and COX2 was only inhibited by colchicine. Casp-1/ICE, GM-CSF, receptor for advanced glycation end-products (RAGE), and toll-like receptors (TLR4) were inhibited by both agents, but bone morphogenetic protein 7 (BMP7) was partially inhibited by SAC and induced by colchicine. Nuclear factor erythroid 2-related factor 2 (Nrf2) was induced by SAC; in contrast, it was inhibited by colchicine. Although they exert opposite effects on TNF-α, COX2, BMP7, and Nrf2, SAC and colchicine exhibit anti-osteoarthritic properties in OAC by modulating redox-sensitive inflammatory signaling.
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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) | 0.002 | 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".