Elucidation of molecular mechanisms underlying the protective effects of thymoquinone against rheumatoid arthritis
Bibliographic record
Abstract
Thymoquinone (TQ) is the major active compound derived from the medicinal Nigella sativa. A few studies have shown that TQ exhibits anti-inflammatory activities in experimental models of rheumatoid arthritis (RA) through mechanisms that are not fully understood. The aim of this work was to evaluate the in vitro and in vivo effects of TQ and to investigate its influence on the major signalling pathways involved in pathophysiological RA changes. We used isolated human RA fibroblast-like synoviocytes (FLS) and a rat adjuvant-induced arthritis model of RA. In isolated RA FLS, TQ (0-10 µM) was not cytotoxic and inhibited slightly lipopolysaccharide (LPS)-induced FLS proliferation and strongly H(2)O(2)-induced 4-hydroxynonenal (HNE) generation. By studying different inflammatory and catabolic factors, we determined that TQ significantly abolished LPS-induced interleukin-1beta (IL-1β), tumour necrosis factor-alpha (TNFα), metalloproteinase-13, cyclooxygenase-2, and prostaglandin E(2). Furthermore, LPS-induced the phosphorylation of p38 mitogen-activated protein kinase, extracellular-regulated kinases ½, and nuclear factor-kappaB-p65 were also blocked by TQ in time-dependent manner. In our experimental RA model, the oral administration of TQ 5 mg/kg/day significantly reduced the serum levels of HNE, IL-1β and TNFα as well as bone turnover markers, such as alkaline phosphatase and tartrate-resistant acid phosphatase. The protective effects of TQ against RA were also evident from the decrease in arthritis scoring and bone resorption. In conclusion, the fact that TQ abolishes a number of factors known to be involved in RA pathogenesis renders it a clinically valuable agent in the prevention of articular diseases, including RA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".