Evaluation of anti-inflammatory and immunomodulatory potential of Lawsone (2-hydroxy-1,4-naphthoquinone) using pre-clinical rodent model of rheumatoid arthritis
Bibliographic record
Abstract
Background: Lawsone (2-hydroxy-1,4-naphthoquinone) is naturally present in Lawsonia Inermis and flowers of Eicchornia crassipes. This study assessed the anti-arthritic potential of Lawsone, using FCA-induced Sprague-Dawley rats. Methods: Arthritic progress was analyzed through a macroscopic scoring scale, measurement of paw edema, and histopathological changes. Effects of Lawsone on mRNA expression levels of inflammatory markers were examined using the reverse transcription PCR technique. ELISA technique was used to evaluate the PGE2 levels. Moreover, levels of biochemical and hematological parameters were also analyzed. Results: The research elucidated that Lawsone showed an inhibitory potential towards arthritic progress and ameliorated the paw edema. The histopathological analysis also validated the inhibition in arthritic development. Treatment with Lawosne reduced the expression levels of inflammatory markers in rats i.e., VEGF, TNF-α, MMP-2, MMP-3, NF-κB, IL-1β, and IL-6. PGE2 levels (all p < 0.001) were also found reduced in treatment groups. Lab investigations showed improved results of hematological and hepatic parameters in the treated groups as compared to the positive control. This study found no hepatotoxic or nephrotoxic effects of Lawsone in the test doses. Conclusion: Lawsone possesses an anti-arthritic property which could be ascribed to its immunomodulatory and anti-inflammatory effects.
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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 | 0.001 |
| 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".