Exploring the Antioxidant and Anti-Inflammatory Potential of Wilckia maritima: In Vitro and In Silico Investigations
Bibliographic record
Abstract
This research aimed to assess the anti-inflammatory and antioxidant potential of methanol extract of Wilckia maritima, a plant belonging to the family Brassicaceae, which is enriched with natural antioxidants. Qualitative phytochemical studies showed the presence of numerous compounds including glycosides, phenols, triterpenoids, and GC-MS studies revealed the presence of 35 bioactive components, including n-hexadecanoic acid (26.96%), 9,12,15 octadecatrienoic acid (cis) (25.52%), 3,5 di-hydroxy-6-methyl 2,3-di-hydro-4-pyran 4-one (14.35%), and 3-tertiary butyl-4-hydroxy-anisol (11.68%) as major components, which are thought to be responsible for anti-inflammatory and antioxidant potentials of methanol extract of W. maritima., flavonoids, steroids, tannins, and saponins. The antioxidant potential of the extract was determined by performing various assays, including DPPH free radical scavenging, ferrous reducing, and hydrogen peroxide assays, which showed significant percentage inhibition (83.55 ± 0.89, 79.40 ± 1.17, and 81.26 ± 0.36%, respectively) as compared to ascorbic acid (standard). The extract also exhibited significant anti-inflammatory activity with percentage inhibition 65.66 ± 0.42% compared to standard ibuprofen, which showed 73.20 ± 0.21% inhibition. In vivo analysis further confirmed this anti-inflammatory potential of the extract, showing a 75.55 ± 0.11% reduction in edema at 300 mg/kg as compared with standard diclofenac sodium 70.27 ± 0.012%. Moreover, in silico investigations revealed that the phytocompounds in W. maritima exhibited excellent antioxidant and anti-inflammatory characteristics, which could provide novel biological molecules for target receptors. Overall, our findings suggest that W. maritima can be utilized as a potential resource of natural compounds with antioxidants and anti-inflammatory potential, with promising therapeutic effect in relieving various ailments related to inflammatory response.
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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) | 0.001 | 0.001 |
| 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".