Anti-inflammatory and cytotoxic effects of Jatropha podagrica extracts on skin cancer
Bibliographic record
Abstract
Background and purpose: Jatropha podagrica Hook, belongs to the Euphorbiaceae family, which possesses anticancer activities and is traditionally applied to treat skin diseases. No reports of J. podagrica anti-neoplastic activity on an amelanotic melanoma and associated inflammatory mediators exist. Experimental approach: The biological activities, including cytotoxic and anti-inflammatory effects of J. podagrica extracts, were evaluated. Key compounds in the extracts were identified using LC-MS/MS analysis. Findings/Results: The hexane extract of the root (RMH) demonstrated the highest inhibition of NO production with an IC 50 of 4.94 ± 0.25 μg/mL, followed by the ethanolic extracts of the root (RME) and stem (SME) with IC 50 values of 24.90 ± 1.06 and 25.20 ± 0.10 μg/mL, respectively. However, RMH showed cellular toxicity at 50 pg/mL, while other extracts were non-toxic up to 100 μg/mL. None of the extracts affected the concentrations of inflammatory mediators PGE 2 or TNF-α. The cytotoxic activity of SME showed an IC 50 of 5.62 ± 0.58 μg/mL, comparable to that of the anticancer drug 5-fluorouracil, with an IC 50 of 0.59 ± 0.01 μg/mL. The selectivity index of SME was >17.79, significantly higher than that of 5-fluorouracil, which was 0.08. LC-MS/MS analysis identified two main compounds from the coumarin group: fraxetin at 5.357 min and its positional isomer tomentin at 5.943 min. Conclusion and implications: The study indicates that SME exhibits good cytotoxic activity and inhibits key cancer hallmarks such as NO production. The presence of coumarins, identified through LC-MS/MS, suggests that these compounds may play a crucial role in the extract's anticancer effects, highlighting the potential for future development as cancer therapeutics.
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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 | 0.001 | 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".