Cytotoxicity of alkaloids isolated from<i>Argemone mexicana</i>on SW480 human colon cancer cell line
Bibliographic record
Abstract
CONTEXT: Argemone mexicana Linn. (Papaveraceae) has been used as traditional medicine in India and Taiwan for the treatment of skin diseases, inflammations, bilious, fever, etc. Some alkaloids of A. mexicana have been screened for their cytotoxicity on different cancer cell lines. OBJECTIVE: The study investigates potential cytotoxic effects of alkaloids isolated from aerial part of A. mexicana on SW480 human colon cancer cell line. MATERIALS AND METHODS: Six alkaloids, 13-oxoprotopine, protomexicine, 8-methoxydihydrosanguinarine, dehydrocorydalmine, jatrorrhizine, and 8-oxyberberine were isolated from the methanol extract of A. mexicana. Cytotoxicity of these alkaloids was studied on SW480 human colon cancer cell line at 1, 25, 50, 75, 100, 125, 150, and 200 µg/mL for 24 and 48 h. Cells were seeded in a 96-well micro-plate at a concentration of 2 × 10(4) cells per well and MTS assay was performed to assess cytotoxicity in terms of cell viability. RESULTS: At 200 µg/mL, protomexicine and 13-oxoprotopine showed mild cytotoxicity (∼24-28%) whereas dehydrocorydalmine exhibited moderate cytotoxicity (∼48%). 8-Oxyberberine was mildly cytotoxic (∼27%) at 24 h but was more potent (∼76%) at 48 h. Jatrorrhizine and 8-methoxydihydrosanguinarine were most potent (∼95-100%) in inhibiting the human colon cancer cell proliferation showing complete reduction in cell viability. DISCUSSION AND CONCLUSION: This is the first study on the effect of these alkaloids on SW480 human colon cancer cell line. This study indicates that some alkaloids of A. mexicana strongly inhibit the cell proliferation in human colon cancer cells, and it might be a basis for future development of a potent chemotherapeutic drug.
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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) | 0.001 | 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".