Comparison of Cytotoxicity between Ethyl Acetate and Ethanol Extract of White Turmeric (Kaempferia rotunda) Rhizome Extract Against HeLa Cervical Cancer Cell Activity
Bibliographic record
Abstract
Aim: The aim of this study is to compare between ethanol and ethyl acetate rhizome extract of K.rotunda against HeLa cervical cancer cell in vitro.Material and Methods: Methods used in this research are test the chemical compound of extracts using Thin Layer Chromatography (TLC) and phytochemical screening test, also cytotoxicity test using MTT assay.Result: Ethyl acetate extract contains flavonoid, alkaloid, tannin, and triterpenoid, while ethanol extract have flavonoid, triterpenoid, and alkaloid.In addition, ethanol extract has strong cytotoxic activity (IC 50 = 16,939 µg/ml) while ethyl acetate extract has moderate cytotoxic activity (IC 50 = 127,9 µg/ml).Each of extracts showed significant results (p ≤ 0,05) although when compared between concentrations there are several concentrations that are not significant and also small coefficient of determinant values caused by various confounding factors.Conclusion: The ethanol extract of K.rotunda rhizome extract has the higher cytotoxicity activity compared to ethyl acetate extract of K.rotunda rhizome extract against HeLa cervical cancer cell.
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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".