In Vitro Phytochemical Screening, Cytotoxicity Studies of Curcuma longa Extracts with Isolation and Characterisation of Their Isolated Compounds
Bibliographic record
Abstract
The Curcuma longa plant is endowed with multiple traditional and therapeutic utilities and is here explored for its phytochemical constituents and cytotoxic potential. Turmeric rhizomes were extracted from three different solvents and screened for the presence of different phytochemical constituents, observation of which indicated that the polar solvents favoured extraction of greater versatile phytochemical constituents. These extracts were investigated for their cytotoxic potential by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay on three different of cell lines including SCC-29B (oral cancer cell line), DU-145 (prostate cancer cell line) and the Vero cell line (healthy cell line/non-cancerous cell line). This assay was performed by taking three extracts from isolated curcuminoids and a pure bioactive compound bisdemethoxycurcumin (BD). Bisdemethoxycurcumin was isolated from curcuminoids and purified by column and thin-layer chromatography, and its structural characterisation was performed with different spectroscopic techniques such as FTIR, NMR (1H Proton and 13C Carbon-NMR) and LC-MS. Amongst the extracts, the ethanolic extracts exhibited stronger cytotoxic potential against the oral cancer cell line (SCC-29B) with an IC50value of 11.27 μg/mL, and that this was too low of a cytotoxicity against the Vero cell line. Although, curcuminoids have also shown a comparable cytotoxic potential against SCC-29B (IC50 value 16.79 μg/mL), it was not as potent against the ethanolic extract, and it was even found to be cytotoxic against healthy cell lines at a very low dose. While considering the isolated compound, bisdemethoxycurcumin, it also possessed a cytotoxic potential against the prostate cancer cell line (DU-145) (IC50 value of 93.28 μg/mL), but was quite safe for the healthy cell line in comparison to doxorubicin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".