<i>In vitro</i> anti‐hepatoma activity of fifteen natural medicines from Canada
Bibliographic record
Abstract
Fifteen crude drugs, Stellaria media Cyrill. (Caryophyllaceae), Calendula officinalis L. (Compositae), Achillea millefolium L. (Compositae), Verbascum thapsus L. (Scrophulariaceae), Plantago major L. (Plantaginaceae), Borago officinalis L. (Boraginaceae), Satureja hortensis L. (Labiatae), Coptis groenlandica Salisb. (Ranunculaceae), Cassia angustifolia Vahl. (Leguminosae), Origanum majorana L. (Labiatae), Centella asiatica L. (Umbelliferae), Caulophyllum thalictroides Mich. (Berberidaceae), Picea rubens Sargent. (Pinaceae), Rhamnus purshiana D.C. (Rhamnaceae) and Hibiscus sabdariffa L. (Malvaceae), which have been used as folk medicine in Canada, were evaluated for their anti-hepatoma activity on five human liver-cancer cell lines, i.e. HepG2/C3A, SK-HEP-1, HA22T/VGH, Hep3B and PLC/PRF/5. The samples were examined by in vitro evaluation for their cytotoxicity. The results showed that the effects of crude drugs on hepatitis B virus genome-containing cell lines were different from those against non hepatitis B virus genome-containing cell lines. C. groenlandica was observed to be the most effective against the growth of all five cell lines and its chemotherapeutic values will be of interest for further studies.
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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) | 0.002 | 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".