Inhibitory Effect of Antioxidant Extracts From Various Potatoes on the Proliferation of Human Colon and Liver Cancer Cells
Bibliographic record
Abstract
Antioxidant extracts from 5 potato lines were evaluated for antioxidant activity, total phenolics, chlorogenic acid, anthocyanin content, and in vitro anticancer capacity. Analysis showed that Mexican wild species S. pinnatisectum had the highest antioxidant activity, total phenolic, and chlorogenic acid content. The proliferation of colon cancer and liver cancer cells was significantly inhibited by potato antioxidant extracts. The highest antiproliferative activity was observed in extracts of S. pinnatisectum and the lowest in Northstar. An inverse correlation was found between total phenolics and the EC(50) of colon cancer cell (R(2) = 0.9303), as well as liver cancer cell proliferation (R(2) = 0.8992). The relationship between antioxidant activity and EC(50) of colon cancer/liver cancer cell proliferation was significant (R(2) = 0.8144; R(2) = 0.956, respectively). A significant difference in inhibition of cancer cells (P < 0.01) existed between the 3 polyphenols: chlorogenic acid, pelargonidin chloride, and malvidin chloride, suggesting that chlorogenic acid was a critical factor in the antiproliferation of colon cancer and liver cancer cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".