Soyasaponins: The Relationship Between Chemical Structure and Colon Anticarcinogenic Activity
Bibliographic record
Abstract
Soyasaponins are bioactive compounds found in many legumes. Although crude soyasaponins have been shown to have anti-colon carcinogenic activity, there have been no structure-activity studies. In this study, therefore, purified soyasaponins and soyasapogenins were tested for their ability to suppress the growth of HT-29 colon cancer cells, as determined by the WST-1 assay, over a concentration range of 0-50 ppm. Soyasaponin I and III, soyasapogenol B monoglucuronide, soyasapogenol B, soyasaponin A1, soyasaponin A2, and soyasapogenol A were evaluated. Also tested were mixtures comprising acetylated group A soyasaponins, deacetylated group A soyasaponins, and group B soyasaponins. The most potent compounds were the aglycones soyasapogenol A and B, which showed almost complete suppression of cell growth. The glycosidic soyasaponins by comparison were largely inactive. Soyasaponin A(1), A(2), and I, group B and deacetylated and acetylated group A fractions had no effect on cell growth. Soyasaponin III and soyasapogenol B monoglucuronide were marginally bioactive. These results suggested that the bioactivity of soyasaponins increased with increased lipophilicity. Results from in vitro fermentation suggested that colonic microflora readily hydrolyzed the soyasaponins to aglycones. These observations suggest that the soyasaponins may be an important dietary chemopreventive agent against colon cancer, after alteration by microflora.
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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".