Non-digestible fraction of cooked bean (Phaseolus vulgaris L.) cultivar Bayo Madero suppresses colonic aberrant crypt foci in azoxymethane-induced rats
Bibliographic record
Abstract
The non-digestible fraction (NDF) of common bean (Phaseolus vulgaris L.) cultivar Bayo Madero was evaluated for its chemopreventive effect on azoxymethane (AOM) induced aberrant crypt foci (ACF) in rats. Diets containing cooked beans (CB) or its non-digestible fraction (NDF) were fed to 72 male rats after 2 azoxymethane injections (15 mg kg(-1) of body weight once a week for 2 weeks). ACF number, short chain fatty acids (SCFA) and β-glucuronidase activity were measured in colon sections from rats sacrificed 7 weeks after the last AOM injection. Food intake and weight gain of rats were unaffected by CB and NDF. CB and NDF suppressed the AOM-induced formation of ACF (0.8 and 1.5 ACF/distal zone, respectively vs. 6.6 ACF/distal zone based on methylene blue stain) and lowered β-glucuronidase activity in cecal, colonic and fecal content compared to AOM group. SCFA production was not significantly different among fecal, cecal and colonic content. These results indicate that CB and NDF from Bayo Madero provide direct chemoprotection against early stage of azoxymethane (AOM)-induced colon cancer in rats.
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".