Nutritional Modulation of Antitumor Efficacy and Diarrhea Toxicity Related to Irinotecan Chemotherapy in Rats Bearing the Ward Colon Tumor
Bibliographic record
Abstract
PURPOSE: To evaluate and compare the influence of dietary elements on cancer progression, chemotherapy efficacy, and toxicity, particularly severe, late-onset diarrhea related to irinotecan (CPT-11) treatment. EXPERIMENTAL DESIGN: We used laboratory rats fed a standardized basal diet, Ward colon tumor, and CPT-11 therapy for the study of CPT-11-induced diarrhea. Dietary interventions were selected from nutrients already established to modify other forms of colitis and which have been hypothesized to mitigate chemotherapy-induced gastrointestinal injury (glutamine, n-3 fatty acids, prebiotic oligosaccharides). Animals adapted to test diets were treated with CPT-11 at the maximum tolerated dose (125 mg/kg x 3 days) and diarrhea was followed continuously for 1 week. RESULTS: The inclusion of n-3 fatty acids in the diet (5%, w/w of total fat) suppressed tumor growth and enhanced CPT-11's efficacy; this treatment did not affect the incidence or severity of diarrhea. By contrast, oral glutamine bolus (0.75 g/kg) administered prior to each CPT-11 treatment reduced the incidence of severe diarrhea (34.1 +/- 4.7% versus 53.8 +/- 4.2%, P < 0.005) and decreased the area under the curve of diarrhea score (16.5 +/- 1.0 versus 18.8 +/- 0.5, P < 0.05). Identical results were obtained with i.v. bolus glutamine administration. Glutamine treatment did not alter CPT-11's antitumor efficacy. The addition of prebiotic oligosaccharides to the diet (8%, w/w of diet) did not mitigate the severity of diarrhea, and it raised the activity of beta-glucuronidase in cecal contents, a key bacterial enzyme mediating CPT-11-related intestinal toxicity. CONCLUSION: Our experiments suggest that glutamine and n-3 fatty acids might be potentially useful adjuncts to CPT-11 treatment.
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) | 0.001 | 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 | 0.001 |
| 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".