Effect of Irinotecan (CPT‐11) on fatty acid status in rats with colorectal cancer
Bibliographic record
Abstract
Chemotherapy drugs may cause profound changes in fatty acid metabolism. Irinotecan (CPT‐11) is currently used for treatment of colorectal cancer. This study characterized amount and types of fatty acids in phospholipids (PL) and triglycerides (TG) in plasma and liver, in rats (n=15) implanted with a colorectal tumour (Ward) and treated with irinotecan (CPT‐11). Once tumour was established (2cm 3 )CPT‐11 (100mg/kg/day) was administered on 3 consecutive days. Blood and liver were collected 1d and 7d later. A Folch method was used to isolate fatty acids from liver and plasma and thin layer chromatography used to separate TG and PL. Types and amounts of fatty acids were determined using gas chromatography. Liver TG contained 50% less saturated fatty acid 1d post treatment compared with non‐treated rats (p<0.05). Higher C22:4n‐6 and C22:5n‐6 were observed 7 days after treatment, compared with other groups in liver PL (p<0.05). Total plasma PL, C18:0, C18:2n‐6, C20:5n‐3 and total saturated fatty acid decreased 25%, rats treated with chemotherapy when compared with untreated groups (p<0.05). There were no differences in amount or types of fatty acids in plasma TG. The results of this study have implications for dietary intervention during treatment for cancer. This research project was funded by the Canadian Institute of Health Research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".