Irinotecan (CPT-11) Chemotherapy Alters Intestinal Microbiota in Tumour Bearing Rats
Bibliographic record
Abstract
Intestinal microbiota mediate toxicity of irinotecan (CPT-11) cancer therapies and cause systemic infection after CPT-11-induced loss of barrier function. The intestinal microbiota and their functions are thus potential targets for treatment to mitigate CPT-11 toxicity. However, microbiota changes during CPT-11 therapy remain poorly described. This study analysed changes in intestinal microbiota induced by CPT-11 chemotherapy. Qualitative and quantitative taxonomic analyses, and functional analyses were combined to characterize intestinal microbiota during CPT-11-based chemotherapy, and in presence or absence of oral glutamine, a treatment known to reduce CPT-11 toxicity. In the first set of experiments tumour-bearing rats received a dose-intensive CPT-11 regimen (125 mg kg(-1)×3 days), with or without oral glutamine bolus (0.75 g kg(-1)). In a subsequent more clinically-oriented chemotherapy regimen, rats received two cycles of CPT-11 (50 mg kg(-1)) followed by 5-flurouracil (50 mg kg(-1)). The analysis of fecal samples over time demonstrated that tumours changed the composition of intestinal microbiota, increasing the abundance of clostrridial clusters I, XI, and Enterobacteriaceae. CPT-11 chemotherapy increased cecal Clostridium cluster XI and Enterobacteriaceae, particularly after the dose-intensive therapy. Glutamine treatment prevented the reduced abundance of major bacterial groups after CPT-11 administration; i.e. total bacteria, Clostridium cluster VI, and the Bacteroides-group. Virulence factor/toxin genes of pathogenic Escherichia coli and Clostridium difficile were not detected in the cecal microbiota. In conclusion, both colon cancer implantation and CPT-11-based chemotherapies disrupted the intestinal microbiota. Oral glutamine partially mitigated CPT-11 toxicity and induced temporary changes of the intestinal microbiota.
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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) | 0.001 | 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".