Protein metabolism in the small intestine during cancer cachexia and chemotherapy in mice.
Bibliographic record
Abstract
The impact of cancer cachexia and chemotherapy on small intestinal protein metabolism and its subsequent recovery was investigated. Cancer cachexia was induced in mice with colon 26 adenocarcinoma, which is a small and slow-growing tumor characteristic of the human condition, and can be cured with 100% efficacy using an experimental nitrosourea, cystemustine (C6H12ClN3O4S). Both healthy mice and tumor-bearing mice were given a single i.p. injection of cystemustine (20 mg/kg) 3 days after the onset of cachexia. Cancer cachexia led to a reduced in vivo rate of protein synthesis in the small intestine relative to healthy mice (-13 to -34%; P < 0.05), resulting in a 25% loss of protein mass (P < 0.05), and decreased villus width and crypt depth (P < 0.05). In treated mice, acute cytotoxicity of chemotherapy did not promote further wasting of small intestinal protein mass, nor did it result in further damage to intestinal morphology. In contrast, mucosal damage and a 17% reduction in small intestinal protein mass (P < 0.05) were evident in healthy mice treated with cystemustine, suggesting that the effects of chemotherapy on the small intestine in a state of cancer cachexia are not additive, which was an unexpected finding. Complete and rapid recovery of small intestinal protein mass in cured mice resulted from an increase in the rate of protein synthesis compared with healthy mice (23-34%; P < 0.05). Northern hybridizations of mRNA encoding components of the major proteolytic systems suggested that proteolysis may not have mediated intestinal wasting or recovery. A major clinical goal should be to design methods to improve small intestinal protein metabolism before the initiation of chemotherapy.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".