Lactose maldigestion during methotrexate-induced gastrointestinal mucositis in a rat model
Bibliographic record
Abstract
Patients with chemotherapy-induced gastrointestinal mucositis suffer from anorexia, diarrhea, and stomach pain, often causing weight loss and malnutrition. When the intestinal function during mucositis would be known, a rational feeding strategy might improve the nutritional state, accelerate recuperation, and increase survival of mucositis patients. We developed a methotrexate (MTX)-induced mucositis rat model to study nutrient digestion and absorption. To determine lactose digestion and absorption of its derivative glucose during mucositis, we injected Wistar rats intravenously with MTX (60 mg/kg) or 0.9% NaCl (controls). Four days later, we orally administered trace amounts of [1-(13)C]lactose and [U-(13)C]glucose and quantified the appearance of labeled glucose in the blood for 3 h. Finally, we determined plasma citrulline level and harvested the small intestine to assess histology, myeloperoxidase level, glycohydrolase activity, immunohistochemical protein, and mRNA expression. MTX-treated rats showed profound villus atrophy and epithelial damage. During the experimental period, the absorption of lactose-derived [1-(13)C]glucose was 4.2-fold decreased in MTX-treated rats compared with controls (P < 0.01). Lactose-derived [1-(13)C]glucose absorption correlated strongly with villus length (rho = 0.86, P < 0.001) and with plasma citrulline level (rho = 0.81, P < 0.001). MTX treatment decreased jejunal lactase activity (19.5-fold, P < 0.01) and immunohistochemical protein and mRNA expression (39.7-fold, P < 0.01) compared with controls. Interestingly, MTX treatment did not affect the absorption of [U-(13)C]glucose during the experimental period. We conclude that lactose digestion is severely decreased during mucositis while glucose absorption is still intact, when supplied in trace amounts. Plasma citrulline level might be a useful objective, noninvasive marker for lactose maldigestion during mucositis in clinic.
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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 | 0.001 |
| 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 | 0.001 | 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".