A Combination of Dexamethasone and Glucagon‐like Peptide‐2 Increase Intestinal Morphology and Glucose Uptake in Suckling Rats
Bibliographic record
Abstract
OBJECTIVES: Glucagon-like peptide (GLP)-2 enhances nutrient uptake in adult animals. Glucocorticosteroids accelerate intestinal ontogeny and increase nutrient uptake in adult animals. We hypothesized that administering GLP-2 and dexamethasone (DEX) to suckling rats will enhance sugar uptake and that this effect persists into the postweaning period. METHODS: Suckling rats were treated for 10 days with GLP-2 (0.1 microg/g/d, twice daily), DEX (0.128 microg/g/d, once daily), GLP-2 + Dex (same doses as above), or placebo. The rate of intestinal uptake of glucose and fructose in sucklings (19-21 days old) and weanlings (49 days old) was assessed using an in vitro ring technique. RESULTS: DEX reduced body weight in weanlings, whereas GLP-2 + DEX prevented this effect. In sucklings, GLP-2 + DEX increased ileal villous height and jejunal and ileal villous width and crypt depth. In sucklings, GLP-2 + DEX increased the maximal transport rate (Vmax) for jejunal glucose uptake, whereas DEX reduced the ileal Vmax. In weanlings, GLP-2 + DEX increased jejunal villous height, whereas ileal villous width and crypt depth were reduced. DEX increased the ileal Vmax and apparent affinity constant for glucose in weanlings. CONCLUSIONS: The combination of these hormones may be useful in stimulating glucose uptake in the developing intestine, and giving DEX to sucklings may enhance glucose uptake in later life.
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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 | 0.000 | 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".