Differential Effects on Intestinal Adaptation Following Exogenous Glucagon‐Like Peptide 2 Therapy With and Without Enteral Nutrition in Neonatal Short Bowel Syndrome
Bibliographic record
Abstract
BACKGROUND: We aim to study the efficacy of exogenously administered glucagon-like peptide 2 (GLP-2) on intestinal adaptation in 2 preclinical models of neonatal short bowel syndrome (SBS) according to remnant intestinal anatomy, with and without ileum. Furthermore, we aim to determine if this adaptive effect was potentiated with enteral nutrition (EN). METHODS: Neonatal piglets were block-randomized to 75% mid-intestinal (JI group, retains ileum) or distal-intestinal (JC group, has no ileum) resection or no resection (sham control) and GLP-2 treatment (11 nmol/kg/d) or saline control for 7 days. Piglets received nutrition support, either 100% parenteral nutrition (PN; 0% EN, n = 32 in total) or 80% PN + 40% EN (n = 28 in total). Adaptation was assessed by morphological and histological changes, as well as RT quantitative polymerase chain reaction of nutrient transporters and tight junctional proteins and fat absorption. Data are analyzed by 3-way analysis of variance (ANOVA) and 2-way ANOVA per EN level. RESULTS: GLP-2 treatment lengthened villi, deepened crypts, and improved intestinal weight in the remnant intestine of JC piglets. EN was a more potent adaptive stimulus for JI piglets. Small intestinal lengthening occurred only in the JI group, when given EN. There was no difference in total fat absorption and messenger RNA expression of nutrient transporters and tight junctional proteins. CONCLUSIONS: GLP-2 administration augmented structural adaptation in JC piglets with distal intestinal resection. Given JI anatomy, further stimulation by GLP-2 treatment over innate adaptation and stimulation by EN was modest and restricted to ileum. The differential effect of GLP-2 in neonatal SBS, depending on remnant anatomy, has important implications for clinical translation and planning of clinical trials.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".