Enteral Feeding Induces Early Intestinal Adaptation in a Parenterally Fed Neonatal Piglet Model of Short Bowel Syndrome
Bibliographic record
Abstract
BACKGROUND: Successful small intestinal (SI) adaptation following surgical resection is essential for optimizing newborn growth and development, but the potential for adaptation is unknown. The authors developed an SI resection model in neonatal piglets supported by intravenous and enteral nutrition. METHODS: Piglets (n = 33, 12-13 days old) were randomized to 80% SI resection with parenteral nutrition feeding (R-PN), 80% SI resection with PN + enteral feeding (R-EN), or sham SI transection with PN + enteral feeding (sham-EN). In resected pigs, the distal 100 cm of ileum (residual SI) and 30 cm of proximal SI were left intact. All pigs received parenteral nutrition postsurgery. Enteral nutrition piglets received continuous gastric infusion of elemental diet from day 3 (40:60 parenteral nutrition:enteral nutrition). Piglets were killed 4, 6, or 10 days postsurgery. RESULTS: By 10 days, R-EN piglets had longer residual SI than R-PN and sham-EN pigs (P < .05). At days 6 and 10, R-EN piglets had greater weight per length of intact SI (P < .05) and isolated mucosa (P < .05) compared to other groups. Greater gut weight in R-EN piglets was facilitated by a greater cellular proliferation index (P < .01) by 4 days compared to other groups and greater overall ornithine decarboxylase activity vs R-PN piglets (P < .05). CONCLUSIONS: This new model demonstrated profound SI adaptation, initiated early postsurgery by polyamine synthesis and crypt cell proliferation and only in response to enteral feeding. These changes translated to greater gut mass and length within days, likely improving functional capacity long term.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".