Novel Neonatal Piglet Models of Surgical Short Bowel Syndrome With Intestinal Failure
Bibliographic record
Abstract
OBJECTIVES: Short bowel syndrome occurring after surgery for acquired or congenital intestinal abnormalities causes considerable neonatal morbidity and mortality. Animal models are a valuable research tool for this problem; however, few successful neonatal models have been developed and most do not include distal intestinal resection as seen commonly in human babies. We report novel piglet models addressing these gaps. SUBJECTS AND METHODS: Neonatal piglets (1-6 days) underwent venous and gastric catheter insertion and 75% intestinal resection. Group 1 (n = 6) had midintestinal resection with jejunoileal anastomosis; group 2 (n = 5) had distal intestinal resection with jejunocolic anastomosis; group 3 (n = 5) were sham controls; and group 4 (n = 5) were sow reared. Postoperatively, groups 1 to 3 piglets commenced parenteral nutrition (PN), and enteral nutrition was introduced and advanced using a standard regimen. Data collection included days on PN, weight gain, fat absorption, small intestine lengthening, and bowel/liver histology. RESULTS: Group 2 piglets had more days on PN (P = 0.008), less weight gain (P = 0.027), and greater malabsorption (P = 0.012). They did not show small intestine lengthening and had more cholestatic liver disease. Group 1 piglets had histological evident intestinal adaptation and 1.5-fold intestinal lengthening (P = 0.001). CONCLUSIONS: These novel piglet models of short bowel syndrome are the first to represent the full clinical spectrum of intestinal failure as observed in human neonates. By considering the impact of different short bowel anatomy on potential for adaptation and growth, these animal models are a significant advance. They permit evaluation of new therapies to promote intestinal adaptation and reduce complications, such as cholestasis.
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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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".