Preserving the mucosal barrier during small bowel storage1
Bibliographic record
Abstract
BACKGROUND: A major obstacle to successful small bowel transplantation is that of bacterial infection. The aim of this study was to preserve the small bowel mucosal barrier by using oxygenated luminal perfusion with a proven amino acid (AA)-based solution. METHODS: Rat small bowel (n=4) was flushed vascularly with modified University of Wisconsin solution and flushed luminally as follows: group 1, none (control); group 2, AA solution; group 3, 1-hr perfusion then storage with AA; group 4, continuous perfusion with AA. Energetics, malondialdehyde (MDA), glutathione (reduced), and histology were assessed over 24 hr at 4 degrees C. RESULTS: Within 4 hr, adenosine triphosphate (ATP) dropped by 25% to 65% in all groups except for group 4, which remained unchanged from fresh tissue values throughout 12 hr. After 12 hr, ATP in groups 1 through 3 had dropped to 0.5 to 0.9 micromol/g, compared with 1.5 micromol/g for group 4. Even after 24 hr, group 4 levels were more than twofold greater than groups 1 through 3. MDA increased transiently in tissues subjected to simple flush (no perfusion), whereas levels in perfused tissues remained elevated throughout the 24-hr period. Glutathione in group 1 dropped by greater than 50% from fresh tissue values but increased over 24 hr in groups 2 and 3 by 50% to 55%. Overall, histologic injury was markedly less in groups 2 through 4; however, after 24 hr, the lowest injury was observed in group 3 (median, grade 2) compared with groups 1 and 4 (grades 7 and 4). CONCLUSIONS: Our data indicate that perfusion clearly improves tissue energetics. However, mucosal integrity is markedly superior, with only a brief 1-hr period of perfusion; oxidative and mechanical stress are the factors likely responsible for injury resulting from continuous perfusion.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".