Alleviating Ischemia-Reperfusion Injury in Small Bowel
Bibliographic record
Abstract
An amino acid-based solution has been recently developed and has demonstrated significant protective effects during cold storage of small bowel (SB). This study was designed to examine the role of this novel solution in ameliorating intestinal injury in an in vivo model of ischemia-reperfusion (IR). The impact of luminal treatment with an amino acid-based (AA) solution was assessed throughout reperfusion after 60-min warm ischemia (WI) in rodent SB. Energetics (ATP and total adenylates) remained significantly elevated throughout 60-min reperfusion in AA-treated tissue compared with untreated controls. Increases in end-products (ammonia and alanine) and increases in alanine aminotransferase and glutaminase activity implicated greater amino acid metabolism in AA-treated tissues. After reperfusion, malondialdehyde levels were similar between all groups. Glutathione levels were consistently elevated in AA-treated tissues and by 60 min reperfusion values were sixfold greater than control. AA-mediated protection during IR resulted in reduced neutrophil infiltration suggesting a weaker inflammatory response. Barrier function and electrophysiology parameters exhibited a clear pattern of mucosal preservation in AA-treated tissues; histology supported these findings. This study raises the possibility of a role for a luminal nutrient-rich solution during ischemic storage of small bowel in the clinic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.002 | 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".