Adenosine receptor activation improves microcirculation in experimental intestinal ischemia/reperfusion
Bibliographic record
Abstract
Gut ischemia and reperfusion (IR), e.g. in small bowel transplantation or during resuscitation, may result in severe impairment of the intestinal microcirculation. Potential sequelae are mucosal damage, loss of intestinal barrier function, bacterial translocation, systemic inflammation, multiple organ failure and death. We hypothesized a protective role for extracellular adenosine signalling in intestinal IR injury. Using intravital microscopy we investigated the effects of the adenosine receptor (AR) agonist NECA (5'-N-ethyl carboxamide adenosine) on leukocyte-endothelial interactions and capillary perfusion in the intestinal microcirculation following intestinal IR. Six groups of Lewis rats (n = 44) were studied: control, NECA (5'-N-ethyl carboxamide adenosine), IR (30 minutes of intestinal ischemia, 2 hours of reperfusion), IR + NECA, IR + NECA + MRS1754 (A(2B)AR antagonist), IR + NECA + DPCPX (A(1)AR antagonist). All substances were administered i.v. immediately after declamping of the superior mesenteric artery. Intravital microscopy was performed after 2 hours of reperfusion. Following IR we observed a significant increase of leukocyte adhesion in the intestinal submucosal venules and a reduced capillary perfusion within the muscular layers. NECA reduced leukocyte activation and improved capillary perfusion significantly. Administration of A(2B)AR antagonist completely reversed the NECA effect, whereas A(1)AR inhibition only partially abolished the action of NECA. The data support the hypothesis that adenosine signalling is involved in intestinal IR injury. A(2B)AR may be more important than A(1)AR because A(2B)AR inhibition by MRS1754 completely reversed the effect of the adenosine receptor agonist NECA.
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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) | 0.001 | 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".