Platelets modulate ischemia/reperfusion-induced leukocyte recruitment in the mesenteric circulation
Bibliographic record
Abstract
P-selectin-dependent leukocyte-endothelial cell adhesion has been implicated in the pathogenesis of ischemia/reperfusion (I/R) injury in several vascular beds, including the gut. Because platelet-endothelial (P/E) cell adhesion also occurs in postischemic venules, the possibility exists that the expression of P-selectin on the surface of platelets that are adherent to venular endothelial cells may mediate the leukocyte recruitment elicited by I/R. P-selectin expression [dual radiolabeled monoclonal antibody (MAb) technique] and neutrophil accumulation [myeloperoxidase (MPO) activity] were measured in the postischemic small intestine of untreated rats and rats treated with either antiplatelet serum (APS) or MAbs directed against either P-selectin, GPIIb/IIIa, or fibrinogen. The increases in P-selectin expression and tissue MPO normally elicited by I/R were significantly attenuated in the different treatment groups, suggesting that I/R-induced neutrophil recruitment is a platelet-dependent, P-selectin-mediated process. Intravital microscopy was then employed to examine this process relative to leukocyte-endothelial cell adhesion in postischemic rat mesenteric venules. The recruitment of adherent and emigrated leukocytes after I/R was attenuated by pretreatment with a MAb against, either P-selectin, GPIIb/IIIa, or fibrinogen, as well as an Arg-Gly-Asp peptide. Whereas thrombocytopenia greatly blunted leukocyte emigration, it did not alter the leukocyte adherence response to I/R. These findings suggest that platelet-associated P-selectin contributes to the accumulation of leukocytes in postischemic tissue via a mechanism that alters transendothelial leukocyte migration.
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) | 0.001 | 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".