PMN transendothelial migration decreases nuclear NFκB in IL-1β–activated endothelial cells
Bibliographic record
Abstract
During the systemic inflammatory response, circulating cytokines interact with the vascular endothelium, resulting in activation and nuclear accumulation of the nuclear transcription factor, nuclear factor kappa B (NFkappaB). In turn, NFkappaB transactivates relevant proinflammatory genes, resulting in an amplification of the inflammatory response. Because this scenario is potentially detrimental to the host, mechanisms exist to limit this amplification. Using an in vitro system that mimics the vascular-interstitial interface during inflammation (cell culture inserts), we provide evidence for the existence of a novel negative feedback mechanism on NFkappaB activity. We show that the interleukin 1beta-induced accumulation of nuclear NFkappaB in human umbilical vein endothelial cell monolayers is dramatically reduced when polymorphonuclear leukocytes (PMN) are allowed to migrate across these monolayers. This effect does not appear to be due to PMN-derived elastase or nitric oxide. Fixed PMN (adhere but do not migrate) did not affect nuclear NFkappaB. Furthermore, cross-linking of platelet-endothelial cell adhesion molecule-1 (PECAM-1), but not intercellular adhesion molecule-1, reduces human umbilical vein endothelial cell nuclear NFkappaB induced by interleukin 1beta. Finally, interaction of PMN with PECAM-1-deficient endothelial cells does not reduce nuclear NFkappaB. These observations indicate that engagement of PECAM-1 by emigrating PMN is a pivotal event in this negative feedback on NFkappaB activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".