Polymorphonuclear leukocyte (PMN) migration across vascular endothelial cells (EC) in the absence or presence of IL‐1β differentially regulate expression of EC adhesion molecules ICAM‐1 and E‐selectin
Bibliographic record
Abstract
Our findings indicate that PMN migration across activated EC results in down‐regulation of EC nuclear transcription factor, NFκB. However, the subsequent functional consequences are largely unknown. In this study we assessed the effects of PMN transendothelial migration on NFκB‐dependent expression of EC adhesion molecules, ICAM‐1 and E‐selectin during inflammation. To this end human endothelial cells (HUVEC) were grown in Traswell inserts and stimulated with IL‐1β (1ng/ml; 4 hrs). Subsequently, PMN were added and allowed to migrate across HUVEC in response to fMLP (10 −8 M) chemotactic gradient in the absence (i.e. across washed HUVEC) or presence of IL‐1β. ICAM‐1 and E‐selectin gene expression in EC was assessed by RT‐PCR after 4 or 24 hrs following PMN migration. The obtained results indicate that migration of PMN across IL‐1β treated and subsequently washed HUVEC results in a marked down‐regulation of IL‐1 β‐induced ICAM‐1, and to a lesser degree, E‐selectin gene expression as assessed 4 and 24 hrs following PMN migration. On the contrary, migration of PMN across activated HUVEC in the presence of IL‐1β results in a further increase in both, ICAM‐1 and E‐selectin expression. Taken together these findings indicate that migrating PMN differentially modulate expression of EC adhesion molecules during inflammation and can offer EC with both, anti‐ and pro‐inflammatory stimuli (HSFO‐NA5580/NA6171)
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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) | 0.000 | 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 | 0.000 |
| 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".