Endothelin-1 Changes Polymorphonuclear Leukocytes' Deformability and CD11b Expression and Promotes Their Retention in the Lung
Bibliographic record
Abstract
Endothelin (ET)1 influences polymorphonuclear leukocyte (PMN)- endothelial cell interactions. The aim of this study was to examine the effect of ET-1 on factors that influence PMN-endothelial interaction and retention in the lung both in vitro and in vivo. In vitro, high concentration of ET-1 (> or = 10(-8) M) rapidly increased PMN F-actin content (10(-7) M: 58 +/- 6% increase, P<0.01), whereas lower concentration of ET-1 (< or = 10(-9) M) caused a small but consistent decrease in F-actin content (10(-10) M: 6.9+/-1.5% decrease, P< 0.01). Preincubation of PMNs with the nitric oxide donor sodium nitroprusside (SNP) inhibited the F-actin content increase by 10(-7) M of ET-1 (P<0.01), and enhanced the F-actin content decrease by 10(-10) M of ET-1 (P<0.01). Preincubation of PMNs with Nomega-nitro-L-arginine methylester prevented the F-actin content decrease by 10(-10) M of ET-1. ET-1 (10(-7) M) reduced the deformability of PMNs (P<0.01), which was inhibited by preincubation of PMNs with SNP (P<0.05). ET-1 (10(-9) to 10(-7) M) increased CD11b expression of PMNs (P<0.01), which was inhibited by preincubation of PMNs with SNP. In vivo studies showed that the retention of PMNs treated with ET-1 increased from 45+/-8 to 70+/-5% compared with naive PMNs during their first pass through the lung (P<0.05). We conclude that ET-1 changes the F-actin content, the deformability, and the CD11b expression of PMNs in a dose-dependent fashion and that this leads to increased PMN sequestration in pulmonary microvessels.
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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 | 0.001 |
| 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".