Endothelial PI 3-kinase activity regulates lymphocyte diapedesis
Bibliographic record
Abstract
Lymphocyte recruitment to sites of inflammation involves a bidirectional series of cues between the endothelial cell (EC) and the leukocyte that culminate in lymphocyte migration into the tissue. Remodeling of the EC F-actin cytoskeleton has been observed after leukocyte adhesion, but the signals to the EC remain poorly defined. We studied the dependence of peripheral blood lymphocyte transendothelial migration (TEM) through an EC monolayer in vitro on EC phosphatidylinositol 3-kinase (PI 3-kinase) activity. Lymphocytes were perfused over cytokine-activated EC using a parallel-plate laminar flow chamber. Inhibition of EC PI 3-kinase activity using LY-294002 or wortmannin decreased lymphocyte TEM (48 +/- 6 or 34 +/- 7%, respectively, vs. control; mean +/- SE; P < 0.05). Similarly, EC knockdown of the p85alpha regulatory subunit of PI 3-kinase decreased lymphocyte transmigration. Treatment of EC with jasplakinolide to inhibit EC F-actin remodeling also decreased lymphocyte TEM to 24 +/- 10% vs. control (P < 0.05). EC PI 3-kinase inhibition did not change the strength of lymphocyte adhesion to the EC or formation of the EC "docking structure" after intercellular adhesion molecule-1 ligation, whereas this was inhibited by jasplakinolide treatment. A similar fraction of lymphocytes migrated on control or LY-294002-treated EC and localized to interendothelial junctions. However, lymphocytes failed to extend processes below the level of vascular endothelial (VE)-cadherin on LY-294002-treated EC. Together these observations indicate that EC PI 3-kinase activity and F-actin remodeling are required during lymphocyte diapedesis and identify a PI 3-kinase-dependent step following initial separation of the VE-cadherin barrier.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".