Co‐regulation of Transcellular and Paracellular Leak Across Microvascular Endothelium By Dynamin and Rac
Bibliographic record
Abstract
Increased permeability of the endothelium is the hallmark of inflammation. Leakage can occur between (paracellular) or through (transcytosis) endothelial cells, yet little is known about whether these pathways are linked. We investigated whether transcytosis and paracellular leakage are co‐regulated. Using molecular and pharmacologic approaches, we inhibited transcytosis of albumin in primary human microvascular endothelium and measured paracellular permeability. Blockade of transcytosis induced an increase in paracellular leak that was not explained by decreases in caveolin‐1 or by increased activity of nitric oxide synthase. The effect required caveolin‐1 but occurred in cells depleted of clathrin, indicating that it was not due to the general inhibition of endocytosis. Inhibiting transcytosis by blocking dynamin increased paracellular leak concomitantly with the loss of cortical actin from the plasma membrane and the displacement of active Rac from the plasmalemma. Importantly, inhibition of paracellular leak by sphingosine‐1‐phosphate, which activates Rac and induces cortical actin, caused a significant increase in transcytosis of albumin in vitro and in an ex vivo whole lung model. Dominant‐negative Rac diminished albumin uptake by endothelia. Thus, transcytosis and paracellular permeability are co‐regulated through a signalling pathway linking dynamin, Rac and actin.
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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 | 0.001 |
| 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".