Endothelial Domes Encapsulate Adherent Neutrophils and Minimize Increases in Vascular Permeability in Paracellular and Transcellular Emigration
Bibliographic record
Abstract
Local edema, a cardinal sign of inflammation associates closely with neutrophil emigration. Neutrophil emigration has been described to occur primarily through endothelial junctions (paracellular) and more rarely directly through endothelial cells (transcellular). Recently, we reported that unlike in wild-type (wt) mice, Mac-1-/- (CD11b) neutrophils predominantly emigrated transcellularly and was significantly delayed taking 20-30 min longer than the paracellular emigration (wt). In the present study we noted significant anatomical disruption of the endothelium and hypothesized that transcellular emigration would greatly increase vascular permeability. Surprisingly, despite profound disruption of the endothelial barrier as the neutrophils moved through the cells, the changes in vascular permeability during transcellular emigration (Mac-1-/-) were not increased more than in wt mice. Instead increased vascular permeability completely tracked the number of emigrated cells and as such, permeability changes were delayed in Mac-1-/- mice. However, by 60 min neutrophils from both sets of mice were emigrating in large numbers. Electron-microscopy and spinning disk multichannel fluorescence confocal microscopy revealed endothelial docking structures that progressed to dome-like structures completely covering wt and Mac-1-/- neutrophils. These domes completely enveloped the emigrating neutrophils in both wt and Mac-1-/- mice making the mode of emigration underneath these structures extraneous to barrier function. In conclusion, predominantly paracellular versus predominantly transcellular emigration does not affect vascular barrier integrity as endothelial dome-like structures retain barrier function.
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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".