Analysis of tight junctions during neutrophil transendothelial migration
Bibliographic record
Abstract
Intercellular junctions have long been considered the main sites through which adherent neutrophils (PMNs) penetrate the endothelium. Tight junctions (TJs; zonula occludens) are the most apical component of the intercellular cleft and they form circumferential belt-like regions of intimate contact between adjacent endothelial cells. Whether PMN transmigration involves disruption of the TJ complex is unknown. We report here that endothelial TJs appear to remain intact during PMN adhesion and transmigration. Human umbilical vein endothelial cell (HUVEC) monolayers, a commonly used model for studying leukocyte trafficking, were cultured in astrocyte-conditioned medium to enhance TJ expression. Immunofluorescence microscopy and immunoblot analysis showed that activated PMN adhesion to resting monolayers or PMN migration across interleukin-1-treated monolayers does not result in widespread proteolytic loss of TJ proteins (ZO-1, ZO-2, and occludin) from endothelial borders. Ultrastructurally, TJs appear intact during and immediately following PMN transendothelial migration. Similarly, transendothelial electrical resistance is unaffected by PMN adhesion and migration. Previously, we showed that TJs are inherently discontinuous at tricellular corners where the borders of three endothelial cells meet and PMNs migrate preferentially at tricellular corners. Collectively, these results suggest that PMN migration at tricellular corners preserves the barrier properties of the endothelium and does not involve widespread disruption of endothelial TJs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".