Hyperosmolarity enhances the lung capillary barrier
Bibliographic record
Abstract
Although capillary barrier deterioration underlies major inflammatory lung pathology, barrier-enhancing strategies are not available. To consider hyperosmolar therapy as a possible strategy, we gave 15-minute infusions of hyperosmolar sucrose in lung venular capillaries imaged in real time. Surprisingly, this treatment enhanced the capillary barrier, as indicated by quantification of the capillary hydraulic conductivity. The barrier enhancement was sufficient to block the injurious effects of thrombin, TNF-alpha, and H2O2 in single capillaries, and of intratracheal acid instillation in the whole lung. Capillary immunofluorescence indicated that the hyperosmolar infusion markedly augmented actin filament formation and E-cadherin expression at the endothelial cell periphery. The actin-depolymerizing agent latrunculin B abrogated the hyperosmolar barrier enhancement as well as the actin filament formation, suggesting a role for actin in the barrier response. Furthermore, hyperosmolar infusion blocked TNF-alpha-induced P-selectin expression in an actin-dependent manner. Our results provide the first evidence to our knowledge that in lung capillaries, hyperosmolarity remodels the endothelial barrier and the actin cytoskeleton to enhance barrier properties and block proinflammatory secretory processes. Hyperosmolar therapy may be beneficial in lung inflammatory disease.
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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 | 0.000 |
| 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".