Vascular Barrier Regulation by PAF, Ceramide, Caveolae, and NO - an Intricate Signaling Network with Discrepant Effects in the Pulmonary and Systemic Vasculature
Bibliographic record
Abstract
Increased endothelial permeability and vascular barrier failure are hallmarks of inflammatory responses in both the pulmonary and the systemic circulation. Platelet-activating factor (PAF) has been implicated as an important lipid mediator in the formation of pulmonary and extrapulmonary edema. Ostensibly, the PAF-induced signaling pathways in endothelial cells utilize similar structures and molecules including acid sphingomyelinase, ceramide, caveolae, endothelial nitric oxide synthase, and nitric oxide, in pulmonary and systemic microvessels. Yet, the constituents of these signaling pathways act and respond in distinctly different and frequently opposing ways in the lung versus organs of the systemic circulation. By confronting seemingly discrepant findings from the literature, we reconstruct the differential signaling pathways by which PAF regulates edema formation in the systemic and the pulmonary vascular bed, and trace this dichotomy from the level of myosin light chain kinase via the regulation of endothelial nitric oxide synthase and sphingomyelinase signaling to the level of caveolar trafficking. Here, we propose that PAF regulates vascular barrier function in individual organs by opposing signaling pathways that culminate in increased respectively decreased nitric oxide synthesis in the systemic and the pulmonary endothelium. The present review may provide a physiological explanation for the overall disappointing results of previous pharmacological strategies in conditions of generalized barrier failure such as sepsis, and instead advertises the development of organ-specific interventions by targeting the individual composition or trafficking of endothelial caveolae.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".