Vascular signaling through cholesterol-rich domains: implications in hypertension
Bibliographic record
Abstract
PURPOSE OF REVIEW: Lipid rafts are emerging as key players in the integration of cellular responses. Alterations in these highly regulated signaling cascades are important in structural, mechanical and functional abnormalities that underlie vascular pathological processes. The present review focuses on recent advances in signal transduction through caveolae/lipid rafts, implicated in hypertensive processes. RECENT FINDINGS: Caveolae/lipid rafts function as sites of dynamic regulatory events in receptor-induced signal transduction. Mediators of vascular function, including G-protein coupled receptors, Src family tyrosine kinases, receptor tyrosine kinases, protein phosphatases and nitric oxide synthase, are concentrated within these microdomains. The assembly of functionally active nicotinamide adenine dinucleotide phosphate oxidase and subsequent reactive oxygen species production are also dependent on interactions within the caveolae/lipid rafts. Recent findings have also demonstrated the importance of actin-cytoskeleton and focal adhesion sites for protein interactions with caveolae/lipid raft. SUMMARY: Many vascular signaling processes are altered in hypertension. Whether these events involve lipid rafts/caveolae remains unclear. A better understanding of how signaling molecules compartmentalize in lipid rafts/caveolae will provide further insights into molecular mechanisms underlying vascular damage in cardiovascular 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".