Caveolins, caveolae, and lipid rafts in cellular transport, signaling, and disease
Bibliographic record
Abstract
Caveolae were initially described some 50 years ago. For many decades, they remained predominantly of interest to structural biologists. The identification of a molecular marker for these domains, caveolin, combined with the possibility to isolate such cholesterol- and sphingolipid-rich regions as detergent-insoluble membrane complexes paved the way to more rigorous characterization of composition, regulation, and function. Experiments with knock-out mice for the caveolin genes clearly demonstrate the importance of caveolin-1 and -3 in formation of caveolae. Nonetheless, detergent-insoluble domains are also found in cells lacking caveolin expression and are referred to here as lipid rafts. Caveolae and lipid rafts were shown to represent membrane compartments enriched in a large number of signaling molecules whose structural integrity is essential for many signaling processes. Caveolin-1 is an essential structural component of cell surface caveolae, important for regulating trafficking and mobility of these vesicles. In addition, caveolin-1 is found at many other intracellular locations. Variations in subcellular localization are paralleled by a plethora of ascribed functions for this protein. Here, more recent data addressing the role of caveolin-1 in cellular signaling and the development of diseases like cancer will be preferentially discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".