Cholesterol facilitates the native mechanism of Ca2+-triggered membrane fusion
Bibliographic record
Abstract
The process of regulated exocytosis is defined by the Ca2+-triggered fusion of two apposed membranes, enabling the release of vesicular contents. This fusion step involves a number of energetically complex steps and requires both protein and lipid membrane components. The role of cholesterol has been investigated using isolated release-ready native cortical secretory vesicles to analyze the Ca2+-triggered fusion step of exocytosis. Cholesterol is a major component of vesicle membranes and we show here that selective removal from membranes, selective sequestering within membranes, or enzymatic modification causes a significant inhibition of the extent, Ca2+ sensitivity and kinetics of fusion. Depending upon the amount incorporated, addition of exogenous cholesterol to cholesterol-depleted membranes consistently recovers the extent, but not the Ca2+ sensitivity or kinetics of fusion. Membrane components of comparable negative curvature selectively recover the ability to fuse, but are unable to recover the kinetics and Ca2+ sensitivity of vesicle fusion. This indicates at least two specific positive roles for cholesterol in the process of membrane fusion: as a local membrane organizer contributing to the efficiency of fusion, and, by virtue of its intrinsic negative curvature, as a specific molecule working in concert with protein factors to facilitate the minimal molecular machinery for fast Ca2+-triggered fusion.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".