Bibliographic record
Abstract
Exocytosis is the process of fusion of a membrane-bound vesicle with the cell membrane and subsequent release of the vesicle content to the outside. It is now widely accepted that SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) proteins are key components in the molecular machinery of exocytosis. SNARE proteins on the vesicle membrane selectively form complexes with specific SNAREs on the cell membrane. In a variant of exocytosis, called compound exocytosis, secretory vesicles still fuse with the cell membrane but vesicle-to-vesicle fusion enhances secretory output. Two types of compound exocytosis occur, either vesicles fuse with each other and then fuse with the cell membrane, or a vesicle fuses with the cell membrane and then becomes a target for further vesicles to fuse with it. It is expected that SNAREs are important for vesicle-to-vesicle fusion but the mechanism(s) that control these processes is unknown. In our recent paper (Behrendorff et al. 2011) we provide evidence that VAMP8 (a Q-SNARE) is essential in regulating compound exocytosis. Here we discuss the implications of our findings with reference to a new model for the control of vesicle-to-vesicle fusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".