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Mechanisms of exocytosis

2007· review· en· W2107453029 on OpenAlexaff
Shuzo Sugita

Bibliographic record

VenueActa Physiologica · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsExocytosisExocystMunc-18Cell biologySecretionSecretory VesicleBiologySecretory pathwayVesicleSecretory proteinVesicle fusionChemistryBiochemistryMembraneSynaptic vesicleGolgi apparatus

Abstract

fetched live from OpenAlex

Catecholamines and peptides secreted from dense-core vesicles (DCVs) of adrenal chromaffin cells regulate a wide variety of physiological processes. For instance, the release of noradrenaline and adrenaline plays a key role in regulating heart rate and blood pressure. Thus understanding the mechanisms of secretory processes of DCVs is crucial for understanding the basis of diseases such as hypertension. DCVs undergo several stages of secretory processing before they are exocytosed. These include docking, priming and triggering of membrane fusion/exocytosis. Molecular studies of DCV exocytosis have identified many proteins critically involved in DCV secretion. These proteins include SNARE proteins, Munc18-1, phosphatidylinositol transfer protein, type I phosphatidylinositol-4-phosphate-5-kinases, NSF, Munc13, CAPS1, synaptotagmins, RalA/RalB GTPases and exocyst proteins. In this article, I will discuss the functions of these proteins within the context of the stages (i.e. docking, priming and triggering of membrane fusion/exocytosis) in DCV secretion.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.005

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.

Opus teacher head0.051
GPT teacher head0.307
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations53
Published2007
Admission routes1
Has abstractyes

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