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Record W2166933033 · doi:10.1101/cshperspect.a016915

Presynaptic Membrane Retrieval and Endosome Biology: Defining Molecularly Heterogeneous Synaptic Vesicles

2013· review· en· W2166933033 on OpenAlexfundno aff
Jennifer R. Morgan, H. Skye Comstra, M. Cohen, Victor Faúndez

Bibliographic record

VenueCold Spring Harbor Perspectives in Biology · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesSchool of Medicine, Emory UniversityNational Institutes of HealthCanada Excellence Research Chairs, Government of CanadaEmory University
KeywordsSynaptic vesicleBiologyExocytosisVesicleKiss-and-run fusionEndosomeSynapseEndocytosisVesicle fusionNeuroscienceBulk endocytosisSynaptic vesicle recyclingCell biologySecretionCellBiochemistryMembraneIntracellular

Abstract

fetched live from OpenAlex

The release and uptake of neurotransmitters by synaptic vesicles is a tightly controlled process that occurs in response to diverse stimuli at morphologically disparate synapses. To meet these architectural and functional synaptic demands, it follows that there should be diversity in the mechanisms that control their secretion and retrieval and possibly in the composition of synaptic vesicles within the same terminal. Here we pay particular attention to areas where such diversity is generated, such as the variance in exocytosis/endocytosis coupling, SNAREs defining functionally diverse synaptic vesicle populations and the adaptor-dependent sorting machineries capable of generating vesicle diversity. We argue that there are various synaptic vesicle recycling pathways at any given synapse and discuss several lines of evidence that support the role of the endosome in synaptic vesicle recycling.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0000.002
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.003

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.

Opus teacher head0.021
GPT teacher head0.282
Teacher spread0.261 · 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 designTheoretical or conceptual
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

Citations40
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCold Spring Harbor Perspectives in BiologySame topicCellular transport and secretionFrench-language works237,207