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Record W2002769233 · doi:10.1002/mus.1044

Molecular mechanisms of neurotransmitter release

2001· review· en· W2002769233 on OpenAlexaff
Edward A. Fon, Robert H. Edwards

Bibliographic record

VenueMuscle & Nerve · 2001
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsNeurotransmitterNeurotransmissionNeurotransmitter AgentsSynaptic vesicleNeurotransmitter receptorActive zoneNeuroscienceReuptakeBiologyPostsynaptic potentialSynaptic vesicle recyclingSynapsinCell biologyReceptorVesicleBiochemistryCentral nervous systemSerotonin

Abstract

fetched live from OpenAlex

The release of neurotransmitter from neurons represents one of the pivotal events in synaptic transmission. Neurotransmitters are released from synaptic vesicles in presynaptic neurons in response to neural activity, diffuse across the synaptic cleft, and bind specific receptors in order to bring about changes in postsynaptic neurons. Some of the molecular processes that govern neurotransmitter release are now becoming better understood. The steps involved can be broken down into two partially overlapping presynaptic cycles, the neurotransmitter cycle and the synaptic vesicle cycle. The neurotransmitter cycle involves transmitter biosynthesis, storage, reuptake, and degradation. The synaptic vesicle cycle involves targeting to the nerve terminal, docking, fusion, endocytosis, and recycling. Biochemical and structural studies have yielded important insight into our understanding of each of these two cycles. Further, both pharmacological and genetic interference with either of these cycles results in profound alterations in synaptic transmission and behavior, demonstrating the crucial role of neurotransmitter release.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.105
GPT teacher head0.376
Teacher spread0.271 · 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

Citations85
Published2001
Admission routes1
Has abstractyes

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