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Vesicular Zinc Regulates the Ca <sup>2+</sup> Sensitivity of a Subpopulation of Presynaptic Vesicles at Hippocampal Mossy Fiber Terminals

2011· article· en· W2082489639 on OpenAlexafffund
N. Lavoie, Danny V. Jeyaraju, Modesto R. Peralta, László Seress, Luca Pellegrini, Katalin Tóth

Bibliographic record

VenueJournal of Neuroscience · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsQueen's UniversityUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSynaptic vesicleVesicleMossy fiber (hippocampus)EndosomeNeurotransmissionZincHippocampal formationCell biologyBiologyBiophysicsGlutamatergicChemistryBiochemistryNeuroscienceMembraneGlutamate receptor

Abstract

fetched live from OpenAlex

Synaptic vesicles segregate into functionally diverse subpopulations within presynaptic terminals, yet there is no information about how this may occur. Here we demonstrate that a distinct subgroup of vesicles within individual glutamatergic, mossy fiber terminals contain vesicular zinc that is critical for the rapid release of a subgroup of synaptic vesicles during increased activity in mice. In particular, vesicular zinc dictates the Ca(2+) sensitivity of release during high-frequency firing. Intense synaptic activity alters the subcellular distribution of zinc in presynaptic terminals and decreases the number of zinc-containing vesicles. Zinc staining also appears in endosomes, an observation that is consistent with the preferential replenishment of zinc-enriched vesicles by bulk endocytosis. We propose that functionally diverse vesicle pools with unique membrane protein composition support different modes of transmission and are generated via distinct recycling pathways.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.231
Teacher spread0.209 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2011
Admission routes2
Has abstractyes

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