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Record W2951698410 · doi:10.3389/fncel.2019.00291

The Stability of Glutamatergic Synapses Is Independent of Activity Level, but Predicted by Synapse Size

2019· article· en· W2951698410 on OpenAlexafffund
Dylan P. Quinn, Annette Kolar, Sydney A. Harris, Michael Wigerius, J. Paul Fawcett, Stefan Krueger

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlutamatergicSynapseNeuroscienceSilent synapseHippocampal formationGlutamate receptorActive zoneBiologySynaptic vesicleChemistryReceptorBiochemistryVesicle

Abstract

fetched live from OpenAlex

Neuronal activity is thought to drive the remodeling of circuits in the mammalian cerebral cortex. However, its precise function in the underlying formation and elimination of glutamatergic synapses has remained controversial. To clarify the role of activity in synapse turnover, we have assessed the effects of inhibition of glutamate release from a sparse subset of cultured hippocampal neurons on synapse turnover. Sustained chemogenetic attenuation of release through presynaptic expression of a designer receptor exclusively activated by designer drugs (DREADD) had no effect on the formation or elimination of glutamatergic synapses. Sparse expression of tetanus neurotoxin light chain (TeNT-LC), a synaptobrevin-cleaving protease that completely abolishes neurotransmitter release, likewise did not lead to changes in the rate of synapse elimination, although it reduced the rate of synapse formation. The stability of active and silenced synapses correlated with measures of synapse size. While not excluding a modulatory role in synapse elimination, our findings show that synaptic activity is neither required for the removal nor the maintenance of glutamatergic synapses between hippocampal neurons. Our results also demonstrate that the stability of glutamatergic synapses scales with their size irrespective of their activity.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.279
Teacher spread0.244 · 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.

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

Citations30
Published2019
Admission routes2
Has abstractyes

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