MétaCan
Menu
Back to cohort
Record W2905430542 · doi:10.1126/science.aav1483

Synaptotagmin-3 drives AMPA receptor endocytosis, depression of synapse strength, and forgetting

2018· article· en· W2905430542 on OpenAlexafffund
Ankit Awasthi, Binu Ramachandran, Saheeb Ahmed, Eva Benito, Yo Shinoda, Noam Nitzan, Alina S. Heukamp, Sabine Rannio, Henrik Martens, Katja Burk, Yu Tian Wang, André Fischer, Camin Dean

Bibliographic record

VenueScience · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of British Columbia
FundersFP7 Ideas: European Research CouncilDeutsche ForschungsgemeinschaftCanadian Institutes of Health ResearchAlexander von Humboldt-Stiftung
KeywordsAMPA receptorLong-term potentiationEndocytic cycleNeuroscienceLong-term depressionForgettingSynaptic plasticityPostsynaptic potentialSilent synapseSynapseMetaplasticityGlutamate receptorCell biologyBiologyChemistryEndocytosisReceptorPsychologyBiochemistryCognitive psychology

Abstract

fetched live from OpenAlex

Forgetting is important. Without it, the relative importance of acquired memories in a changing environment is lost. We discovered that synaptotagmin-3 (Syt3) localizes to postsynaptic endocytic zones and removes AMPA receptors from synaptic plasma membranes in response to stimulation. AMPA receptor internalization, long-term depression (LTD), and decay of long-term potentiation (LTP) of synaptic strength required calcium-sensing by Syt3 and were abolished through Syt3 knockout. In spatial memory tasks, mice in which Syt3 was knocked out learned normally but exhibited a lack of forgetting. Disrupting Syt3:GluA2 binding in a wild-type background mimicked the lack of LTP decay and lack of forgetting, and these effects were occluded in the Syt3 knockout background. Our findings provide evidence for a molecular mechanism in which Syt3 internalizes AMPA receptors to depress synaptic strength and promote forgetting.

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)0.003
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 score0.006
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.033
GPT teacher head0.345
Teacher spread0.312 · 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

Citations138
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueScienceSame topicNeuroscience and Neuropharmacology ResearchFrench-language works237,207