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Record W1616451653 · doi:10.1016/j.celrep.2015.05.034

MicroRNA-22 Gates Long-Term Heterosynaptic Plasticity in Aplysia through Presynaptic Regulation of CPEB and Downstream Targets

2015· article· en· W1616451653 on OpenAlexaff
Ferdinando Fiumara, Priyamvada Rajasethupathy, Igor Antonov, Stylianos Kosmidis, Wayne S. Sossin, Eric R. Kandel

Bibliographic record

VenueCell Reports · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersHoward Hughes Medical Institute
KeywordsAplysiaNeuroscienceDownregulation and upregulationBiologyCell biologySynaptic plasticitySynapseRegulatorNeurotransmitterNeurotransmissionReceptorCentral nervous systemGeneGenetics

Abstract

fetched live from OpenAlex

The maintenance phase of memory-related long-term facilitation (LTF) of synapses between sensory and motor neurons of the gill-withdrawal reflex of Aplysia depends on a serotonin (5-HT)-triggered presynaptic upregulation of CPEB, a functional prion that regulates local protein synthesis at the synapse. The mechanisms whereby serotonin regulates CPEB levels in presynaptic sensory neurons are not known. Here, we describe a sensory neuron-specific microRNA 22 (miR-22) that has multiple binding sites on the mRNA of CPEB and inhibits it in the basal state. Serotonin triggers MAPK/Erk-dependent downregulation of miR-22, thereby upregulating the expression of CPEB, which in turn regulates, through functional CPE elements, the presynaptic expression of atypical PKC (aPKC), another candidate regulator of memory maintenance. Our findings support a model in which the neurotransmitter-triggered downregulation of miR-22 coordinates the regulation of genes contributing synergistically to the long-term maintenance of memory-related synaptic plasticity.

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)0.000
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 score0.134
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.237
Teacher spread0.226 · 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

Citations71
Published2015
Admission routes1
Has abstractyes

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