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Record W2911843365 · doi:10.1080/15476286.2019.1572435

miR-151-5p modulates APH1a expression to participate in contextual fear memory formation

2019· article· en· W2911843365 on OpenAlexaff
Xu‐Feng Xu, Youcui Wang, Liang Zong, Xiaolong Wang

Bibliographic record

VenueRNA Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
FundersNatural Science Foundation of Shandong Province
KeywordsHippocampal formationmicroRNABiologyNeuroscienceLong-term memoryDownregulation and upregulationHippocampusMemory consolidationMemory impairmentCell biologyMemory formationGene expressionGeneGeneticsCognition

Abstract

fetched live from OpenAlex

Long-term memory formation requires gene expression and new protein synthesis. MicroRNAs (miRNAs), a family of small non-coding RNAs that inhibit target gene mRNA expression, are involved in new memory formation. In this study, elevated miR-151-5p (miR-151) levels were found to be responsible for hippocampal contextual fear memory formation. Using a luciferase reporter assay, we demonstrated that miR-151 targets APH1a, a protein that has been identified as a key factor in γ-secretase activity, namely APH1a. Blocking miR-151 can upregulate APH1a protein levels and subsequently impair hippocampal fear memory formation. These results indicate that miR-151 is involved in hippocampal contextual fear memory by inhibiting APH1a protein expression. This work provides novel evidence for the role of miRNAs in memory formation and demonstrates the implication of APH1a protein in miRNA processing in the adult brain.

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 score0.022
Threshold uncertainty score0.494

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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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