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Record W2624230523 · doi:10.1073/pnas.1701201114

Dynamic changes in murine forebrain miR-211 expression associate with cholinergic imbalances and epileptiform activity

2017· article· en· W2624230523 on OpenAlexaff
Uriya Bekenstein, Nibha Mishra, Dan Z. Milikovsky, Geula Hanin, Daniel Zelig, Liron Sheintuch, Amit Berson, David Greenberg, Alon Friedman, Hermona Soreq

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsDalhousie University
FundersSeventh Framework ProgrammeEuropean Research CouncilMinistry of Agriculture and Rural DevelopmentIsrael Science Foundation
KeywordsCholinergicForebrainNeuroscienceVesicular acetylcholine transporterEpileptogenesisEpilepsyBiologyCentral nervous systemCholine acetyltransferase

Abstract

fetched live from OpenAlex

Significance Acute traumatic stress increases the sensitivity to develop epileptic seizures in certain people. It is therefore important to discover physiological mechanisms that avoid epilepsy. To test if rapidly inducible microRNAs (miRs) could mediate such protection, we combined mouse engineering, RNA sequencing, electric recording of brain activity, and learning tests. We discovered that miR-211, originating from an epilepsy-related genomic locus, may be involved, and therefore engineered mice produce a drug-suppressible excess of brain miR-211. In these mice, suppressing miR-211 excess to the original expression levels in normal brains led to electrically recorded epilepsy and hypersensitivity to epilepsy-inducing compounds; it also modified acetylcholine receptor composition. The functional impact of miR-211 dynamics on seizure threshold may enable future development of miR-211–directed therapeutics.

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 score0.454
Threshold uncertainty score0.175

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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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

Citations63
Published2017
Admission routes1
Has abstractyes

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