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Record W2610766532 · doi:10.3389/fnmol.2017.00127

MotomiRs: miRNAs in Motor Neuron Function and Disease

2017· review· en· W2610766532 on OpenAlexafffund
Zachary C. E. Hawley, Danae Campos‐Melo, Cristian A. Droppelmann, Michael J. Strong

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2017
Typereview
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsWestern University
FundersE-RareALS Society of Canada
KeywordsAmyotrophic lateral sclerosisMotor neuronNeuroscienceSpinal muscular atrophySMA*microRNADiseaseBiologyMotor functionFunction (biology)MedicineSpinal cordPhysical medicine and rehabilitationPathologyGeneGeneticsComputer science

Abstract

fetched live from OpenAlex

MiRNAs are key regulators of the mammalian transcriptome that have been increasingly linked to degenerative diseases of the motor neurons. Although many of the miRNAs currently incriminated as participants in the pathogenesis of these diseases are also important to the normal development and function of motor neurons, at present there is no knowledge of the complete miRNA profile of motor neurons. In this review, we examine the current understanding with respect to miRNAs that are specifically required for motor neuron development, function and viability, and provide evidence that these should be considered as a functional network of miRNAs which we have collectively termed MotomiRs. We will also summarize those MotomiRs currently known to be associated with both amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA), and discuss their potential use as biomarkers.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.055
GPT teacher head0.361
Teacher spread0.306 · 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 designOther design
Domainnot available
GenreReview

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

Citations33
Published2017
Admission routes2
Has abstractyes

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