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Record W2929734511 · doi:10.14348/molcells.2018.0243

RNA-Binding Proteins in Amyotrophic Lateral Sclerosis.

2018· review· en· W2929734511 on OpenAlexaff
Melody Zhao, Jihye Rachel Kim, Rebekah van Bruggen, Jeehye Park

Bibliographic record

VenuePubMed · 2018
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsRNA-binding proteinAmyotrophic lateral sclerosisStress granuleBiologyPathogenesisRNANeuroscienceGeneGeneticsDiseaseMedicineMessenger RNATranslation (biology)PathologyImmunology

Abstract

fetched live from OpenAlex

Significant research efforts are ongoing to elucidate the complex molecular mechanisms underlying amyotrophic lateral sclerosis (ALS), which may in turn pinpoint potential therapeutic targets for treatment. The ALS research field has evolved with recent discoveries of numerous genetic mutations in ALS patients, many of which are in genes encoding RNA binding proteins (RBPs), including TDP-43, FUS, ATXN2, TAF15, EWSR1, hnRNPA1, hnRNPA2/B1, MATR3 and TIA1. Accumulating evidence from studies on these ALS-linked RBPs suggests that dysregulation of RNA metabolism, cytoplasmic mislocalization of RBPs, dysfunction in stress granule dynamics of RBPs and increased propensity of mutant RBPs to aggregate may lead to ALS pathogenesis. Here, we review current knowledge of the biological function of these RBPs and the contributions of ALS-linked mutations to disease pathogenesis.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.162
GPT teacher head0.335
Teacher spread0.172 · 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

Citations134
Published2018
Admission routes1
Has abstractyes

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