MétaCan
Menu
Back to cohort
Record W2087995224 · doi:10.3389/fgene.2013.00149

Structural disorder and the loss of RNA homeostasis in aging and neurodegenerative disease

2013· article· en· W2087995224 on OpenAlexafffund
Douglas A. Gray, John Woulfe

Bibliographic record

VenueFrontiers in Genetics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsRNABiologyDiseaseRNA-binding proteinRibonucleoproteinMechanism (biology)HomeostasisProtein aggregationCell biologyComputational biologyGeneticsMedicineGenePathology

Abstract

fetched live from OpenAlex

Whereas many cases of neurodegenerative disease feature the abnormal accumulation of protein, an abundance of recent literature highlights loss of RNA homeostasis as a ubiquitous and central feature of pathological states. In some diseases expanded repeats have been identified in non-coding regions of disease-associated transcripts, calling into question the relevance of protein in the disease mechanism. We review the literature in support of a hypothesis that intrinsically disordered proteins (proteins that lack a stable three dimensional conformation) are particularly sensitive to an age-related decline in maintenance of protein homeostasis. The potential consequences for structurally disordered RNA-binding proteins are explored, including their aggregation into complexes that could be transmitted through a prion-like mechanism. We propose that the spread of ribonucleoprotein complexes through the nervous system could propagate a neuronal error catastrophe at the level of RNA metabolism.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.247

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 head0.005
GPT teacher head0.229
Teacher spread0.224 · 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 designObservational
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

Citations7
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in GeneticsSame topicRNA Research and SplicingFrench-language works237,207