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Record W2136078441 · doi:10.1093/brain/awq329

A mutation in the RNF170 gene causes autosomal dominant sensory ataxia

2010· article· en· W2136078441 on OpenAlexafffundabout
Paul N. Valdmanis, Nicolas Dupré, Mathieu Lachance, Shawn J. Stochmanski, Véronique Belzil, Patrick A. Dion, Isabelle Thiffault, Bernard Brais, Lyle Weston, Louis Saint‐Amant, Mark E. Samuels, Guy A. Rouleau

Bibliographic record

VenueBrain · 2010
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsDalhousie UniversityHorizon Health NetworkUniversité de MontréalUniversité LavalMcGill UniversityHôpital Notre-Dame
FundersCanadian Institutes of Health Research
KeywordsGeneticsBiologyZebrafishAtaxiaMutationGeneDanioMissense mutationUbiquitin ligaseMutantUbiquitinNeuroscience

Abstract

fetched live from OpenAlex

Autosomal dominant sensory ataxia is a rare genetic condition that results in a progressive ataxia that is caused by degeneration of the posterior columns of the spinal cord. To date only two families have been clinically ascertained with this condition, both from Maritime Canada. We previously mapped both families to chromosome 8p12-8q12 and have now screened the majority of annotated protein-coding genes in the shared haplotype region by direct DNA sequencing. We have identified a putative pathogenic mutation in the gene encoding ring-finger protein RNF170, a potential ubiquitin ligase. This mutation is a rare non-synonymous change in a well-conserved residue and is predicted to be pathogenic by SIFT, PolyPhen, PANTHER and Align-GVD. Microinjection of wild-type or mutant orthologous messenger RNAs into zebrafish (Danio rerio) embryos confirmed that the mutation dominantly disrupts normal embryonic development. Together these results suggest that the mutation in RNF170 is causal for the sensory ataxia in these families.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.282
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2010
Admission routes3
Has abstractyes

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