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Record W4206222264 · doi:10.3410/f.734691109.793581668

Faculty Opinions recommendation of Mutation in POLR3K causes hypomyelinating leukodystrophy and abnormal ribosomal RNA regulation.

2021· dataset· en· W4206222264 on OpenAlexaff
Benoit Coulombe

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2021
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsBiologyLeukodystrophyGeneticsZebrafishRibosomal RNAMutationExome sequencingGeneDisease gene identificationRNAMedicineDiseasePathology

Abstract

fetched live from OpenAlex

Objective: To identify the genetic cause of hypomyelinating leukodystrophy in 2 consanguineous families.Methods: Homozygosity mapping combined with whole-exome sequencing of consanguineous families was performed. Mutation consequences were determined by studying the structural change of the protein and by the RNA analysis of patients' fibroblasts.Results: We identified a biallelic mutation in a gene coding for a Pol III-specific subunit, POLR3K (c.121C>T/p.Arg41Trp), that cosegregates with the disease in 2 unrelated patients. Patients expressed neurologic and extraneurologic signs found in POLR3A- and POLR3B-related leukodystrophies with a peculiar severe digestive dysfunction. The mutation impaired the POLR3K-POLR3B interactions resulting in zebrafish in abnormal gut development. Functional studies in the 2 patients' fibroblasts revealed a severe decrease (60%-80%) in the expression of 5S and 7S ribosomal RNAs in comparison with control.Conclusions: These analyses underlined the key role of ribosomal RNA regulation in the development and maintenance of the white matter and the cerebellum as already reported for diseases related to genes involved in transfer RNA or translation initiation factors. PMID: 30584594

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.324
Teacher spread0.305 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

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