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Record W3126947084 · doi:10.12703/r/10-12

POLR3-related leukodystrophy: How do mutations affecting RNA polymerase III subunits cause hypomyelination?

2021· review· en· W3126947084 on OpenAlexafffund
Benoit Coulombe, Alexa Derksen, Roberta La Piana, Bernard Brais, Marie‐Soleil Gauthier, Geneviève Bernard

Bibliographic record

VenueFaculty Reviews · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsMontreal Neurological Institute and HospitalMcGill UniversityUniversité de MontréalMontreal Clinical Research InstituteMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsLeukodystrophyRNA polymerase IIIBiologyGeneticsRNARNA polymeraseTranscription (linguistics)GeneCell biologyMolecular biologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Hypomyelinating leukodystrophies are a group of genetic disorders characterized by insufficient myelin deposition during development. A subset of hypomyelinating leukodystrophies, named RNA polymerase III (Pol III or POLR3)-related leukodystrophy or 4H (Hypomyelination, Hypodontia and Hypogonadotropic Hypogonadism) leukodystrophy, was found to be caused by biallelic variants in genes encoding subunits of the enzyme Pol III, including POLR3A, POLR3B, POLR3K, and POLR1C. Pol III is one of the three nuclear RNA polymerases that synthesizes small non-coding RNAs, such as tRNAs, 5S RNA, and others, that are involved in the regulation of essential cellular processes, including transcription, translation and RNA maturation. Affinity purification coupled with mass spectrometry (AP-MS) revealed that a number of mutations causing POLR3-related leukodystrophy impair normal assembly or biogenesis of Pol III, often causing a retention of the unassembled subunits in the cytoplasm. Even though these proteomic studies have helped to understand the molecular defects associated with leukodystrophy, how these mutations cause hypomyelination has yet to be defined. In this review we propose two main hypotheses to explain how mutations affecting Pol III subunits can cause hypomyelination.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.066
GPT teacher head0.364
Teacher spread0.298 · 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 designNot applicable
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

Citations14
Published2021
Admission routes2
Has abstractyes

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