MétaCan
Menu
Back to cohort
Record W4386255683 · doi:10.1093/hmg/ddad138

Polyglutamine disease in peripheral tissues

2023· review· en· W4386255683 on OpenAlexaff
Taylor Barwell, Laurent Seroude

Bibliographic record

VenueHuman Molecular Genetics · 2023
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsQueen's University
Fundersnot available
KeywordsHuntingtinBiologyNeurodegenerationPolyglutamine tractHuntingtin ProteinHuntington's diseaseMilestoneTrinucleotide repeat expansionDiseaseNeuroscienceCell biologyGeneGeneticsMutantPathologyAlleleMedicine

Abstract

fetched live from OpenAlex

This year is a milestone anniversary of the discovery that Huntington's disease is caused by the presence of expanded polyglutamine repeats in the huntingtin gene leading to the formation of huntingtin aggregates. 30 years have elapsed and there is still no cure and the only FDA-approved treatment to alleviate the debilitating locomotor impairments presents several adverse effects. It has long been neglected that the huntingtin gene is almost ubiquitously expressed in many tissues outside of the nervous system. Growing evidence indicates that these peripheral tissues can contribute to the symptoms of the disease. New findings in Drosophila have shown that the selective expression of mutant huntingtin in muscle or fat is sufficient to cause detrimental effects in the absence of any neurodegeneration. In addition, it was discovered that a completely different tissue distribution of Htt aggregates in Drosophila muscles is responsible for a drastic aggravation of the detrimental effects. This review examines the peripheral tissues that express huntingtin with an added focus on the nature and distribution of the aggregates, if any.

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 score0.004
Threshold uncertainty score0.012

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 science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.109
GPT teacher head0.380
Teacher spread0.272 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHuman Molecular GeneticsSame topicGenetic Neurodegenerative DiseasesFrench-language works237,207