MétaCan
Menu
Back to cohort
Record W2904702421 · doi:10.18192/uojm.v8i2.3462

Antisense Oligonucleotide Gene Therapy for Neuromuscular Disorders

2018· article· en· W2904702421 on OpenAlexaffvenue
Ryan Gotesman

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSpinal muscular atrophyAntisense therapyAmyotrophic lateral sclerosisMedicineGenetic enhancementNeuromuscular diseaseOligonucleotideBioinformaticsDuchenne muscular dystrophyDiseaseMuscular dystrophyGeneComputational biologyNeurosciencePharmacologyBiologyGeneticsPathologyInternal medicine

Abstract

fetched live from OpenAlex

Antisense oligonucleotides (ASOs) are synthetic, single-stranded DNA molecules that can bind to specific mRNA sequences and alter protein expression. ASO gene therapies are leading to breakthroughs in the treatment of once intractable neuromuscular disorders. In 2016, ASOs became the first FDA-approved drugs for treating spinal muscular atrophy and Duchenne muscular dystrophy. Recent trials also suggest ASOs may be effective in combating Huntington’s disease, amyotrophic lateral sclerosis and hereditary transthyretin amyloidosis. This article highlights ASOs’ mechanism of action, their use in treating neuromuscular disease and future obstacles the gene therapy must overcome, providing an update on the state of ASO technology.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.275
Teacher spread0.257 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueUniversity of Ottawa Journal of MedicineSame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207