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Record W4400457665 · doi:10.1080/14737175.2024.2376840

The importance of synthetic pharmacotherapy for recessive cerebellar ataxias

2024· review· en· W4400457665 on OpenAlexaff
Marie Beaudin, Nicolas Dupré, Mario Manto

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2024
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPharmacotherapyNeuroscienceDiseaseMedicineAtaxiaPsychiatryBiologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The last decade has witnessed major breakthroughs in identifying novel genetic causes of hereditary ataxias, deepening our understanding of disease mechanisms, and developing therapies for these debilitating disorders. AREAS COVERED: This article reviews the currently approved and most promising candidate pharmacotherapies in relation to the known disease mechanisms of the most prevalent autosomal recessive ataxias. Omaveloxolone is an Nrf2 activator that increases antioxidant defense and was recently approved for treatment of Friedreich ataxia. Its therapeutic effect is modest, and further research is needed to find synergistic treatments that would halt or reverse disease progression. Promising approaches include upregulation of frataxin expression by epigenetic mechanisms, direct protein replacement, and gene replacement therapy. For ataxia-telangiectasia, promising approaches include splice-switching antisense oligonucleotides and small molecules targeting oxidative stress, inflammation, and mitochondrial function. Rare recessive ataxias for which disease-modifying therapies exist are also reviewed, emphasizing recently approved therapies. Evidence supporting the use of riluzole and acetyl-leucine in recessive ataxias is discussed. EXPERT OPINION: Advances in genetic therapies for other neurogenetic conditions have paved the way to implement feasible approaches with potential dramatic benefits. Particularly, as we develop effective treatments for these conditions, we may need to combine therapies, consider newborn testing for pre-symptomatic treatment, and optimize non-pharmacological approaches.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
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 head0.121
GPT teacher head0.445
Teacher spread0.324 · 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
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

Citations1
Published2024
Admission routes1
Has abstractyes

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