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Record W6892115632 · doi:10.5061/dryad.37628q6

Data from: Valproic acid is protective in cellular and worm models of oculopharyngeal muscular dystrophy

2018· dataset· en· W6892115632 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2018
Typedataset
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsUniversité de MontréalMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsOculopharyngeal muscular dystrophyValproic AcidMuscular dystrophyCaenorhabditis elegansCell cultureCellMotilityPhenotypeMutant

Abstract

fetched live from OpenAlex

Objective: To explore valproic acid (VPA) as a potentially beneficial drug in cellular and worm models of oculopharyngeal muscular dystrophy (OPMD). Methods: Using a combination of live cell imaging and biochemical measures, we evaluated the potential protective effect of VPA in a stable C2C12 muscle cell model of OPMD, in lymphoblastoid cell lines derived from patients with OPMD and in a transgenic Caenorhabditis elegans OPMD model expressing human mutant PABPN1. Results: We demonstrated that VPA protects against the toxicity of mutant PABPN1. Of note, we found that VPA confers its long-term protective effects on C2C12 cell survival, proliferation, and differentiation by increasing the acetylated level of histones. Furthermore, VPA enhances the level of histone acetylation in lymphoblastoid cell lines derived from patients with OPMD. Moreover, treatment of nematodes with moderate concentrations of VPA significantly improved the motility of the PABPN-13 Alanines worms. Conclusions: Our results suggest that VPA helps to counteract OPMD-related phenotypes in the cellular and C elegans disease models.

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)0.001
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.048
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0480.025

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 head0.043
GPT teacher head0.298
Teacher spread0.255 · 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
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
Published2018
Admission routes1
Has abstractyes

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