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Record W2806895491 · doi:10.1111/cts.12562

Anisomycin Activates Utrophin Upregulation Through a p38 Signaling Pathway

2018· article· en· W2806895491 on OpenAlexafffund
Jeremiah Hadwen, Faraz Farooq, Luke Witherspoon, Sarah Schock, Kevin Mongeon, Alex MacKenzie

Bibliographic record

VenueClinical and Translational Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsAgricultural Research Institute of OntarioUniversity of Ottawa
FundersGenome British ColumbiaNational Institutes of HealthCanadian Institutes of Health ResearchGenome CanadaOntario GenomicsOntario Genomics Institute
KeywordsUtrophinDuchenne muscular dystrophyAnisomycinDystrophinDownregulation and upregulationMedicineMuscular dystrophyMyocyteBiologyCell biologyInternal medicineGeneticsGeneKinase

Abstract

fetched live from OpenAlex

Duchenne muscular dystrophy is a recessive X-linked disease characterized by progressive muscle wasting; cardiac or respiratory failure causes death in most patients by the third decade. The disease is caused by mutations in the dystrophin gene that lead to a loss of functional dystrophin protein. Although there are currently few treatments for Duchenne muscular dystrophy, previous reports have shown that upregulating the dystrophin paralog utrophin in Duchenne muscular dystrophy mouse models is a promising therapeutic strategy. We conducted in silico mining of the Connectivity Map database for utrophin-inducing agents, identifying the p38-activating antibiotic anisomycin. Treatments of C2C12, undifferentiated murine myoblasts, and mdx primary myoblasts with anisomycin conferred increases in utrophin protein levels through p38 pathway activation. Anisomycin also induced utrophin protein levels in the diaphragm of mdx mice. Our study shows that repositioning small molecules such as anisomycin may prove to have Duchenne muscular dystrophy clinical utility.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.034
GPT teacher head0.342
Teacher spread0.308 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations11
Published2018
Admission routes2
Has abstractyes

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