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Record W4366430367 · doi:10.1016/j.molmed.2023.03.008

AMPK is mitochondrial medicine for neuromuscular disorders

2023· review· en· W4366430367 on OpenAlexafffund
Andrew I. Mikhail, Sean Y. Ng, Stephanie R. Mattina, Vladimir Ljubicic

Bibliographic record

VenueTrends in Molecular Medicine · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchOntario Ministry of Economic Development, Job Creation and TradeInstitute of Musculoskeletal Health and ArthritisNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMuscular Dystrophy Canada
KeywordsSpinal muscular atrophyDuchenne muscular dystrophyAMPKSMA*Myotonic dystrophyNeuromuscular diseaseMedicineNeuroscienceMuscular dystrophyNeuromuscular junctionProtein kinase ABioinformaticsBiologyDiseaseInternal medicineGeneticsKinaseComputer science

Abstract

fetched live from OpenAlex

Duchenne muscular dystrophy (DMD), myotonic dystrophy type 1 (DM1), and spinal muscular atrophy (SMA) are the most prevalent neuromuscular disorders (NMDs) in children and adults. Central to a healthy neuromuscular system are the processes that govern mitochondrial turnover and dynamics, which are regulated by AMP-activated protein kinase (AMPK). Here, we survey mitochondrial stresses that are common between, as well as unique to, DMD, DM1, and SMA, and which may serve as potential therapeutic targets to mitigate neuromuscular disease. We also highlight recent advances that leverage a mutation-agnostic strategy featuring physiological or pharmacological AMPK activation to enhance mitochondrial health in these conditions, as well as identify outstanding questions and opportunities for future pursuit.

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 score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.047
GPT teacher head0.382
Teacher spread0.335 · 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

Citations24
Published2023
Admission routes2
Has abstractyes

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