MétaCan
Menu
Back to cohort
Record W2079196978 · doi:10.1073/pnas.0705501104

Overexpression of wild-type androgen receptor in muscle recapitulates polyglutamine disease

2007· article· en· W2079196978 on OpenAlexafffund
D. Ashley Monks, Jamie A. Johansen, Kaiguo Mo, Pengcheng Rao, Bryn Eagleson, Zhigang Yu, Andrew P. Lieberman, S. Marc Breedlove, Cynthia L. Jordan

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchCollege of Engineering, Michigan State UniversityNational Institutes of HealthMichigan State University FoundationMichigan State University
KeywordsAndrogen receptorSpinal and bulbar muscular atrophySkeletal muscleMuscle weaknessMuscle atrophyBiologyAtrophyTransgeneEndocrinologyAndrogenGenetically modified mouseInternal medicineGeneMedicineAnatomyGeneticsProstate cancerHormoneCancer

Abstract

fetched live from OpenAlex

We created transgenic mice that overexpress WT androgen receptor (AR) exclusively in their skeletal muscle fibers. Unexpectedly, these mice display androgen-dependent muscle weakness and early death, show changes in muscle morphology and gene expression consistent with neurogenic atrophy, and exhibit a loss of motor axons. These features reproduce those seen in models of Kennedy disease, a polyglutamine expansion disorder caused by a CAG repeat expansion in the AR gene. These findings demonstrate that toxicity in skeletal muscles is sufficient to cause motoneuron disease and indicate that overexpression of the WT AR can exert toxicity comparable with the polyglutamine expanded protein. This model has two clear implications for Kennedy disease: (i) mechanisms affecting AR gene expression may cause neuromuscular symptoms similar to those of Kennedy disease and (ii) therapeutic approaches targeting skeletal muscle may provide effective treatments for this disease.

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)0.001
metaresearch head score (Gemma)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
GPT teacher head0.312
Teacher spread0.265 · 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

Citations172
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicGenetic Neurodegenerative DiseasesFrench-language works237,207