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Record W2942938364 · doi:10.1016/j.celrep.2019.04.017

Skeletal Muscle Glycogen Chain Length Correlates with Insolubility in Mouse Models of Polyglucosan-Associated Neurodegenerative Diseases

2019· article· en· W2942938364 on OpenAlexaff
Mitchell A. Sullivan, Silvia Nitschke, Evan P. Skwara, Peixiang Wang, Xiaochu Zhao, Xiao Shan Pan, Erin E. Chown, Travis Wang, Ami M. Perri, Jennifer P.Y. Lee, Francisco Vilaplana, Berge A. Minassian, Felix Nitschké

Bibliographic record

VenueCell Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicGlycogen Storage Diseases and Myoclonus
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
FundersNational Institute of Neurological Disorders and StrokeNational Health and Medical Research Council
KeywordsGlycogenLafora diseaseGlycogen branching enzymeGlycogen synthaseBiochemistryGlycogen storage diseaseChemistrySkeletal muscleGlycogen debranching enzymeIn vivoBiologyPhosphorylationEndocrinologyGenetics

Abstract

fetched live from OpenAlex

), the separation of soluble and insoluble muscle glycogen is described, enabling separate analysis of each fraction. Total glycogen is increased in LD and APBD mice, which, together with abnormal chain length and molecule size distributions, is largely if not fully attributed to insoluble glycogen. Soluble glycogen consists of molecules with distinct chain length distributions and differential corresponding solubility, providing a mechanistic link between soluble and insoluble glycogen in vivo. Phosphorylation states differ across glycogen fractions and mouse models, demonstrating that hyperphosphorylation is not a basic feature of insoluble glycogen. Lastly, model-specific variances in protein and activity levels of key glycogen synthesis enzymes suggest uninvestigated regulatory mechanisms.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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 designObservational
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

Citations70
Published2019
Admission routes1
Has abstractyes

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