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Record W2623955964 · doi:10.1016/j.ymgmr.2017.05.009

Higher oxidative stress in skeletal muscle of McArdle disease patients

2017· article· en· W2623955964 on OpenAlexaff
Jan Jacek Kaczor, Holly A. Robertshaw, Mark A. Tarnopolsky

Bibliographic record

VenueMolecular Genetics and Metabolism Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicGlycogen Storage Diseases and Myoclonus
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInternal medicineOxidative stressEndocrinologySuperoxide dismutaseXanthine oxidaseSkeletal muscleCatalaseGlutathione peroxidaseMyopathyChemistryExercise intoleranceBiochemistryMedicineEnzymeHeart failure

Abstract

fetched live from OpenAlex

McArdle disease (MCD) is an autosomal recessive condition resulting from skeletal muscle glycogen phosphorylase deficiency. The resultant block in glycogenolysis leads to an increased flux through the xanthine oxidase pathway (myogenic hyperuricemia) and could lead to an increase in oxidative stress. We examined markers of oxidative stress (8-isoprostane and protein carbonyls), NAD(P)H-oxidase, xanthine oxidase and antioxidant enzyme (superoxide dismutase, catalase and glutathione peroxidase) activity in skeletal muscle of MCD patients (N = 12) and controls (N = 12). Eight-isoprostanes and protein carbonyls were higher in MCD patients as compared to controls (p < 0.05). There was a compensatory up-regulation of catalase protein content and activity (p < 0.05), mitochondrial superoxide dismutase (MnSOD) protein content (p < 0.01) and activity (p < 0.05) in MCD patients, yet this increase was not sufficient to protect the muscle against elevated oxidative damage. These results suggest that oxidative stress in McArdle patients occurs and future studies should evaluate a potential role for oxidative stress contributing to acute pathology (rhabdomyolysis) and possibly later onset fixed myopathy.

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 score0.134
Threshold uncertainty score0.547

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 studies0.0000.000
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 head0.255
Teacher spread0.247 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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