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Mitochondrial Myopathies: Diagnosis, Exercise Intolerance, and Treatment Options

2005· review· en· W2078789786 on OpenAlexaff
Mark A. Tarnopolsky, Sandeep Raha

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcMaster UniversityHamilton Health SciencesMcMaster University Medical Centre
Fundersnot available
KeywordsExercise intoleranceMitochondrial myopathyMitochondrial diseaseMitochondrial biogenesisMitochondrionMedicineMitochondrial DNACoenzyme Q10Anaerobic exerciseHeteroplasmyEndurance trainingInternal medicinePhysiologyEndocrinologyBiologyBiochemistryHeart failure

Abstract

fetched live from OpenAlex

Mitochondrial myopathies are caused by genetic mutations that directly influence the functioning of the electron transport chain (ETC). It is estimated that 1 of 8,000 people have pathology inducing mutations affecting mitochondrial function. Diagnosis often requires a multifaceted approach with measurements of serum lactate and pyruvate, urine organic acids, magnetic resonance spectroscopy (MRS), muscle histology and ultrastructure, enzymology, genetic analysis, and exercise testing. The ubiquitous distribution of the mitochondria in the human body explains the multiple organ involvement. Exercise intolerance is a common but often an overlooked hallmark of mitochondrial myopathies. The muscle consequences of ETC dysfunction include increased reliance on anaerobic metabolism (lactate generation, phosphocreatine degradation), enhanced free radical production, reduced oxygen extraction and electron flux through ETC, and mitochondrial proliferation or biogenesis (see article by Hood in current issue). Treatments have included antioxidants (vitamin E, alpha lipoic acid), electron donors and acceptors (coenzyme Q10, riboflavin), alternative energy sources (creatine monohydrate), lactate reduction strategies (dichloroacetate) and exercise training. Exercise is a particularly important modality in diagnosis as well as therapy (see article by Taivassalo in current issue). Increased awareness of these disorders by exercise physiologists and sports medicine practitioners should lead to more accurate and more rapid diagnosis and the opportunity for therapy and genetic counseling.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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 designOther design
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

Citations141
Published2005
Admission routes1
Has abstractyes

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