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Record W2081884930 · doi:10.14740/cr359w

3-Methylglutaconyl-Coenzyme-A Hydratase Deficiency and the Development of Dilated Cardiomyopathy

2014· article· en· W2081884930 on OpenAlexvenueaboutno aff
Craig D. Spergel, Mariya Milko, Christopher Edwards, Jeff P. Steinhoff

Bibliographic record

VenueCardiology Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHeart failureDilated cardiomyopathyCardiologyInternal medicineCardiomyopathyEndocrinology

Abstract

fetched live from OpenAlex

A 25-year-old Canadian male with a history of 3-methylglutaconyl-coenzyme-A hydratase deficiency, also known as 3-methylglutaconic aciduria type I, a very rare inborn error of metabolism, presented with respiratory distress, nausea, vomiting and signs of multisystem organ failure due to a suspected underlying infectious process. An electrocardiogram revealed bilateral atrial enlargement and an elevated brain natriuretic peptide on the initial laboratory studies, which prompted a more thorough cardiac workup. The transthoracic echocardiogram revealed a dilated cardiomyopathy with severe systolic dysfunction. The deficient enzyme present in this patient is involved in the pathway of leucine catabolism and is particularly important in various tissues for energy production and sterol synthesis. The dilated cardiomyopathy in this patient possibly had a variety of potential mechanisms including: a mitochondrial myopathy due to the deficiency of this enzyme leading to a defect in energy production inside cardiac myocytes; or a direct toxicity from 3-methylglutaconic acid (3-MGA) and its toxic metabolites; or a cardiac dysfunction due to a variety of other potential mechanisms. In conclusion, this patient's clinical presentation suggested that 3-methylglutaconyl-CoA hydratase deficiency could cause a severe dilated cardiomyopathy and heart failure.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.211
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.033
GPT teacher head0.341
Teacher spread0.308 · 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

Citations9
Published2014
Admission routes2
Has abstractyes

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