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Record W4214535119 · doi:10.37766/inplasy2022.2.0113

Efficacy of CoQ10 supplementation for the treatment of primary CoQ10 deficiency

2022· report· en· W4214535119 on OpenAlexaff
Siegfried Hekimi, Ying Wang

Bibliographic record

Venuenot available
Typereport
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCoenzyme Q10 studies and effects
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoenzyme Q10Mitochondrial respiratory chainRespiratory chainMitochondrial diseaseCoenzyme Q – cytochrome c reductaseDiseaseGeneBioinformaticsMedicineMitochondrial DNABiologyPediatricsMitochondrionInternal medicineGenetics

Abstract

fetched live from OpenAlex

Review question / Objective: How effective is oral CoQ10 supplementation to treat primary CoQ10 deficiency? Condition being studied: Coenzyme Q10 (CoQ10), also known as ubiquinone, is an essential component of the mitochondrial respiratory chain. CoQ10 is also known to be involved in several other cellular functions besides the respiratory chain. All cells rely exclusively on endogenous CoQ synthesis. So far, 13 COQ genes whose products participate in CoQ10 biosynthesis have been identified in humans. Mutations in COQ genes cause primary CoQ10 deficiency (PUD), a rare, clinically heterogenous, disorder. Symptoms are those of inborn mitochondrial respiratory chain disorders, including early onset, multi-organ involvement, and prevalence of neurological and muscular manifestations. With the increasing availability and affordability of genomic sequencing technology, more and more PUD patients and novel PUD disease variants are being reported. CoQ10 supplementation as replacement therapy is frequently initiated immediately after diagnosis, and the majority of the literature on CoQ10 deficiency claims that this treatment is effective. However, there is lack of clear evidence for this claim. The planned review aims to identify, summarize and evaluate all the available evidence for the effectiveness of CoQ10 supplementation for the treatment of PUD.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.509

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 head0.031
GPT teacher head0.324
Teacher spread0.293 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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