MétaCan
Menu
Back to cohort
Record W3119381293 · doi:10.32598/bcn.11.6.1100.1

Coenzyme Q10 Insufficiency Contributes to the Duration and Frequency of Seizures in Epileptic Patients

2020· article· en· W3119381293 on OpenAlexaff
Leila Simani, Omidvar Rezaei, Fari Ryan, Masoumeh Sadeghi, Etrat Hooshmandi, Mahtab Ramezani, Hossin Pakdaman

Bibliographic record

VenueBasic and Clinical Neuroscience Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCoenzyme Q10 studies and effects
Canadian institutionsMcGill University Health Centre
FundersShahid Beheshti University of Medical Sciences
KeywordsCoenzyme Q10EpilepsyOxidative stressPathogenesisMedicineReactive oxygen speciesInternal medicineEpileptic seizureGastroenterologyBiologyPsychiatryBiochemistry

Abstract

fetched live from OpenAlex

INTRODUCTION: Oxidative stress has recently emerged as a possible mechanism in the pathogenesis of epilepsy. Coenzyme Q10 (CoQ10) is a strong endogenous antioxidant that protects cells from lipid oxidation and Reactive Oxygen Species (ROS) production; however, the impact of CoQ10 on seizure characteristics in epileptic patients is unclear. METHODS: The current study enrolled patients with Epileptic Seizure (ES) to evaluate their serum concentration of CoQ10 and to investigate whether a relationship exists between CoQ10 levels with the duration, frequency, and type of seizure. RESULTS: A total of 39 patients with epileptic seizures and 35 healthy controls were included in the study. The levels of CoQ10 in ES patients were significantly lower in comparison with healthy controls (11.99±5.93 vs (ng/ml). 16.48±4.20 (ng/ml) P<0.001). We also found that the duration of epilepsy and seizure frequency was negatively correlated with serum CoQ10 levels. CONCLUSION: These findings indicate that CoQ10 deficiency might substantially contribute to the clinical signs of epileptic patients.

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)0.002
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 score0.064
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.019
GPT teacher head0.293
Teacher spread0.274 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBasic and Clinical Neuroscience JournalSame topicCoenzyme Q10 studies and effectsFrench-language works237,207