Coenzyme Q10 Insufficiency Contributes to the Duration and Frequency of Seizures in Epileptic Patients
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".