Peripheral Oxidative Stress Markers in Patients with Bipolar Disorder during Euthymia and in Siblings
Bibliographic record
Abstract
AIMS: Oxidative stress is increased during the acute phases of bipolar disorder (BD). Our aim here was to analyze oxidative stress biomarkers in patients with BD during euthymia and their siblings. METHOD: A cross-sectional study was performed in euthymic patients with BD-I (n=48), unaffected siblings (n=23) and genetically unrelated healthy controls (n=21). Protein carbonyl content (PCC), total antioxidant capacity (TRAP), lipid peroxidation (TBARS) and uric acid were measured as biomarkers of oxidative stress in blood. RESULTS: The antioxidant capacity (TRAP) was lower (p<0.001) in patients with BD compared to their siblings and controls, whereas no differences were observed in PCC, TBARS or uric acid. In patients, the concentrations of TRAP and TBARS were positively associated with the dose of valproic acid (p<0.05 and p<0.001, respectively). The concentrations of these biomarkers were not significantly associated with any of socio-demographic and clinical variables. CONCLUSION: A selective reduction in antioxidant capacity is present in BD during euthymia state, whereas other markers of oxidative stress are unaltered during euthymia. Siblings did not show any alterations in oxidative stress biomarkers. Oxidative stress might represent a state-dependent marker in BD. The association between treatment with valproic acid and oxidative stress markers in euthymia deserves further studies.
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) | 0.001 | 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".