Oxidative Stress and Emergence of Psychosis
Bibliographic record
Abstract
Treatment and prevention strategies for schizophrenia require knowledge about the mechanisms involved in the psychotic transition. Increasing evidence suggests a redox imbalance in schizophrenia patients. This narrative review presents an overview of the scientific literature regarding blood oxidative stress markers' evolution in the early stages of psychosis and chronic patients. Studies investigating peripheral levels of oxidative stress in schizophrenia patients, first episode of psychosis or UHR individuals were considered. A total of 76 peer-reviewed articles published from 1991 to 2022 on PubMed and EMBASE were included. Schizophrenia patients present with increased levels of oxidative damage to lipids in the blood, and decreased levels of non-enzymatic antioxidants. Genetic studies provide evidence for altered antioxidant functions in patients. Antioxidant blood levels are decreased before psychosis onset and blood levels of oxidative stress correlate with symptoms severity in patients. Finally, adjunct treatment of antipsychotics with the antioxidant N-acetyl cysteine appears to be effective in schizophrenia patients. Further studies are required to assess its efficacy as a prevention strategy. Redox imbalance might contribute to the pathophysiology of emerging psychosis and could serve as a therapeutic target for preventive or adjunctive therapies, as well as biomarkers of disease progression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".