Oxidative damage to RNA but not DNA in the hippocampus of patients with major mental illness
Bibliographic record
Abstract
BACKGROUND: Oxidative damage in the central nervous system is increasingly recognized as an important pathological process in many diseases. Previously, our laboratory found that oxidative damage to lipids and proteins was increased in postmortem brain tissue from patients with bipolar disorder and schizophrenia. In the current study, we analyzed oxidative damage to nucleic acids in the CA1, CA3 and dentate gyrus regions of postmortem hippocampus tissue from patients with bipolar disorder, schizophrenia and major depression. METHODS: We examined oxidative damage to nucleic acids by performing immunohistochemistry with a monoclonal antibody that recognizes both 8-hydroxy-guanosine in RNA and 8-hydroxy-2'-deoxyguanosine in DNA. RESULTS: We found that the amount of oxidative damage to nucleic acids was elevated in the CA1, CA3 and dentate gyrus regions of the hippocampus among patients with bipolar disorder, schizophrenia and major depressive disorder. This damage was predominantly in the cytoplasm, suggesting that the damage was primarily to RNA. Compared with oxidative damage in control samples, the magnitude of damage was high in patients with schizophrenia, modest in patients with bipolar disorder and lower in patients with major depression. LIMITATIONS: The interpretation of our results is limited by a number of factors, including the retrospective review of patient history, the relatively small sample size and the inclusion of patients who had substance abuse and were undergoing various drug treatments at the time of death. CONCLUSION: Our results suggest that oxidative damage to RNA, rather than to DNA, occurs in vulnerable neurons of the brain in patients with major mental illness and may contribute to the pathology of these disorders. The magnitude of RNA oxidative damage may be associated with the severity of mental illness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".