PM524. VEGF may have a neuroprotective role in the improvement of schizophrenia or in the treatment effects of antipsychotics
Bibliographic record
Abstract
Presentation preference Abstact number Abstract Objective: The aim of this study was to determine whether or not there was a difference in plasma VEGF levels between patients with schizophrenia and healthy controls. We also explored alterations in plasma VEGF levels in patients with schizophrenia before and after treatment with antipsychotic agents. Method: We examined plasma levels of VEGF in 50 patients with schizophrenia (SPR) and 50 healthy control subjects. We also explored any changes in plasma VEGF levels after 6-week treatment with antipsychotic agents in patients with schizophrenia. All subjects with schizophrenia were either medication-naïve or medication-free for at least 4 weeks before assessment. A trained psychiatrist assessed the psychopathological status of patients using the Positive and Negative Syndrome Scale (PANSS). Results: Plasma VEGF levels in all subjects were significantly correlated with smoking duration, which was considered to be a significant covariate. Pre-treatment plasma VEGF levels in patients with schizophrenia were significantly lower than those in healthy controls. Plasma VEGF levels at baseline were significantly lower in medication-naïve and medication-free patients than in healthy controls (F (2, 97) = 7.779, p = 0.001). After controlling for BMI (p = 0.402) and smoking duration (p = 0.002), VEGF levels in medication-naïve and medication-free patients were still lower than those in healthy controls (F (2, 95) = 8.181, p = 0.01). Post-treatment VEGF levels were significantly increased in patients with schizophrenia. Plasma VEGF levels in patients with schizophrenia did not exhibit significant correlation with the total or subscale scores of the Positive and Negative Syndrome Scale (PANSS) either at baseline or at the end of the 6-week treatment. Conclusions: Although the mechanism of VEGF in the pathophysiology of schizophrenia has not yet been explained, it may be that VEGF has a neuroprotective role in the improvement of schizophrenia or in the treatment effects of antipsychotics.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".