The altered volume of striatum: A neuroimaging marker of treatment in first-episode and drug-naïve schizophrenia
Bibliographic record
Abstract
Although schizophrenia patients exhibit structural abnormalities in the striatum, it remains largely unknown for the role of the striatum subregions in the treatment response of antipsychotic drugs. The purpose of this study was to investigate the associations between the striatal subregions and improved clinical symptoms in first-episode drug-naïve (FEDN) schizophrenia. Forty-two FEDN schizophrenia patients and 29 healthy controls (HCs) were recruited. At baseline, the Positive and Negative Syndrome Scale (PANSS) was used to assess the clinical symptoms of patients, MRI scanner was used to obtain anatomical images of patients and HCs. After 12-week stable doses of risperidone treatment, clinical symptoms were obtained in 38 patients and anatomical images in 26 patients. After 12 weeks of treatment, the left nucleus accumbens volume decreased, whereas the left pallidum volume increased in schizophrenia patients. The decreased left nucleus accumbens volume was positively correlated with cognitive factor improvement measured by PANSS. Intriguingly, greater left nucleus accumbens volume at baseline predicted greater cognitive improvements. Furthermore, the responders who had >50 % improvement in cognitive symptoms exhibited significantly greater baseline left nucleus accumbens volume compared to non-responders. The left striatum volume at baseline and after treatment predicted the cognitive improvements in FEDN schizophrenia, which could be a potential biomarker for the development of precision medicine approaches targeting cognitive function.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".