Activity-dependent modulation of glutamate, glutamine and glutathione in first-episode schizophrenia: A 7T functional MRS study
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Glutamatergic abnormalities have been implicated as an important component of schizophrenia symptoms. Functional magnetic resonance spectroscopy (fMRS) has emerged as a strong candidate for making dynamic observations of neurometabolites, overcoming the challenges of single-state observations in traditional magnetic resonance spectroscopy studies. To date, dynamic measurements of glutathione have not been presented in patients in the early stages of schizophrenia. STUDY DESIGN: Dynamic glutamate, glutamine, and glutathione concentrations were quantified from the dorsal anterior cingulate cortex of 33 first-episode schizophrenia and 23 healthy control volunteers. A four-block 7 T fMRS paradigm was employed using the color-word Stroop task as the cognitive demand. Non-baseline blocks were also normalized relative to the baseline block for metabolite percentage change observations. STUDY RESULTS: ANOVA revealed significant effects of time, metabolite and time x diagnosis x metabolite. Activation and prolonged elevation of glutathione in response to the cognitive stimuli were observed in healthy controls but only glutamate effects were notable in first-episode schizophrenia. Significantly lower glutamate concentrations during the second recovery blocks in both groups compared to their baseline glutamate levels. Normalized glutamate levels revealed a positive correlation between the recovery 2 block and both PANSS-8 Positive and PANSS-8 General scores. CONCLUSIONS: A potential inability to mount an appropriate antioxidant response to short-term oxidative stress may occur in the early stages of schizophrenia. A longitudinal study of fMRS is required to better understand the regulation of oxidative stress across the different stages of schizophrenia.
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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 | 0.000 | 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".