Glutamate, NAA, and energy metabolism in clinical high risk and first episode psychosis
Bibliographic record
Abstract
Abstract Regulation of brain glutamate is closely related to brain energy metabolism. Changes in both central glutamatergic function and peripheral energy metabolism have been implicated in psychosis risk, onset and long-term illness, but there is a lack of empirical evidence to link these processes. We investigated the relationships between glutamate and N -acetyl-aspartate (NAA, a potential marker of neuronal metabolic integrity) in the anterior cingulate cortex (ACC), measured using proton magnetic resonance spectroscopy ( 1 H-MRS), and peripheral markers of energy metabolism (mitochondrial complex I–V content, pyruvate and lactate) in individuals either at clinical high risk for psychosis or in the first episode of psychosis ( N = 36) and healthy controls ( N = 20). ACC Glx (glutamate + glutamine) levels were positively related with principal components relating to mitochondrial complex content, and this relationship did not differ between groups. These findings are consistent with the importance of mitochondrial ATP generation in regulating glutamatergic neurotransmission. While we did not find evidence that this relationship is disrupted in clinical high risk or first episode psychosis, further work is required to understand the mechanisms linking glutamate and energy metabolism in psychosis, including studies in larger cohorts, later stages of illness or in individuals with greater illness burden.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".