Elevated Myo-Inositol, Choline, and Glutamate Levels in the Associative Striatum of Antipsychotic-Naive Patients With First-Episode Psychosis: A Proton Magnetic Resonance Spectroscopy Study With Implications for Glial Dysfunction
Bibliographic record
Abstract
Glial disturbances are highly implicated in the pathophysiology of schizophrenia and may be linked with glutamatergic dysregulation. Myo-inositol (mI), a putative marker of glial cells, and choline (Cho), representative of membrane turnover, are both present in larger concentrations within glial cells than in neurons, and their elevation is often interpreted to reflect glial activation. Proton magnetic resonance spectroscopy ((1)H-MRS) allows for the evaluation of mI, Cho, glutamate, glutamate + glutamine (Glx), and N-acetylaspartate (NAA). A collective investigation of these measures in antipsychotic-naive patients experiencing their first nonaffective episode of psychosis (FEP) can improve the understanding of glial dysfunction and its implications in the early stages of schizophrenia. 3-Tesla (1)H-MRS (echo time = 35 ms) was performed in 60 antipsychotic-naive patients with FEP and 60 age- and sex-matched healthy controls. mI, Cho, glutamate, Glx, and NAA were estimated using LCModel and corrected for cerebrospinal fluid composition within the voxel. mI, Cho, and glutamate were elevated in the FEP group. After correction for multiple comparisons, mI positively correlated with grandiosity. The relationships between mI and glutamate, and Cho and glutamate, were more positive in the FEP group. These findings are suggestive of glial activation in the absence of neuronal loss and may thereby provide support for the presence of a neuroinflammatory process within the early stages of schizophrenia. Dysregulation of glial function might result in the disruption of glutamatergic neurotransmission, which may influence positive symptomatology in patients with FEP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".