Defining the disturbance in cortical glutamate and GABA function in psychosis and its origins and consequences
Bibliographic record
Abstract
Abstract It is widely thought that the onset of psychotic symptoms in schizophrenia may arise from an early neurotoxic phase, possibly related to oxidative stress or inflammation, and a late residual damage phase associated with persistent negative symptoms. We tested this hypothesis in a 3-centre study using magnetic resonance spectroscopy (MRS) to determine whether abnormalities in glutamate, glutamine and GABA content in anterior cingulate cortex (ACC) differed between people with minimally treated ‘Recent’ onset schizophrenia and an ‘Established’ group with > 10 years of treatment. We tested whether neurochemical abnormalities were i) mediated by raised circulating inflammatory cytokine concentrations, c-reactive protein (CRP) and interleukin-6 (IL-6), or depletion of glutathione and ii) associated with ratings of positive and negative symptoms. Relative to age-matched controls, the Established group showed significantly greater reduction in ACC glutamate than the Recent group, which did not differ from controls. This effect was not attributable to antipsychotic drug exposure. Patient ACC glutathione was negatively correlated with age. IL-6 was increased in both clinical groups, while increases in CRP were greater in the Established than Recent group. Elevated CRP was entirely accounted for by greater antipsychotic drug exposure and BMI, while residual elevation in IL-6 in the Established group did not account for their lower ACC glutamate. GABA was reduced relative to controls across ACC and occipital voxels. This reduction was not associated with drug treatment, BMI or cytokine levels. Only ACC GABA content correlated significantly with symptoms, lower content with greater positive and negative symptoms across both groups.
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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 | 0.001 |
| 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".