A multistage, dual voxel study of glutamate in the anterior cingulate cortex in schizophrenia supports a primary pyramidal dysfunction model of disorganization
Bibliographic record
Abstract
Abstract Background Schizophrenia is an illness where glutamatergic dysfunction in the anterior cingulate cortex (ACC) has been long suspected; Recent in vivo evidence (Adams et al. 2022) has implicated pyramidal dysfunction (reduced glutamate tone) as the primary pathophysiology contributing to subtle features, with a secondary disinhibition effect (higher glutamate tone) resulting in the later emergence of prominent clinical symptoms. We investigate if genetic high risk (GHR) for schizophrenia reduces glutamatergic tone in ACC when compared to the states of clinical high risk (CHR) and first episode schizophrenia (FES) where symptoms are already prominent. Methods We recruited 302 individuals across multiple stages of psychosis (CHR, n=63; GHR, n=76; FES, n=96) and healthy controls (n=67) and obtained proton magnetic resonance spectroscopy of glutamate from perigenual ACC (pACC) and dorsal ACC (dACC) using 3-Tesla scanner. Results GHR had lower Glu compared to CHR while CHR had higher Glu compared to FES and HC. Higher disorganization burden, but not any other symptom domain, was predicted by lower levels of Glu in the GHR group (dACC and pACC) and in the CHR group (pACC only). Conclusions The reduction in glutamatergic tone in GHR supports the case for a pyramidal dysfunction contributing to higher disorganization, indicating disorganization to be the core domain in the pathophysiology of schizophrenia. Higher glutamate (likely due to disinhibition) is apparent when psychotic symptoms are raising to be prominent (CHR), though at the full-blown stage of psychosis, the relationship between glutamate and symptoms ceases to be a simple linear one.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".