Investigating structural subdivisions of the anterior cingulate cortex in schizophrenia, with implications for treatment resistance and glutamatergic levels
Bibliographic record
Abstract
BACKGROUND: Abnormalities in the anterior cingulate cortex (ACC) are thought to play an important role in the pathophysiology of schizophrenia. Given regional variations in ACC structure, the present study aimed to examine ACC structural subdivisions and their relationships to treatment resistance and glutamatergic levels in schizophrenia. METHODS: This study included 100 patients with schizophrenia and 52 healthy controls from 2 cohorts. We applied non-negative matrix factorization to identify accurate and stable spatial components of ACC structure. Between groups, we compared ACC structural indices in each spatial component based on treatment resistance or response and tested relationships with ACC glutamate + glutamine levels. RESULTS: We detected reductions in cortical thickness and increases in mean diffusivity in the spatial components on the surface of the cingulate sulcus, especially in patients with treatment-resistant and clozapine-resistant schizophrenia. Notably, mean diffusivity in these components was higher in patients who did not respond to clozapine compared to those who did. Furthermore, these ACC structural alterations were related to elevated ACC glutamate + glutamine levels but not related to symptomatology or antipsychotic dose. LIMITATIONS: Sample sizes, cross-sectional findings and mixed antipsychotic status were limitations of this study. CONCLUSION: This study identified reproducible abnormalities in ACC structures in patients with treatment-resistant and clozapine-resistant schizophrenia. Given that these spatial components play a role in inhibitory control, the present study strengthens the notion that glutamate-related disinhibition is a common biological feature of treatment resistance in 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".