Frontostriatal Structural Connectivity and Striatal Glutamatergic Levels in Treatment-Resistant Schizophrenia: An Integrative Analysis of DTI and 1H-MRS
Bibliographic record
Abstract
Abstract Given that approximately one-third of patients with schizophrenia do not respond to antipsychotics, different neurobiological bases may underlie treatment resistance in schizophrenia. Previous studies showed that treatment response is associated with both frontostriatal connectivity and glutamatergic neurometabolite levels in the caudate in patients with schizophrenia, which leads to the hypothesis that the relationship between them may be altered, specifically in patients with treatment-resistant schizophrenia (TRS). Employing analyses of covariance and subsequent partial correlation analyses, we compared the relationship between glutamate+glutamine (Glx) levels in the caudate and fractional anisotropy (FA) values in the tract between the dorsolateral prefrontal cortex and caudate in 19 patients with TRS, 20 patients responsive to first-line antipsychotics (FL-Resp), and 19 healthy controls (HCs). TRS was defined by severe positive symptomatology despite first-line antipsychotic treatment. Patients with TRS had lower FA values in the bilateral frontostriatal tracts than patients with FL-Resp and HCs (P < .001), while no group differences were found in caudate Glx levels. There was a significant frontostriatal FA value-by-group interaction on caudate Glx levels (F = 7.37, P = .009). Frontostriatal FA values positively correlated with caudate Glx levels in HCs (r = −.55, P = .028), while they were negatively associated with caudate Glx levels in the TRS group (r = .53, P = .043). Furthermore, in the FL-Resp group, frontostriatal FA values did not significantly correlated with caudate Glx levels. The altered relationship between white matter integrity and the glutamate system in the frontostriatal circuit in the TRS group may reflect the pathophysiology underlying treatment response/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 | 0.001 | 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".