Longitudinal grey-matter and glutamatergic losses in first-episode schizophrenia
Bibliographic record
Abstract
BACKGROUND: Progressive volumetric changes in the brains of people with schizophrenia have been attributed to a number of factors. AIMS: To determine whether glutamatergic changes in patients with schizophrenia correlated with grey-matter losses during the first years of illness. METHOD: Left anterior cingulate and thalamic glutamatergic metabolite levels and grey-matter volumes were examined in 16 patients with first-episode schizophrenia before and after 10 months and 30 months of antipsychotic treatment and in 16 healthy participants on two occasions 30 months apart. RESULTS: Higher than normal glutamine levels were found in the anterior cingulate and thalamus of never-treated patients. Thalamic levels of glutamine were significantly reduced after 30 months. Limited grey-matter reductions were seen in patients at 10 months followed by widespread grey-matter loss at 30 months. Parietal and temporal lobe grey-matter loss was correlated with thalamic glutamine loss. CONCLUSIONS: Elevated glutamine levels in never-treated patients followed by decreased thalamic glutamine and grey-matter loss in connected regions could indicate either neurodegeneration or a plastic response to reduced subcortical activity.
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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 | 0.000 | 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 | 0.001 |
| 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".