O6.3. PATTERNS OF GRAY MATTER ABNORMALITIES IN PATIENTS WITH FIRST-EPISODE AND TREATMENT-NAïVE SCHIZOPHRENIA
Bibliographic record
Abstract
To detect schizophrenia-related anatomical changes that are not confounded by antipsychotic treatment and to establish clinically identifiable subgroups that differ in underlying neuroanatomical patterns. This case-control study was conducted at West China hospital in China, and analysis was undertaken in Robarts Research Institute, London, Canada. 206 patients with schizophreniform psychosis and schizophrenia and 170 healthy controls were scanned on a Signa 3.0-T MR scanner; 137 patients with schizophreniform psychosis and schizophrenia and 172 healthy controls were scanned on a 3.0 T MR scanner. All the patients were first-episode and treatment-naïve. Source based morphometry (SBM) performed to analyze the gray matter (GM) concentration. Latent class analysis used to identify clinical subtypes of patients using the scores of symptom dimensions. GMC component-based connectomes were constructed to study the graphic organization of structural brain network of subtypes of schizophrenia. Patients showed prominent reduction in GM in two components; one including anterior insula, inferior frontal gyrus, anterior cingulate and another with superior temporal gyrus, and precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Increased GM was seen in one component of cerebellar tonsil and inferior semi-lunar lobule, and the other component of middle temporal gyrus, superior temporal gyrus, middle frontal gyrus and putamen. Greater GM of latter component was associated with less severe positive symptoms and better performance on cognitive tests. Reduced global efficiency only existed in a subgroup of patients with severe negative and disorganization symptoms. These findings delineate a common pattern of gray matter changes in schizophrenia, and a subgroup of patients with robust cortical reorganization suggestive of compensatory plasticity after first episode.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".