Evaluation of the Glymphatic System in Schizophrenia Spectrum Disorder Using Proton Magnetic Resonance Spectroscopy Measurement of Brain Macromolecule and Diffusion Tensor Image Analysis Along the Perivascular Space Index
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: The glymphatic system (GS), a brain waste clearance pathway, is disrupted in various neurodegenerative and vascular diseases. As schizophrenia shares clinical characteristics with these conditions, we hypothesized GS disruptions in patients with schizophrenia spectrum disorder (SCZ-SD), reflected in increased brain macromolecule (MM) and decreased diffusion-tensor-image-analysis along the perivascular space (DTI-ALPS) index. STUDY DESIGN: Forty-seven healthy controls (HCs) and 103 patients with SCZ-SD were studied. Data included 135 proton magnetic resonance spectroscopy (1H-MRS) sets, 96 DTI sets, with 79 participants contributing both. MM levels were quantified in the dorsal-anterior cingulate cortex (dACC), dorsolateral prefrontal cortex, and dorsal caudate (point resolved spectroscopy, echo-time = 35ms). Diffusivities in the projection and association fibers near the lateral ventricle were measured to calculate DTI-ALPS indices. General linear models were performed, adjusting for age, sex, and smoking. Correlation analyses examined relationships with age, illness duration, and symptoms severity. STUDY RESULTS: MM levels were not different between patients and HCs. However, left, right, and bilateral DTI-ALPS indices were lower in patients compared with HCs (P < .001). In HCs, age was positively correlated with dACC MM and negatively correlated with left, right, and bilateral DTI-ALPS indices (P < .001). In patients, illness duration was positively correlated with dACC MM and negatively correlated with the right DTI-ALPS index (P < .05). In the entire population, dACC MM and DTI-ALPS indices showed an inverse correlation (P < .01). CONCLUSIONS: Our results suggest potential disruptions in the GS of patients with SCZ-SD. Improving brain's waste clearance may offer a potential therapeutic approach for patients with SCZ-SD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".