Assessing grey matter structural alterations in systemic lupus erythematosus using synthetic MRI
Bibliographic record
Abstract
OBJECTIVES: To assess brain grey matter alterations in patients with SLE and their correlation with neuropsychological testing using synthetic MRI (SyMRI). METHODS: This prospective study enrolled patients with SLE and age, gender and education-matched healthy controls (HC). Study assessments included brain MRI using SyMRI and neuropsychological tests: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Digit Span Test, Self-Rating Anxiety Scale and Self-Rating Depression Scale (SDS). SyMRI post-processing and Automated Anatomical Labeling were used for grey matter mapping. Correlation analysis was performed to assess the relationship between brain grey matter structural alterations and neuropsychological testing. RESULTS: 77 patients with SLE (57 non-neuropsychiatric SLE (non-NPSLE), 20 NPSLE) and 29 HC participants were enrolled. Patients with SLE showed reduced grey matter volume compared with HC (p<0.05). The NPSLE group exhibited more extensive increases in longitudinal (T1) and transverse (T2) relaxation times in grey matter than the non-NPSLE group (p<0.001). Proton density values were lower in patients with SLE (p<0.001). Lower brain parenchymal volume correlated with higher SLE Disease Activity Index (p<0.05). Lower MMSE/MoCA scores correlated with increased T1/T2 in the left medial cingulate and paracingulate gyri (p<0.05). Higher SDS scores correlated with increased T1/T2 in the left calcarine fissure and surrounding cortex (p<0.05). These changes were also linked to disease markers (C3, C4, immunoglobulin M, erythrocyte sedimentation rate) (p<0.05). CONCLUSIONS: Grey matter alterations in patients with SLE correlate with cognitive impairment, depression and disease activity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".