Assessing brain iron and volume of subcortical nuclei in idiopathic rapid eye movement sleep behavior disorder
Bibliographic record
Abstract
STUDY OBJECTIVES: The relationship of iron with cognitive and motor impairment in idiopathic rapid eye movement sleep behavior disorder (iRBD) remains unknown. METHODS: Twenty-nine (29) patients and 28 healthy controls (HCs) underwent susceptibility weighted imaging and susceptibility mapping. These images were used to evaluate the nigrosome-1 (N1) sign in the substantia nigra (SN), global and regional high-iron (RII) content, and volume of subcortical nuclei. RESULTS: The number of iRBD patients with N1 loss (12) was significantly higher than HCs (2) (p = 0.005). Compared with HCs, the iRBD patients had reduced volume of the right caudate nucleus (RCN) (p < 0.05, false discovery rate [FDR] correction) but no significant changes in global and RII iron of the subcortical nuclei (all p > 0.05, FDR correction). Multiple regression analysis revealed that: for cognitive function, the RII iron of the RCN was significantly correlated with visuospatial function and the global iron of the right dentate nucleus (RDN) was correlated with memory function; for motor function, the RII iron of the left DN (LDN) and global iron of the left CN correlated with the Alternate-Tap test (left, average), the global iron of the LDN correlated with the Alternate-Tap test (right), and the global iron of the left GP correlated with the 3-m Timed Up and Go test (all p < 0.05, FDR correction). CONCLUSIONS: Our exploratory analysis found that iRBD patients had a higher incidence of N1 loss and reduced RCN volume after FDR correction. Cognitive and motor impairment were associated with iron deposition in several cerebral nuclei after FDR correction.
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) | 0.001 | 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".