Brain iron deposition in primary insomnia—An in vivo susceptibility‐weighted imaging study
Bibliographic record
Abstract
BACKGROUND: To study the brain iron deposition and its relationships with cognitive impairment and sleep quality in primary insomnia (PI). METHODS: Thirty-five patients with PI and 35 volunteers underwent MRI scanning using high-resolution susceptibility-weighted imaging sequence. Bilateral anterior cingulate cortices, posterior cingulate cortex, hippocampus, caudate nucleus, globus pallidus, putamen, thalamus, red nucleus, substantia nigra, parietal cortex, and frontal white matter were selected as regions of interest. The phase shift values of the above areas were compared between the two groups. Partial correlations between phase shifts values and neuropsychological scale scores including Pittsburgh Sleep Quality Index, Insomnia Severity Index, Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living Scale, and Clinical Dementia Rating of the PI patients were analyzed. RESULTS: Compared with the normal controls, the PI patients showed significant lower MMSE and MoCA scores and increased phase shift values in the left caudate nucleus, left putamen, left hippocampus, and bilateral thalamus (p < 0.05). Close correlation was found between the phase shift value of the left hippocampus and the MMSE scores of the PI patients (R = -0.447, p < 0.01). CONCLUSION: The PI patients exhibited significant cognitive impairment and increased iron deposition in several brain regions. The iron concentration of the left hippocampus is a biomarker of cognitive impairment and may play an important role in the pathophysiological mechanism.
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 | 0.000 |
| 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".