Decreased Water Diffusivity Along the Perivascular Space in Older Adults With Poor Sleep Quality
Bibliographic record
Abstract
This study included 52 Japanese older adults with Pittsburgh Sleep Quality Index (PSQI) scores > 5 and 52 healthy controls (HCs) with PSQI score ≤ 5. Diffusion-weighted imaging (DWI) and 3D T1-weighted imaging were acquired using 3T magnetic resonance imaging. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) index was calculated using preprocessed DWI. The choroid plexus volume (CPV) was calculated using FreeSurfer 6.0. The mean ALPS index and CPV were compared between the older adults with poor sleep quality (PSQ) and HCs using a general linear model, adjusted for covariates including age, sex, years of education, total intracranial volume, systolic blood pressure, hemoglobin A1c, and white matter lesion volume. We also conducted a partial correlation analysis between the mean ALPS index and CPV, Montreal Cognitive Assessment (MoCA), and PSQI scores, adjusting for all the mentioned covariates. The PSQ group had a significantly lower mean ALPS index than HCs. The mean ALPS index in the PSQ group was negatively correlated with CPV and positively correlated with the MoCA score. Therefore, older adults with PSQ may experience dysfunction in the excretory pathway of the perivascular space around the medullary veins. This impairment may be associated with an increase in CPV and cognitive dysfunction.
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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".