Whole‐brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease
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Bibliographic record
Abstract
Abstract The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole‐brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid‐beta (Aβ 42 ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole‐brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ 42 alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ 42 , phosphorylated tau protein (p‐Tau) and total tau (t‐Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p‐Tau and t‐Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early‐stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it