Hypoperfusion Precedes Tau Deposition in the Entorhinal Cortex: A Retrospective Evaluation of ADNI-2 Data
Bibliographic record
Abstract
Background and Purpose Tau deposition in the entorhinal cortex is the earliest pathological feature of Alzheimer's disease (AD).However, this feature has also been observed in cognitively normal (CN) individuals and those with mild cognitive impairment (MCI).The precise pathophysiology for the development of tau deposition remains unclear.We hypothesized that reduced cerebral perfusion is associated with the development of tau deposition.Methods A subset of the Alzheimer's Disease Neuroimaging Initiative data set was utilized.Included patients had undergone arterial spin labeling perfusion MRI along with [ 18 F]flortaucipir tau PET at baseline, within 1 year of the MRI, and a follow-up at 6 years.The association between baseline cerebral blood flow (CBF) and the baseline and 6-year tau PET was assessed.Univariate and multivariate linear modeling was performed, with p<0.05 indicating significance.Results Significant differences were found in the CBF between patients with AD and MCI, and CN individuals in the left entorhinal cortex (p=0.013),but not in the right entorhinal cortex (p=0.076).The difference in maximum standardized uptake value ratio between 6 years and baseline was significantly and inversely associated with the baseline mean CBF (p=0.042,R 2 =0.54) in the left entorhinal cortex but not the right entorhinal cortex.Linear modeling demonstrated that CBF predicted 6-year tau deposition (p=0.015,R 2 =0.11). ConclusionsThe results of this study suggest that a reduction in CBF at the entorhinal cortex precedes tau deposition.Further work is needed to understand the mechanism underlying tau deposition in aging and disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".