Effects of Alzheimer and Lewy Body Disease Pathologies on Brain Metabolism
Bibliographic record
Abstract
OBJECTIVE: F-fluorodeoxyglucose positron emission tomography (FDG-PET) related to postmortem Lewy body disease (LBD) pathology in clinical Alzheimer disease (AD). METHODS: FDG-PET scans were analyzed in 62 autopsy-confirmed patients and 110 controls in the Alzheimer's Disease Neuroimaging Initiative. Based on neuropathologic evaluations on Braak stage for neurofibrillary tangle, Consortium to Establish a Registry for AD score for neuritic plaque, and Lewy-related pathology, subjects were classified into AD(-)/LBD(-), AD(-)/LBD(+), AD(+)/LBD(-), and AD(+)/LBD(+) groups. The association between postmortem LBD and AD pathologies and antemortem brain metabolism was evaluated. RESULTS: AD and LBD pathologies had significant interaction effects to decrease metabolism in the cerebellar vermis, bilateral caudate, putamen, basal frontal cortex, and anterior cingulate cortex in addition to the left side of the entorhinal cortex and amygdala, and significant interaction effects to increase metabolism in the bilateral parietal and occipital cortices. LBD pathology was associated with hypermetabolism in the cerebellar vermis, bilateral putamen, anterior cingulate cortex, and basal frontal cortex, corresponding to the Lewy body-related hypermetabolic patterns. AD pathology was associated with hypometabolism in the bilateral hippocampus, entorhinal cortex, and posterior cingulate cortex regardless of LBD pathology, whereas LBD pathology was associated with hypermetabolism in the bilateral putamen and anterior cingulate cortex regardless of AD pathology. INTERPRETATION: Postmortem LBD and AD pathologies had significant interaction effects on the antemortem brain metabolism in clinical AD patients. Specific metabolic patterns related to AD and LBD pathologies could be elucidated when simultaneously considering the two pathologies. ANN NEUROL 2022;91:853-863.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".