P3‐338: AMYLOID AND MICROGLIAL ACTIVATION SYNERGY LEADS TO HYPOMETABOLISM IN AD BRAIN: MICROPET LONGITUDINAL STUDY
Bibliographic record
Abstract
The decline in regional brain metabolism in Alzheimer's disease (AD) has been evident in individuals with high level of amyloidosis. However, recent evidence suggests that neuroinflammation plays an intimate role in propagating the amyloidosis effects in the downstream cascade of AD pathophysiology. The positron emission tomography (PET) tracer specific for mitochondrial translocator protein (TSPO) in activated microglia allows precise investigation of neuroinflammation. Here, we employed [F]AZD4694, [F]FDG, and [F]PBR06 for amyloidosis, metabolism, and neuroinflammation, respectively. We aim to study the effects of amyloidosis and neuroinflammation on brain metabolism in McGill-R-Thy1-APP transgenic (Tg) rat model. This model is unique to display full AD-like amyloid pathology without neurofibrillary tangles (NFTs) or cell deaths that are invariantly present in AD patients. Here, we hypothesize that amyloidosis and neuroinflammation have synergistic effects on brain metabolism in McGill-R-Thy-APP Tg compared to wild type (WT) animals. A total of 7 WT and 7 Tg rats were used. Each animal underwent longitudinal PET [F]AZD4694, [F]FDG, [F]PBR06, and MRI at 10 and 17 months old. All images were registered to individual MRI with lsq6. Then, they are normalized into sample average template using lsq12 with nonlinear transformations. [F]AZD4694 and [F]PBR06 binding potential map (BPND) using cerebellar grey matter as a reference region were generated using Simplified Reference Tissue Method (SRTM). [F]FDG SUVR was generated using pons as a reference region. For statistical analysis, we performed voxel-wise analysis using VoxelStats to show the effect of [F]PBR06 BPND on [F]FDG SUVR: [F]FDG SUVR ∼ [F]PBR06 BPND. Furthermore, [F]AZD4694 and [F]PBR06 interaction model was applied in Tg to investigate the synergistic effect of amyloidosis and neuroinflammation on brain metabolism: [F]FDG SUVR ∼ [F]AZD4694 BPND * [F]PBR06 BPND. WT showed only positive association between neuroinflammation and brain metabolism in neocortex and piriform cortex. Furthermore, the interaction model revealed a negative synergistic effect between amyloidosis and neuroinflammation in neocortex driving the metabolic decline while positive synergistic effect was found in striatum and nucleus accumbens.
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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 | 0.000 |
| 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 | 0.001 |
| 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".