Imaging microglial activation and amyloid burden in amnestic mild cognitive impairment
Bibliographic record
Abstract
Amnestic mild cognitive impairment (aMCI) is defined as a transitional state between normal aging and Alzheimer’s disease (AD). Given the replicated finding of increased microglial activation in AD, we sought to investigate whether microglial activation is also elevated in aMCI and whether it is related to amyloid beta (Aβ) burden in-vivo . Eleven aMCI participants and 14 healthy volunteers completed positron emission tomography (PET) scans with [ 18 F]-FEPPA and [ 11 C]-PIB. Given the known sensitivity in affinity of second-generation TSPO radioligands, participants were genotyped for the TSPO polymorphism and only high-affinity binders were included. Dynamic [ 18 F]-FEPPA PET images were analyzed using the 2-tissue compartment model with arterial plasma input function. Additionally, a supplementary method, the standardized uptake value ratio (SUVR), was explored. [ 11 C]-PIB PET images were analyzed using the Logan graphical method. aMCI participants had significantly higher [ 11 C]-PIB binding in the cortical regions. No significant differences in [ 18 F]-FEPPA binding were observed between aMCI participants and healthy volunteers. In the aMCI group, [ 18 F]-FEPPA and [ 11 C]-PIB bindings were correlated in the hippocampus. There were no correlations between our PET measures and cognition. Our findings demonstrate that while Aβ burden is evident in the aMCI stage, microglial activation may not be present.
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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 | 0.001 | 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".