Bioluminescence imaging of Aβ deposition in bigenic mouse models of Alzheimer's disease
Bibliographic record
Abstract
Transgenic (Tg) mouse models of Alzheimer's disease have served as valuable tools for investigating pathogenic mechanisms related to Aβ accumulation. However, assessing disease status in these animals has required time-consuming behavioral assessments or postmortem neuropathological analysis. Here, we report a method for tracking the progression of Aβ accumulation in vivo using bioluminescence imaging (BLI) on two lines of Tg mice, which express luciferase (luc) under control of the Gfap promoter as well as mutant human amyloid precursor protein. Bigenic mice exhibited an age-dependent increase in BLI signals that correlated with the deposition of Aβ in the brain. Bioluminescence signals began to increase in 7-mo-old Tg(CRND8:Gfap-luc) mice and 14-mo-old Tg(APP23:Gfap-luc) mice. When Tg(APP23:Gfap-luc) mice were inoculated with brain homogenates from aged Tg(APP23) mice, BLI detected the accelerated disease onset and induced Aβ deposition at 11 mo of age. Because of its rapid, noninvasive, and quantitative format, BLI permits the objective repeated analysis of individual mice at multiple time points, which is likely to facilitate the testing of Aβ-directed therapeutics.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".