Altered amyloid-β structure markedly reduces gliosis in the brain of mice harboring the Uppsala APP deletion
Bibliographic record
Abstract
Abstract Deposition of amyloid beta (Aβ) into plaques is a major hallmark of Alzheimer’s disease (AD). Different amyloid precursor protein ( APP ) mutations cause early-onset AD by altering the production or aggregation properties of Aβ. We recently identified the Uppsala APP mutation ( APPUpp ), which causes Aβ pathology by a triple mechanism: increased β-secretase and altered α-secretase APP cleavage, leading to increased formation of a unique Aβ conformer that rapidly aggregates and deposits in the brain. The aim of this study was to further explore the effects of APPUpp in a transgenic mouse model (tg-UppSwe), expressing human APP with the APPUpp mutation together with the APPSwe mutation. Aβ pathology was studied in tg-UppSwe brains at different ages, using ELISA and immunohistochemistry. In vivo PET imaging with three different PET radioligands was conducted in aged tg-UppSwe mice and two other mouse models; tg-ArcSwe and tg-Swe. Finally, glial responses to Aβ pathology were studied in cell culture models and mouse brain tissue, using ELISA and immunohistochemistry. Tg-UppSwe mice displayed increased β-secretase cleavage and suppressed α-secretase cleavage, resulting in AβUpp42 dominated diffuse plaque pathology appearing from the age of 5–6 months. The γ-secretase cleavage was not affected. Contrary to tg-ArcSwe and tg-Swe mice, tg-UppSwe mice were [ 11 C]PiB-PET negative. Antibody-based PET with the 3D6 ligand visualized Aβ pathology in all models, whereas the Aβ protofibril selective mAb158 ligand did not give any signals in tg-UppSwe mice. Moreover, unlike the other two models, tg-UppSwe mice displayed a very faint glial response to the Aβ pathology. The tg-UppSwe mouse model thus recapitulates several pathological features of the Uppsala APP mutation carriers. The presumed unique structural features of AβUpp42 aggregates were found to affect their interaction with anti-Aβ antibodies and profoundly modify the Aβ-mediated glial response, which may be important aspects to consider for further development of AD therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".