Cryo-EM studies of amyloid-β fibrils from human and murine brains carrying the Uppsala APP mutation (Δ690–695)
Bibliographic record
Abstract
Abstract Today, 13 intra-amyloid-β (Aβ) amyloid precursor protein (APP) gene mutations are known to cause familial Alzheimer’s disease (AD). Most of them are point mutations causing an increased production or a change in the conformation of Aβ. The Uppsala APP mutation (Δ690–695 in APP, Δ19–24 in Aβ) is the first known multi-codon deletion causing autosomal dominant AD. Here, we applied cryo-electron microscopy (cryo-EM) to investigate the structure of Aβ fibrils with the Uppsala APP mutation from tg-UppSwe mouse brain tissue. Murine AβUpp(1–42)Δ19–24 are made of two identical S-shaped protofilaments with an ordered fibril core of S8-A42. The murine Aβ fold is almost identical to previously described human type II filaments, although the amino acid sequences differ considerably. In addition, we report the cryo-EM structure of Aβ fibrils from the temporal cortex of a patient with the Uppsala APP mutation. The observed structure of the human Aβ fold closely resembles previously described type I fibrils. Structural modeling suggests that these fibrils are composed of wild-type Aβ, which implies that AβUpp may be less soluble and thus not readily accessible for cryo-EM image processing and structure determination. Additionally, from the human sample we determined the structures of tau paired helical filaments and tau straight filaments, which are identical to those found in sporadic AD cases. Finally, we present the 3D cryo-EM structures of four dominant AβUpp(1–42)Δ19–24 fibril polymorphs, formed in vitro. All four polymorphs differ from the observed folds of Uppsala Aβ in murine and human brain tissue, respectively.
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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 | 0.000 |
| 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".