Distinct Molecular Signatures of Amyloid-Beta and Tau in Alzheimer’s Disease Associated with Down Syndrome
Bibliographic record
Abstract
Limited comparative data exist on the molecular spectrum of amyloid-beta (Aβ) and tau deposition in individuals with Down syndrome (DS) and sporadic Alzheimer’s disease (sAD). We assessed Aβ and tau deposition severity in the temporal lobe and cerebellum of ten DS and ten sAD cases. Immunohistochemistry was performed using antibodies against eight different Aβ epitopes (6F/3D, Aβ38, Aβ39, Aβ40, Aβ42, Aβ43, pyroglutamate Aβ at third glutamic acid (AβNp3E), phosphorylated- (p-)Aβ at 8th serine (AβpSer8)), and six different pathological tau epitopes (p-Ser202/Thr205, p-Thr231, p-Ser396, Alz50, MC1, GT38). Findings were evaluated semi-quantitatively and quantitatively using digital pathology. DS cases had significantly higher neocortical parenchymal deposition (Aβ38, Aβ42, and AβpSer8), and cerebellar parenchymal deposition (Aβ40, Aβ42, AβNp3E, and AβpSer8) than sAD cases. Furthermore, DS cases had a significantly larger mean plaque size (6F/3D, Aβ42, AβNp3E) in the temporal lobe, and significantly greater deposition of cerebral and cerebellar Aβ42 than sAD cases in the quantitative analysis. Western blotting corroborated these findings. Regarding tau pathology, DS cases had significantly more severe cerebral tau deposition than sAD cases, especially in the white matter (p-Ser202/Thr205, p-Thr231, Alz50, and MC1). Greater total tau deposition in the white matter (p-Ser202/Thr205, p-Thr231, and Alz50) of DS cases was confirmed by quantitative analysis. Our data suggest that the Aβ and tau molecular signatures in DS are distinct from those in sAD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".