Lack of difference between amyloid‐beta burden at gyral crests and sulcal depths in diverse neurodegenerative diseases
Bibliographic record
Abstract
AIMS: The aim of this study is to clarify whether there is a difference in amyloid-beta burden between gyral crests (GCs) and sulcal depths (SDs) in different neurodegenerative proteinopathies. METHODS: We analysed the burden and distribution of amyloid-beta deposition in post-mortem brain samples from 138 autopsies, including Alzheimer's disease (n = 30), Down's syndrome (n = 11), Lewy body disease (LBD; n = 53), multiple system atrophy (n = 8) and progressive supranuclear palsy (n = 36). We applied quantitative amyloid-beta burden analysis to compare amyloid-beta deposition in both GCs and SDs. We also evaluated the prevalence of amyloid-beta plaques in both regions in samples exhibiting high or low amounts of amyloid-beta pathology. RESULTS: Amyloid-beta burden was evaluated in 67 and 84 samples of the frontal and temporal cortices, respectively. We did not find significant differences in the amyloid-beta burden between GCs and SDs in these regions in any examined disease. In addition, amyloid-beta plaques were almost evenly distributed in both regions in cases with low amounts of amyloid-beta pathology. Females in the LBD group showed significantly higher amyloid-beta burden than males (temporal cortex, p < 0.01). Furthermore, only one LBD case showed SD-predominant deposition associated with the coarse-grained plaques. CONCLUSIONS: We have shown that amyloid-beta is almost evenly distributed in both GCs and SDs in the frontal and temporal lobes from the early stage, in diverse neurodegenerative diseases. Sex may contribute to differences in the amyloid-beta burden. The coarse-grained plaque may show SD-predominant neuritic tau deposition that must be carefully distinguished from chronic traumatic encephalopathy-related SD tau pathology.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".