Drusen in the Peripheral Retina of the Alzheimer’s Eye
Bibliographic record
Abstract
BACKGROUND: Recent work on Alzheimer's disease (AD) diagnosis focuses on neuroimaging modalities; however, these methods are expensive, invasive, and not available to all patients. Ocular imaging of biomarkers, such as drusen in the peripheral retina, could provide an alternative method to diagnose AD. OBJECTIVE: This study compares macular and peripheral drusen load in control and AD eyes. METHODS: Postmortem eye tissues were obtained from donors with a neuropathological diagnosis of AD. Retina from normal donors were processed and categorized into younger (<55 years) and older (>55 years) groups. After fixation and dissection, 3-6 mm punches of RPE/choroid were taken in macular and peripheral (temporal, superior, and inferior) retinal regions. Oil red O positive drusen were counted and grouped into two size categories: small (<63 μm) and intermediate (63-125 μm). RESULTS: There was a significant increase in the total number of macular and peripheral hard drusen in older, compared to younger, normal eyes (p<0.05). Intermediate hard drusen were more commonly found in the temporal region of AD eyes compared to older normal eyes, even after controlling for age (p<0.05). Among the brain and eye tissues from AD donors, there was a significant relationship between cerebral amyloid angiopathy (CAA) severity and number of temporal intermediate hard drusen (r=0.78, p<0.05). CONCLUSION: Imaging temporal drusen in the eye may have benefit for diagnosing and monitoring progression of AD. Our results on CAA severity and temporal intermediate drusen in the AD eye are novel. Future studies are needed to further understand the interactions among CAA and drusen formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".