P2‐262: DISTRIBUTION OF AMYLOID DEPOSITS ACROSS THE RETINA IN ASSOCIATION WITH ALZHEIMER'S DISEASE AS A FUNCTION OF DISEASE SEVERITY
Bibliographic record
Abstract
In Alzheimer's disease (AD), amyloid deposits have been reported primarily in the far peripheral retina. We reported that the number of retinal amyloid deposits correlates with the severity of AD pathology in the brain. In polarimetry images, we examine signal strength, location of retinal deposits and predictions from these deposits of AD associated disease changes in the brain. The severity of AD associated brain pathology was assessed (NIA guidelines) and retinas from donors diagnosed with AD (n=26) and those not (n=4) were stained with 0.1% Thioflavin-S, counter-stained with DAPI and imaged using a fluorescence microscope fitted with a polarimeter. Polarization properties of amyloid deposits were calculated. Variation in deposit density with radial distance from the optic nerve head was determined. Ignoring the far periphery, we tested the prediction of severity of AD associated changes in the brain by retinal deposits. Amyloid deposits had linear retardance signals much stronger than the background retina (Fig 1). The 1014 deposits with polarization signals occurred more frequently in the peripheral retina (Fig 2). The retinal area increases with radial distance from the optic nerve head (ONH). The normalized deposit densities versus radial distance were not statistically different (K-S test) for differing brain pathologies (Fig. 3). For pathology of intermediate severity, the density distribution was not different from uniform. For low and high severities of pathology, the retinal deposit densities were non-uniform (Table 1) with higher density in the central retina (Fig. 3). Ignoring the far periphery, the number of retinal deposits still correlated significantly with the cumulative score of severity of AD associated brain changes (p<0.05) (Fig.4).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".