Describing biomarkers for Alzheimer’s disease: Localization of amyloid‐β in the retina
Bibliographic record
Abstract
Abstract Background Retinal glial cells, Aβ deposition and their colocalization were examined in post‐mortem retinal cross‐sections of Alzheimer’s disease (AD) donors and age‐matched controls. Method Immunohistochemistry was performed on paraffin‐embedded cross‐sections of central and mid‐peripheral retinal tissues of AD donors (n = 9) and age‐matched controls (n = 12) to detect Aβ (6F/3D, 12F4, and 6E10) with neuronal profile (TUBB), astrocytes and Muller cells (GFAP), and microglia (IBA‐1). Astrocytes and Muller cells were further distinguished by double‐labelling of GFAP and glutamine synthetase (GS) antibody. The tissues were imaged with a confocal microscope and the degree of immunoreactivity and colocalization were measured layer‐wise and compared (α=.05) between the AD and control groups. Result The AD group showed more Aβ load in the mid‐peripheral retina but not central retina. For glial cells, less GFAP immunoreactivity in the central and mid‐peripheral retina and more microglia immunoreactivity in the mid‐peripheral retina were observed in the AD group. In the double‐labelling of GFAP and GS, activated Muller cells (labelled by GFAP and GS) were reduced in the AD group but not astrocytes (labelled only by GFAP). The AD group also showed greater co‐localization of Aβ with neuronal profile but less with microglia. Conclusion The reduced Muller cell metabolism and increase amount of microglia but with reduced colocalization with Aβ indicate complex glial dysfunction in the AD retina.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".