The Lack of Amyloidogenic Activity Is Persistent in Old WT and APPswe/PS1ΔE9 Mouse Retinae
Bibliographic record
Abstract
We have previously reported that vision decline was not associated with amyloidogenesis processing in aging C57BL/6J wild-type (WT) mice and in a mouse model of Alzheimer’s disease, the APPswe/PS1ΔE9 transgenic mouse model (APP/PS1). This conclusion was drawn using middle-aged (10–13 months old) mice. Here, we hypothesized that compared with hippocampal and cortical neurons, the weak amyloidogenic activity of retinal neurons may result in a detectable release of amyloid β (Aβ) only in aged mice, i.e., between 14 and 24 months of age. The aim of the present study was thus to follow potential activity changes in the amyloidogenic and nonamyloidogenic pathways of young (4 months) and old (20–24 months) WT and APP/PS1 mice. Our results showed that in spite of retinal activity loss reported by electroretinogram (ERG) recordings, the level of amyloid beta precursor protein (APP) and its derivatives did not significantly vary in the eyes of old vs. young mice. Strikingly, the ectopic expression of human APPswe in APP/PS1 mice did not allow us to detect Aβ monomers at 23 months. In contrast, Aβ was observed in hippocampal and cortical tissues at this age but not at 4 months of life. In contrast, optic nerve transection-induced retinal ganglion cell injury significantly affected the level of retinal APP and the secretion of soluble APP alpha in the vitreous. Collectively, these results suggest that the amyloidogenic and nonamyloidogenic pathways are not involved in visual function decline in aging mice. In WT and APP/PS1 mice, it is proposed that retinal neurons do not have the capacity to secrete Aβ in contrast with other cortical and hippocampal neurons.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".