Human Tau Expression Does Not Induce Mouse Retina Neurodegeneration, Suggesting Differential Toxicity of Tau in Brain vs. Retinal Neurons
Bibliographic record
Abstract
The implication of the microtubule-associated protein (MAP) Tau in the ocular manifestations of Alzheimer's disease (AD) is elusive due to the lack of relevant animal model. However, signs of AD have been reported in the brain of transgenic mice expressing human Tau (hTau). To assess whether hTau is sufficient to induce AD pathogenesis in the retina as well, in the present study, we compared the retinal structure and function of KO mice deprived of Tau (mTKO) with those of transgenic mice expressing hTau. Our results revealed that hTau is particularly abundant in the inner nuclear layer (INL) cells of the retina. By electroretinogram (ERG) recording, light-induced retinal cell activation was not altered in hTau compared with mTKO littermates. Surprisingly, the ERG response mediated by cone photoreceptor stimulation was even stronger in hTau than in mTKO retinae. Immunofluorescent analysis of retinal sections allowed us to observe thicker inner retina in hTau than in mTKO eyes. By Western Blotting (WB), the upregulation of mTOR that was found in hTau mice may underlie retinal structure and function increases. Taken together, our results not only indicate that hTau expression is not toxic for retinal cells but they also suggest that it may play a positive role in visual physiology. The use of hTau may be envisaged to improve visual recovery in ocular diseases affecting the retinal function such as glaucoma or diabetic retinopathy.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".