Characterization of adeno-associated viral transduction of retinal ganglion cells in adult and old mice
Bibliographic record
Abstract
Adeno-associated viral (AAV) vectors are being used increasingly in developing treatments for age-related ocular diseases, including those impacting retinal ganglion cells (RGCs), the output neurons of the eye. However, the effects of persistent transgene expression on RGC structure and function have not been thoroughly investigated. In this study, viral transduction was studied in parallel cohorts of adult (3–6 month-old) and old (18–24 month-old) mice and the persistence of viral expression characterized in aging mice. Age-related differences in viral transduction were investigated using in vivo imaging and immunohistochemical analyses. Effects of viral transduction on RGC function were examined using calcium imaging in intact-isolated retinal preparations. We demonstrate that AAV expression persists over 18 months following a single viral injection. Decreases in RGC density observed in AAV-injected aged mice were not significantly different from age-matched controls, suggesting age-related RGC loss unrelated to viral injection. Moreover, mice aged to 18 months post-AAV injection and old mice had similar loss of RGC function when compared to adult mice, despite differences in transduction durations. Our study found no deleterious effects of AAV transduction and highlights the potential of AAV-based methods for long-term RGC labeling and therapeutic strategies.
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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 | 0.000 |
| 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".