Catalytic Nanoceria Are Preferentially Retained in the Rat Retina and Are Not Cytotoxic after Intravitreal Injection
Bibliographic record
Abstract
Cerium oxide nanoparticles (nanoceria) possess catalytic and regenerative radical scavenging activities. The ability of nanoceria to maintain cellular redox balance makes them ideal candidates for treatment of retinal diseases whose development is tightly associated with oxidative damage. We have demonstrated that our stable water-dispersed nanoceria delay photoreceptor cell degeneration in rodent models and prevent pathological retinal neovascularization in vldlr mutant mice. The objectives of the current study were to determine the temporal and spatial distributions of nanoceria after a single intravitreal injection, and to determine if nanoceria had any toxic effects in healthy rat retinas. Using inductively-coupled plasma mass spectrometry (ICP-MS), we discovered that nanoceria were rapidly taken up by the retina and were preferentially retained in this tissue even after 120 days. We also did not observe any acute or long-term negative effects of nanoceria on retinal function or cytoarchitecture even after this long-term exposure. Because nanoceria are effective at low dosages, nontoxic and are retained in the retina for extended periods, we conclude that nanoceria are promising ophthalmic therapeutics for treating retinal diseases known to involve oxidative stress in their pathogeneses.
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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 | 0.000 | 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".