In Vivo Assessment of Thickness and Reflectivity in a Rat Outer Retinal Degeneration Model with Ultrahigh Resolution Optical Coherence Tomography
Bibliographic record
Abstract
PURPOSE: To provide in vivo quantitative assessment of sodium iodate-induced retinal damage in a rat model of outer retinal degeneration using ultrahigh resolution optical coherence tomography (UHR-OCT). METHODS: Outer retinal degeneration was induced in four female Long Evans rats via tail vein injection of sodium iodate (40 mg/kg). Changes in the thickness and optical reflectivity of individual retinal layers were extracted using a semi-automatic segmentation algorithm and were assessed in vivo at 6 hours, days 1, 3, and 7, and up to 3 months post injection with UHR-OCT. Hematoxylin and eosin (H&E) histology was used to confirm the morphologic changes observed in the UHR-OCT images. RESULTS: UHR-OCT tomograms showed progressive structural damage in the rat retina over time, such as swelling, thinning, complete disintegration of individual retinal layers, and clustering of highly reflective cellular debris. Photoreceptor swelling was observed 6 hours after injection of sodium iodate, followed by progressive structural decomposition of the outer retina. At 3 months post injection, the outer retina was completely disintegrated, and the inner nuclear layer (INL) was in direct contact with the choroid. Changes in the reflectivity of individual retinal layers were observed over time and correlated well with the morphologic changes. CONCLUSIONS: UHR-OCT permits in vivo, noninvasive, longitudinal, quantitative assessment of the progressive changes in retinal morphology and optical reflectivity in a sodium iodate rodent model of outer retinal degeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".