Quantification of microvascular change of retinal degeneration in Royal College of Surgeons rats using high-resolution spectral domain optical coherence tomography angiography
Bibliographic record
Abstract
Significance: For research on retinitis pigmentosa in humans, the Royal College of Surgeons (RCS) rat is commonly used as the primary animal model since the disease process is similar. Therefore, it is necessary to understand how the disease develops and determine whether the treatment is effective. Aim: In this study, structural and microvascular change of retinal degeneration in RCS rats was assessed non-invasively on specific dates over 3.5 months. Approach: Using a high-resolution spectral domain (SD) optical coherence tomography angiography (OCTA), the retinal degeneration in RCS rats, from day 14 until day 126, was qualitatively and quantitatively analyzed. Results: Aside from the thinning of the retina thickness starting from 2 weeks of age, blood vessels in the deep layer of the retina also began to degenerate at about 4 weeks of age. Hole structures appeared at the inner nuclear layer and the inner plexiform layer by the age of 10 weeks. Observations of abnormal angiogenesis in the choroid began by 12 weeks of age. Conclusions: We conducted a longitudinal study of retina degeneration structure and vascular changes in an RCS rat model using a supercontinuum laser based high-resolution SD-OCTA. Combined with OCTA, OCT leads to a better understanding of photoreceptor pathology as retinal degeneration by identifying tissue and vessel loss.
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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) | 0.002 | 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".