Noninvasive imaging of the early effect of sodium iodate toxicity in a rat model of outer retina degeneration with spectral domain optical coherence tomography
Bibliographic record
Abstract
An ultrahigh resolution spectral domain optical coherence tomography (SD-OCT) system is used to observe for the first time in vivo the early effect of sodium iodate (NaIO3) toxicity on retinal morphology. Retinal degeneration is induced in rats via tail vein injection of NaIO3 and structural changes in the outer retina are assessed longitudinally at baseline and 1, 2, 3, 6, 8, and 10 h, and 12 post drug administration with OCT, H&E histology, and IgG immunochemistry. Disruption of the structural integrity and changes in the optical reflectivity of the photoreceptor inner (IS) and outer segment (OS) layers are observed as early as 1 h post NaIO3 injection. A new layer is observed in the OCT tomograms to form between the retinal pigmented epithelium and the photoreceptors OS a few hours post NaIO3 injection. The dynamics and the low optical reflectivity of this layer, as well as cell swelling and disruption of the blood-retina barrier observed in the histological and immunohistochemistry cross-sections suggest that the layer corresponds to temporary fluid accumulation in the retina. Results from this study demonstrate the effectiveness of OCT technology for monitoring dynamic changes in the retinal morphology and provide better understanding of the early stages of outer retina degeneration induced by NaIO3 toxicity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".