Imaging Retinal Vascular Changes in the Mouse Model of Oxygen-Induced Retinopathy
Bibliographic record
Abstract
PURPOSE: Oxygen-induced retinopathy in the mouse is the standard experimental model of retinopathy of prematurity. Assessment of the pathology involves in vitro analysis of retinal vaso-obliteration and retinal neovascularization. The authors studied the clinical features of oxygen-induced retinopathy in vivo using topical endoscopy fundus imaging (TEFI), in comparison to standard investigations, and evaluated a system for grading these features. METHODS: Postnatal day (P)7 mice were exposed to 75% oxygen for five days to induce retinopathy or maintained in room air as controls. Retinal vascular competence was graded against standard photographs by three masked graders. Retinal photographs were obtained at predetermined ages using TEFI. Postmortem, retinal vaso-obliteration was measured in whole mounts with labeled vasculature, and retinal neovascularization was quantified in hematoxylin- and eosin-stained ocular cross sections. RESULTS: Fundus photography by TEFI was possible from P15, when retinal vascular incompetence, including dilatation and tortuosity, was significant in mice with oxygen-induced retinopathy in comparison to controls. Vascular incompetence peaked in severity at P17 and persisted through P25. Comparison with in vitro analyses indicated that vascular changes were most severe after retinal avascularity had begun to decrease in area, and coincident with the maximum of retinal neovascularization. A weighted Fleiss-Cohen kappa indicated good intra- and interobserver agreement for a 5-point grading system. CONCLUSIONS: Topical endoscopy fundus imaging demonstrates retinal vascular incompetence in mice with oxygen-induced retinopathy. The technique complements standard postmortem analysis for following the course of the model. TRANSLATIONAL RELEVANCE: Topical endoscopy fundus imaging has application in the evaluation of novel biologic drugs for retinopathy of prematurity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".