Retinal tissue oxygenation differs between eye fundus regions, but not with age, sex, and intraocular pressure in non‐human primates
Bibliographic record
Abstract
Abstract Purpose: Oxygen plays a central role in multiple physiological and pathophysiological processes, and retinal oxygen supply has been found to be an important factor in many ocular diseases. Animal models are often used to study the pathophysiological mechanisms of diseases, especially non‐human primates (NHP) due to their great similarities with humans. Few data are available on the quantification of oxygen in the retina of NHP. The objectives of the study were to establish NHP tissue oxygen saturation (StO2) normative values in different eye fundus regions, compare StO2 in these regions and analyse how StO2 correlates to age, sex and intraocular pressure (IOP). Methods: 44 vervet monkeys (28 males/16 females, 5–28 years old) were included in the study. IOP was measured in both eyes with an ocular tonometer. StO2 was measured in both eyes using the Zilia Ocular oximeter in the temporal (tONH) and nasal (nONH) optic nerve head, the peripapillary region (pPL) and the perifovea (pFV). T‐tests were used to compare between regions (paired), between both eyes (paired) and between sexes (independent). Kendall's tau was used to assess the correlation between StO2 and age, as well as that between StO2 and IOP. Results: Mean StO2 was 55.7% ± 4.3% in the tONH, 55.0% ± 3.9% in the nONH, 63.9% ± 7.3% in the pPL and 74.2% ± 3.4% in the pFV. No significant difference in StO2 was observed between the left and the right eyes, just as no significant difference was observed between tONH and nONH. The StO2 was lower in tONH and nONH than in pPL (p = 0.0226 and 0.0060, respectively). No correlation was found between StO2 and age, StO2 and sex, or StO2 and IOP. Conclusions: StO2 in the retinal tissue of NHP has been assessed for the first time. Regional variations similar to previous human studies were observed. The results of this study show the applicability of the Zilia Ocular on NHP and provide normative values that can serve as a basis for future studies.
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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 | 0.001 |
| 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 | 0.000 |
| 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".