RGC Sensitivity to Mild Systemic Hypoxia
Bibliographic record
Abstract
PURPOSE: Systemic hyperoxia, hypercapnia, and hypoxia are known to alter retinal perfusion. The effects such experimentally induced systemic blood gas perturbations have on inner neuroretinal function in humans were examined. METHODS: Twenty healthy adults participated in each of three test sessions. The effects of breathing pure oxygen (O2), carbogen, or a hypoxic gas on the pattern electroretinogram (pERG) were investigated. The stimulus consisted of high-contrast, black-and-white, 48-min arc checks reversing at 1 Hz. pERGs were recorded with a Dawson-Trick-Litzkow electrode at the end of 5 minutes of breathing room air, 5 minutes of breathing the test gas, immediately after the flow of gas was stopped, and 10 minutes after the flow of gas was stopped. RESULTS: Amplitudes and implicit times of the major positive (P50) and negative (N95) components of the pERG were not altered during the pure O2 and carbogen breathing sessions. Although the amplitude and implicit time of P50 were not modified significantly with systemic hypoxia, they were depressed and delayed, respectively, for N95. CONCLUSIONS: Inner neuroretinal function remained unchanged during increased blood O2 and carbon dioxide levels known to alter retinal blood flow, but it was altered during decreased blood O2 levels. Overall, these results indicate that the generators of P50 are resistant to systemic hyperoxia, hypercapnia/hyperoxia, and hypoxia. They further indicate that the generators of N95, namely the retinal ganglion cells, are particularly sensitive to transient, mild systemic hypoxia.
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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 | 0.000 | 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".