Systemic Hyperoxia and Retinal Vasomotor Responses
Bibliographic record
Abstract
PURPOSE: Several studies have investigated the changes in retinal vessel diameter during physiological stress or pathologic conditions. These studies were principally based on individual fundus photographs and as such did not allow the evaluation of vessel dynamics over time. The research objective was to detail the time course and amplitude changes in the diameter of arteries and veins across all retinal quadrants, during and after hyperoxic vascular stress. METHODS: The dynamics of changes in retinal vessel diameter were quantified with a retinal vessel analyzer, which digitizes fundus images in real time and simultaneously quantifies vessel diameter. The arterial and venous diameters within one disc diameter of the optic nerve head in each quadrant were studied. Twenty young adults participated in this study in which the vessel diameters were measured during successive phases of breathing either room air or pure oxygen. The oxygen saturation level (SaO(2)), end-tidal carbon dioxide (EtCO(2)), pulse rate (PR), respiratory rate (RR), and blood pressure (BP) were also monitored throughout testing. RESULTS: Breathing 100% O(2) caused an increase in SaO(2) and a decrease in the EtCO(2). All other systemic parameters measured (PR, RR, BP, and ocular perfusion pressure [OPP]) remained unchanged. However, the retinal veins and arteries constricted by approximately 14% and approximately 9% respectively, in all retinal quadrants. After experimental hyperoxia, inhalation of room air was associated with a progressive increase in the caliber of vessels toward their pretest size. The amplitude and overall profile of vessel reactivity to and recovery from hyperoxia was the same across retinal quadrants. CONCLUSIONS: These data indicate that, during systemic hyperoxic stress, the retinal vessels change in caliber uniformly across retinal quadrants in healthy young adults. This type of physiological vascular provocation could be used to investigate the quality of vascular regulation during aging and in vascular diseases of the eye.
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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 | 0.000 | 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) | 0.002 | 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".