Consequences of an Increase in the Ocular Perfusion Pressure on the Pulsatile Ocular Blood Flow
Bibliographic record
Abstract
PURPOSE: In previous studies we have demonstrated that physical exertion constricted the major retinal arteries, increased the redness of the optic nerve head, and attenuated scotopic white flash oscillatory potentials. These anatomic and functional changes in the human retina suggested that blood flow to the innermost retinal layers was modified in some way to cause these changes. The objective of this study was to determine whether physical exertion also affected blood flow in the choroid, the exclusive source of blood to the outermost layers of the retina. METHODS: Eighteen healthy adults volunteered for this study. An OBF Tonograph system (OBF Laboratories UK Ltd., Malmesbury, Wiltshire, U.K.) was used to derive the pulsatile ocular blood flow, which reflects the pulsatile component of blood flow in the choroid, at rest and 20 minutes after biking at a heart rate of 140 beats/min. RESULTS: At the systemic level, biking increased the blood pressure and the heart rate. At the ocular level, the duration of the systolic and diastolic phases of the intraocular pulse was shortened, and the pulse amplitude and volume were reduced. Despite the attenuation of the intraocular pulse parameters, the pulsatile ocular blood flow increased by some 18% after exercise largely because of the much larger increase in heart rate. The ocular perfusion pressure increased, whereas the intraocular pressure decreased. CONCLUSIONS: Physical exertion in the form of aerobic exercise increased the pulsatile component of blood flow in the choroid. Because the choroid is the sole blood supply to the outer retina, it was concluded that the degree of perfusion of the photoreceptors necessary for vision is increased by physical exertion. This increased choroidal blood flow is presumably to sustain vision as blood is directed to the large muscle groups involved in the physical activity.
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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".