In vivo optical assessment of cerebral and skeletal muscle microvascular response to phenylephrine
Bibliographic record
Abstract
This study aimed to investigate the simultaneous response of the cerebral and skeletal muscle microvasculature to the same phenylephrine (PE) boluses. A hybrid optical system that combines hyperspectral near-infrared spectroscopy (hs-NIRS) and diffuse correlation spectroscopy (DCS) was used to monitor changes in tissue oxygenation and perfusion. Data were collected from the head and hind limb of seven male Sprague-Dawley rats while administering intravenous (IV) injections of PE or saline to all animals. The response to saline was used as a control. Skeletal muscle oxygenation decreased significantly after PE injection, while a statistically underpowered decrease in perfusion was observed, followed by an increase beyond baseline. Vascular conductance also decreased in the muscle reflecting the drug's vasoconstrictive effects. Tissue oxygenation and perfusion increased in the brain in response to PE. Initially, there was a sharp increase in cerebral perfusion but no changes in cerebral vascular conductance. Subsequently, cerebral flow and vascular conductance decreased significantly below baseline, likely reflecting autoregulatory mechanisms to manage the excess flow. Further, fitting an exponential function to the secondary decrease in cerebral perfusion and increase in muscular blood flow revealed a quicker kinetic response in the brain to adjust blood flow. In the skeletal muscle, PE caused a transient decrease in blood volume due to vasoconstriction, which resulted in an overall decrease in hemoglobin content and tissue oxygen saturation. Since PE does not directly affect cerebral vessels, this peripheral vasoconstriction shunted blood into the brain, resulting in an initial increase in oxygenated hemoglobin and oxygen saturation.
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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".