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Simultaneous Monitoring of the Cerebral and Skeletomuscular Microcirculation using Hyperspectral Near Infrared Spectroscopy and Intravital Video Microscopy

2021· article· en· W3168573316 on OpenAlexafffund
Laura Mawdsley, Ajay Rajaram, Lawrence C. M. Yip, Naomi Abayomi, Natalie Li, Stephanie Milkovich, Jeffrey J. L. Carson, Keith St. Lawrence, Christopher G. Ellis, Mamadou Diop

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsRobarts Clinical TrialsLawson Health Research InstituteWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhenylephrineMicrocirculationBolus (digestion)MedicineIntravital microscopySkeletal muscleBiomedical engineeringAnesthesiaAnatomyInternal medicineBlood pressure

Abstract

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Introduction Phenylephrine is a vasoconstrictor commonly used in cardiac surgery to increase mean arterial pressure without affecting cardiac output; however, its effects on the microcirculation of the brain and in skeletal muscle are unclear. In the current study, the timing and effects of a phenylephrine bolus on brain and skeletal muscle microvasculature were investigated using hyperspectral near infrared spectroscopy ( h ‐NIRS) and intravital video microscopy (IVVM. The objective of this study is to compare the effects of a timed phenylephrine bolus in the brain microvasculature, to the effects of the same bolus on the skeletal muscle microvasculature using both invasive (IVVM) and non‐invasive ( h ‐NIRS) methods. Methods The IVVM system uses an inverted Olympus microscope and two Rolera XR cameras to record 20X videos of individual capillaries in the Sprague Dawley rat (n=8, 158±10g) extensor digitorum longus muscle. The h ‐NIRS system uses two Ocean Insight spectrometers (MayaPro and QE65000) and an Ocean Insight HL‐2000 halogen light source. 3‐D printed probe‐holders were positioned on the left hind limb and the top of the skull, with a source‐detector distance of 10mm. Seven microvascular challenges were monitored with the h ‐NIRS system by recording a two‐minute baseline, then injecting 0.1mL of phenylephrine (0.1ug/mL) or 0.1mL of saline intravenously, then collecting data for 8 minutes. The same challenges were also monitored using IVVM simultaneously, by recording 1 minute at baseline and 2 minutes post‐IV injection. One representative phenylephrine bolus was chosen for this abstract. Results The h ‐NIRS system measured a 3.75% decrease in deoxygenated hemoglobin (Hb) and a 0.87% increase in oxygenated hemoglobin (HbO) in the brain microcirculation ( Fig .1A), as well as a 2.78% decrease in Hb and a 1.13% decrease in HbO the skeletal muscle microcirculation ( Fig .1B) in the seconds following the phenylephrine bolus. Total hemoglobin (tHb) decreased by 2.88% in the brain and 3.91% in the skeletal muscle. Results obtained from IVVM show an increase in optical density for frequencies reflecting microvascular activity immediately following the phenylephrine bolus ( Fig . 2), followed by a gradual return to baseline activity. Discussion This is the first report of the use of h ‐NIRS and IVVM to monitor the effects of phenylephrine on multiple microvascular beds in a healthy animal. Phenylephrine caused a decrease in Hb and tHb in both the brain and skeletal muscle microvasculature, but did not cause a prolonged decrease as both microvascular beds returned to baseline levels by the end of the 10‐minute collection. The same pattern was measured in the optical density ( Fig . 2). Unlike Hb, HbO levels increase in the brain after the phenylephrine bolus but decrease in skeletal muscle. This may be due to the oxygen requirements of the brain. Future work includes incorporating diffuse correlation spectroscopy into the methodology to provide insight into blood flow during the vascular challenge.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.287
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations1
Published2021
Admission routes2
Has abstractyes

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