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Assessment by Multi‐Distance Hyperspectral NIRS of Changes in the Oxidation State of Cytochrome C Oxidase (oxCCO) to Carotid Artery Compressions

2022· article· en· W4225391082 on OpenAlexafffund
Leena N. Shoemaker, Marianne Suwalski, Daniel Milej, J. Kevin Shoemaker, Jason Chui, Keith St. Lawrence

Bibliographic record

VenueThe FASEB Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsLondon Health Sciences CentreWestern University
FundersCanadian Institutes of Health Research
KeywordsHyperspectral imagingCytochrome c oxidaseCarotid arteriesCytochromeChemistryCardiologyInternal medicineMedicineBiochemistryComputer scienceArtificial intelligenceEnzyme

Abstract

fetched live from OpenAlex

Introduction The occlusion of the common carotid artery (CCA) during carotid endarterectomy (CEA) is associated with a risk of cerebral ischemia due to inadequate collateral blood flow 1 . By monitoring tissue oxygen saturation (StO 2 ), near‐infrared spectroscopy (NIRS) is frequently employed during CEA 2 to determine sufficient oxygen delivery. However, StO 2 is only a proxy of oxygen metabolism and an unreliable marker of ischemic injury. In contrast, cytochrome c oxidase (oxCCO) is an enzyme in the mitochondrial electron transport chain and therefore a specific marker of aerobic metabolism 3 . Thus, the aim of this study was to assess the ability of a multi‐distance hyperspectral (hs) NIRS to monitor changes in StO 2 and oxCCO during CCA compressions in healthy participants. We hypothesized that changes in oxCCO concentration would be greater in the brain (i.e., long source‐detector distance, SDD) than in the extracerebral tissue (i.e., short SDD), and this difference would be larger than that of StO 2 . Methods We modified an in‐house built hsNIRS 4 to include a second channel for acquiring data at two SDD (1 and 3 cm) to detect potential changes in the extracerebral tissue. Data from 10 young, healthy participants was acquired continuously during one 30‐second unilateral digital CCA compression, performed ipsilateral to the location of the optic probes. In addition, cerebral blood flow index was determined using diffuse correlation spectroscopy and mean arterial blood pressure by finger photoplethysmography. Results During CCA compression, the change in oxCCO at 3 cm vs. 1 cm (0.4 ± 0.3 µM vs. 0.06 ± 0.1 µM, p = 0.027) was approximately 50% greater than the change in StO 2 at 3 cm vs. 1cm (‐4.0 ± 2.2% vs. 1.2 ± 0.7% p = 0.007). The corresponding decrease in cerebral blood flow was 57 ± 14% (p < 0.001 vs. baseline). Mean arterial blood pressure increased 4 ± 1 mmHg (p < 0.001 vs. baseline). Discussion A larger difference between the two distances was observed for oxCCO than StO 2 , likely due to the greater concentration of mitochondria in the brain compared to extracerebral tissues. Collecting multi‐distance hsNIRS demonstrated the enhanced sensitivity of oxCCO to the brain. Lastly, this study demonstrates the utility of momentary unilateral CCA compressions as a fast, easy, and strong perturbation for transiently altering cerebral inflow and metabolism. References (1) Aceto, Eur. J. Anestesiol.(2020); (2) Yu, Cochrane Database Syst. Rev.(2014); (3) Bale, J. Biomed. Opt. (2020); (4) Rajaram, Brain Sci (2020).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.324
Teacher spread0.305 · 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
Published2022
Admission routes2
Has abstractyes

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