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Model‐based analysis of microcirculatory parameters affecting O <sub>2</sub> transport in skeletal muscle subjected to fixed surface PO <sub>2</sub>

2021· article· en· W3167610309 on OpenAlexaff
Keith C. Afas, Daniel Goldman

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsWestern University
Fundersnot available
KeywordsSkeletal muscleOxygen transportMicrocirculationCapillary actionBlood flowChemistryPartial pressureHemodynamicsPerfusionBiomedical engineeringAnatomyMaterials scienceOxygenCardiologyInternal medicineBiologyMedicine

Abstract

fetched live from OpenAlex

Microcirculation in skeletal muscle determines both blood flow distribution and O 2 transport. The partial pressure of oxygen (PO 2 ) is a prime candidate to assess in tissue, as PO 2 variations herald a functionality decline in skeletal muscle. Traditional non‐invasive microcirculatory techniques such as Intra‐vital Video Microscopy (IVVM) allowing for blood velocity and capillary saturation (SO 2 ) measurements, are unable to directly assess skeletal muscle tissue PO 2 . Instead, modern microcirculatory O 2 analysis relies on biophysical models to recreate tissue PO 2 distributions. (Ellis et al, Microcirc 2012 , 19:5). Recently, a continuous coupled partial differential equation (PDE) model of two layers of skeletal muscle coupled via diffusion at their boundaries was developed accounting for tissue O 2 diffusion, capillary O 2 convection, tissue O 2 consumption, and capillary‐tissue O 2 transfer. This model was developed to study an IVVM protocol involving a controlled exposure of skeletal muscle using an O 2 exchange chamber. In the protocol studied, hemodynamic parameters in the skeletal muscle region near to the O 2 chamber are experimentally shown to exhibit substantial variations. The prevailing theory is capillary perfusion limits the depth of penetration of the chamber O 2 , and local hemodynamic parameter responses serve to regulate capillary SO 2 in skeletal muscle; this would be towards either a fixed target value or homogeneity with neighboring capillary modules. The coupled PDE two‐layer model was developed for steady‐state PO 2 distributions and was solved using traditional math techniques such as operator decoupling and Fourier decomposition, and exhibited the ability to rapidly and accurately calculate PO 2 distributions in skeletal muscle which agreed with experimental values. (Afas and Goldman, Vasc Bio 2020 ). The solution affords for the unique ability not allowed in previous convection‐diffusion analytic models of O 2 transport, to observe the interaction of both skeletal muscle layers. This is achieved by assuming baseline hemodynamic parameters in the layer far from the O 2 chamber and allowing the near layer to take on a range of parameter variations; these variations can be compared to experimental observations. In this study, the behavior of both layers of skeletal muscle adjacent to an O 2 chamber will be modelled by the a‐priori fixing of parameters in the region far from the O 2 chamber and allowing near‐layer parameters to be perturbed. Several parameters, including capillary density φ, velocity v B , inlet saturation S IN , hematocrit H T , and tissue consumption μ will have this variation method applied from previous baselines (Afas et al, Math Biosci 2021 , in press ), and the resultant two‐layer O 2 profiles will be visualized, as well as the conditions under which the capillary SO 2 is homogenized in both layers of skeletal muscle.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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 designSimulation or modeling
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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Citations0
Published2021
Admission routes1
Has abstractyes

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