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Record W4409653303 · doi:10.1111/micc.70011

Convection Effect of Plasma Flow on Oxygen Transport in Capillaries: An In‐Depth Numerical Investigation

2025· article· en· W4409653303 on OpenAlexafffund
Junfeng Zhang

Bibliographic record

VenueMicrocirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsConvectionOxygen transportOxygenMechanicsPéclet numberChemistryDiffusionFlux (metallurgy)PlasmaCapillary actionLattice Boltzmann methodsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: The convection effect of plasma flow on gas transport in the microcirculation has been a controversial topic in the literature. We aim to clarify this concern via thorough and rigorous analysis of the oxygen release process from red blood cells (RBCs) to the surrounding tissue. METHODS: We develop a comprehensive model that considers the plasma flow, RBC deformation, oxygen transport and oxygen-hemoglobin reaction kinetics. The boundary integral and lattice Boltzmann methods are employed in the numerical solutions. In particular, the oxygen fluxes due to plasma convection and mass diffusion are separately calculated along the capillary wall for further comparison. RESULTS: Our results show that the most significant diffusive flux occurs in the narrow gap between the RBC side surface and the capillary wall and the diffusive flux is primarily directed outward, which favors oxygen release into the surrounding tissue. Furthermore, although the axial convective flux is the most profound in magnitude, it contributes little to the overall blood-to-tissue oxygen transport in the radial direction. The radial convective flux also has a larger magnitude compared to the diffusive oxygen flux, but is limited to two small areas and to opposite directions. This results in a negligible net effect of the plasma convection compared to the diffusive flux on the overall oxygen transport. This observation is further confirmed by comparing the oxygen distributions and diffusive fluxes from simulations with and without considering the plasma convection flow relative to RBCs. Moreover, we revisit the Peclet number definition and propose that different characteristic length scales should be adopted for oxygen diffusion and convection in capillaries. The revised Peclet number has a value three orders of magnitude lower than that from the classical Peclet number definition. CONCLUSIONS: Our simulation results show that the influence of plasma convection on the overall oxygen transport can be neglected in typical microcirculation situations. This is consistent with the revised Peclet number value, suggesting that the revised Peclet number can better reflect the relative importance of convection and diffusion mechanisms in microvascular gas transport.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

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 science0.0000.001
Research integrity0.0010.000
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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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