Evidence map›Paper›PMID 41420392›Full record

ArticlePhysiological reports2025

An algorithm for generating biophysically realistic three-dimensional arteriolar networks applied to rat skeletal muscle.

Yuki Bao, Jefferson C Frisbee, Daniel Goldman

Abstract read
In one paragraph

Article in Physiological reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuki BaoDepartment of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.
Jefferson C FrisbeeDepartment of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.ORCID 0000-0003-2751-0599
Daniel GoldmanDepartment of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.

Funding

Gouvernement du Canada | Canadian Institutes of Health Research (IRSC) 389769Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-2018-05450Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-2019-06086
6 · The paper itself

Abstract

The microcirculation comprises small vessel networks that regulate blood perfusion within tissues. The relationship between tissue shape or size and its microvascular properties is not yet clear. This study develops an algorithm for computationally simulating branching arteriolar networks within ellipsoidal tissue volumes, including user-adjustable parameters (e.g., tissue width-length-height dimensions and microvessel density) for application within different rodent skeletal muscles. The algorithm is developed using principles from constrained constructive optimization, an iterative network generation framework based on proposed mechanisms of vascular growth. Networks generated within muscles of varying shapes and sizes were analyzed over a range of geometric (e.g., mean diameter, length, and number of bifurcations per Strahler's and centrifugal order, fractal dimension) and hemodynamic (e.g., Murray's law exponent, hematocrit) properties. Statistical similarity was observed across different skeletal muscle tissues, with differences due to tissue shape being observed only above a vessel diameter threshold of ~25 μm (varying at large or small tissue volumes at the scale m

Indexed as

AlgorithmsModels, CardiovascularMuscle, SkeletalAnimalsArteriolesComputer SimulationHemodynamicsMaleMicrocirculationRatsarteriolar networkbiosimulationcomputational modelingfractalgeometrymicrocirculationperfusion distributiontopology

Identifiers

PMID41420392
PMCPMC12717470

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.