MétaCan
Menu
← Back to cohort

Geometric and Topological Analysis of Arteriolar Networks in the Rat Gluteus Maximus Muscle: One Network to Rule Them All?

2016· article· en· W4389027515 on OpenAlexafffund
Mohammed Al Tarhuni, Daniel Goldman, Dwayne N. Jackson

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrocirculationGeometrySkeletal muscleTopology (electrical circuits)Blood flowMedial axisIntravital microscopyMathematicsAlgorithmAnatomyComputer scienceBiologyMedicineCombinatoricsCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction A detailed evaluation of in vivo geometry and topology of skeletal muscle arteriolar networks is essential to understanding microvascular blood flow regulation. Beyond increasing understanding of skeletal muscle hemodynamics, such data provides critical experimental inputs for theoretical blood flow simulation studies. Generally, past studies have relied on data collected from vascular casting experiments or data collected from incomplete microvascular trees or segments. The objective of this study was to comprehensively analyze the geometry and topology of complete arteriolar networks within the rat gluteus maximus (GM) muscle. The data generated were used to generate an index of geometric/topological homology across GM networks and produce essential experimental data to use as inputs for future theoretical studies of hemodynamics. Methods The rat GM provides the ideal experimental model to study locomotive skeletal muscle. Its planar geometry and uniform thinness enable access (within a single focal plane) to its entire microcirculation for microscopic imaging and perturbation. Using intravital videomicroscopy, the GM (n=4) was scanned under baseline conditions and photomontages were compiled (~400 images per network). Photomontages were registered to a MATLAB x–y coordinate system and scaled digital networks were generated. Arteriolar diameters and lengths were measured along the arteriolar network and a centrifugal ordering algorithm was applied, resulting in arterioles ranging from 1 st (feed) to 9 th (terminal) order. Mean diameters, lengths, and number of segments were outputted and grouped with respect to arteriolar order. Results The coefficients of variation at each order were consistently greater for lengths than diameters. The relationships of arteriolar diameter and segment length as a function of vessel order were fitted with an exponential decay function and resulted in relatively stronger goodness of fit values for diameters (R 2 = 0.62 to 0.75) than lengths (R 2 = 0.32 to 0.53), suggesting greater predictability and homology between arteriolar diameter and vessel order. Topological analyses were extended to plotting the logarithm of diameters and lengths as a function of vessel order in an effort to validate Horton's laws in the GM and derive diameter, length, and bifurcation ratios. Finally, a “mean” arteriolar network that describes all relevant geometric and topological parameters was explored. Conclusion This study provides the first comprehensive analysis of rat GM topology and geometry. The data presented herein will serve as ideal experimental inputs for future computational studies of skeletal muscle hemodynamics and microvascular blood flow regulation. Support or Funding Information NSERC

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
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
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.030
GPT teacher head0.274
Teacher spread0.244 · 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 designObservational
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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicCardiovascular Health and Disease Prevention→French-language works237,207→