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Modeling the hemodynamic response due to vasodilatory signals conducted upstream along the arteriolar tree

2008· article· en· W2749153614 on OpenAlexaff
Stewart Mackie, Stephanie Milkovich, Christopher G. Ellis, Daniel Goldman

Bibliographic record

VenueThe FASEB Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsWestern University
FundersNational Institutes of Health
KeywordsArterioleHemodynamicsChemistryBlood flowVasodilationHematocritAttenuationMicrocirculationAnatomyMaterials sciencePhysicsInternal medicineBiologyMedicineOptics

Abstract

fetched live from OpenAlex

To study local regulation of convective O 2 delivery, in vivo experiments were conducted using a gas chamber to oscillate the O 2 environment at one surface of rat skeletal muscle. Intravital video microscopy enabled quantification of the hemodynamic (RBC velocity, V, and hematocrit, H) and O 2 saturation responses in capillaries. To assess how changes in arteriolar diameters lead to the observed blood flow response, a model of the lower three levels of the arteriolar tree was constructed based on published data. Sinusoidal changes in vessel diameter were imposed at the distal end of one terminal arteriole, and the upstream conduction of these diameter changes was simulated. A quasi‐steady model of two‐phase (RBCs and plasma) blood flow was used to calculate time‐dependent hemodynamics in the network. For a range of forcing frequencies, conduction velocities (V cond ), and attenuation lengths, the ability of the system to control RBC supply in a terminal arteriole was studied. Attenuation lengths within the physiological range (2mm to 2cm) did not affect the flow response. Decreases in frequency and increases in V cond increased the amplitude of the flow response. For a frequency of 0.025 Hz, varying V cond from 10 μm/sec to 50 μm/sec increased the RBC supply response by 35%. Predicted changes in H and V showed qualitative agreement with experimental results. Supported by NIH HL‐089125, CIHR to CGE and DG, and NSERC to SJMM.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.026
GPT teacher head0.253
Teacher spread0.227 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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