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Application of a Novel Microfluidic Device for Studying Microvascular Blood Flow Regulation In Vivo

2019· article· en· W3173385678 on OpenAlexaff
Gaylene M. Russell McEvoy, Hamza Shogan, Graham Fraser

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBiomedical engineeringBlood flowPerfusionChemistryAnatomyMaterials scienceMedicineCardiology

Abstract

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Objective Validate the efficacy of a novel liquid microfluidic device (LMFD) to manipulate microvascular blood flow by maintaining a fixed solute concentration, temperature, and physiologic gas conditions in a microscale region of tissue while simultaneously allowing for visualization and quantification of vascular geometry and hemodynamics. Methods LMFD flow channels were moulded in polydimethylsiloxane (PDMS) using soft lithography techniques. A diffusive exchange window was created by patterning a 600×300 μm laser cut micro‐outlet into a glass coverslip. Cured PDMS flow channels were plasma bound to both the coverslip containing the micro‐outlet, and a glass slide to produce a complete LMFD. Ten Sprague‐Dawley rats (149–197g) were anesthetized with sodium pentobarbital; indwelling cannulas were placed into the left common carotid and right jugular vein for systemic monitoring, anaesthetic administration and fluid resuscitation; animals were then tracheotomized and mechanically ventilated. The extensor digitorum longus muscle of the lower hind‐limb was carefully dissected, externalized, and reflected across the LMFD secured in the stage of an inverted Olympus IX73 microscope. The muscle was allowed to equilibrate for 30 minutes while the LMFD was perfused with buffered Krebs solution at 37□. Logarithmic doses (10 −8 M to 10 −3 M) of adenosine triphosphate (ATP), acetylcholine (Ach), and phenylephrine (PE) were sequentially administered to the muscle via perfusion through the LMFD. The LMFD was perfused with each drug concentration for 5 minutes prior to data collection. Video of microvascular blood flow was recorded from multiple focal planes within the volume directly overlying the micro‐outlet. Recordings were analyzed offline to measure velocity, hematocrit, and supply rate. All animal protocols were approved by Memorial University's Institutional Animal Care Committee. Results ATP significantly increased red blood cell supply rate (RBC SR) to 36.1 and 36.5 cell/s at concentrations of 10 −4 and 10 −3 M respectively (p < 0.01) compared to the baseline level of 14.4 cell/s. Increasing concentrations of PE caused a graded change in RBC SR with significant decreases to 9.1, 3.5, and 0.8 cells/s at 10 −5 , 10 −4 , 10 −3 M respectively (p < 0.02). Changes in perfusion were observed only in areas directly overlying the micro‐outlet and within 200–300 μm of the window. Functional images generated at the highest drug concentrations showed that microvascular perfusion was unaffected in regions at greater distances from the micro‐outlet. Evan's Blue dye was used to confirm there were no leaks around the exchange window and that only tissue overlying the micro‐outlet was directly exposed to solutions perfusing the LMFD. Conclusions Our novel LMFD allows for a controlled, continuous delivery of dissolved substances to highly constrained regions of microvasculature while simultaneously allowing visualization and measurement of blood flow within discrete vessels and networks. Blood flow changes can be directly observed in the region of interest while the surrounding vasculature is unaffected thus preserving integrated regulation to the tissue as a whole. Support or Funding Information Project funded through a NSERC Discovery grant to GM Fraser. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 science0.0000.000
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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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