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Abstract 4143515: Microbubble Cavitation Under Ultrasound Causes Microvessel Deformation at Mega-Hertz Frequency: Insights into Microvascular Mechanics

2024· article· en· W4404359650 on OpenAlexaff
Sae Jang, Cheng Chen, Xucai Chen, Brandon Helfield, Flordeliza S. Villanueva

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsConcordia University
Fundersnot available
KeywordsMedicineCavitationMicrovesselHertzDeformation (meteorology)UltrasoundMechanicsPathologyRadiologyComposite material

Abstract

fetched live from OpenAlex

Background: There is growing interest in understanding microbubble ( MB ) behavior under ultrasound ( US ) in complex in vivo environments, to optimize safety and efficacy for various clinical applications, e.g. , large molecule drug delivery, temporary blood-brain-barrier opening, and thrombus disintegration. However, there have been few mechanistic in vivo studies due to the challenges of visualizing vibrating MBs in the circulation at high temporal resolutions. Our study elucidates MB interactions with surrounding microvessels using ultra-fast intravital imaging of the rat cremaster muscle. Hypothesis: MB vibration-induced stress deforms surrounding microvessels in vivo. Deformations are influenced by not only the US parameters, but also the biomechanical properties of the vessel wall. Methods: Definity® was injected via the femoral artery of anesthetized rats and imaged in externalized cremaster muscle using an ultrafast microscope (up to 12 Mfps). Concurrently, a single US pulse of 6-10 cycles [1 MHz, peak negative pressures ( PNP ) 0.5-2.0 MPa] was delivered. Images were analyzed to calculate MB and vessel dimensions and to perform Fourier analyses. Stress-strain curves were generated using normal stress exerted by the MB (derived from the linearized Euler’s equation) and measured circumferential vessel strain (Diameter/initial Diameter-1). Results: MBs expanded in both circular and elliptical shapes (Fig 1A), and vibrated nonlinearly under US. Vessels vibrated in-phase with the MBs at higher PNP (Fig 1B). Fourier analyses revealed nonlinear vessel vibration (Fig 1C) at fundamental and harmonic US frequencies. Calculated normal stress exerted by the MB of three MB-vessel pairs displayed linear relationships with measured circumferential vessel strain (Fig 1D), with slopes (representing Young’s modulus, or stiffness) between 0.6-1.7 MPa. Conclusions: We demonstrate, for the first time, microvascular harmonic behavior in response to MB vibration under US; the associated bioeffects warrant further investigation. Finally, we introduce a novel method for measuring in vivo microvessel stiffness using MBs as mechanical probes, where vessel stiffness is represented by the slope of the presented stress-strain curve.

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 score0.004
Threshold uncertainty score0.015

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)0.0040.000

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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