Evidence map›Paper›PMID 39944082›Full record

ArticleAIP advances2025

Ultrafast optical and passive acoustic mapping characterization of nanoscale cavitation nuclei based on gas vesicle proteins.

Cameron A B Smith, Avinoam Bar-Zion, Qiang Wu, Dina Malounda, Luca Bau, Eleanor Stride, Mikhail G Shapiro, Constantin C Coussios

Abstract read
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Article in AIP advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Pressure estimation of ultra-high frequency ultrasound using gas vesicles.The Journal of the Acoustical Society of America · 2024
    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

8 authors.

Avinoam Bar-ZionDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.
Qiang WuDepartment of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.
Dina MaloundaDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.ORCID https://orcid.org/0000-0001-7086-9877
Luca BauDepartment of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.ORCID https://orcid.org/0000-0002-4882-1356
Eleanor StrideDepartment of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.ORCID https://orcid.org/0000-0003-3371-5929
Constantin C CoussiosDepartment of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.ORCID https://orcid.org/0000-0001-8792-7818

Funding

Biogenic Gas Nanostructures As Molecular Imaging Reporters For UltrasoundR01EB018975 · NIBIB · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI Mikhail Shapiro · 2014 to 2026
$5.9M
NIBIB NIH HHS R01 EB018975
6 · The paper itself

Abstract

Genetically encodable gas-filled particles, known as gas vesicles (GVs), have shown promise as a biomolecular contrast agent for ultrasound imaging and have the potential to be used as cavitation nuclei for ultrasound therapy. In this study, we used passive acoustic mapping techniques to characterize GV-seeded cavitation, utilizing 0.5 and 1.6 MHz ultrasound insonation over peak rarefactional pressures ranging from 100 to 2200 kPa. We found that GVs produce cavitation for the duration of the first applied pulse, up to at least 5000 cycles, but that bubble activity diminishes rapidly over subsequent pulses. At 0.5 MHz, the frequency content of cavitation emissions was predominantly broadband in nature, while at 1.6 MHz, narrowband content at harmonics of the main excitation frequency dominated. Simulations and high-speed camera imaging suggest that the received cavitation emissions come not from individual GVs but instead from the coalescence of GV-released gas into larger bubbles during the applied ultrasound pulse. These results will aid the future development of GVs as cavitation nuclei in ultrasound therapy.

Identifiers

PMID39944082
PMCPMC11811905

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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 OpenQuestion graph.