Evidence map›Paper›PMID 41744707›Full record

ReviewBiosensors2026

Acoustic Bubble Sensing Techniques and Bioapplications.

Renjie Ning, Jonathan Faulkner, Mengren Wu, Yuan Gao

Abstract readReview
In one paragraph

Review in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Renjie NingDepartment of Mechanical Engineering, University of Memphis, Memphis, TN 38152, USA.
Jonathan FaulknerDepartment of Mechanical Engineering, University of Memphis, Memphis, TN 38152, USA.
Mengren WuDepartment of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-7059-4305
Yuan GaoDepartment of Mechanical Engineering, University of Memphis, Memphis, TN 38152, USA.ORCID 0000-0002-5464-1626

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acoustic bubbles are emerging as powerful microscale sensors that convert local biochemical and biomechanical cues into measurable signals in a remote, label-free, and clinically compatible manner. Originally developed as vascular contrast agents, microbubbles are now engineered so that their resonance frequency, nonlinear oscillations, cavitation emissions, microstreaming, and radiation-force-induced motion encode information about pressure, rheology, oxygenation, and cell or tissue mechanics. In this review, we first summarize the fundamental physics of bubble dynamics, and then describe how these dynamics are translated into practical sensing observables. We then highlight key bioapplications where acoustic bubbles function as environment-responsive probes, ranging from hemodynamic pressure and fluid rheology to oxygen levels and cellular mechanics. Across these examples, we emphasize advantages such as non-invasive and wireless readout, high sensitivity arising from nonlinear bubble dynamics, and biochemical and molecular tunability. Finally, we outline current challenges and future opportunities for translating acoustic bubble-based sensing into robust, quantitative tools for biomedical applications.

Indexed as

acoustic bubblesbioapplicationsbiomechanical sensingbiosensingoscillating bubbles

Identifiers

PMID41744707
PMCPMC12938097

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.