Evidence map›Paper›PMID 41372151›Full record

ArticleLight, science & applications2025

Whispering-gallery-mode resonators for detection and classification of free-flowing nanoparticles and cells through photoacoustic signatures.

Jie Liao, Maxwell Adolphson, Hangyue Li, Dipayon Kumar Sikder, Chenyang Lu, Lan Yang

Abstract read
In one paragraph

Article in Light, science & applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Jie Liao *Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, 63130, USA.ORCID http://orcid.org/0000-0003-2333-1454
Maxwell Adolphson *Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, 63130, USA.
Hangyue LiDepartment of Computer Science and Engineering, Washington University, St. Louis, MO, 63130, USA.
Dipayon Kumar SikderDepartment of Electrical and Systems Engineering, Washington University, St. Louis, MO, 63130, USA.ORCID http://orcid.org/0009-0005-6900-1372
Chenyang LuDepartment of Electrical and Systems Engineering, Washington University, St. Louis, MO, 63130, USA.ORCID http://orcid.org/0000-0003-1709-6769
Lan YangDepartment of Electrical and Systems Engineering, Washington University, St. Louis, MO, 63130, USA. yang@seas.wustl.edu.ORCID http://orcid.org/0000-0002-9052-0450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Micro and nanoscale particles have played crucial roles across diverse fields, from biomedical imaging and environmental processes to early disease diagnosis, influencing numerous scientific research and industrial applications. Their unique characteristics demand accurate detection, characterization, and identification. However, conventional spectroscopy and microscopy commonly used to characterize and identify tiny objects often involve bulky equipment and intricate, time-consuming sample preparation. Over the past two decades, optical micro-sensors have emerged as a promising sensor technology with their high sensitivity and compact configuration. However, their broad applicability is constrained by the requirement of surface binding for selective sensing and the difficulty in differentiating between various sensing targets, which limits their application in detecting targets in their native state or in complex biological samples. Developing label-free and immobilization-free sensing techniques that can directly detect target particles in complex solutions is crucial for overcoming the inherent limitations of current biosensors. In this study, we design and demonstrate an optofluidic, high throughput, ultra-sensitive optical microresonator sensor that can capture subtle acoustic signals, generated by tiny particles from the absorption of pulsed light energy, providing photoacoustic spectroscopy information for real-time, label-free detection and interrogation of particles and cells in their native solution environments across an extended sensing volume. Leveraging unique optical absorption of the targets, our technique can selectively detect and classify particles flowing through the sensor systems without the need for surface binding, even in a complex sample matrix, such as whole blood samples. We showcase the measurement of gold nanoparticles with diverse geometries and different species of red blood cells in the presence of other cellular elements and a wide variety of proteins. These particles are effectively identified and classified based on their photoacoustic fingerprint that captures particle shape, composition, molecule properties, and morphology features. This work opens up new avenues to achieve rapid, reliable, and high-throughput particle and cell identification in clinical and industrial applications, offering a valuable tool for understanding complex biological and environmental systems.

Identifiers

PMID41372151
PMCPMC12695887

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Registered trials

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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.