A framework for real-time image detection of bioaerosols.

Ryne A Juidici, Yan Ye, Francisco J Romay, Miles Owen, Qisheng Ou, David Y H Pui

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Ryne A JuidiciMechanical Engineering, University of Minnesota, 111 Church St SE, Mechanical Engineering Building, Minneapolis, MN, 55455, USA. juidi002@umn.edu.

Yan YeMechanical Engineering, University of Minnesota, 111 Church St SE, Mechanical Engineering Building, Minneapolis, MN, 55455, USA.

Francisco J RomayMechanical Engineering, University of Minnesota, 111 Church St SE, Mechanical Engineering Building, Minneapolis, MN, 55455, USA.

Miles OwenU.S. Army Primary Standards Laboratory, Redstone Arsenal, AL, USA.

Qisheng OuMechanical Engineering, University of Minnesota, 111 Church St SE, Mechanical Engineering Building, Minneapolis, MN, 55455, USA.

David Y H PuiMechanical Engineering, University of Minnesota, 111 Church St SE, Mechanical Engineering Building, Minneapolis, MN, 55455, USA. dyhpui@umn.edu.

Funding

US Army Test, Measurement, and Diagnostic Equipment Activity Contract W9124P23RJ024

6 · The paper itself

Abstract

Starting from the elastic light scattering and the induced fluorescence emission from airborne particles and extending to the counting and differentiation of the associated signals, a framework is proposed to describe the detection of bioaerosols using an image sensor. For validation, monodisperse NaCl particles were generated to mimic abiotic particles, while monodisperse 1% mass riboflavin particles were generated to mimic biotic particles. By challenging a prototype sensor with these particles, the exposure time, particle speed, and signal-to-noise ratio were shown to be critical parameters for detection. Additionally, it was displayed that the induced fluorescence emission can be isolated from the elastic light scattering by using a well-selected long-pass filter. Furthermore, correlating the color of the captured signals to an induced fluorescence contribution was shown to be a potential avenue of differentiation between biotic and abiotic particles. It is predicted that this color differentiation method can distinguish between a near-continuous range of visible induced fluorescence emission wavelengths, giving the ability to distinguish individual fluorophores from one another using simple filtering and a single detector. This framework will be used to further optimize the image-based bioaerosol sensor evaluated here.

Identifiers

PMID41466094

DOI10.1038/s41598-025-32744-x

PMCPMC12824191

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LicenceCC BY

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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.