Evidence map›Paper›PMID 35273286›Full record

ArticleScientific reports2022

Thermometric lateral flow immunoassay with colored latex beads as reporters for COVID-19 testing.

Terumitsu Azuma, Yuen Yung Hui, Oliver Y Chen, Yuh-Lin Wang, Huan-Cheng Chang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
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

9 citing papers in PubMed, 27 citations in OpenAlex.

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  9. Nanomaterial and interface advances in immunoassay biosensors.The journal of physical chemistry. C, Nanomaterials and interfaces · 2022
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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

5 authors at 2 institutions in 1 country.

Terumitsu AzumaInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan, ROC.
Yuen Yung HuiInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan, ROC.
Oliver Y ChenInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan, ROC.
Yuh-Lin WangInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan, ROC.
Huan-Cheng ChangInstitute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 106, Taiwan, ROC. hchang@gate.sinica.edu.tw.
Institute of Atomic and Molecular Sciences, Academia Sinica · TWNational Taiwan University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Temperature sensing is a promising method of enhancing the detection sensitivity of lateral flow immunoassay (LFIA) for point-of-care testing. A temperature increase of more than 100 °C can be readily achieved by photoexcitation of reporters like gold nanoparticles (GNPs) or colored latex beads (CLBs) on LFIA strips with a laser power below 100 mW. Despite its promise, processes involved in the photothermal detection have not yet been well-characterized. Here, we provide a fundamental understanding of this thermometric assay using non-fluorescent CLBs as the reporters deposited on nitrocellulose membrane. From a measurement for the dependence of temperature rises on the number density of membrane-bound CLBs, we found a 1.3-fold (and 3.2-fold) enhancement of the light absorption by red (and black) latex beads at 520 nm. The enhancement was attributed to the multiple scattering of light in this highly porous medium, a mechanism that could make a significant impact on the sensitivity improvement of LFIA. The limit of detection was measured to be 1 × 10

Indexed as

MicrospheresCOVID-19COVID-19 TestingHumansImmunoassayMicroscopy, Electron, ScanningThermometry

Identifiers

PMID35273286
PMCPMC8913781
OpenAlexW4221021410

What OpenQuestion holds

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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.