Evidence map›Paper›PMID 35726910›Full record

ArticleThe Analyst2022

Smartphone clip-on instrument and microfluidic processor for rapid sample-to-answer detection of Zika virus in whole blood using spatial RT-LAMP.

Aaron M Jankelow, Hankeun Lee, Weijing Wang, Trung-Hieu Hoang, Amanda Bacon, Fu Sun, Seol Chae, Victoria Kindratenko, Katherine Koprowski, Robert A Stavins and 7 more

Abstract read
In one paragraph

Article in The Analyst, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

17 authors.

Aaron M JankelowDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. evalerac@illinois.edu.ORCID http://orcid.org/0000-0002-8329-3560
Hankeun LeeNick Holonyak Jr Micro and Nanotechnology Lab, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Weijing WangNick Holonyak Jr Micro and Nanotechnology Lab, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.ORCID http://orcid.org/0000-0001-7460-7735
Trung-Hieu HoangDepartment of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.ORCID http://orcid.org/0000-0002-4143-5401
Amanda BaconNick Holonyak Jr Micro and Nanotechnology Lab, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Fu SunNick Holonyak Jr Micro and Nanotechnology Lab, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.ORCID http://orcid.org/0000-0001-7171-8210
Seol ChaeNick Holonyak Jr Micro and Nanotechnology Lab, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Victoria KindratenkoDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. evalerac@illinois.edu.
Katherine KoprowskiDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. evalerac@illinois.edu.
Robert A StavinsDepartment of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.ORCID http://orcid.org/0000-0003-3176-3214
Dylann D CerianiGener8, LLC, Carlsbad, CA 92011, USA.
Zachary W EngelderGener8, LLC, Carlsbad, CA 92011, USA.
William P KingNick Holonyak Jr Micro and Nanotechnology Lab, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Minh N DoDepartment of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.ORCID http://orcid.org/0000-0001-5132-4986
Rashid BashirDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. evalerac@illinois.edu.ORCID http://orcid.org/0000-0002-7225-9180
Enrique ValeraDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. evalerac@illinois.edu.ORCID http://orcid.org/0000-0003-1359-6619
Brian T CunninghamDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. evalerac@illinois.edu.

Funding

Smartphone-linked system for diagnosis and epidemiological reporting of pathogens at the point of careR01AI139401 · NIAID · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI BASHIR, RASHID, CUNNINGHAM, BRIAN T. · 2019 to 2022
$1.7M
NIAID NIH HHS R01 AI139401
6 · The paper itself

Abstract

Rapid, simple, inexpensive, accurate, and sensitive point-of-care (POC) detection of viral pathogens in bodily fluids is a vital component of controlling the spread of infectious diseases. The predominant laboratory-based methods for sample processing and nucleic acid detection face limitations that prevent them from gaining wide adoption for POC applications in low-resource settings and self-testing scenarios. Here, we report the design and characterization of an integrated system for rapid sample-to-answer detection of a viral pathogen in a droplet of whole blood comprised of a 2-stage microfluidic cartridge for sample processing and nucleic acid amplification, and a clip-on detection instrument that interfaces with the image sensor of a smartphone. The cartridge is designed to release viral RNA from Zika virus in whole blood using chemical lysis, followed by mixing with the assay buffer for performing reverse-transcriptase loop-mediated isothermal amplification (RT-LAMP) reactions in six parallel microfluidic compartments. The battery-powered handheld detection instrument uniformly heats the compartments from below, and an array of LEDs illuminates from above, while the generation of fluorescent reporters in the compartments is kinetically monitored by collecting a series of smartphone images. We characterize the assay time and detection limits for detecting Zika RNA and gamma ray-deactivated Zika virus spiked into buffer and whole blood and compare the performance of the same assay when conducted in conventional PCR tubes. Our approach for kinetic monitoring of the fluorescence-generating process in the microfluidic compartments enables spatial analysis of early fluorescent "bloom" events for positive samples, in an approach called "Spatial LAMP" (S-LAMP). We show that S-LAMP image analysis reduces the time required to designate an assay as a positive test, compared to conventional analysis of the average fluorescent intensity of the entire compartment. S-LAMP enables the RT-LAMP process to be as short as 22 minutes, resulting in a total sample-to-answer time in the range of 17-32 minutes to distinguish positive from negative samples, while demonstrating a viral RNA detection as low as 2.70 × 10

Indexed as

Zika VirusZika Virus InfectionHumansMicrofluidicsMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesRNA, ViralSensitivity and SpecificitySmartphoneSurgical InstrumentsRNA, Viral

Identifiers

PMID35726910
PMCPMC9399074

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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.