Evidence map›Paper›PMID 40236689›Full record

ArticleSensors and actuators reports2024

Rapid and portable quantification of HIV RNA via a smartphone-enabled digital CRISPR device and deep learning.

Hoan T Ngo, Patarajarin Akarapipad, Pei-Wei Lee, Joon Soo Park, Fan-En Chen, Alexander Y Trick, Tza-Huei Wang, Kuangwen Hsieh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors and actuators reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. HIV infection detection using CRISPR/Cas systems: Present and future prospects.Computational and structural biotechnology journal · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Hoan T NgoDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Patarajarin AkarapipadDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Pei-Wei LeeDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Joon Soo ParkDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Fan-En ChenDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Alexander Y TrickDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Tza-Huei WangDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Kuangwen HsiehDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

Funding

Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
Technology development for point-of-care detection and antimicrobial susceptibility testing of Neisseria gonorrhoeaeR01AI138978 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF · 2018 to 2021
$5.1M
A "Culture" Shift: Integrated Bacterial Screening and Antibacterial Susceptibility Test on Microfluidic Digital Array for Bloodstream InfectionsR01AI137272 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF, YANG, SAMUEL · 2018 to 2022
$3.6M
Streamlined 15-min HIV Viral Load Self-Testing Using Finger-Stick BloodR61AI154628 · NIAID · JOHNS HOPKINS UNIVERSITY · PI HSIEH, YU-HSIANG, MANABE, YUKARI C · 2020 to 2022
$1.4M
NIAID NIH HHS P30 AI094189NIAID NIH HHS R01 AI137272NIAID NIH HHS R01 AI138978NIAID NIH HHS R61 AI154628
6 · The paper itself

Abstract

For the 29.8 million people in the world living with HIV/AIDS and receiving antiretroviral therapy, it is crucial to monitor their HIV viral loads. To this end, rapid and portable diagnostic tools that can quantify HIV RNA are critically needed. We report herein a rapid and quantitative digital CRISPR-assisted HIV RNA detection assay that has been implemented within a portable smartphone-based device as a potential solution. Specifically, we first developed a fluorescence-based reverse transcription recombinase polymerase amplification (RT-RPA)-CRISPR assay that can efficiently detect HIV RNA at 42 °C. We then implemented this assay within a commercial stamp-sized digital chip, where RNA molecules were quantified as strongly fluorescent digital reaction wells. The isothermal reaction condition and the strong fluorescence in the digital chip simplified the design of thermal and optical modules, allowing us to engineer a palm-size device measuring 70 × 115 × 80 mm and weighing less than 0.6 kg. We also capitalized the smartphone by developing a custom app to control the device, perform the digital assay, and capture fluorescence images throughout the assay using the smartphone's camera. Moreover, we trained and verified a deep learning-based algorithm for analyzing fluorescence images and identifying positive digital reaction wells with high accuracy. Using our smartphone-enabled digital CRISPR device, we successfully detected as low as 75 copies of HIV RNA in just 15 min, showing its potential toward monitoring of HIV viral loads and aiding the global effort to combat the HIV/AIDS epidemic.

Indexed as

CRISPR-based diagnosticsDeep learningHIV viral load monitoringPoint-of-care diagnosticsRT-RPA isothermal amplificationSmartphone-based medical device

Identifiers

PMID40236689
PMCPMC11997716

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.