Evidence map›Paper›PMID 35620142›Full record

ArticleMicrochemical journal : devoted to the application of microtechniques in all branches of science2022

A new RT-LAMP-on-a-Chip Instrument for SARS-CoV-2 diagnostics.

Geovani Torezin Mendonça, Mateus Cassaboni Stracke, Bruna de Oliveira Coelho, Heloisa Bruna Soligo Sanchuki, Viviane Klassen de Oliveira, Fabricio Klerynton Marchini, Dalila Lucíola Zanette, Mateus Nóbrega Aoki, Emilson Ribeiro Viana, Lucas Blanes

Abstract read
In one paragraph

Article in Microchemical journal : devoted to the application of microtechniques in all branches of science, 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
–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

9 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

10 authors.

Geovani Torezin MendonçaLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Mateus Cassaboni StrackeLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Bruna de Oliveira CoelhoLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Heloisa Bruna Soligo SanchukiLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Viviane Klassen de OliveiraParaná Institute of Molecular Biology, Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Fabricio Klerynton MarchiniLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Dalila Lucíola ZanetteLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Mateus Nóbrega AokiLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.
Emilson Ribeiro VianaResearch and Characterization of Nanomaterials and Nanodevices Laboratory (LPCA-NN), Physics Department, Federal University of Technology - Paraná, 7 de setembro 3165 Avenue, Curitiba, Paraná, Brazil.
Lucas BlanesLaboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Professor Algacyr Munhoz Mader 3775 St., Curitiba, Paraná, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work describes the development of a Point-of-Care (POC) Lab-on-a-Chip (LOC) instrument for diagnosis of SARS-CoV-2 by Reverse-Transcription Loop-mediated isothermal amplification (RT-LAMP). The hardware is based on a Raspberry Pi computer ($35), a video camera, an Arduino Nano microcontroller, a printed circuit board as a heater and a 3D printed housing. The chips were manufactured in polymethyl methacrylate (PMMA) using a CO2 laser cutting machine and sealed with a PCR optic plastic film. The chip temperature is precisely controlled by a proportional-integral-derivative (PID) algorithm. During the RT-LAMP amplifications the chip was maintained at ∼ (65.0 ± 0.1) °C for 25 minutes and 5 minutes cooling down, totaling a 30 minutes of reaction .The software interpretation occurs in less than a second. The chip design has four 25 µL chambers, two for clinical samples and two for positive and negative control-samples. The RT-LAMP master mix solution added in the chip chambers contains the pH indicator Phenol Red, that is pink (for pH ∼ 8.0) before amplification and becomes yellow (pH ∼ 6.0) if the genetic material is amplified. The RT-LAMP SARS-CoV-2 diagnostic was made by color image recognition using the OpenCV machine vision software library. The software was programmed to automatically distinguish the HSV color parameter distribution in each one of the four chip chambers. The instrument was successfully tested for SARS-CoV-2 diagnosis, in 22 clinic samples, 11 positives and 11 negatives, achieving an assertiveness of 86% when compared to the results obtained by RT-LAMP standard reactions performed in conventional PCR equipment.

Indexed as

COVID-19diagnosticLAMP-on-a-chipOpenCVRaspberry PiSARS-CoV-2

Identifiers

PMID35620142
PMCPMC9121651

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.