Evidence map›Paper›PMID 39372017›Full record

ArticleACS omega2024

Optimization of Reverse Transcription Loop-Mediated Isothermal Amplification for In Situ Detection of SARS-CoV-2 in a Micro-Air-Filtration Device Format.

Jacob Fry, Jean Y H Lee, Julie L McAuley, Jessica L Porter, Ian R Monk, Samuel T Martin, David J Collins, Gregory J Barbante, Nicholas J Fitzgerald, Timothy P Stinear

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jacob FryARC Centre of Excellence in Exciton Science, The School of Chemistry, The University of Melbourne, Masson Rd, Parkville, Victoria 3010, Australia.ORCID https://orcid.org/0009-0009-0080-8636
Jean Y H LeeDepartment of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia.
Julie L McAuleyDepartment of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia.
Jessica L PorterDepartment of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia.
Ian R MonkDepartment of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia.
Samuel T MartinDepartment of Biomedical Engineering, The University of Melbourne, Building 261/203 Bouverie St, Carlton, Victoria 3053, Australia.
David J CollinsDepartment of Biomedical Engineering, The University of Melbourne, Building 261/203 Bouverie St, Carlton, Victoria 3053, Australia.ORCID https://orcid.org/0000-0001-5382-9718
Gregory J BarbanteDefence Science and Technology Group, Australian Department of Defence, 506 Lorimer Street, Fishermans Bend, Victoria 3207, Australia.
Nicholas J FitzgeraldDefence Science and Technology Group, Australian Department of Defence, 506 Lorimer Street, Fishermans Bend, Victoria 3207, Australia.
Timothy P StinearDepartment of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia.ORCID https://orcid.org/0000-0003-0150-123X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Coronavirus disease 2019 (COVID-19) pandemic has supercharged innovation in the field of molecular diagnostics and led to the exploration of systems that permit the autonomous identification of airborne infectious agents. Airborne virus detection is an emerging approach for determining exposure risk, although current methods limit intervention timeliness. Here, we explore reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays for one-pot detection of Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) (SCV2) run on membrane filters suitable for micro-air-filtration of airborne viruses. We use a design of experiments statistical framework to establish the optimal additive composition for running RT-LAMP on membrane filters. Using SCV2 liquid spike-in experiments and fluorescence detection, we show that single-pot RT-LAMP on glass fiber filters reliably detected 0.10 50% tissue culture infectious dose (TCID

Identifiers

PMID39372017
PMCPMC11447726

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.