Evidence map›Paper›PMID 39585872›Full record

ArticlePLOS global public health2024

Automation for lateral flow rapid tests: Protocol for an open-source fluid handler and applications to dengue and African swine fever tests.

Rohan Laurent, Benjamin Hinnant, Michael D Talbott, Kenneth Kim

Abstract read
In one paragraph

Article in PLOS global public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Diagnostic Techniques for Dengue Virus.Current topics in microbiology and immunology · 2026
    Review
  2. 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

4 authors.

Rohan LaurentHistopathology Core, La Jolla Institute for Immunology, La Jolla, California, United States of America.ORCID https://orcid.org/0009-0008-2247-166X
Benjamin HinnantHistopathology Core, La Jolla Institute for Immunology, La Jolla, California, United States of America.
Michael D TalbottLa Jolla Institute for Immunology, La Jolla, California, United States of America.
Kenneth KimHistopathology Core, La Jolla Institute for Immunology, La Jolla, California, United States of America.ORCID https://orcid.org/0000-0002-5993-4575

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lateral flow rapid diagnostic tests (RDTs, RTs) are cost-effective with low infrastructure requirements for limited-resource settings, and in any setting can represent a bridge between early disease monitoring at outbreak onset and fully-scaled molecular testing for human or animal diseases. However, the potential of RTs to handle higher throughput testing is hampered by the need for manual processing. Here we review dengue virus and African swine fever virus rapid tests, and present a novel protocol that employs an open-source fluid handler to automate the execution of up to 42 RTs per run. A publicly accessible website, rtWIZARD.lji.org, provides printouts for correctly spacing cassettes, worksheets for sample organization, and test-specific fluid handler protocols to accurately deliver samples from a 48-tube rack to each cassette's sample and running buffer wells. An optional QR-coded sheet allows for de-identified sample-to-result traceability by producing a unique printable label for each cassette, enabling results to be entered via a scanner. This work describes a highly cost-effective model for increasing outbreak diagnostic efficiency and of increasing RT throughput for other applications including workplace testing, food safety, environmental testing, and defense applications.

Identifiers

PMID39585872
PMCPMC11588214

What OpenQuestion holds

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LicenceCC BY
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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.