Evidence map›Paper›PMID 35895419›Full record

ArticleThe American journal of tropical medicine and hygiene2022

Gold Nanoshells-Based Lateral Flow Assay for the Detection of Chagas Disease at the Point-of-Care.

Melisa Medina-Rivera, Washington B Cárdenas, David Erickson, Saurabh Mehta

Abstract read
In one paragraph

Article in The American journal of tropical medicine and hygiene, 2022. 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. Article
  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.

Melisa Medina-RiveraDivision of Nutritional Sciences, Cornell University, Ithaca, New York.
Washington B CárdenasLaboratorio para Investigaciones Biomédicas, Escuela Superior Politécnica del Litoral, Guayaquil, Guayas, Ecuador.
David EricksonDivision of Nutritional Sciences, Cornell University, Ithaca, New York.
Saurabh MehtaDivision of Nutritional Sciences, Cornell University, Ithaca, New York.

Funding

J. NRSA Training CoreTL1TR002386 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI Genevieve Giny Fouda Amou ou · 2017 to 2026
$5.8M
FeverPhone: Point of Care Diagnosis of Acute Febrile Illness using a Mobile DeviceR01EB021331 · NIBIB · CORNELL UNIVERSITY · PI ERICKSON, DAVID CARL, MEHTA, SAURABH · 2016 to 2020
$3.0M
NCATS NIH HHS TL1 TR002386NIBIB NIH HHS R01 EB021331
6 · The paper itself

Abstract

Chagas disease is a neglected parasitic infection and a major public health problem in the Americas. It remains underdiagnosed in the United States and internationally due to the lack of affordable testing and disparities in healthcare, particularly for those most at risk. We describe a proof-of-concept lateral flow immunoassay employing a recombinant Chagas multiantigen conjugated to gold nanoshells (AuNS) to detect circulating human anti-Chagas IgG antibodies. This is one of the first lateral flow immunoassays to capitalize on the larger surface area of AuNS compared with nanoparticles that can help amplify low-magnitude signals. Results were compared with 42 positive and negative Chagas serum samples, of which a subset of 27 samples was validated against an ELISA (Hemagen®). The sensitivity and specificity of our assay were 83% and 95%, respectively. These results suggest that an AuNS-based rapid testing for Chagas disease could facilitate in-field screening/diagnosis with a performance comparable to commercial methods.

Indexed as

Chagas DiseaseNanoshellsTrypanosoma cruziAntibodies, ProtozoanEnzyme-Linked Immunosorbent AssayGoldHumansImmunoassayPoint-of-Care SystemsSensitivity and SpecificityAntibodies, ProtozoanGold

Identifiers

PMID35895419
PMCPMC9393437

What OpenQuestion holds

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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.