Evidence map›Paper›PMID 33069957›Full record

ArticleBiosensors & bioelectronics2021

Multiplexed detection and quantification of human antibody response to COVID-19 infection using a plasmon enhanced biosensor platform.

Nathaniel C Cady, Natalya Tokranova, Armond Minor, Nima Nikvand, Klemen Strle, William T Lee, William Page, Ernest Guignon, Arturo Pilar, George N Gibson

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in Biosensors & bioelectronics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
2.2field-weighted citation impact, top 7% of its field
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

56 citing papers in PubMed, 105 citations in OpenAlex.

  1. Review
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  3. Article
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  5. Article
  6. Applications of Gold Nanoparticles in Plasmonic and Nanophotonic Biosensing.Advances in biochemical engineering/biotechnology · 2024
    Review
  7. Article
  8. Article
  9. Insight of smart biosensors for COVID-19: A review.Luminescence : the journal of biological and chemical luminescence · 2023
    Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Capacitive immunosensor for COVID-19 diagnosis.Microelectronic engineering · 2023
    Article
  17. Review
  18. Article
  19. Article
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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 at 5 institutions in 1 country.

Nathaniel C CadyCollege of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA. Electronic address: ncady@sunypoly.edu.
Natalya TokranovaCollege of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
Armond MinorCollege of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
Nima NikvandCollege of Nanoscale Science & Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
Klemen StrleWadsworth Center, New York State Department of Health, Albany, NY, USA and School of Public Health, University at Albany, Albany, NY, USA.
William T LeeWadsworth Center, New York State Department of Health, Albany, NY, USA and School of Public Health, University at Albany, Albany, NY, USA.
William PageCiencia, Inc., East Hartford, CT, USA.
Ernest GuignonCiencia, Inc., East Hartford, CT, USA.
Arturo PilarCiencia, Inc., East Hartford, CT, USA.
George N GibsonCiencia, Inc., East Hartford, CT, USA; University of Connecticut, Storrs, CT, USA.
SUNY Polytechnic Institute · USHartford Financial Services (United States)New York State Department of Health · USUniversity at Albany, State University of New York · USUniversity of Connecticut · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 2019 SARS CoV-2 (COVID-19) pandemic has illustrated the need for rapid and accurate diagnostic tests. In this work, a multiplexed grating-coupled fluorescent plasmonics (GC-FP) biosensor platform was used to rapidly and accurately measure antibodies against COVID-19 in human blood serum and dried blood spot samples. The GC-FP platform measures antibody-antigen binding interactions for multiple targets in a single sample, and has 100% selectivity and sensitivity (n = 23) when measuring serum IgG levels against three COVID-19 antigens (spike S1, spike S1S2, and the nucleocapsid protein). The GC-FP platform yielded a quantitative, linear response for serum samples diluted to as low as 1:1600 dilution. Test results were highly correlated with two commercial COVID-19 antibody tests, including an enzyme linked immunosorbent assay (ELISA) and a Luminex-based microsphere immunoassay. To demonstrate test efficacy with other sample matrices, dried blood spot samples (n = 63) were obtained and evaluated with GC-FP, yielding 100% selectivity and 86.7% sensitivity for diagnosing prior COVID-19 infection. The test was also evaluated for detection of multiple immunoglobulin isotypes, with successful detection of IgM, IgG and IgA antibody-antigen interactions. Last, a machine learning approach was developed to accurately score patient samples for prior COVID-19 infection, using antibody binding data for all three COVID-19 antigens used in the test.

Indexed as

Clinical Laboratory TechniquesAntibodies, ViralBetacoronavirusBiosensing TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingDried Blood Spot TestingEquipment DesignFluorescenceHumansImmunoglobulin GLab-On-A-Chip DevicesPandemicsPneumonia, ViralSARS-CoV-2Antibodies, ViralImmunoglobulin GAntibodyBiosensorCOVID-19MultiplexPlasmonicQuantitative

Identifiers

PMID33069957
PMCPMC7545244
OpenAlexW3092617095

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.