Evidence map›Paper›PMID 29155743›Full record

ArticleJournal of visualized experiments : JoVE2017

Snap Chip for Cross-reactivity-free and Spotter-free Multiplexed Sandwich Immunoassays.

Huiyan Li, Sebastien Bergeron, Heidi Larkin, David Juncker

Open access · bronzeAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2017. 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
0.2field-weighted citation impact, top 43% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. 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 at 2 institutions in 1 country.

Huiyan LiMcGill University and Génome Québec Innovation Centre; Biomedical Engineering Department, McGill University.
Sebastien BergeronParallex BioAssays Inc.
Heidi LarkinMcGill University and Génome Québec Innovation Centre; Biomedical Engineering Department, McGill University; Parallex BioAssays Inc.
David JunckerMcGill University and Génome Québec Innovation Centre; Biomedical Engineering Department, McGill University; David.juncker@mail.mcgill.ca.
McGill University and Génome Québec Innovation Centre · CAMcGill University · CA

Funding

Canadian Institutes for Health Research
6 · The paper itself

Abstract

Multiplexed protein analysis has shown superior diagnostic sensitivity and accuracy compared to single proteins. Antibody microarrays allow for thousands of micro-scale immunoassays performed simultaneously on a single chip. Sandwich assay format improves assay specificity by detecting each target with two antibodies, but suffers from cross-reactivity between reagents thus limiting their multiplexing capabilities. Antibody colocalization microarray (ACM) has been developed for cross-reactivity-free multiplexed protein detection, but requires an expensive spotter on-site for microarray fabrication during assays. In this work, we demonstrate a snap chip technology that transfers reagent from microarray-to-microarray by simply snapping two chips together, thus no spotter is needed during the sample incubation and subsequent application of detection antibodies (dAbs) upon storage of pre-spotted slides, dissociating the slide preparation from assay execution. Both single and double transfer methods are presented to achieve accurate alignment between the two microarrays and the slide fabrication for both methods are described. Results show that <40 μm alignment has been achieved with double transfer, reaching an array density of 625 spots/cm

Indexed as

Cross ReactionsHumansImmunoassayProtein Array AnalysisProteinsProteins

Identifiers

PMID29155743
PMCPMC5755379
OpenAlexW2770455150

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.