Evidence map›Paper›PMID 25641598›Full record

ArticleLangmuir : the ACS journal of surfaces and colloids2015

Surface Enzyme Chemistries for Ultrasensitive Microarray Biosensing with SPR Imaging.

Jennifer B Fasoli, Robert M Corn

Abstract read
In one paragraph

Article in Langmuir : the ACS journal of surfaces and colloids, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

11 citing papers in PubMed, 41 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Jennifer B FasoliDepartment of Chemistry, University of California-Irvine , Irvine, California 92697, United States.
Robert M CornDepartment of Chemistry, University of California-Irvine , Irvine, California 92697, United States.
University of California, Irvine · US

Funding

SPR IMAGING STUDIES OF PROTEIN/DNA INTERACTIONSR01GM059622 · NIGMS · UNIVERSITY OF WISCONSIN MADISON · PI CORN, ROBERT M · 1999 to 2018
$5.1M
NIGMS NIH HHS GM059622NIGMS NIH HHS R01 GM059622
6 · The paper itself

Abstract

The sensitivity and selectivity of surface plasmon resonance imaging (SPRI) biosensing with nucleic acid microarrays can be greatly enhanced by exploiting various nucleic acid ligases, nucleases, and polymerases that manipulate the surface-bound DNA and RNA. We describe here various examples from each of these different classes of surface enzyme chemistries that have been incorporated into novel detection strategies that either drastically enhance the sensitivity of or create uniquely selective methods for the SPRI biosensing of proteins and nucleic acids. A dual-element generator-detector microarray approach that couples a bioaffinity adsorption event on one microarray element to nanoparticle-enhanced SPRI measurements of nucleic acid hybridization adsorption on a different microarray element is used to quantitatively detect DNA, RNA, and proteins at femtomolar concentrations. Additionally, this dual-element format can be combined with the transcription and translation of RNA from surface-bound double-stranded DNA (dsDNA) templates for the on-chip multiplexed biosynthesis of aptamer and protein microarrays in a microfluidic format; these microarrays can be immediately used for real-time SPRI bioaffinity sensing measurements.

Indexed as

Protein Array AnalysisSurface Plasmon ResonanceDNA, CatalyticDNA-Directed DNA PolymeraseLigasesNucleic AcidsProteinsSurface PropertiesDNA, CatalyticDNA-Directed DNA PolymeraseLigasesNucleic AcidsProteins

Identifiers

PMID25641598
PMCPMC4564839
OpenAlexW2316713732

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.