Evidence map›Paper›PMID 27265624›Full record

ArticleScientific reports2016

High-contrast grating resonators for label-free detection of disease biomarkers.

Tianbo Sun, Shu Kan, Gerard Marriott, Connie Chang-Hasnain

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.4field-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

14 citing papers in PubMed, 61 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Pedestal High-Contrast Gratings for Biosensing.Nanomaterials (Basel, Switzerland) · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Towards Portable Nanophotonic Sensors.Sensors (Basel, Switzerland) · 2019
    Review
  14. 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 1 institution in 1 country.

Tianbo SunDepartment of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA.
Shu KanDepartment of Bioengineering, University of California, Berkeley, CA 94720, USA.
Gerard MarriottDepartment of Bioengineering, University of California, Berkeley, CA 94720, USA.
Connie Chang-HasnainDepartment of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA.
University of California, Berkeley · US

Funding

New Classes of Genetically-Encoded Fluorescence Anisotropy ProbeR21EB017387 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI MARRIOTT, GERARD · 2014 to 2015
$431k
New classes of optical switch chelate to study the role of Ca2+-oscillations in cell signalingR21CA199512 · NCI · UNIVERSITY OF CALIFORNIA BERKELEY · PI MARRIOTT, GERARD · 2015 to 2016
$376k
NCI NIH HHS R21 CA199512NIBIB NIH HHS R21 EB017387
6 · The paper itself

Abstract

A label-free optical biosensor is described that employs a silicon-based high-contrast grating (HCG) resonator with a spectral linewidth of ~500 pm that is sensitive to ligand-induced changes in surface properties. The device is used to generate thermodynamic and kinetic data on surface-attached antibodies with their respective antigens. The device can detect serum cardiac troponin I, a biomarker of cardiac disease to 100 pg/ml within 4 mins, which is faster, and as sensitive as current enzyme-linked immuno-assays for cTnI.

Indexed as

Biosensing TechniquesBiomarkersHeart DiseasesHumansKineticsLigandsSensitivity and SpecificitySurface PropertiesThermodynamicsTroponin IBiomarkersLigandsTroponin I

Identifiers

PMID27265624
PMCPMC4893738
OpenAlexW2468751844

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.