Evidence map›Paper›PMID 34960341›Full record

ArticleSensors (Basel, Switzerland)2021

Peptide-Based Capture of Chikungunya Virus E2 Protein Using Porous Silicon Biosensor.

Rabeb Layouni, Tengfei Cao, Matthew B Coppock, Paul E Laibinis, Sharon M Weiss

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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
0.3field-weighted citation impact, top 45% 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, 5 citations in OpenAlex.

  1. Review
  2. Review
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

5 authors at 2 institutions in 1 country.

Rabeb LayouniDepartment of Chemical & Biomolecular Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Tengfei CaoInterdisciplinary Material Science Program, Vanderbilt University, Nashville, TN 37235, USA.
Matthew B CoppockHuman Research and Engineering Directorate, DEVCOM Army Research Laboratory, Adelphi, MD 20783, USA.
Paul E LaibinisDepartment of Chemical & Biomolecular Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Sharon M WeissInterdisciplinary Material Science Program, Vanderbilt University, Nashville, TN 37235, USA.
Vanderbilt University · USUnited States Army Combat Capabilities Development Command · US

Funding

United States Army Research Office W911NF-18-2-0176
6 · The paper itself

Abstract

The detection of pathogens presents specific challenges in ensuring that biosensors remain operable despite exposure to elevated temperatures or other extreme conditions. The most vulnerable component of a biosensor is typically the bioreceptor. Accordingly, the robustness of peptides as bioreceptors offers improved stability and reliability toward harsh environments compared to monoclonal antibodies that may lose their ability to bind target molecules after such exposures. Here, we demonstrate peptide-based capture of the Chikungunya virus E2 protein in a porous silicon microcavity biosensor at room temperature and after exposure of the peptide-functionalized biosensor to high temperature. Contact angle measurements, attenuated total reflectance-Fourier transform infrared spectra, and optical reflectance measurements confirm peptide functionalization and selective E2 protein capture. This work opens the door for other pathogenic biomarker detection using peptide-based capture agents on porous silicon and other surface-based sensor platforms.

Indexed as

Biosensing TechniquesChikungunya virusPeptidesPorosityReproducibility of ResultsSiliconPeptidesSiliconChikungunya virusoptical biosensorpeptideporous silicon

Identifiers

PMID34960341
PMCPMC8708774
OpenAlexW4200067540

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.