Evidence map›Paper›PMID 30445706›Full record

ArticleBiosensors2018

Electrochemical Determination of β-Lactoglobulin Employing a Polystyrene Bead-Modified Carbon Nanotube Ink.

Judith Molinari, Laura Florez, Anahí Medrano, Leandro Monsalve, Gabriel Ybarra

Abstract read
In one paragraph

Article in Biosensors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Judith MolinariU.T. Nanomateriales, INTI-Procesos Superficiales, Instituto Nacional de Tecnología Industrial, Av. Gral. Paz 5445, San Martín B1650WAB, Argentina. molinari@inti.gov.ar.
Laura FlorezU.T. Nanomateriales, INTI-Procesos Superficiales, Instituto Nacional de Tecnología Industrial, Av. Gral. Paz 5445, San Martín B1650WAB, Argentina. lflorez@inti.gov.ar.
Anahí MedranoCentro de Micro y Nanoelectrónica, Instituto Nacional de Tecnología Industrial, Av. Gral. Paz 5445, San Martín B1650WAB, Argentina. amedrano@inti.gov.ar.
Leandro MonsalveCentro de Micro y Nanoelectrónica, Instituto Nacional de Tecnología Industrial, Av. Gral. Paz 5445, San Martín B1650WAB, Argentina. monsalve@inti.gov.ar.ORCID 0000-0001-9306-8618
Gabriel YbarraU.T. Nanomateriales, INTI-Procesos Superficiales, Instituto Nacional de Tecnología Industrial, Av. Gral. Paz 5445, San Martín B1650WAB, Argentina. gabriel@inti.gov.ar.

Funding

ANPCyT PICT 2013-0427, PICT 2014-3748, PICT 2014-3750 and PICT 2017-2787
6 · The paper itself

Abstract

In this article, we introduce the use of a carboxy-functionalized waterborne carbon nanotube ink for the fabrication of an amperometric biosensor aimed at the quantification of β-lactoglobulin. Detection of this protein from cow's milk was performed by a sandwich immunoassay onto printed carbon nanotube electrodes. The electrodes were printed using a carbon nanotube ink modified with polystyrene beads containing a high amount of carboxylic groups for protein immobilization. This strategy showed enhanced sensing performance compared to the use of oxidative treatments for the functionalization of electrodes. These electrodes showed an excellent electrochemical behavior, and proteins could be immobilized on their surface via the carbodiimide reaction. These antibody-immobilized carbon nanotube electrodes allowed for the detection of β-lactoglobulin in sub-ppm concentrations.

Indexed as

AnimalsBiosensing TechniquesCattleInkLactoglobulinsMilkNanotubes, CarbonLactoglobulinsNanotubes, Carboncarbon nanotubeselectrochemical biosensorfood allergenβ-lactoglobulin

Identifiers

PMID30445706
PMCPMC6316051

What OpenQuestion holds

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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.