Evidence map›Paper›PMID 31817717›Full record

ArticleBiosensors2019

Establishing a Field-Effect Transistor Sensor for the Detection of Mutations in the Tumour Protein 53 Gene (TP53)-An Electrochemical Optimisation Approach.

Lisa Crossley, Bukola Attoye, Vincent Vezza, Ewen Blair, Damion K Corrigan, Stuart Hannah

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

6 authors at 1 institution in 1 country.

Lisa CrossleyDepartment of Biomedical Engineering, University of Strathclyde, 40 George Street, Glasgow G1 1QE, UK.
Bukola AttoyeDepartment of Biomedical Engineering, University of Strathclyde, 40 George Street, Glasgow G1 1QE, UK.
Vincent VezzaDepartment of Biomedical Engineering, University of Strathclyde, 40 George Street, Glasgow G1 1QE, UK.
Ewen BlairDepartment of Biomedical Engineering, University of Strathclyde, 40 George Street, Glasgow G1 1QE, UK.
Damion K CorriganDepartment of Biomedical Engineering, University of Strathclyde, 40 George Street, Glasgow G1 1QE, UK.
Stuart HannahDepartment of Biomedical Engineering, University of Strathclyde, 40 George Street, Glasgow G1 1QE, UK.
University of Strathclyde · GB

Funding

British Council Institutional Links grant 20180209Engineering and Physical Sciences Research Council EP/L015595/1
6 · The paper itself

Abstract

We present a low-cost, sensitive and specific DNA field-effect transistor sensor for the rapid detection of a common mutation to the tumour protein 53 gene (TP53). The sensor consists of a commercially available, low-cost, field-effect transistor attached in series to a gold electrode sensing pad for DNA hybridisation. The sensor has been predominantly optimised electrochemically, particularly with respect to open-circuit potentiometry as a route towards understanding potential (voltage) changes upon DNA hybridisation using a transistor. The developed sensor responds sensitively to TP53 mutant DNA as low as 100 nM concentration. The sensor responds linearly as a function of DNA target concentration and is able to differentiate between complementary and noncomplementary DNA target sequences.

Indexed as

Biosensing TechniquesElectrochemical TechniquesTransistors, ElectronicDNAHumansMutationNucleic Acid HybridizationTumor Suppressor Protein p53DNATumor Suppressor Protein p53biosensorelectrochemistryfield-effect transistoropen-circuit potentialTP53

Identifiers

PMID31817717
PMCPMC6956290
OpenAlexW2993720362

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.