Evidence map›Paper›PMID 27618185›Full record

ArticlePloS one2016

Rapid Bacterial Detection via an All-Electronic CMOS Biosensor.

Nasim Nikkhoo, Nichole Cumby, P Glenn Gulak, Karen L Maxwell

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.4field-weighted citation impact, top 13% 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

10 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  9. Article
  10. Microbiological Sensing Technologies: A Review.Bioengineering (Basel, Switzerland) · 2018
    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

4 authors at 1 institution in 1 country.

Nasim NikkhooDepartment of Electrical and Computer Engineering, University of Toronto, Toronto, ON, M5S 3G4, Canada.
Nichole CumbyDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, M5S 3E1, Canada.
P Glenn GulakDepartment of Electrical and Computer Engineering, University of Toronto, Toronto, ON, M5S 3G4, Canada.
Karen L MaxwellDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, M5S 3E1, Canada.
University of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The timely and accurate diagnosis of infectious diseases is one of the greatest challenges currently facing modern medicine. The development of innovative techniques for the rapid and accurate identification of bacterial pathogens in point-of-care facilities using low-cost, portable instruments is essential. We have developed a novel all-electronic biosensor that is able to identify bacteria in less than ten minutes. This technology exploits bacteriocins, protein toxins naturally produced by bacteria, as the selective biological detection element. The bacteriocins are integrated with an array of potassium-selective sensors in Complementary Metal Oxide Semiconductor technology to provide an inexpensive bacterial biosensor. An electronic platform connects the CMOS sensor to a computer for processing and real-time visualization. We have used this technology to successfully identify both Gram-positive and Gram-negative bacteria commonly found in human infections.

Indexed as

Biosensing TechniquesSemiconductorsBacteriaBacteriocinsElectronicsMetalsPotassiumBacteriocinsMetalsPotassium

Identifiers

PMID27618185
PMCPMC5019397
OpenAlexW2519265864

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.