Evidence map›Paper›PMID 34138310›Full record

ArticleNano-micro letters2021

Sniffing Bacteria with a Carbon-Dot Artificial Nose.

Nitzan Shauloff, Ahiud Morag, Karin Yaniv, Seema Singh, Ravit Malishev, Ofra Paz-Tal, Lior Rokach, Raz Jelinek

Open access · diamondAbstract read
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Article in Nano-micro letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-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

9 citing papers in PubMed, 39 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Nitzan ShauloffDepartment of Chemistry, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Ahiud MoragDepartment of Chemistry, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Karin YanivDepartment of Biotechnology Engineering, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Seema SinghDepartment of Chemistry, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Ravit MalishevDepartment of Chemistry, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Ofra Paz-TalChemistry Department, Nuclear Research Center, Negev, P.O. Box 9001, 84190, Beer Sheva, Israel.
Lior RokachDepartment of Software and Information System Engineering, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Raz JelinekDepartment of Chemistry, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel. razj@bgu.ac.il.
Ben-Gurion University of the Negev · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

highlightsNovel artificial nose based upon electrode-deposited carbon dots (C-dots). Significant selectivity and sensitivity determined by "polarity matching" between the C-dots and gas molecules. The C-dot artificial nose facilitates, for the first time, real-time, continuous monitoring of bacterial proliferation and discrimination among bacterial species, both between Gram-positive and Gram-negative bacteria and between specific strains. Machine learning algorithm furnishes excellent predictability both in the case of individual gases and for complex gas mixtures. Continuous, real-time monitoring and identification of bacteria through detection of microbially emitted volatile molecules are highly sought albeit elusive goals. We introduce an artificial nose for sensing and distinguishing vapor molecules, based upon recording the capacitance of interdigitated electrodes (IDEs) coated with carbon dots (C-dots) exhibiting different polarities. Exposure of the C-dot-IDEs to volatile molecules induced rapid capacitance changes that were intimately dependent upon the polarities of both gas molecules and the electrode-deposited C-dots. We deciphered the mechanism of capacitance transformations, specifically substitution of electrode-adsorbed water by gas molecules, with concomitant changes in capacitance related to both the polarity and dielectric constants of the vapor molecules tested. The C-dot-IDE gas sensor exhibited excellent selectivity, aided by application of machine learning algorithms. The capacitive C-dot-IDE sensor was employed to continuously monitor microbial proliferation, discriminating among bacteria through detection of distinctive "volatile compound fingerprint" for each bacterial species. The C-dot-IDE platform is robust, reusable, readily assembled from inexpensive building blocks and constitutes a versatile and powerful vehicle for gas sensing in general, bacterial monitoring in particular.

Indexed as

Bacterial detectionBacterially emitted volatile moleculesCapacitive gas sensorsCarbon dotsGas polarity

Identifiers

PMID34138310
PMCPMC8058130
OpenAlexW3163488843

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.