Evidence map›Paper›PMID 36739311›Full record

ArticleScientific reports2023

Red cabbage extract-mediated colorimetric sensor for swift, sensitive and economic detection of urease-positive bacteria by naked eye and Smartphone platform.

Cagla Celik, Naim Yagiz Demir, Memed Duman, Nilay Ildiz, Ismail Ocsoy

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. 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
2.6field-weighted citation impact, top 10% 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, 24 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

5 authors at 3 institutions in 1 country.

Cagla CelikDepartment of Analytical Chemistry, Faculty of Pharmacy, Erciyes University, Kayseri, 38039, Turkey.
Naim Yagiz DemirNanotechnology and Nanomedicine Division, Institute of Science, Hacettepe University, Ankara, 06800, Turkey.
Memed DumanNanotechnology and Nanomedicine Division, Institute of Science, Hacettepe University, Ankara, 06800, Turkey.
Nilay IldizDepartment of Pharmaceutical Microbiology, Faculty of Pharmacy, Erciyes University, 38039, Kayseri, Turkey. nilaygucluer@yahoo.com.
Ismail OcsoyDepartment of Analytical Chemistry, Faculty of Pharmacy, Erciyes University, Kayseri, 38039, Turkey. ismailocsoy@erciyes.edu.tr.ORCID 0000-0002-5991-3934
Erciyes University · TRHacettepe University · TRHitit Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The bacterial pathogens have caused various serious infectious diseases in the human body, and even some threats to human life by leading to deaths. Enterobacteriaceae species especially urease positive ones, Proteus mirabilis (P. mirabilis) and Klebsiella pneumoniae (K. pneumoniae), show resistance to antibiotics and cause respiratory and urinary tract infections. We have developed natural indicator-incorporated colorimetric urease tests with a naked eye and smartphone readout to rapidly, sensitively and economically detect P. mirabilis and K. pneumoniae. We utilized anthocyanin found as a predominant component in red cabbage (Brassica oleracea) extract as a natural pH indicator instead of toxic and synthetic indicators. As a mechanistic explanation for the detection of P. mirabilis and K. pneumoniae, urease enzymes secreted from the P. mirabilis and K. pneumoniae hydrolyze urea to produce ammonia (NH

Indexed as

BacteriaBrassicaColorimetryUreaseAnthocyaninsKlebsiella pneumoniaePlant ExtractsProteus mirabilisSmartphoneAnthocyaninsPlant ExtractsUrease

Identifiers

PMID36739311
PMCPMC9899230
OpenAlexW4319227708

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.