Evidence map›Paper›PMID 37286753›Full record

ArticleMikrochimica acta2023

An ultrasensitive aptamer-based fluorescent on/off system for trace amount evaluation of Yersinia enterocolitica in food samples.

Milad Tavassoli, Arezou Khezerlou, Hamed Hamishehkar, Ali Ehsani, Balal Khalilzadeh

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Article in Mikrochimica acta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. 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

5 authors at 2 institutions in 1 country.

Milad TavassoliStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
Arezou KhezerlouStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
Hamed HamishehkarDrug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Ali EhsaniDepartment of Food Science and Technology, Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran. ehsani@tbzmed.ac.ir.
Balal KhalilzadehStem Cell Research Center (SCRC), Tabriz University of Medical Sciences, Tabriz, 51666-14711, Iran.
Tabriz University of Medical Sciences · IRBiotechnology Research Center · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An innovative aptamer labeled with 5-FAM has been developed with a high affinity for Yersinia enterocolitica (Y. enterocolitica) using graphene oxide (GO) as a quenching platform. The selectivity of the prepared system was evaluated in the presence of common coexisted bacteria like Yersinia pseudotuberculosis, Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, and Salmonella typhimurium. Some experimental factors like pH and stability were investigated. The results showed that in the absence of Y. enterocolitica, aptamer labeled with 5-FAM was bonded with GO, causing fluorescence to be relatively weak. After the addition of Y. enterocolitica, the aptamer is released from the GO surface and binds to the target bacteria, and significantly increases the fluorescence intensity with an excitation wavelength of 410 nm and an emission wavelength of 530 nm. After optimizing all conditions, the system exhibited a wide linear response for Y. enterocolitica in the concentration range 10 to 1.0 × 10

Indexed as

Yersinia enterocoliticaYersinia pseudotuberculosisEscherichia coliLimit of DetectionOligonucleotidesSalmonella typhimuriumOligonucleotidesAptasensorFluorescenceFood analysisGraphene oxideYersinia enterocolitica

Identifiers

PMID37286753
OpenAlexW4379619270

What OpenQuestion holds

Textmetadata
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.