Evidence map›Paper›PMID 34203018›Full record

ArticleNanomaterials (Basel, Switzerland)2021

Bead-Immobilized Multimodal Molecular Beacon-Equipped DNA Machinery for Specific RNA Target Detection: A Prototypical Molecular Nanobiosensor.

Jeonghun Kim, So Yeon Ahn, Soong Ho Um

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2021. 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
–field-weighted citation impact
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.

  1. Role of Nano-miRNAs in Diagnostics and Therapeutics.International journal of molecular sciences · 2022
    Review
  2. 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

3 authors.

Jeonghun KimSchool of Chemical Engineering, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea.
So Yeon AhnSchool of Chemical Engineering, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea.
Soong Ho UmSchool of Chemical Engineering, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea.ORCID 0000-0002-2910-5629

Funding

National Research Foundation of Korea 2019R1 A2 C2002390
6 · The paper itself

Abstract

A variety of nanostructured diagnostic tools have been developed for the precise detection of known genetic variants. Molecular beacon systems are very promising tools due to their specific selectivity coupled with relatively lower cost and time requirements than existing molecular detection tools such as next generation sequencing or real-time PCR (polymerase chain reaction). However, they are prone to errors induced by secondary structure responses to environmental fluctuations, such as temperature and pH. Herein, we report a temperature-insensitive, bead-immobilized, molecular beacon-equipped novel DNA nanostructure for detection of cancer miRNA variants with the consideration of thermodynamics. This system consists of three parts: a molecular beacon for cancer-specific RNA capture, a stem body as a core template, and a single bead for solid-support. This DNA system was selectively bound to nanosized beads using avidin-biotin chemistry. Synthetic DNA nanostructures, designed based on the principle of fluorescence-resonance enhanced transfer, were effectively applied for in vitro cancer-specific RNA detection. Several parameters were optimized for higher performance, with a focus on thermodynamic stability. Theoretical issues regarding the secondary structure of a single molecular beacon and its combinatory forms were also studied. This study provides design guidelines for new sensing systems of miRNA variation for next-generation biotechnological applications.

Indexed as

DNA nanostructuremiRNAmolecular beaconsensor

Identifiers

PMID34203018
PMCPMC8235652

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Registered trials

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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.