Evidence map›Paper›PMID 31754805›Full record

ArticleMikrochimica acta2019

A tetrahedral DNA nanoflare for fluorometric determination of nucleic acids and imaging of microRNA using toehold strands.

Liang Li, Yingcai Meng, Ling Li, Shengfeng Wang, Jinsong Ding, Wenhu Zhou

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Article in Mikrochimica acta, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

6 authors.

Liang LiXiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410013, Hunan, China.
Yingcai MengXiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410013, Hunan, China.
Ling LiSchool of Pharmaceutical Sciences, Changsha Medical University, Changsha, 410013, Hunan, China.
Shengfeng WangXiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410013, Hunan, China.
Jinsong DingXiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410013, Hunan, China. dingjs0221@163.com.
Wenhu ZhouXiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410013, Hunan, China. zhouwenhuyaoji@163.com.ORCID 0000-0003-3794-661X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The authors describe a tetrahedral DNA nanostructure loaded with SYBR Green (SG-TDN) for fluorometric determination of nucleic acids. After intercalating into the TDN, fluorescence of SG is enhanced by 260-fold (exc 480 nm, em 524 nm), and the resulting SG-TDN nanoflare displays >7-fold stronger fluorescence than that of FAM-labeled TDN. The SG-TDNs were coupled to magnetic microparticles and polydopamine nanoparticles to construct multi-functional nanoprobes through sequence hybridization using a toehold strand. The method was applied to detect a stretch of microRNA sequence (20 bp) in buffer and in undiluted serum with excellent selectivity, over a wide linear range and with a low limit of detection (0.2 nM). The probe was also applied for visualization of tumor-related microRNA in living cells via fluorescence imaging. Graphical abstract Schematic representation of tetrahedron-based DNA nanoflare for fluorometric nucleic acid determination in undiluted blood serum and living cells.

Indexed as

A549 CellsBiosensing TechniquesDNAFluorescent DyesFluorometryHEK293 CellsHumansIndolesIntercalating AgentsLimit of DetectionMicroRNAsNanostructuresNucleic Acid HybridizationNucleic AcidsOptical ImagingPolymersDNAFluorescent DyesIndolesIntercalating AgentsMicroRNAsNucleic AcidspolydopaminePolymersCancerDiagnosticsDNA nanostructureLabel-freeNucleic acids detectionSerumSurvivinTetrahedron

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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.