Evidence map›Paper›PMID 33720708›Full record

ArticleACS sensors2021

Single-Molecule FRET-Based Dynamic DNA Sensor.

Anoja Megalathan, Kalani M Wijesinghe, Soma Dhakal

Abstract read
In one paragraph

Article in ACS sensors, 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
–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

9 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

3 authors.

Anoja MegalathanDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.
Kalani M WijesingheDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.
Soma DhakalDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.ORCID 0000-0002-3734-139X

Funding

Research Supplement to Promote Diversity in Health Related ResearchUL1TR002649 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI MOELLER, FREDERICK GERARD · 2018 to 2022
$19.1M
NCATS NIH HHS UL1 TR002649
6 · The paper itself

Abstract

Selective and sensitive detection of nucleic acid biomarkers is of great significance in early-stage diagnosis and targeted therapy. Therefore, the development of diagnostic methods capable of detecting diseases at the molecular level in biological fluids is vital to the emerging revolution in the early diagnosis of diseases. However, the vast majority of the currently available ultrasensitive detection strategies involve either target/signal amplification or involve complex designs. Here, using a p53 tumor suppressor gene whose mutation has been implicated in more than 50% of human cancers, we show a background-free ultrasensitive detection of this gene on a simple platform. The sensor exhibits a relatively static mid-FRET state in the absence of a target that can be attributed to the time-averaged fluorescence intensity of fast transitions among multiple states, but it undergoes continuous dynamic switching between a low- and a high-FRET state in the presence of a target, allowing a high-confidence detection. In addition to its simple design, the sensor has a detection limit down to low femtomolar (fM) concentration without the need for target amplification. We also show that this sensor is highly effective in discriminating against single-nucleotide polymorphisms (SNPs). Given the generic hybridization-based detection platform, the sensing strategy developed here can be used to detect a wide range of nucleic acid sequences enabling early diagnosis of diseases and screening genetic disorders.

Indexed as

DNAFluorescence Resonance Energy TransferBase SequenceDNA ProbesHumansNucleic Acid HybridizationDNADNA ProbesbiomarkersDNA/RNA detectionfluorescence resonance energy transfer (FRET)hybridization sensorsingle moleculesingle-nucleotide polymorphism (SNP)ultrasensitive sensor

Identifiers

PMID33720708
PMCPMC8311664

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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.