Evidence map›Paper›PMID 22241768›Full record

ArticleNucleic acids research2012

Sensitive and label-free biosensing of RNA with predicted secondary structures by a triplex affinity capture method.

Laura G Carrascosa, S Gómez-Montes, A Aviñó, A Nadal, M Pla, R Eritja, L M Lechuga

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

12 citing papers in PubMed, 38 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

7 authors at 4 institutions in 1 country.

Laura G CarrascosaNanobiosensors and Bioanalytical Applications Group, CIBER-BBN and Research Center on Nanoscience and Nanotechnology (CIN2) CSIC, Barcelona, Spain. lcarrascosa@cin2.es
S Gómez-Montes
A Aviñó
A Nadal
M Pla
R Eritja
L M Lechuga
Institute of Advanced Chemistry of Catalonia · ESInstitute for Research in Biomedicine · ESBiomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine · ESUniversity of Girona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel biosensing approach for the label-free detection of nucleic acid sequences of short and large lengths has been implemented, with special emphasis on targeting RNA sequences with secondary structures. The approach is based on selecting 8-aminoadenine-modified parallel-stranded DNA tail-clamps as affinity bioreceptors. These receptors have the ability of creating a stable triplex-stranded helix at neutral pH upon hybridization with the nucleic acid target. A surface plasmon resonance biosensor has been used for the detection. With this strategy, we have detected short DNA sequences (32-mer) and purified RNA (103-mer) at the femtomol level in a few minutes in an easy and level-free way. This approach is particularly suitable for the detection of RNA molecules with predicted secondary structures, reaching a limit of detection of 50 fmol without any label or amplification steps. Our methodology has shown a marked enhancement for the detection (18% for short DNA and 54% for RNA), when compared with the conventional duplex approach, highlighting the large difficulty of the duplex approach to detect nucleic acid sequences, especially those exhibiting stable secondary structures. We believe that our strategy could be of great interest to the RNA field.

Indexed as

Base SequenceDNANucleic Acid ConformationReproducibility of ResultsRNASurface Plasmon ResonanceDNARNA

Identifiers

PMID22241768
PMCPMC3333861
OpenAlexW2155134990

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.