Evidence map›Paper›PMID 35879425›Full record

ArticleAnalytical and bioanalytical chemistry2022

Isothermal circular strand displacement-based assay for microRNA detection in liquid biopsy.

Noemi Bellassai, Roberta D'Agata, Giuseppe Spoto

Open access · hybridAbstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. 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

3 authors at 1 institution in 1 country.

Noemi BellassaiDipartimento di Scienze Chimiche, Università degli Studi di Catania, Viale Andrea Doria 6, 95125, Catania, Italy.
Roberta D'AgataDipartimento di Scienze Chimiche, Università degli Studi di Catania, Viale Andrea Doria 6, 95125, Catania, Italy.
Giuseppe SpotoDipartimento di Scienze Chimiche, Università degli Studi di Catania, Viale Andrea Doria 6, 95125, Catania, Italy. giuseppe.spoto@unict.it.
University of Catania · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular miRNAs are promising targets for developing new assays for the early diagnosis and prognosis of diseases based on liquid biopsy. The detection of miRNAs in liquid biopsies is challenged by their short sequence length, low concentration, and interferences with bodily fluid components. Isothermal circular strand displacement polymerization has emerged as a convenient method for nucleic acid amplification and detection. Herein, we describe an innovative strategy for microRNA detection directly from biological fluids based on hairpin probe-assisted isothermal amplification reaction. We designed and optimized the assay to detect target analytes in 1 µL of the complex media's biological matrix using a microfluidic device for the straightforward analysis of multiple samples. We validated the assay to detect circulating miR-127-5p in synovial fluid, recently indicated as a predictive biomarker for osteoarthritis disease. The combined use of a mutant polymerase operating with high yield and a primer incorporating locked nucleic acid nucleosides allowed detection of miR-127-5p with 34 fmol L

Indexed as

Biosensing TechniquesMicroRNAsBiological AssayLiquid BiopsyNucleic Acid Amplification TechniquesPolymerizationMicroRNAsIsothermal amplificationLiquid biopsyMicrofluidic devicesMicroRNANucleic acid amplificationOsteoarthritis

Identifiers

PMID35879425
PMCPMC9411226
OpenAlexW4287831735

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.