Evidence map›Paper›PMID 38907916›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Liquid and Solid Hybridization Methods to Detect RNAs.

Waqar Ahmad, Jasmin Baby, Bushra Gull, Farah Mustafa

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Waqar AhmadDepartment of Biochemistry & Molecular Biology, College of Medicine and Health Sciences, United Arab Emirates (UAE) University, Al Ain, United Arab Emirates.
Jasmin BabyDepartment of Biochemistry & Molecular Biology, College of Medicine and Health Sciences, United Arab Emirates (UAE) University, Al Ain, United Arab Emirates.
Bushra GullDepartment of Biochemistry & Molecular Biology, College of Medicine and Health Sciences, United Arab Emirates (UAE) University, Al Ain, United Arab Emirates.
Farah MustafaDepartment of Biochemistry & Molecular Biology, College of Medicine and Health Sciences, United Arab Emirates (UAE) University, Al Ain, United Arab Emirates. fmustafa@uaeu.ac.ae.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Northern blotting (NB) has been a long-standing method for RNA detection. However, its labor-intensive nature, reliance on high-quality RNA, and use of radioactivity have diminished its appeal over time. Nevertheless, the emergence of microRNAs (miRNAs) has reignited the demand for sensitive and quantitative NB techniques. We have recently developed cost-effective and rapid protocols for RNA detection using solid and liquid hybridization (LH) techniques which exhibit high sensitivity without the need for radioactive or specialized reagents like locked nucleic acid (LNA) probes. Our assays incorporate biotinylated probes and improved techniques for probe hybridization, transfer, cross-linking, and signal enhancement. We demonstrate that while NB is sensitive in detecting mRNAs and small RNAs, our LH protocol efficiently detects these as well as miRNAs at lower amounts of RNA, achieving higher sensitivity comparable to radiolabeled probes. Compared to NB, LH offers benefits of speed, sensitivity, and specificity in detecting mRNAs, small RNAs, and miRNAs.

Indexed as

MicroRNAsNucleic Acid HybridizationBlotting, NorthernHumansRNARNA, MessengerMicroRNAsRNARNA, MessengerBiomolecular imagingBiotinylationExonuclease ILiquid hybridization (LH) assaymiRNAmRNANorthern blotting (NB)Small RNA

Identifiers

What OpenQuestion holds

Textmetadata
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.