Evidence map›Paper›PMID 35518319›Full record

ArticleRSC advances2020

A rapid and reliable CE-LIF method for the quantitative analysis of miRNA-497 in plasma and organs and its application to a pharmacokinetic and biodistribution study.

Eunmi Ban, Haejin Kwon, Eun Joo Song

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2020. 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
0.4field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 10 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

3 authors at 1 institution in 1 country.

Eunmi BanCollege of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University Seoul 03760 Korea esong@ewha.ac.kr.
Haejin KwonCollege of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University Seoul 03760 Korea esong@ewha.ac.kr.
Eun Joo SongCollege of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University Seoul 03760 Korea esong@ewha.ac.kr.ORCID https://orcid.org/0000-0002-2420-6666
Ewha Womans University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are involved in the pathogenesis of many human diseases, and various miRNAs have been reported and developed as therapeutic candidates for treating various diseases. Various miRNA and carrier modification systems have been investigated for effective systemic miRNA delivery to cells, organs, and tissues of interest. Consequently, effective and reliable analytical methods of miRNAs are required for evaluating the pharmacokinetics and biodistribution of miRNAs as therapeutic candidates. The capillary electrophoresis with laser-induced fluorescence (CE-LIF) method has been recently reported as a promising and relatively rapidly developing tool with the potential to provide highly sensitive and specific analysis of biological molecules including miRNAs. Here, the CE-LIF method was used for application in the pharmacokinetic and distribution studies of miRNA-497 as a model miRNA for a lung target; miRNA-497 hybridized with 6-FAM-labeled DNA probes were separated using CE-LIF and detected within 6 min without any interference. This method showed a wide calibration range of 1.0-50 nM and 0.1-50 nM for plasma and the four organs, liver, spleen, lung, and kidney, respectively, with acceptable precision and accuracy. Using CE-LIF, the miRNA-497 level was evaluated in rat plasma and organs after intravenously administering 1 mg ml

Identifiers

PMID35518319
PMCPMC9053904
OpenAlexW3024573111

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.