Evidence map›Paper›PMID 26902536›Full record

ArticleScientific reports2016

High-resolution Identification and Separation of Living Cell Types by Multiple microRNA-responsive Synthetic mRNAs.

Kei Endo, Karin Hayashi, Hirohide Saito

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  15. RNA-based gene circuits for cell regulation.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2016
    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.

Kei EndoDepartment of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
Karin HayashiDepartment of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
Hirohide SaitoDepartment of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The precise identification and separation of living cell types is critical to both study cell function and prepare cells for medical applications. However, intracellular information to distinguish live cells remains largely inaccessible. Here, we develop a method for high-resolution identification and separation of cell types by quantifying multiple microRNA (miRNA) activities in live cell populations. We found that a set of miRNA-responsive, in vitro synthesized mRNAs identify a specific cell population as a sharp peak and clearly separate different cell types based on less than two-fold differences in miRNA activities. Increasing the number of miRNA-responsive mRNAs enhanced the capability for cell identification and separation, as we precisely and simultaneously distinguished different cell types with similar miRNA profiles. In addition, the set of synthetic mRNAs separated HeLa cells into subgroups, uncovering heterogeneity of the cells and the level of resolution achievable. Our method could identify target live cells and improve the efficiency of cell purification from heterogeneous populations.

Indexed as

Cell SeparationGene Expression RegulationGenes, ReporterGreen Fluorescent ProteinsHeLa CellsHumansLuminescent ProteinsMCF-7 CellsMicroRNAsPlasmidsRed Fluorescent ProteinRNA, MessengerTransfectionenhanced green fluorescent proteinGreen Fluorescent ProteinsLuminescent ProteinsMicroRNAsRed Fluorescent ProteinRNA, Messenger

Identifiers

PMID26902536
PMCPMC4763229

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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.