Evidence map›Paper›PMID 30957983›Full record

ArticleCurrent protocols in cell biology2019

Preparation of Cells from Embryonic Organs for Single-Cell RNA Sequencing.

Rei Sekiguchi, Belinda Hauser

Open access · greenAbstract read
In one paragraph

Article in Current protocols in cell biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. Cell-type Specific Alteration ofbioRxiv : the preprint server for biology · 2026
    Article
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  7. Single Cell Analysis in Vascular Biology.Frontiers in cardiovascular medicine · 2020
    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

2 authors at 2 institutions in 1 country.

Rei SekiguchiDepartment of Oral and Craniofacial Sciences, School of Dentistry, University of Missouri-Kansas City, Kansas City, Missouri.
Belinda HauserMatrix and Morphogenesis Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland.
National Institute of Dental and Craniofacial Research · USNational Institutes of Health · US

Funding

Craniofacial Developmental DynamicsZIADE000525 · NIDCR · NATIONAL INSTITUTE OF DENTAL & CRANIOFACIAL RESEARCH · PI YAMADA, KENNETH · 2009 to 2025
$14.5M
Intramural NIH HHS ZIA DE000525
6 · The paper itself

Abstract

Although single-cell RNA sequencing (scRNA-seq) has become one of the most powerful methods available for transcriptome analysis, the quality of scRNA-seq data largely depends on cell preparation. Cell preparation from cultured cells and tissues requires different methods because of the inherent differences between these two categories of cells. Compared to cultured cells, tissues have more extracellular matrix, and the cells are generally more adherent and thus difficult to dissociate. The challenge is to achieve sufficient dissociation, cell counts, and viability all at the same time. This protocol describes approaches that help achieve these goals. These include a cold dissociation technique using cryophilic proteases active at cold temperature, timing of trituration during protease digestion, as well as filtration and washing methods that optimize cell viability and retention. Materials and equipment that optimize the process also discussed. © 2019 by John Wiley & Sons, Inc.

Indexed as

AnimalsCell SeparationEmbryo, MammalianLacrimal ApparatusMiceSalivary GlandsSequence Analysis, RNASingle-Cell Analysiscold dissociationcryophilic proteaseembryonic organembryonic tissuescRNA-seq

Identifiers

PMID30957983
PMCPMC6506382
OpenAlexW2935811030

What OpenQuestion holds

Textmetadata
LicenceTDM
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.