Evidence map›Paper›PMID 28467679›Full record

ReviewJournal of cellular biochemistry2017

CRISPR Editing in Biological and Biomedical Investigation.

Han Zhang, Nami McCarty

Abstract readReview
In one paragraph

Review in Journal of cellular biochemistry, 2017. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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.

Han ZhangCenter for Stem Cell and Regenerative Disease, Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases (IMM), University of Texas-Health Science Center at Houston, Houston, Texas, 77030.
Nami McCartyCenter for Stem Cell and Regenerative Disease, Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases (IMM), University of Texas-Health Science Center at Houston, Houston, Texas, 77030.ORCID 0000-0002-7384-5165

Funding

Targeting Stem-Cell Dependent Drug Resistance in Human MCLR01CA181319 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCCARTY, NAMI · 2014 to 2025
$3.4M
Delineating roles for a novel tri-protein complex (TRIM44) in the multiple myeloma stem cell nicheR21CA202212 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCCARTY, NAMI · 2016 to 2017
$368k
NCI NIH HHS R01 CA181319NCI NIH HHS R21 CA202212
6 · The paper itself

Abstract

The revolutionary technology for genome editing known as the clustered regularly interspaced short palindromic repeat (CRISPR)-CRISPR-associated protein 9 (Cas9) system has sparked advancements in biological and biomedical research. The scientific breakthrough of the development of CRISPR-Cas9 technology has allowed us to recapitulate human diseases by generating animal models of interest ranging from zebrafish to non-human primates. The CRISPR-Cas9 system can also be used to delineate the mechanisms underlying the development of human disorders and to precisely correct disease-causing mutations. Repurposing this technology enables wider applications in transcriptome and epigenome manipulation and holds promise to reach the clinic. In this review, we highlight the latest advances of the CRISPR-Cas9 system in different platforms and discuss the hurdles and challenges this technology is facing. J. Cell. Biochem. 118: 4152-4162, 2017. © 2017 Wiley Periodicals, Inc.

Indexed as

CRISPR-Cas SystemsAnimalsDisease Models, AnimalGene EditingHumansTargeted Gene RepairCRISPRaCRISPR-Cas9CRISPRiDISEASE MODELSGENE CORRECTIONGENOME EDITINGIMAGING

Identifiers

PMID28467679
PMCPMC7166568

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.