Evidence map›Paper›PMID 28632820›Full record

ReviewThe review of diabetic studies : RDS2017

The Nexus of Stem Cell-Derived Beta-Cells and Genome Engineering.

Sara D Sackett, Aida Rodriguez, Jon S Odorico

Open access · diamondAbstract readReview
In one paragraph

Review in The review of diabetic studies : RDS, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 11 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.

Sara D SackettDivision of Transplantation, Department of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI 53711, USA.
Aida RodriguezDivision of Transplantation, Department of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI 53711, USA.
Jon S OdoricoDivision of Transplantation, Department of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI 53711, USA.
University of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes, type 1 and type 2 (T1D and T2D), are diseases of epidemic proportions, which are complicated and defined by genetics, epigenetics, environment, and lifestyle choices. Current therapies consist of whole pancreas or islet transplantation. However, these approaches require life-time immunosuppression, and are compounded by the paucity of available donors. Pluripotent stem cells have advanced research in the fields of stem cell biology, drug development, disease modeling, and regenerative medicine, and importantly allows for the interrogation of therapeutic interventions. Recent developments in beta-cell differentiation and genomic modifications are now propelling investigations into the mechanisms behind beta-cell failure and autoimmunity, and offer new strategies for reducing the propensity for immunogenicity. This review discusses the derivation of endocrine lineage cells from human pluripotent stem cells for the treatment of diabetes, and how the editing or manipulation of their genomes can transcend many of the remaining challenges of stem cell technologies, leading to superior transplantation and diabetes drug discovery platforms.

Indexed as

AnimalsCell DifferentiationDiabetes Mellitus, Type 1Genetic EngineeringGenome, HumanGenomicsHumansInduced Pluripotent Stem CellsInsulin-Secreting CellsPluripotent Stem Cells

Identifiers

PMID28632820
PMCPMC6115001
OpenAlexW2646431921

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.