Evidence map›Paper›PMID 24838150›Full record

ReviewImmunologic research2014

Skin deep: from dermal fibroblasts to pancreatic beta cells.

Gohar S Manzar, Eun-Mi Kim, Pavana Rotti, Nicholas Zavazava

Abstract readReview
PubMed Publisher
In one paragraph

Review in Immunologic research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 28% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 1 country.

Gohar S ManzarDivision of Immunology, Department of Internal Medicine, University of Iowa Hospitals and Clinics, C429-1 GH, 200 Hawkins Dr., Iowa City, IA, 52242, USA.
Eun-Mi Kim
Pavana Rotti
Nicholas Zavazava
University of Iowa Hospitals and Clinics · USVeterans Health Administration · US

Funding

EMBRYONIC STEM CELLS INDUCE SPECIFIC GRAFT TOLERANCER01HL073015 · NHLBI · UNIVERSITY OF IOWA · PI ZAVAZAVA, NICHOLAS · 2004 to 2012
$2.5M
NHLBI NIH HHS 5R01HL073015-08
6 · The paper itself

Abstract

Type I diabetes (T1D) is a chronic autoimmune disease caused by pancreatic β-cell destruction induced by autoantibodies and autoreactive T cells. After significant reduction of the β-cell mass, diabetes sets in and can cause significant complications. It is estimated that more than 3 million Americans have T1D, and its prevalence among young individuals is progressively rising; however, the reasons for this increase are not known. Islet transplantation is recognized as the ultimate cure for T1D, but unfortunately, the severe scarcity of available islets makes it necessary to establish alternative sources of β-cells. Our lab seeks to establish human-induced pluripotent stem cells as an unlimited, novel source of insulin-producing cells (IPCs) that are patient-specific, obviating the requirement for immunosuppression. Although several reports have emerged demonstrating successful derivation of IPCs from human pluripotent stem cells, the efficiencies of derivation are inadequate and these IPCs do not respond to glucose stimulation in vitro. We reasoned that the use of a growth factor sequestering bioscaffold and promotion of cell-cell signaling through 3D clustering would enhance the generation of functionally superior IPCs compared to those derived by 2D differentiation. Here, we discuss a novel 3D platform for the generation of highly efficient human IPCs.

Indexed as

AnimalsDermisDiabetes Mellitus, Type 1FibroblastsGlucoseHumansInduced Pluripotent Stem CellsInsulin-Secreting CellsPortraits as TopicSweetening AgentsGlucoseSweetening Agents

Identifiers

PMID24838150
OpenAlexW2153975581

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.