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Engineering human renal epithelial cells for transplantation in regenerative medicine

Overview of attention for article published in Medical Engineering & Physics, April 2017
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Article details
Title
Engineering human renal epithelial cells for transplantation in regenerative medicine
Published in
Medical Engineering & Physics, April 2017
DOI 10.1016/j.medengphy.2017.03.009
Pubmed ID
Authors
Abstract

Cellular transplantation may treat several human diseases by replacing damaged cells and/or providing a local source of trophic factors promoting regeneration. We utilized human renal epithelial cells (hRECs) isolated from cadaveric donors as a cell model. For efficacious implementation of hRECs for treatment of kidney diseases, we evaluated a novel encapsulation strategy for immunoisolation of hRECs and lentiviral transduction of the Green Fluorescent Protein (GFP) as model gene for genetic engineering of hRECs to secrete desired trophic factors. In specific, we determined whether encapsulation through conformal coating and/or GFP transduction of hRECs allowed preservation of cell viability and of their trophic factor secretion. To that end, we optimized cultures of hRECs and showed that aggregation in three-dimensional spheroids significantly preserved cell viability, proliferation, and trophic factor secretion. We also showed that both wild type and GFP-engineered hRECs could be efficiently encapsulated within conformal hydrogel coatings through our fluid dynamic platform and that this resulted in further improvement of cell viability and trophic factors secretion. Our findings may lay the groundwork for future therapeutics based on transplantation of genetically engineered human primary cells for treatment of diseases affecting kidneys and potentially other tissues.

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Mendeley demographics

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 10 33%
Student > Master 4 13%
Researcher 4 13%
Student > Doctoral Student 3 10%
Student > Ph. D. Student 3 10%
Other 5 17%
Unknown 1 3%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 7 23%
Biochemistry, Genetics and Molecular Biology 4 13%
Agricultural and Biological Sciences 4 13%
Pharmacology, Toxicology and Pharmaceutical Science 3 10%
Neuroscience 3 10%
Other 6 20%
Unknown 3 10%