Journal
RESEARCH
Volume 2022, Issue -, Pages -Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.34133/2022/9784273
Keywords
-
Categories
Funding
- NSF [CBET-1803517]
- New Jersey Commission on Spinal Cord [CSCR17IRG010, CSCR22ERG023]
- NIH [5T32EB005583, R01 c1R01DC016612, 3R01DC016612-01S1, 5R01DC016612-02S1]
Ask authors/readers for more resources
A systematic investigation of stem cell-derived neural interfaces can help uncover the molecular mechanisms behind cell behavior in neurological disorders and expedite the development of stem cell-based therapies. However, the high-throughput investigation of cell-type-specific biophysical cues associated with these neural interfaces remains a significant challenge. Therefore, we developed a combinatorial nanoarray-based method that enables high-throughput investigation of neural interface micro-/nanostructures and their effects on stem cell fate decisions.
A systematic investigation of stem cell-derived neural interfaces can facilitate the discovery of the molecular mechanisms behind cell behavior in neurological disorders and accelerate the development of stem cell-based therapies. Nevertheless, high-throughput investigation of the cell-type-specific biophysical cues associated with stem cell-derived neural interfaces continues to be a significant obstacle to overcome. To this end, we developed a combinatorial nanoarray-based method for high-throughput investigation of neural interface micro-/nanostructures (physical cues comprising geometrical, topographical, and mechanical aspects) and the effects of these complex physical cues on stem cell fate decisions. Furthermore, by applying a machine learning (ML)-based analytical approach to a large number of stem cell-derived neural interfaces, we comprehensively mapped stem cell adhesion, differentiation, and proliferation, which allowed for the cell-type-specific design of biomaterials for neural interfacing, including both adult and human-induced pluripotent stem cells (hiPSCs) with varying genetic backgrounds. In short, we successfully demonstrated how an innovative combinatorial nanoarray and ML-based platform technology can aid with the rational design of stem cell-derived neural interfaces, potentially facilitating precision, and personalized tissue engineering applications.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available