scholarly journals Deconstructing Retinal Organoids: Single Cell RNA-Seq Reveals the Cellular Components of Human Pluripotent Stem Cell-Derived Retina

Stem Cells ◽  
2019 ◽  
Vol 37 (5) ◽  
pp. 593-598 ◽  
Author(s):  
Joseph Collin ◽  
Rachel Queen ◽  
Darin Zerti ◽  
Birthe Dorgau ◽  
Rafiqul Hussain ◽  
...  
Author(s):  
Chia-Lung Wu ◽  
Amanda Dicks ◽  
Nancy Steward ◽  
Ruhang Tang ◽  
Dakota B Katz ◽  
...  

Stem Cells ◽  
2017 ◽  
Vol 36 (3) ◽  
pp. 313-324 ◽  
Author(s):  
M. Joseph Phillips ◽  
Peng Jiang ◽  
Sara Howden ◽  
Patrick Barney ◽  
Jee Min ◽  
...  

2015 ◽  
Vol 112 (40) ◽  
pp. 12516-12521 ◽  
Author(s):  
Michael P. Schwartz ◽  
Zhonggang Hou ◽  
Nicholas E. Propson ◽  
Jue Zhang ◽  
Collin J. Engstrom ◽  
...  

Human pluripotent stem cell-based in vitro models that reflect human physiology have the potential to reduce the number of drug failures in clinical trials and offer a cost-effective approach for assessing chemical safety. Here, human embryonic stem (ES) cell-derived neural progenitor cells, endothelial cells, mesenchymal stem cells, and microglia/macrophage precursors were combined on chemically defined polyethylene glycol hydrogels and cultured in serum-free medium to model cellular interactions within the developing brain. The precursors self-assembled into 3D neural constructs with diverse neuronal and glial populations, interconnected vascular networks, and ramified microglia. Replicate constructs were reproducible by RNA sequencing (RNA-Seq) and expressed neurogenesis, vasculature development, and microglia genes. Linear support vector machines were used to construct a predictive model from RNA-Seq data for 240 neural constructs treated with 34 toxic and 26 nontoxic chemicals. The predictive model was evaluated using two standard hold-out testing methods: a nearly unbiased leave-one-out cross-validation for the 60 training compounds and an unbiased blinded trial using a single hold-out set of 10 additional chemicals. The linear support vector produced an estimate for future data of 0.91 in the cross-validation experiment and correctly classified 9 of 10 chemicals in the blinded trial.


2021 ◽  
Vol 16 (10) ◽  
pp. 2548-2564
Author(s):  
Thomas Allison ◽  
Justin Langerman ◽  
Shan Sabri ◽  
Marcos Otero-Garcia ◽  
Andrew Lund ◽  
...  

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