Title |
Mechanics-guided embryonic patterning of neuroectoderm tissue from human pluripotent stem cells
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Published in |
Nature Materials, May 2018
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DOI | 10.1038/s41563-018-0082-9 |
Pubmed ID | |
Authors |
Xufeng Xue, Yubing Sun, Agnes M. Resto-Irizarry, Ye Yuan, Koh Meng Aw Yong, Yi Zheng, Shinuo Weng, Yue Shao, Yimin Chai, Lorenz Studer, Jianping Fu |
Abstract |
Classic embryological studies have successfully applied genetics and cell biology principles to understand embryonic development. However, it remains unresolved how mechanics, as an integral driver of development, is involved in controlling tissue-scale cell fate patterning. Here we report a micropatterned human pluripotent stem (hPS)-cell-based neuroectoderm developmental model, in which pre-patterned geometrical confinement induces emergent patterning of neuroepithelial and neural plate border cells, mimicking neuroectoderm regionalization during early neurulation in vivo. In this hPS-cell-based neuroectoderm patterning model, two tissue-scale morphogenetic signals-cell shape and cytoskeletal contractile force-instruct neuroepithelial/neural plate border patterning via BMP-SMAD signalling. We further show that ectopic mechanical activation and exogenous BMP signalling modulation are sufficient to perturb neuroepithelial/neural plate border patterning. This study provides a useful microengineered, hPS-cell-based model with which to understand the biomechanical principles that guide neuroectoderm patterning and hence to study neural development and disease. |
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France | 1 | 3% |
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Demographic breakdown
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Scientists | 16 | 40% |
Science communicators (journalists, bloggers, editors) | 2 | 5% |
Practitioners (doctors, other healthcare professionals) | 2 | 5% |
Mendeley readers
Geographical breakdown
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Unknown | 289 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 64 | 22% |
Researcher | 53 | 18% |
Student > Master | 29 | 10% |
Student > Doctoral Student | 24 | 8% |
Student > Bachelor | 22 | 8% |
Other | 42 | 15% |
Unknown | 55 | 19% |
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Engineering | 37 | 13% |
Agricultural and Biological Sciences | 30 | 10% |
Materials Science | 19 | 7% |
Neuroscience | 14 | 5% |
Other | 41 | 14% |
Unknown | 72 | 25% |