What insights can spatiotemporal esophageal atlases and deep learning bring to engineering the esophageal mucosa?

Journal: Developmental cell
PMID: 40328228

Abstract

In this issue of Developmental Cell, Yang et al. present an integrated experimental and computational platform that maps the spatiotemporal development of the human esophagus and predicts key signaling pathways governing epithelial differentiation. Their findings enable a xeno-free, scalable strategy for generating esophageal mucosa from human pluripotent stem cells (hPSCs), demonstrating the power of combining spatial developmental data with deep learning.

Authors

  • Shuyan Wang
    Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China.
  • Nianping Liu
    Department of Genetics, Stanford University, Palo Alto, CA 94304, USA.
  • Kun Qu
    Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China. qukun@ustc.edu.cn.

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