Tongji University Nature publication: A deep learning-based neural stem cell differentiation fate prediction system

Neural stem cells (NSCs) have the potential for self-renewal and tri-lineage differentiation.

Professor Cheng Liming and Professor Zhu Rongrong from the Key Laboratory of Regeneration and Repair of Spinal Cord Injury of the Ministry of Education, Tongji Hospital Affiliated to Tongji University, published an online publication titled "Deep learning-based predictive identification of" in the internationally renowned academic journal "Nature Communications" Neural stem cell differentiation" research paper, the paper was selected as the editor's recommendation article in the journal "stem cells" (Editors' Highlights in'Stem cells)

This study constructed a NSCs differentiation fate prediction system based on high-throughput flow cytometry single-cell imaging technology, and verified its predictive effect on the fate of NSCs under the action of inducers of different forms and different mechanisms of action

The results show that the prediction system established by the research has high prediction accuracy in different differentiation days and differentiation directions of NSCs, and can accurately predict the future differentiation of cells after a short time processing of factors/small molecules/nanomaterials using flow cytometric single cell brightfield images Among them, the shortest directions of neurons, astrocytes and oligodendrocytes only take 1 day, 12 hours, and 1 day, respectively.

Zhu Yanjing of the affiliated Tongji Hospital and Huang Ruiqi, a doctoral student of the School of Medicine, are the co-first authors of the paper, and Professor Cheng Liming and Professor Zhu Rongrong are the co-corresponding authors

Link to the paper: https://