Results 211 to 220 of about 1,438,323 (398)

In Vitro Differentiation of Size‐Sieved Stem Cells into Electrically Active Neural Cells [PDF]

, 2002
Shih‐Chieh Hung, Henrich Cheng, Chien‐Yuan Pan, Yun‐Li Ma, Lung‐Sen Kao, Hsiao‐Li Ma   +5 more
openalex   +1 more source

Recent Advances in Stimuli‐Responsive Materials and Soft Robotic Actuators for Bioelectronic Medicine

Advanced Materials, EarlyView.
This review explores the integration of responsive materials and soft robotic actuators with implantable electronics to address key challenges in bioelectronic medicine. By enabling shape actuation, these technologies improve deployment, adaptability, and accuracy in minimally invasive procedures.
Chaoqun Dong, George G. Malliaras
wiley   +1 more source

Microarray analysis of selected genes in neural stem and progenitor cells [PDF]

, 2002
Yongquan Luo, Jingli Cai, Ying Liu, Haipeng Xue, Francis J. Chrest, Robert P. Wersto, Mahendra S. Rao   +6 more
openalex   +1 more source

Cardiac Organoid Model Inspired Micro‐Robot Smart Patch to Treat Myocardial Infarction

Advanced Materials, EarlyView.
The heart organoid model exhibits the acidic microenvironment characteristic of myocardial infarction, which emerges as a pivotal force propelling the movement of micro‐robots. These micro‐robots, administered through microneedles, can penetrate deep into the tissue, effectively delivering therapeutic payloads to facilitate heart repair.
Fangfang Wang, Zilu Xu, Feiyang Zheng, Dongcheng Yang, Kaige Xu, Ming Ke, Xiao Zhou, Xiaohan Zhang, Ju Tan, Yong Liu, Yansha Hao, Malcolm Xing, Chuhong Zhu   +12 more
wiley   +1 more source

A computational scheme connecting gene regulatory network dynamics with heterogeneous stem cell regeneration [PDF]

arXiv
Stem cell regeneration is a vital biological process in self-renewing tissues, governing development and tissue homeostasis. Gene regulatory network dynamics are pivotal in controlling stem cell regeneration and cell type transitions. However, integrating the quantitative dynamics of gene regulatory networks at the single-cell level with stem cell ...
arxiv  

Fast‐Charging Solid‐State Li Batteries: Materials, Strategies, and Prospects

Advanced Materials, EarlyView.
This review addresses challenges and recent advances in fast‐charging solid‐state batteries, focusing on solid electrolyte and electrode materials, as well as interfacial chemistries. The role of multiscale modeling and simulation in understanding Li+ transport and interfacial phenomena is emphasized, providing insights into materials, strategies, and ...
Jing Yu, Yuhao Wang, Longyun Shen, Jiapeng Liu, Zilong Wang, Shengjun Xu, Ho Mei Law, Francesco Ciucci   +7 more
wiley   +1 more source

Direct Neural Fate Specification from Embryonic Stem Cells

, 2001
Vincent Tropepe, Seiji Hitoshi, Christian Sirard, Tak W. Mak, Janet Rossant, Derek van der Kooy   +5 more
openalex   +1 more source

Protein‐Like Polymers Targeting Keap1/Nrf2 as Therapeutics for Myocardial Infarction

Advanced Materials, EarlyView.
We describe a Keap1 targeting protein‐like polymer (PLP) which activates Nrf2, an important cytoprotective transcription factor for relieving myocardial infarction‐induced oxidative stress. This PLP increases cell survival in vitro in multiple relevant cardiac cell types and elicits pro‐reparative responses, improving cardiac function in a preclinical ...
Joshua M. Mesfin, Kendal P. Carrow, Alexander Chen, Madeline P. Hopps, JoJo J. Holm, Quincy P. Lyons, Michael B. Nguyen, Jervaughn D. Hunter, Assa Magassa, Elyse G. Wong, Kate Reimold, Sriya N. Paleti, Emily Gardner, Matthew P. Thompson, Colin G. Luo, Xiaoyu Zhang, Karen L. Christman, Nathan C. Gianneschi   +17 more
wiley   +1 more source

Properties of a Fetal Multipotent Neural Stem Cell (NEP Cell)

, 2002
Jingli Cai, Yuanyuan Wu, Takumi Mirua, Jeanne L. Pierce, Mary T. Lucero, Kurt H. Albertine, Gerald J. Spangrude, Mahendra S. Rao   +7 more
openalex   +2 more sources

FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking [PDF]

arXiv
This paper presents FlowCyt, the first comprehensive benchmark for multi-class single-cell classification in flow cytometry data. The dataset comprises bone marrow samples from 30 patients, with each cell characterized by twelve markers. Ground truth labels identify five hematological cell types: T lymphocytes, B lymphocytes, Monocytes, Mast cells, and
arxiv