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Regulated Behavior in Living Cells with Highly Aligned Configurations on Nanowrinkled Graphene Oxide Substrates: Deep Learning Based on Interplay of Cellular Contact Guidance.
Park, Rowoon; Kang, Moon Sung; Heo, Gyeonghwa; Shin, Yong Cheol; Han, Dong-Wook; Hong, Suck Won.
Afiliación
  • Park R; Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
  • Kang MS; Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
  • Heo G; Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
  • Shin YC; Department of Inflammation and Immunity, Lerner Research Institute, Cleveland Clinic, Ohio 44195, United States.
  • Han DW; Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
  • Hong SW; Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
ACS Nano ; 18(2): 1325-1344, 2024 Jan 16.
Article en En | MEDLINE | ID: mdl-38099607
ABSTRACT
Micro-/nanotopographical cues have emerged as a practical and promising strategy for controlling cell fate and reprogramming, which play a key role as biophysical regulators in diverse cellular processes and behaviors. Extracellular biophysical factors can trigger intracellular physiological signaling via mechanotransduction and promote cellular responses such as cell adhesion, migration, proliferation, gene/protein expression, and differentiation. Here, we engineered a highly ordered nanowrinkled graphene oxide (GO) surface via the mechanical deformation of an ultrathin GO film on an elastomeric substrate to observe specific cellular responses based on surface-mediated topographical cues. The ultrathin GO film on the uniaxially prestrained elastomeric substrate through self-assembly and subsequent compressive force produced GO nanowrinkles with periodic amplitude. To examine the acute cellular behaviors on the GO-based cell interface with nanostructured arrays of wrinkles, we cultured L929 fibroblasts and HT22 hippocampal neuronal cells. As a result, our developed cell-culture substrate obviously provided a directional guidance effect. In addition, based on the observed results, we adapted a deep learning (DL)-based data processing technique to precisely interpret the cell behaviors on the nanowrinkled GO surfaces. According to the learning/transfer learning protocol of the DL network, we detected cell boundaries, elongation, and orientation and quantitatively evaluated cell velocity, traveling distance, displacement, and orientation. The presented experimental results have intriguing implications such that the nanotopographical microenvironment could engineer the living cells' morphological polarization to assemble them into useful tissue chips consisting of multiple cell types.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Mecanotransducción Celular / Aprendizaje Profundo / Grafito Idioma: En Revista: ACS Nano Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Mecanotransducción Celular / Aprendizaje Profundo / Grafito Idioma: En Revista: ACS Nano Año: 2024 Tipo del documento: Article
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