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Evolution of Telencephalon Anterior-Posterior Patterning through Core Endogenous Network Bifurcation.
Sun, Chen; Yao, Mengchao; Xiong, Ruiqi; Su, Yang; Zhu, Binglin; Chen, Yong-Cong; Ao, Ping.
Afiliação
  • Sun C; Center for Quantitative Life Sciences & Physics Department, Shanghai University, Shanghai 200444, China.
  • Yao M; Center for Quantitative Life Sciences & Physics Department, Shanghai University, Shanghai 200444, China.
  • Xiong R; Center for Quantitative Life Sciences & Physics Department, Shanghai University, Shanghai 200444, China.
  • Su Y; Center for Quantitative Life Sciences & Physics Department, Shanghai University, Shanghai 200444, China.
  • Zhu B; Center for Quantitative Life Sciences & Physics Department, Shanghai University, Shanghai 200444, China.
  • Chen YC; Center for Quantitative Life Sciences & Physics Department, Shanghai University, Shanghai 200444, China.
  • Ao P; School of Biomedical Engineering, Sichuan University, Chengdu 610065, China.
Entropy (Basel) ; 26(8)2024 Jul 26.
Article em En | MEDLINE | ID: mdl-39202101
ABSTRACT
How did the complex structure of the telencephalon evolve? Existing explanations are based on phenomena and lack a first-principles account. The Darwinian dynamics and endogenous network theory-established decades ago-provides a mathematical and theoretical framework and a general constitutive structure for theory-experiment coupling for answering this question from a first-principles perspective. By revisiting a gene network that explains the anterior-posterior patterning of the vertebrate telencephalon, we found that upon increasing the cooperative effect within this network, fixed points gradually evolve, accompanied by the occurrence of two bifurcations. The dynamic behavior of this network is informed by the knowledge obtained from experiments on telencephalic evolution. Our work provides a quantitative explanation for how telencephalon anterior-posterior patterning evolved from the pre-vertebrate chordate to the vertebrate and provides a series of verifiable predictions from a first-principles perspective.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China