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Biasing the Hierarchy Motifs of Nanotoroids: from 1D Nanotubes to 2D Porous Networks.

ABSTRACT: Hierarchical organization of self-assembled structures into superstructures is omnipresent in Nature but has been rarely achieved in synthetic molecular assembly due to the absence of clear structural rules. We herein report on the self-assembly of scissor-shaped azobenzene dyads which form discrete nanotoroids that further organize into 2D porous networks. The steric demand of the peripheral aliphatic units diminishes the trend of the azobenzene dyad to constitute stackable nanotoroids in solution, thus affording isolated (unstackable) nanotoroids upon cooling. Upon drying, these nanotoroids organize at graphite surface to form well-defined 2D porous networks. The photoirradiation with UV and visible light enabled reversible dissociation and reconstruction of nanotoroids through the efficient trans↔cis isomerization of azobenzene moieties in solution.

SUBMITTER: Valera JS

PROVIDER: S-EPMC9299728 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Biasing the Hierarchy Motifs of Nanotoroids: from 1D Nanotubes to 2D Porous Networks.

Valera Jorge S JS Arima Hironari H Naranjo Cristina C Saito Takuho T Suda Natsuki N Gómez Rafael R Yagai Shiki S Sánchez Luis L

Angewandte Chemie (International ed. in English) 20211215 5

Hierarchical organization of self-assembled structures into superstructures is omnipresent in Nature but has been rarely achieved in synthetic molecular assembly due to the absence of clear structural rules. We herein report on the self-assembly of scissor-shaped azobenzene dyads which form discrete nanotoroids that further organize into 2D porous networks. The steric demand of the peripheral aliphatic units diminishes the trend of the azobenzene dyad to constitute stackable nanotoroids in solut ...[more]

PMID: 34822210

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Project description:Understanding how cells migrate in fibrous environments is important in wound healing, immune function, and cancer progression. A key question is how fiber orientation and network geometry influence cell movement. Here we describe a quantitative, modeling-based approach toward identifying the mechanisms by which cells migrate in fibrous geometries having well controlled orientation. Specifically, U251 glioblastoma cells were seeded onto non-electrospinning Spinneret based tunable engineering parameters fiber substrates that consist of networks of suspended 400 nm diameter nanofibers. Cells were classified based on the local fiber geometry and cell migration dynamics observed by light microscopy. Cells were found in three distinct geometries: adhering two a single fiber, adhering to two parallel fibers, and adhering to a network of orthogonal fibers. Cells adhering to a single fiber or two parallel fibers can only move in one dimension along the fiber axis, whereas cells on a network of orthogonal fibers can move in two dimensions. We found that cells move faster and more persistently in 1D geometries than in 2D, with cell migration being faster on parallel fibers than on single fibers. To explain these behaviors mechanistically, we simulated cell migration in the three different geometries using a motor-clutch based model for cell traction forces. Using nearly identical parameter sets for each of the three cases, we found that the simulated cells naturally replicated the reduced migration in 2D relative to 1D geometries. In addition, the modestly faster 1D migration on parallel fibers relative to single fibers was captured using a correspondingly modest increase in the number of clutches to reflect increased surface area of adhesion on parallel fibers. Overall, the integrated modeling and experimental analysis shows that cell migration in response to varying fibrous geometries can be explained by a simple mechanical readout of geometry via a motor-clutch mechanism.

Dataset Information

Biasing the Hierarchy Motifs of Nanotoroids: from 1D Nanotubes to 2D Porous Networks.

Publications

Biasing the Hierarchy Motifs of Nanotoroids: from 1D Nanotubes to 2D Porous Networks.

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