Bioinspired Anisotropic Collagen-Based Conductive Hydrogels Promote Neuronal Differentiation via Activation of Mechanoelectrical Signaling.
Аннотация
Simulating the anisotropic structure and electromechanical signals of the natural neural extracellular matrix (ECM) is crucial for advancing neural regeneration and constructing in vitro research models. Herein, a three-dimensional collagen-based conductive hydrogel with oriented fibers was constructed by controlling the intrinsic assembly behavior of collagen by combining mechanical pre-deformation with magnetic-driven stretching during gelation. The anisotropic hydrogel exhibited excellent cell compatibility and could guide the orientation and extension of PC-12 cell axons along the fibers. Moreover, under mild electrical stimulation, the oriented collagen network incorporating gelatin-modified carbon nanotubes could significantly promote the acquisition of a neuron-like phenotype of PC-12 cells, as evidenced by upregulating neuron-associated proteins (Tuj1 and MAP-2) and genes. The effect was not only attributed to the external stimuli but also the anisotropic conductive matrix, which facilitates efficient signal transmission. In addition, both immunofluorescent staining, qRT-PCR, and western blot analysis further confirmed that the oriented conductive matrix could activate calcium channels, promote Ca2+ influx, and activate a mechanotransduction cascade involving the integrin-FAK signaling and Yes-associated protein (YAP) nuclear accumulation. Consequently, by utilizing the synergistic effects of aligned topologies, mechanical signals, and electrical stimuli to guide neuronal differentiation, we demonstrated the critical role of matrix microstructure in neuronal formation, as well as provided a platform for directing neural differentiation in vitro.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.