类有机物
祖细胞
计算生物学
支气管肺泡灌洗
生物
细胞生物学
仿形(计算机编程)
病理
计算机科学
肺
干细胞
医学
内科学
操作系统
作者
Yan Yu,Zexin Chen,Bin Zheng,Min Huang,Junlang Li,Gang Li
摘要
Abstract The bronchoalveolar organoid (BAO) model is increasingly acknowledged as an ex‐vivo platform that accurately emulates the structural and functional attributes of proximal airway tissue. The transition from bronchoalveolar progenitor cells to alveolar organoids is a common event during the generation of BAOs. However, there is a pressing need for comprehensive analysis to elucidate the molecular distinctions characterizing the pre‐differentiated and post‐differentiated states within BAO models. This study established a murine BAO model and subsequently triggered its differentiation. Thereafter, a suite of multidimensional analytical procedures was employed, including the morphological recognition and examination of organoids utilizing an established artificial intelligence (AI) image tracking system, quantification of cellular composition, proteomic profiling and immunoblots of selected proteins. Our investigation yielded a detailed evaluation of the morphologic, cellular, and molecular variances demarcating the pre‐ and post‐differentiation phases of the BAO model. We also identified of a potential molecular signature reflective of the observed morphological transformations. The integration of cutting‐edge AI‐driven image analysis with traditional cellular and molecular investigative methods has illuminated key features of this nascent model.
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