Suppr超能文献

血管化微器官和肿瘤系统图像的处理与分析方法

Methods for Processing and Analyzing Images of Vascularized Micro-Organ and Tumor Systems.

作者信息

Hachey Stephanie J, Hatch Christopher J, Gaebler Daniela, Forsythe Alexander G, Ewald Makena L, Chopra Alexander L, Fang Jennifer S, Hughes Christopher C W

机构信息

University of California, Irvine, Molecular Biology and Biochemistry, Irvine, CA, USA.

University of California, Irvine, Biomedical Engineering, Irvine, CA, USA.

出版信息

bioRxiv. 2025 Mar 14:2025.03.12.642741. doi: 10.1101/2025.03.12.642741.

Abstract

Our group has developed and validated an advanced microfluidic platform to improve preclinical modeling of healthy and disease states, enabling extended culture and detailed analysis of tissue-engineered miniaturized organ constructs, or "organs-on-chips." Within this system, diverse cell types self-organize into perfused microvascular networks under dynamic flow within tissue chambers, effectively mimicking the structure and function of native tissues. This setup facilitates physiological intravascular delivery of nutrients, immune cells, and therapeutic agents, and creates a realistic microenvironment to study cellular interactions and tissue responses. Known as the vascularized micro-organ (VMO), this adaptable platform can be customized to represent various organ systems or tumors, forming a vascularized micro-tumor (VMT) for cancer studies. The VMO/VMT system closely simulates in vivo nutrient exchange and drug delivery within a 3D microenvironment, establishing a high-fidelity model for drug screening and mechanistic studies in vascular biology, cancer, and organ-specific pathologies. Furthermore, the optical transparency of the device supports high-resolution, real-time imaging of fluorescently labeled cells and molecules within the tissue construct, providing key insights into drug responses, cell interactions, and dynamic processes such as epithelial-mesenchymal transition. To manage the extensive imaging data generated, we created standardized, high-throughput workflows for image analysis. This manuscript presents our image processing and analysis pipeline, utilizing a suite of tools in Fiji/ImageJ to streamline data extraction from the VMO/VMT model, substantially reducing manual processing time. Additionally, we demonstrate how these tools can be adapted for analyzing imaging data from traditional models and microphysiological systems developed by other researchers.

摘要

我们团队开发并验证了一个先进的微流控平台,以改进健康和疾病状态的临床前建模,能够对组织工程化的微型器官构建体(即“芯片器官”)进行长期培养和详细分析。在该系统中,多种细胞类型在组织腔室内的动态流动下自组织形成灌注微血管网络,有效模拟天然组织的结构和功能。这种设置便于营养物质、免疫细胞和治疗剂进行生理性血管内递送,并创建一个逼真的微环境来研究细胞间相互作用和组织反应。这个适应性强的平台被称为血管化微器官(VMO),可以定制以代表各种器官系统或肿瘤,形成用于癌症研究的血管化微肿瘤(VMT)。VMO/VMT系统在三维微环境中紧密模拟体内营养物质交换和药物递送,为血管生物学、癌症和器官特异性病理学中的药物筛选和机制研究建立了一个高保真模型。此外,该设备的光学透明性支持对组织构建体内荧光标记的细胞和分子进行高分辨率实时成像,为药物反应、细胞相互作用以及上皮-间质转化等动态过程提供关键见解。为了管理生成的大量成像数据,我们创建了标准化的高通量图像分析工作流程。本文介绍了我们的图像处理和分析流程,利用Fiji/ImageJ中的一套工具简化从VMO/VMT模型中提取数据的过程,大幅减少人工处理时间。此外,我们还展示了如何将这些工具用于分析其他研究人员开发的传统模型和微生理系统的成像数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a725/11952417/453ad3b657ea/nihpp-2025.03.12.642741v1-f0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验