Webinars

空间组学新技术与新方法网络研讨会

China • Webinar

Trichomonas parasite in mouse gut, rOTO Embedding and serial sections for array tomography imaging. Sample courtesy Isabelle Guerin-Bonne, Low Kay En, Electron Microscopy Unit, Yong loo Lin School of Medicine, National University of Singapore

Integrated Serial Sectioning and Cryo-EM Workflows for 3D Biological Imaging

This on-demand webinar explores how integrated tools can support electron microscopy workflows from sample preparation to image analysis. Experts Andreia Pinto, Adrian Boey, and Hoyin Lai present the…

3D high-plex imaging in cancer immunology. Overview of a pancreatic tumor section in mouse model, labeled with 15 markers and imaged in one go using STELLARIS with SpectraPlex. (https://www.nature.com/articles/d42473-024-00260-7)

How to Streamline High-Plex Imaging for 3D Spatial Omics Advances

In this webinar, Dr. Julia Roberti and Dr. Luis Alvarez from Leica Microsystems introduce SpectraPlex, a new functionality integrated into the STELLARIS confocal platform for high-plex 3D spatial…

Large volume computational clearing processed Thunder image of human pancreatic islet organoid. Cells segmented using Segment By Example tool, automatically phenotyped, and color-coded based on phenotypes in Aivia. Image courtesy of the Matthias von Herrath Lab, La Jolla Institute of Immunology, La Jolla, CA.

利用人工智能图像分析工具更快、更轻松地获得洞察力

了解 Aivia 如何通过快速设置、准确的人工智能检测和简便的批量处理功能，帮助科学家简化图像分析。

Transfection using the Uncommon Bio reprogramming system. Image acquired using the THUNDER Imager 3D Cell Culture with THUNDER Large Volume Computational Clearing (LVCC) applied. Image courtesy of Samuel East, Uncommon Bio.

利用新型可扩展的干细胞培养设计未来

具有远见卓识的生物技术初创企业 Uncommon Bio 正在应对世界上最大的健康挑战之一：食品可持续性。在这次网络研讨会上，干细胞科学家塞缪尔-伊斯特（Samuel East）将展示他们如何使细胞农业的干细胞培养基既安全又经济可行。了解他们如何将培养基成本降低 1000 倍，并开发出不含动物成分、食品安全的 iPSC 培养基。

Dapi – Nucleus, GFP – Plasma Membrane, Thickness 100µm, 63x objektive, 469 Z planes, 2 channels, THUNDER Imager 3D Cell Culture. Courtesy M.Sc. Dana Krauß, Medical University of Vienna (Austria).

您的 3D 类器官成像和分析工作流程效率如何？

类器官模型已经改变了生命科学研究，但优化图像分析协议仍然是一个关键挑战。本次网络研讨会探讨了类器官研究的简化工作流程，首先是实时的三维细胞培养检查，接下来是高速、高分辨率的三维成像，生成清晰的图像和更纯净的数据，以便对生长速率、细胞迁移和三维细胞相互作用等参数进行准确地人工智能分割和量化，从而实现更深入的洞察。

2D slice of colon cancer tissue stained with 30 markers and imaged using the Cell DIVE system. Analysis performed using Aivia 13’s new multiplex cell detection recipe and automatic clustering tool. Each phenotype denoted in a different color.

基于 AI 引导的多重二维数据向空间洞察的转化

Aivia 13 能够处理大型二维图像，使研究人员能够通过检测数百万个对象和自动聚类多达 30 个标记物，深入理解其表型周围的微环境。