Leica Microsystems: 显微镜科学与教学知识中心

显微镜科学与教学知识中心

徕卡显微系统的知识库提供有关显微镜学科的科学研究和教学材料。内容旨在对显微镜初学者、有经验的显微镜操作实践者和使用显微镜的科学家在他们的日常工作和实验有所帮助。这里有探索交互式教程和应用笔记，你可以找到你需要的显微镜的基础知识以及前沿技术——快来加入徕卡显微知识社区，分享您的专业知识！

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.

Designing the Future with Stem Cell and RNA Technology

Visionary biotech start-up Uncommon Bio is tackling one of the world’s biggest health challenges: food sustainability. In this webinar, Stem Cell Scientist Samuel East will show how they use RNA…

Pancreatic Ductal Adenocarcinoma with 11 Aerobic Glycolysis/Warburg Effect biomarkers shown – BCAT, Glut1, HK2, HTR2B, LDHA, NaKATPase, PCAD, PCK26, PKM2, SMA1, and Vimentin.

Dive into Pancreatic Cancer Research with the Big Data Viewer

Pancreatic cancer, with a mortality rate near 40%, is challenging to treat due to its proximity to major organs. This story explores the complex biology of pancreatic ductal adenocarcinoma (PDAC),…

Colon adenocarcinoma and normal colon at the tumor margin. 13 biomarkers shown including Cadherin, CD3, CD4, CD8, CD20, CD31, CD45, Collagen, Caspase 9, BCL2, Beta-Catenin, Vimentin, and Smooth Muscle Actin.

Uncover the Hidden Complexity of Colon Cancer with the Big Data Viewer

Colorectal cancer poses a significant health burden. While surgery is effective initially, some patients develop recurrent secondary disease with poor prognosis, necessitating advanced therapies like…

Cell DIVE multiplexed image of FFPE tissue section from syngeneic murine cancer model, 4T1.

Mapping Tumor Immune Landscape with AI-Powered Spatial Proteomics

Spatial mapping of untreated tumors provides an overview of the tumor immune architecture, useful for understanding therapeutic responses. Immunocompetent murine models are essential for identifying…

Automated Laser Microdissection for Proteome Analysis

组织中的精密空间蛋白质组学信息

尽管可使用基于成像和质谱的方法进行空间蛋白质组学研究，但是图像与单细胞分辨率蛋白丰度测量值的关联仍然是个巨大的挑战。最近引入的一种方法，深层视觉蛋白质组学（DVP），将细胞表型的人工智能图像分析与自动化的单细胞或单核激光显微切割及超高灵敏度的质谱分析结合在了一起。DVP在保留空间背景的同时，将蛋白丰度与复杂的细胞或亚细胞表型关联在一起。

[Translate to chinese:] Multiplexed Cell DIVE imaging of Adult Human Alzheimer’s brain tissue section demonstrating expression of markers specific to astrocytes (GFAP, S100B), microglia (TMEM119, IBA1), AD-associated markers (p-Tau217, β-amyloid) and immune cells such as CD11b+, CD163+, CD4+, and HLA-DRA+, clustered around the β-amyloid plaques.

Spatial Analysis of Neuroimmune Interactions in Alzheimer’s Disease

Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by neurofibrillary tangles, β-amyloid plaques, and neuroinflammation. These dysfunctions trigger or are exacerbated by…

Pancreatic Ductal Adenocarcinoma imaged with Cell DIVE. Analysis done by Aivia.

A Guide to Spatial Biology

What is spatial biology, and how can researchers leverage its tools to meet the growing demands of biological questions in the post-omics era? This article provides a brief overview of spatial biology…

[Translate to chinese:] Multiplexed Cell DIVE imaging to characterize the spatial landscape in Human Alzheimer’s Cortical Tissue

使用空间多重化探测人类阿尔茨海默病皮层切片

阿尔茨海默病（AD）是最常见的神经退行性疾病，其特征是认知功能的逐渐下降。对 AD 大脑的空间分析可能揭示细胞关系，从而促进对疾病病因的更好理解。本研究捕捉了 AD 皮层组织成分的全球概述，并强调了 Cell DIVE 成像的简化工作流程，从数据采集到使用 Aivia 软件的基于人工智能的分析，最终实现更快的洞察。

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。