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Probing Human Alzheimer's Cortical Section using Spatial Multiplexing
Alzheimer’s disease (AD) is the most common neurodegenerative disease and is characterized by the progressive decline of cognitive function. Spatial profiling of AD brain may reveal cellular…
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Spatial Metabolomics: Exploring Tumor Complexity and Therapeutic Insights
In cancer research, it is vital to understand the interaction between tumor cells and their microenvironment, as the tumor microenvironment influences tumor progression significantly. Spatial…
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Advancing Uterine Regenerative Therapies with Endometrial Organoids
Prof. Kang's group investigates important factors that determine the uterine microenvironment in which embryo insertion and pregnancy are successfully maintained. They are working to develop new…
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Lipidomics Analysis of Sparse Cells based on Laser Microdissection
Delve into cellular intricacies with high-coverage targeted lipidomics analysis of sparse cells. This advanced method, integrating Laser Microdissection (LMD) and Liquid Chromatography-Mass…
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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。
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![[Translate to chinese:] UC Enuity](/fileadmin/_processed_/e/9/csm_UC_Enuity_Detail_Header_411ca2e94e.jpg "UC Enuity")
通过自动切片改善您的超薄切片工作流程
在不断发展的电镜样品制备领域，保持领先地位至关重要。这个网络研讨会提供了关于超薄切片最新进展的重要见解，这些进展可以显著增强您实验室的能力。
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![[Translate to chinese:] AI-based cell counting performed with a phase-contrast and fluorescence image using the Mateo FL microscope.](/fileadmin/_processed_/d/9/csm_AI-based_cell_counting_performed_with_phase-contrast_and_fluorescence_image_99cddfa853.jpg "[Translate to chinese:] AI-based cell counting performed with a phase-contrast and fluorescence image using the Mateo FL microscope.")
利用AI增强的细胞计数实现精准和高效
本文描述了利用AI进行精确和高效的细胞计数。准确的细胞计数对于 2D 细胞培养的研究至关重要，例如细胞动力学、药物发现和疾病建模。精确的细胞计数对于确定细胞存活率、增殖速率和实验条件的影响至关重要。这些因素对于可靠和稳健的结果至关重要。描述了基于人工智能的方法如何显著提高细胞计数的准确性和速度，从而对细胞研究产生重大影响。
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![[Translate to chinese:] AI-based transfection analysis (left) of U2OS cells which were transfected with a fluorescently labelled protein. A fluorescence image of the cells (right) is also shown. The analysis and imaging were performed with Mateo FL.](/fileadmin/_processed_/4/c/csm_AI-based_analysis_of_U2OS_cells_transfected_with_fluorescently_labelled_protein_6c19563c6e.jpg "[Translate to chinese:] AI-based transfection analysis (left) of U2OS cells which were transfected with a fluorescently labelled protein. A fluorescence image of the cells (right) is also shown. The analysis and imaging were performed with Mateo FL.")
利用AI实现细胞转染的高效分析
本文探讨了AI（AI）在优化 2D 细胞培养研究中转染效率测量中的关键作用。对于理解细胞机制而言，精确可靠的 2D 细胞培养转染效率测量至关重要。靶向蛋白的高转染效率对于包括活细胞成像和蛋白纯化在内的实验至关重要。手动估计存在不一致性和不可靠性。借助AI的力量，可以实现高效可靠的转染研究。
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![[Translate to chinese:] Image of confluent cells taken with phase contrast (left) and analyzed for confluency using AI (right).](/fileadmin/_processed_/3/6/csm_Confluent_cells_with_phase_contrast_and_analyzed_for_confluency_using_AI_94fe9276f5.jpg "[Translate to chinese:] Image of confluent cells taken with phase contrast (left) and analyzed for confluency using AI (right).")
通过 AI 汇合度提高 2D 细胞培养的精度
本文解释了如何利用人工智能（AI）进行高效、精确的 2D 细胞培养汇合度评估。准确评估细胞培养的汇合度，即表面积覆盖的百分比，对于可靠的细胞研究至关重要。传统方法使用视觉检查或简单算法，使结果不客观和精确，尤其是对于用于药物发现、组织工程和再生医学的复杂细胞系。利用自动化图像分析和深度学习算法的方法提供更好的精度，并可以增强实验结果。
