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使用珠子作为聚焦基准以辅助基于软件的显微镜自动聚焦精度。

Using Beads as a Focus Fiduciary to Aid Software-Based Autofocus Accuracy in Microscopy.

作者信息

Gibson Isabel, Osterlund Elizabeth Julie, Truant Ray

机构信息

Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, ON, Canada.

出版信息

Bio Protoc. 2025 Jul 20;15(14):e5388. doi: 10.21769/BioProtoc.5388.

Abstract

Brightfield microscopy is an ideal application for studying live cell systems in a minimally invasive manner. This is advantageous in long-term experiments to study dynamic cellular processes such as stress response. Depending on the sample type and preparation, the inherent qualities of brightfield microscopy, being very low contrast, can contribute to technical issues such as focal drift, sequencing lags, and complete failure of software autofocus systems. Here, we describe the use of microbeads as a focus aid for long-term live cell imaging to address these autofocus issues. This protocol is inexpensive to implement, without extensive additional sample preparation, and can be used to capture focused images of transparent cells in a label-free manner. To validate this protocol, a widefield inverted microscope was used with software-based autofocus to image overnight in time-lapse format, demonstrating the use of the beads to prevent focal drift in long-term experiments. This improves autofocus accuracy on relatively inexpensive microscopes without using hardware-based focus aids. To validate this protocol, the KNIME logistics software was used to train a random forest model to perform binary image classification. Key features • Label-free live cell imaging in time-lapse format. • Troubleshooting software autofocus for brightfield mode.

摘要

明场显微镜检查是以微创方式研究活细胞系统的理想应用。这在研究动态细胞过程(如应激反应)的长期实验中具有优势。根据样品类型和制备情况,明场显微镜检查固有的对比度很低的特性,可能会导致诸如焦点漂移、测序滞后以及软件自动对焦系统完全失效等技术问题。在此,我们描述了使用微珠作为长期活细胞成像的焦点辅助工具来解决这些自动对焦问题。该方案实施成本低廉,无需进行大量额外的样品制备,并且可用于以无标记方式捕获透明细胞的聚焦图像。为验证该方案,使用配备基于软件自动对焦功能的宽场倒置显微镜以延时格式进行过夜成像,展示了使用微珠在长期实验中防止焦点漂移。这提高了相对廉价显微镜的自动对焦准确性,而无需使用基于硬件的焦点辅助工具。为验证该方案,使用KNIME物流软件训练随机森林模型以进行二元图像分类。关键特性• 以延时格式进行无标记活细胞成像。• 解决明场模式下软件自动对焦的问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a047/12304461/e74f68d2dd59/BioProtoc-15-14-5388-g001.jpg

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