Lin Meiai, Liu Ting, Zheng Yixiong, Ma Xiangyuan
Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou 515063, China.
Department of Biology, College of Science, Shantou University, Shantou 515063, China.
Biomed Opt Express. 2023 Sep 6;14(10):5048-5059. doi: 10.1364/BOE.502083. eCollection 2023 Oct 1.
We established a deep learning-based dynamic light scattering (DLS) microscopy sensing mitochondria dynamic for label-free identification of triple-negative breast cancer (TNBC) cells. The capacity of DLS microscopy to detect the intracellular motility of subcellular scatters was verified with the analysis of the autocorrelation function. We also conducted an in-depth examination of the impact of mitochondrial dynamics on DLS within TNBC cells, employing confocal fluorescent imaging to visualize the morphology of the mitochondria. Furthermore, we applied the DLS microscopy incorporating the two-stream deep learning method to differentiate the TNBC subtype and HER2 positive breast cancer subtype, with the classification accuracy achieving 0.89.
我们建立了一种基于深度学习的动态光散射（DLS）显微镜技术，用于感知线粒体动态变化，以实现对三阴性乳腺癌（TNBC）细胞的无标记识别。通过自相关函数分析，验证了DLS显微镜检测亚细胞散射体胞内运动的能力。我们还深入研究了线粒体动态变化对TNBC细胞内DLS的影响，采用共聚焦荧光成像来观察线粒体的形态。此外，我们应用结合了双流深度学习方法的DLS显微镜来区分TNBC亚型和HER2阳性乳腺癌亚型，分类准确率达到了0.89。
