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Optical tweezers are ideal tools for cell manipulation in vivo due to their non-contact trapping ability. In the current studies, the optical trapping of cells can only be achieved in light-permeable organs. It is important to expand the application of optical tweezers to opaque tissues and organs, where biological activities are the primary focus of biomedical research. However, the optical manipulation of cells in these opaque organs cannot be imaged using a conventional transillumination microscope due to the opacity of these organs. Here, we use optical tweezers to trap erythrocytes and measure the cell deformability in mouse liver, which are imaged with oblique back-illumination microscopy (OBM). In the microscope system, two fibers are fixed at the same oblique angle on both sides of the microscopic objective, illuminating the trapping target asymmetrically. The dual-wavelength OBM strategy allows for obtaining a differential phase contrast image in a single-shot by color channel separation. The OBM can image the flowing and trapped erythrocytes in vivo in real-time. Furthermore, the erythrocyte deformability in vivo is evaluated with optical tweezers. The spring stiffness in vivo is 8.2 ± 2.1 μN m−1, which is obtained by stretching the trapped cells with blood drag flow. Our works make it possible to utilize optical tweezers to study the live cell dynamics in opaque organs, which will expand the application of optical tweezers in the fields of biomechanical studies. [ABSTRACT FROM AUTHOR]

The study of circulating cells in the blood stream is critical, as it covers many fields of biomedicine, including immunology, cell biology, oncology, and reproductive medicine. In-vivo flow cytometry (IVFC) is a new tool to monitor and count cells in real time for long durations in their native biological environment. This review describes two main categories of IVFC, i.e., labeled and label-free IVFC. It focuses on label-free IVFC and introduces its technological development and related biological applications. Because cell recognition is the basis of flow cytometry counting, this review also describes various methods for the classification of unlabeled cells, including the latest machine learning-based technologies. [ABSTRACT FROM AUTHOR]

Objective: Visualizing cell interactions in blood circulation is of great importance in studies of anticancer immunotherapy or drugs. However, the lack of a suitable imaging system hampers progress in this field. Methods: In this work, we built a dual-channel in vivo imaging flow cytometer to visualize the interactions of circulating tumor cells (CTCs) and dendritic cells (DCs) simultaneously in the bloodstream. Two artificial neural networks were trained to identify blood vessels and cells in the acquired images. Results and Conclusion: Using this technique, single CTCs and CTC clusters were readily distinguished by their morphology. Interactions of CTCs and DCs were identified, while their moving velocities were analyzed. The CTC-DC clusters moved at a slower velocity than that of single CTCs or DCs. This may provide new insights into tumor metastasis and blood rheology. Significance: This in vivo imaging flow cytometry system holds great potential for assessing the efficiency of targeting CTCs with anticancer immune cells or drugs. [ABSTRACT FROM AUTHOR]