Cancer remains a significant global medical challenge, and the selection of effective treatment modalities is crucial for an optimistic prognosis. Photothermal therapy, being non-invasive and targeted, holds immense potential for future therapeutic developments. Due to their high biocompatibility, carbon nano-onions particles are frequently employed as photothermal materials. The investigation of the dynamic three-dimensional distribution of these nanoparticles within cancer cells is imperative for constructing an accurate photothermal conversion model. In this research, we employed digital holographic tomography to monitor the temporal changes in the three-dimensional distribution of onion-like carbon nanoparticles within colorectal cancer cells. We reconstructed the three-dimensional refractive index distribution of carbon nano-onions particles within cancer cells at different time points. Further, we quantified two morphological parameters, surface area and volume, of these nanoparticles within cancer cells and performed preliminary analysis of their temporal evolution. This methodology introduces a novel perspective to study the interaction between Carbon nano-onions particles and cancer cells, enhancing our understanding of the photothermal therapy mechanism.
Recently, advanced flow cytometry analysis technology based on digital holography has been extensively studied, which can meet various challenges in clinical diagnosis. Especially in liquid biopsy, it has incomparable advantages. Urothelial Holographic Flow Cytometry (HFC) microscopy can provide rich intracellular information by changing the cell’s intrinsic properties with label-free and high throughput. Carcinoma (UC) is the second most common malignancy in men. Urine cytology detection is the most convenient early cancer screening method for UC patients. Here, we developed HFC to identify the cancer cells in urine. Holographic microfluidic imaging was performed to obtain the phase images of different cells in simulation urine, including red blood cells, white blood cells, epithelial cells, and a small number of cancer cells. This study demonstrates that HFC can achieve high accuracy, high throughput, and label-free cancer cell identification in the urine.
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