Lung cancer is a malignant tumor with the highest morbidity and mortality rate. Early screening and treatment are crucial in effectively reducing lung cancer mortality. This study presents a novel label-free bioanalysis system integrating fiber optic sensing and two-dimensional (2D) scattering imaging technologies, offering real-time, high-efficiency detection capabilities. The cladding on the fiber surface, followed by immobilization of specific antibodies. Variations in the evanescent wave field at the fiber surface induce changes in the transmission intensity, enabling highly sensitive, realtime detection of target biomolecules. Simultaneously, the light beam transmitted through the fiber optic excites individual biological cells in the fluid chamber, while a micro-optical system captures their 2D light scattering patterns, enabling precise cell identification and classification. The integration of these two technologies allows the sensor system to perform visualized single-cell identification and classification, as well as efficient biomarker detection at the molecular level. Compared to traditional single-technology approaches, this innovative system offers significant advantages in sensitivity, specificity, and detection speed, opening new pathways for bioanalysis. It demonstrates broad application potential in areas such as label-free ion detection and cell classification, particularly in early tumor screening.
Lymphoma has become one of the most prevalent malignant tumors in China, with a significant rise in incidence among young people in recent years. Early diagnosis and treatment are therefore crucial for improving patient outcomes, including efficacy, survival, and quality of life. In this study, we developed a multimodal detection system that combines twodimensional (2D) light scattering and electrochemical techniques to differentiate between normal and tumor cells at the single-cell and molecular level. Using a laser microscopy detection system, we capture 2D light scattering images of individual cells, where the lymphocytes display distinctive patch-like patterns. The texture of these patterns is influenced by the internal cellular structures, and the differentiation of normal and tumor cells is achieved by extracting and analyzing the eigenvalues from the light scattering images. Additionally, electrochemical sensors detect hydrogen peroxide levels in the cellular solution by measuring changes in current, with tumor cells producing a greater current variation than normal cells. A support vector machine (SVM) algorithm was employed to distinguish between normal and tumor cells, achieving an accuracy of 88%. The results demonstrate that the multimodal detection system effectively differentiates normal and tumor cells from both physical and chemical perspectives, enhancing detection accuracy. This system offers a nondestructive, efficient, and cost-effective method for early cancer screening.
Lymphomas encompass Hodgkin lymphoma and non-Hodgkin lymphoma. In this study, we have developed a static cytometry leveraging laser and microscope technology to capture 2D light scattering patterns of individual cells. Within this method, a single lymphoma cell is positioned in a liquid-based chip and vertically stimulated by a 532 nm green laser. The resulting light scattering pattern of the cell is observed and recorded by a COMS detector through a microscope optical system, covering a polar angle range of 75 to 105 degrees. By extracting and analyzing the characteristic values from these scattering patterns, we can achieve lymphoma cell identification. In this study, we successfully differentiated between HDLM-2 and Daudi cells using the SVM algorithm, achieving a classification accuracy of 88%. This outcome underscores the potential of our 2D light scattering static cytometry for lymphoma cell classification, offering a marker-free, cost-effective approach for early cancer screening at the single-cell level.
Efficient detection of cell clusters is of paramount importance in the production and packaging processes of single-cell suspensions, as it can significantly impact cell density uniformity, induce apoptosis, and compromise the accuracy of cell sorting outcomes. This study introduces a novel, high-throughput and label-free method for monitoring cell clusters, leveraging light scattering imaging and microfluidic technologies. Two-dimensional (2D) light scattering, as a vital label free analytical approach, proves effective in detecting and analyzing biological particles with intricate structures. Through optical microscopy coupled with a high-speed camera, this study examines the 2D light scattering patterns produced by cell clusters, facilitating the discrimination between single cells and clustered cells. This label-free methodology offers distinct advantages over traditional labeling techniques, as it preserves cellular integrity without invasive disruptions. Furthermore, innovative microfluidic chip design enables continuous real-time monitoring of cell clusters, empowering rapid and high-throughput detection. Experimental validation involved monitoring silicon oxide (SiO2) microsphere suspensions, demonstrating the method's capacity for high-throughput and high-sensitivity cell cluster monitoring. This research presents a promising tool for efficiently handling and monitoring the production of single-cell suspensions, with potential applications in various fields of cell biology and biotechnology.
Two dimensional (2D) light scattering technology is an important part of the single cell analysis, which can recognize the differences of inherent physical properties of biological particles. Based on the label-free static cytometry, collimated light from a laser with a wavelength of 532 nm is coupled into a multimode optical fiber. The fiber localizes and illuminates single static biological particles. Single particles are excited and their scattered light is collected. In this paper, the 2D light scattering patterns are obtained from 4 μm and 6 μm polystyrene microspheres (PS, refractive index, 1.59) and silica microspheres (SiO2, refractive index, 1.45). The corresponding simulated scattering patterns are obtained by Mie scattering theory. Then, Fourier analysis of the 2D scattering patterns is performed for measuring the refractive index of single particles. The results indicate that the 2D light scattering technique may provide an efficient, low-cost, and easy-to-use approach to the nondestructive identification and classification of cancer cells at the single cell level.
We have recently developed a 2D light scattering static cytometer for cellular analysis in a label-free manner, which measures side scatter (SSC) light in the polar angular range from 79 to 101 degrees. Compared with conventional flow cytometry, our cytometric technique requires no fluorescent labeling of the cells, and static cytometry measurements can be performed without flow control. In this paper we present an improved label-free static cytometer that can obtain 2D light scattering patterns in a wider angular range. By illuminating the static microspheres on chip with a scanning optical fiber, wide-angle 2D light scattering patterns of single standard microspheres with a mean diameter of 3.87 μm are obtained. The 2D patterns of 3.87 μm microspheres contain both large-angle forward scatter (FSC) and SSC light in the polar angular range from 40 to 100 degrees, approximately. Experimental 2D patterns of 3.87 μm microspheres are in good agreement with Mie theory simulated ones. The wide-angle light scattering measurements may provide a better resolution for particle analysis as compared with the SSC measurements. Two dimensional light scattering patterns of HL-60 human acute leukemia cells are obtained by using our static cytometer. Compared with SSC 2D light scattering patterns, wide-angle 2D patterns contain richer information of the HL-60 cells. The obtaining of 2D light scattering patterns in a wide angular range could help to enhance the capabilities of our label-free static cytometry for cell analysis.
Cytometry has wide applications in biomedicine for cell differentiation or disease monitoring. Here we report our newly developed two dimensional (2D) light scattering static cytometric technique for single and multiple cell analysis. The static cytometer adopts a scanning fiber probe for cell excitation and obtains 2D light scattering patterns on a complementary metal oxide semiconductor (CMOS) detector. Our results show that experimental 2D light scattering patterns obtained from single yeast cells are with fringe structure while those from multiple yeast cells give speckle patterns. The experimental results compare favorably with our 2D light scattering Mie theory simulations for both single and multiple cells. The varying of 2D light scattering patterns with different yeast cell clusters, either number or distribution changes, shows the potential of our 2D light scattering static cytometer for cellular diagnostics.
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