Melanoma, developing from melanocytes, is the deadliest type of malignant skin tumors in the world. Due to high light absorption of melanin, rare circulating melanoma cells, as an endogenous marker for metastasis at the early stage, can be quantitatively detected in small superficial vessels of mouse ears by in vivo photoacoustic flow cytometry (PAFC). Before clinical application, the capability of promising PAFC platform should be verified and optimized by mouse vessels, which are similar in size and depth to human vessels. In the current study, compared with optical resolution PAFC (OR-PAFC), we build acoustic resolution PAFC (AR-PAFC) using focused ultrasonic transducer and 1064 nm laser with lower pulse rate, leading to higher detection depth and lower laser power density in mouse models. Besides, based on laser frequency doubling and high absorption coefficient of hemoglobin at 532nm wavelength, the blood vessels can be positioned by lowcost navigation system rather than the expensive system of two coupled lasers or charged coupled device with depth limitation. We confirm that AR-PAFC can be applied to noninvasive label-free counting of circulating melanoma cells in mouse tail veins, and validated by in vitro assays using phantom models, which simulates the scattering and absorption coefficients of living tissue. These results show that AR-PAFC platform has great potential for preoperative diagnosis and postoperative evaluation of melanoma patients.
Melanoma is a malignant tumor whose circulating tumor cell (CTC) count has been shown as a prognostic marker for metastasis development. Therefore detection of circulating melanoma cells plays an important role in monitoring tumor metastasis and prevention after diagnosis. In Vivo Photoacoustic Flow Cytometry (PAFC) is established here to achieve in vivo melanoma inspection, meanwhile guarantees non-invasive and real-time detection.Accurate tumor cell detection is of great significance to achieve highly specific diagnosis and avoid unnecessary medical tests.However, the amount of data detected by PAFC is large and original photoacoustic signal is mixed with various noises.The traditional triple mean square deviation method has lower accuracy and consumes a lot of time in data processing. Here, a classification approach in photoacoustic is proposed, which could discriminate signals and noises based on features extracted from photoacoustic waves compared to normal cells using Support Vector Machines algorithm. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we finally choose the continuity, amplitude, and photoacoustic waveform pulse width as the features to characterize the signal.More than 600,000 samples were selected as the training set (normalized in advance), and a classifier with a precision of 85% accuracy to filter out the photoacoustic signals rapidly was trained by the support vector machine method.The classifier introduced here has proved to optimize the signal acquisition and reduce signal processing time, realizing real-time detection and real-time analysis in PAFC.
Alzheimer's disease (AD) is a chronic neurodegenerative disease. It is generally believed that there are some connections between AD and amyloid protein plaques in the brain. The typical symptoms of AD are memory and spatial learning difficulties, language disorders, loss of motivation and behavioral issues. Currently, the main therapeutic method is pharmacotherapy, which temporarily relieves symptoms, and yet brings with some side effects. Near infrared (NIR) light therapy has been studied in a range of single and multiple irradiation protocols in previous studies and was found beneficial for neuropathology. In our research, we demonstrated the effect of NIR light on AD through transgenic mouse model. We designed an experimental apparatus consisted of a box with a LED array emitting NIR light inside. After the treatment, we assessed the effects of infrared light by testing cognitive performance of mice in Morris water maze, and detecting plaque load by immunofluorescence analysis. Our results show that NIR therapy is able to attenuate the Aβ burden and cognitive deficits in the mouse model. It might provide a novel and safe way to treat AD.
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