Research On The Technology Of Data Collection And Data Processing Of Spectral Flow Cytometer

In the field of cell biology research,flow cytometry can quickly and accurately measure and analyze a single biological particle,but the multi-parameter measurement method of traditional flow cytometry will be interfered by fluorescence leakage,and mass spectrometry flow cytometry will cause cells to be unrecoverable damage.To solve this problem,spectral flow cytometry was proposed.Although the resolution has been improved,the requirements for the quantum efficiency and noise of the detector are more stringent.Based on this,this paper develops a data acquisition system for spectral flow cytometry with high sensitivity,low dark noise,and high frame rate.Use PCA and t-SNE-based clustering optimization algorithm to process the data to realize the identification and classification of mixed cell spectra.Build a set of spectral flow cytometer data acquisition system and write supporting visualization software.The system includes:mechanical structure,control circuit and computer software.In the mechanical structure part,a two-stage refrigeration structure and a sealed cavity environment with a heat pipe fan for heat dissipation are constructed to realize a closed environment with a constant temperature of-10℃;the control circuit part adopts an embedded chip ARM with a programmable logic device FPGA,ARM is mainly responsible for the data communication function,FPGA is responsible for outputting the drive timing to drive the CCD to work;the computer software part,the main functions include parameter adjustment and real-time control of the CCD,complete the data reading of the acquisition board and the fluorescence spectrum data visualization.After the system has been functionally tested,the dark current collection experiment is carried out.The experiment results show the effectiveness and stability of the constant temperature refrigeration module in suppressing dark current;the spectrum collection experiment is carried out on the standard neon-argon light source,and the experiment results show the reliability of the static spectrum collection of the system;A CCD high-speed signal acquisition method is proposed,which uses a very short clearing period to ensure that the acquisition system will not miss sub-millisecond high-speed signals.With the liquid flow system and the optical system,the spectrum collection experiment was performed on the single-particle nano-scale standard fluorescent microspheres within the sub-millisecond integration time.The experimental results show that the system can effectively collect high-speed signals;PCA and t-SNE were used to reduce the dimensionality of the spectral data of cyanobacteria cells,clustering by K-means,and optimized with the principle of normal distribution 2σ.The experimental results show that the clustering optimization algorithm proposed in this paper can accurately classify the fluorescence spectra of mixed cells.