Method for effectively removing mononuclear cell interference in automatic analysis of lymphocyte subpopulation

Abstract

The invention discloses a method for effectively removing mononuclear cell interference in lymphocyte subpopulation automatic analysis. The method comprises the following steps of determining fluorescence intensity of CD3 through CD3, SSC-A, CD45, a density-based clustering algorithm and a nuclear density estimation algorithm, identifying T lymphocytes, determining two-dimensional distribution areas of the lymphocytes on the CD45 and the SSC-A and corresponding position parameters, respectively fitting density curves of cells distributed on CD45 and SS in combination with a nuclear density estimation algorithm, determining density curve thresholds of monocytes and lymphocytes distributed on SS and quantiles of CD45 distribution of T lymphocytes, fitting distribution of lymphocyte T cells on CD4 by utilizing nuclear density estimation, and determining CD4 non-expression and weak expression thresholds; and on the basis of determining the thresholds, performing cell grouping on the multi-dimensional data of SSC-A, CD4, CD45, CD16 and CD19, and distinguishing non-T lymphocytes and monocytes according to the thresholds of SSC-A, CD45 and CD4. According to the method, noise interference can be effectively removed.

Description

technical field [0001] The invention relates to a method for removing monocyte interference. In particular, it relates to a method for effectively removing mononuclear cell interference in the automatic analysis of lymphocyte subsets. Background technique [0002] In flow cytometry, the sample cells to be tested are transported through the liquid flow system to form a single-cell flow. In the laser irradiation area, the fluorescent dyes marked on the cells are excited by the laser to generate fluorescent signals. In different experimental systems, according to the different fluoresceins labeled by cells, different wavelengths of fluorescence are emitted under excitation of different wavelengths, and these fluorescent signals can reflect different biological characteristics of cells. The components of cells can be quantitatively measured by photometry, and various information about different components can be obtained for the same cell, which can be used as the basis for ide...

AI Technical Summary

Problems solved by technology

[0003] In the identification of lymphocyte subsets with 6-color antibody combination, the existing automatic and manual analysis of lymphocyte subsets cannot accurately separate monocytes and lymphocytes

[0004] In the absence of CD45-FIFC / CD14-PE as reverse gating for lymphocytes, the existing artificial cell subpopulation analysis is to gate lymph by SSC / CD45, due to the lack of monocyte-specific CD14 fluorescence Marking, in the lymphatic hilum, cannot identify the mixed monocytes; the instrument simulates manual analysis, which reduces subjective errors caused by personal preference or other factors, but does not perfect the isolation of monocytes

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