rus
Issue #7-8/2021
I.V.Yaminskiy, A.I.Akhmetova
3D-image construction, processing and analysis in biomedical scanning probe microscopy
3D-image construction, processing and analysis in biomedical scanning probe microscopy
DOI: 10.22184/1993-8578.2021.14.7-8.430.433
The scanning probe microscopy is becoming an important and informative tool in biomedicine and medical diagnostics due to the development of efficient data processing algorithms. The software allows measuring sizes, volumes, object areas, contour lengths, angles of crystal structures, surface roughness, form factor, friction and elasticity coefficients, and adhesion values. The data on the imaging of bacterial and cellular structures and the results of their subsequent quantitative description are presented in this paper.
The scanning probe microscopy is becoming an important and informative tool in biomedicine and medical diagnostics due to the development of efficient data processing algorithms. The software allows measuring sizes, volumes, object areas, contour lengths, angles of crystal structures, surface roughness, form factor, friction and elasticity coefficients, and adhesion values. The data on the imaging of bacterial and cellular structures and the results of their subsequent quantitative description are presented in this paper.
Теги: adhesion bacterial and cell structures form factor scanning robe microscope адгезия бактериальные и клеточные структуры сканирующая зондовая микроскопия
INTRODUCTION
In modern biomedical scanning probe microscopy (SPM), construction, processing and analysis of data is the important, challenging and time-consuming task. Viruses, bacteria, cells, living matter and other biological samples are complex objects that require solicitude at all phases of sample preparation, measurement, quantification, results reporting, presentations, papers and other illustrative material. For this reason, the software, with all its necessary features, must have a rich, user-friendly and intuitive interface iso that these data can be effectively used in solving problems of biomedical diagnostics.
3D-IMAGES ANALYSIS AND PROCESSING
When imaging biological objects using atomic force microscopy (AFM), e.g., such as Escherichia coli bacteria (see Fig.1), a large amount of quantitative data like size, volume, area, contour length, roughness, form factor, friction and elasticity coefficients, and adhesion value can be obtained in addition to 3D-imaging [1]. Similar multifactorial information can be received when studying viruses, blood cells (see Fig.2), neuronal networks and various tissues of living organisms. Measurements can be carried out both in liquid and in air, which also gives an estimated degree of shrinkage that biological objects undergo as a result of drying and dehydration.
During the measurements, a histogram can be plotted according to the size of the particles. For example, when measuring viral particles the size scattering is not always related to the measurement error, which is not more than several nanometres, but represents the real size variation of the particles formed during cell infection [2].
The modern 3D-imaging capabilities of biomedical microscopy can easily be demonstrated using FemtoScan Online software [4].
We have recently shown an example, using atomic force microscopy (AFM) data on protein nanoparticles, that a neural network algorithm [5] provides more accurate results for finding nanoparticles whose size is comparable to the noise level.
In biomedical microscopy measurements are made on live bacteria and cells in the natural environment. The initial stage of cell infection is of particular interest. In [6] the receptor layer on the cell surface was visualized in the process of virus binding in the first milliseconds of virus-cell contact with high resolution (<50 nm). In the forse spectroscopy mode AFM shows interaction of individual peptides, proteins and living cells [7].
CONCLUSIONS
Force curves analysis provides data on the mechanical properties of the biological sample concerning adhesion, rigidity, deformation, elastic modulus and energy dissipation. The cantilever modification allows detecting specific biochemical interactions [8].
Thus, biomedical scanning probe microscopy remains a useful tool in research, perfectly complementing the alternative measurement methods and providing researchers with unique information.
ACKNOWLEDGEMENTS
The study was completed with the financial support of the RFBR and the London Royal Society No. 21-58-10005, and RFBR, Project No. 20-32-90036. This research was carried out with financial support from the FASIE, Project No. 71108, and Agreement No. 0071108. ■
Declaration of Competing Interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
In modern biomedical scanning probe microscopy (SPM), construction, processing and analysis of data is the important, challenging and time-consuming task. Viruses, bacteria, cells, living matter and other biological samples are complex objects that require solicitude at all phases of sample preparation, measurement, quantification, results reporting, presentations, papers and other illustrative material. For this reason, the software, with all its necessary features, must have a rich, user-friendly and intuitive interface iso that these data can be effectively used in solving problems of biomedical diagnostics.
3D-IMAGES ANALYSIS AND PROCESSING
When imaging biological objects using atomic force microscopy (AFM), e.g., such as Escherichia coli bacteria (see Fig.1), a large amount of quantitative data like size, volume, area, contour length, roughness, form factor, friction and elasticity coefficients, and adhesion value can be obtained in addition to 3D-imaging [1]. Similar multifactorial information can be received when studying viruses, blood cells (see Fig.2), neuronal networks and various tissues of living organisms. Measurements can be carried out both in liquid and in air, which also gives an estimated degree of shrinkage that biological objects undergo as a result of drying and dehydration.
During the measurements, a histogram can be plotted according to the size of the particles. For example, when measuring viral particles the size scattering is not always related to the measurement error, which is not more than several nanometres, but represents the real size variation of the particles formed during cell infection [2].
The modern 3D-imaging capabilities of biomedical microscopy can easily be demonstrated using FemtoScan Online software [4].
We have recently shown an example, using atomic force microscopy (AFM) data on protein nanoparticles, that a neural network algorithm [5] provides more accurate results for finding nanoparticles whose size is comparable to the noise level.
In biomedical microscopy measurements are made on live bacteria and cells in the natural environment. The initial stage of cell infection is of particular interest. In [6] the receptor layer on the cell surface was visualized in the process of virus binding in the first milliseconds of virus-cell contact with high resolution (<50 nm). In the forse spectroscopy mode AFM shows interaction of individual peptides, proteins and living cells [7].
CONCLUSIONS
Force curves analysis provides data on the mechanical properties of the biological sample concerning adhesion, rigidity, deformation, elastic modulus and energy dissipation. The cantilever modification allows detecting specific biochemical interactions [8].
Thus, biomedical scanning probe microscopy remains a useful tool in research, perfectly complementing the alternative measurement methods and providing researchers with unique information.
ACKNOWLEDGEMENTS
The study was completed with the financial support of the RFBR and the London Royal Society No. 21-58-10005, and RFBR, Project No. 20-32-90036. This research was carried out with financial support from the FASIE, Project No. 71108, and Agreement No. 0071108. ■
Declaration of Competing Interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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