MONTE CARLO SIMULATION OF FLUORESCENCE CORRELATION SPECTROSCOPY DATA

被引:3
|
作者
Kosovan, Peter [1 ]
Uhlik, Filip [1 ]
Kuldova, Jitka [1 ]
Stepanek, Miroslav [1 ]
Limpouchova, Zuzana [1 ]
Prochazka, Karel [1 ]
Benda, Ales [2 ]
Humpolickova, Jana [2 ]
Hof, Martin [2 ]
机构
[1] Charles Univ Prague, Fac Sci, Dept Phys & Macromol Chem, Prague 12843 2, Czech Republic
[2] Acad Sci Czech Republic, J Heyrovsky Inst Phys Chem, VVI, Prague 8, Czech Republic
关键词
Diffusion coefficient; Dynamic light scattering; Fluorescence spectroscopy; Monte Carlo method; Rotational diffusion; Translational diffusion; ATOMIC-FORCE MICROSCOPY; LIGHT-SCATTERING; BEHAVIOR; MICELLES; BINDING;
D O I
10.1135/cccc2009526
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
We employed the Monte Carlo simulation methodology to emulate the diffusion of fluorescently labeled particles and understand the source of differences between values of diffusion coefficients (and consequently hydrodynamic radii) of fluorescently labeled nanoparticles measured by fluorescence correlation spectroscopy (FCS) and dynamic light scattering (DLS). We used the simulation program developed in our laboratory and studied the diffusion of spherical particles of different sizes, which are labeled on their surface. In this study, we focused on two complicating effects: (i) multiple labeling and (ii) rotational diffusion which affect the fluorescence signal from large particles and hinder the analysis of autocorrelation functions according to simple analytical models. We have shown that the fluorescence fluctuations can be well fitted using the analytical model for small point-like particles, but the obtained parameters deviate in some cases significantly from the real ones. It means that the current data treatment yields apparent values of diffusion coefficients and other parameters only and the interpretation of experimental results for systems of particles with sizes comparable to the size of the active illuminated volume requires great care and precaution.
引用
收藏
页码:207 / 222
页数:16
相关论文
共 50 条
  • [31] Monte Carlo simulation of particle detector data stream
    Beretta, M.
    Biassoni, M.
    Gironi, L.
    Maino, M.
    Nastasi, M.
    Pagnanini, L.
    Pozzi, S.
    EUROPEAN PHYSICAL JOURNAL PLUS, 2021, 136 (01):
  • [32] Assessing the reliability of diffuse correlation spectroscopy models on noise-free analytical Monte Carlo data
    Binzoni, Tiziano
    Martelli, Fabrizio
    APPLIED OPTICS, 2015, 54 (17) : 5320 - 5326
  • [33] Spreadsheet data resampling for Monte-Carlo simulation
    Leong, Thin Yin
    Lee, Wee Leong
    SPREADSHEETS IN EDUCATION, 2008, 3 (01): : 70 - 78
  • [34] Monte Carlo fluorescence ray tracing simulation for laser cooling of solids
    Tanaka, Hiroki
    Pueschel, Stefan
    OPTICS EXPRESS, 2024, 32 (02) : 2306 - 2320
  • [35] Monte Carlo simulation of secondary fluorescence in small particles and at phase boundaries
    Llovet, X
    Valovirta, E
    Heikinheimo, E
    MIKROCHIMICA ACTA, 2000, 132 (2-4) : 205 - 212
  • [36] Monte Carlo Simulation of Secondary Fluorescence in Small Particles and at Phase Boundaries
    Xavier Llovet
    Eero Valovirta
    Erkki Heikinheimo
    Microchimica Acta, 2000, 132 (2-4) : 205 - 212
  • [37] Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation
    Churmakov, DY
    Meglinski, IV
    Piletsky, SA
    Greenhalgh, DA
    JOURNAL OF PHYSICS D-APPLIED PHYSICS, 2003, 36 (14) : 1722 - 1728
  • [38] Monte Carlo simulations of the diffuse correlation spectroscopy signals for bounded biomodels
    Kuzmin, Vladimir
    Valkov, Alexey
    Zubkov, Leonid
    2018 INTERNATIONAL CONFERENCE LASER OPTICS (ICLO 2018), 2018, : 483 - 483
  • [39] Monte Carlo fluorescence microtomography
    Cong, Alexander X.
    Hofmann, Matthias C.
    Cong, Wenxiang
    Xu, Yong
    Wang, Ge
    JOURNAL OF BIOMEDICAL OPTICS, 2011, 16 (07)
  • [40] SIMULATION BY MONTE CARLO
    REED, R
    TAPPI, 1966, 49 (01): : 28 - &