An Intermittent Model for Intracellular Motions of Gold Nanostars by k-Space Scattering Image Correlation

Adaptive optics microspectrometer for cross-correlation measurement of microfluidic flows

Mapping flows in vivo is essential for the investigation of cardiovascular pathologies in animal models. The limitation of optical-based methods, such as space-time cross correlation, is the scattering of light by the connective and fat components and the direct wave front distortion by large inhomogeneities in the tissue. Nonlinear excitation of the sample fluorescence helps us by reducing light scattering in excitation. However, there is still a limitation on the signal-background due to the wave front distortion. We develop a diffractive optical microscope based on a single spatial light modulator (SLM) with no movable parts. We combine the correction of wave front distortions to the cross-correlation analysis of the flow dynamics. We use the SLM to shine arbitrary patterns of spots on the sample, to correct their optical aberrations, to shift the aberration corrected spot array on the sample for the collection of fluorescence images, and to measure flow velocities from the cross-correlation functions computed between couples of spots. The setup and the algorithms are tested on various microfluidic devices. By applying the adaptive optics correction algorithm, it is possible to increase up to 5 times the signal-to-background ratio and to reduce approximately of the same ratio the uncertainty of the flow speed measurement. By working on grids of spots, we can correct different aberrations in different portions of the field of view, a feature that allows for anisoplanatic aberrations correction. Finally, being more efficient in the excitation, we increase the accuracy of the speed measurement by employing a larger number of spots in the grid despite the fact that the two-photon excitation efficiency scales as the fourth power of this number: we achieve a twofold decrease of the uncertainty and a threefold increase of the accuracy in the evaluation of the flow speed.

Out of the Randomness: Correlating Noise in Biological Systems

The study of the dynamics of biological systems requires one to follow relaxation processes in time with micron-size spatial resolution. This need has led to the development of different fluorescence correlation techniques with high spatial resolution and a tremendous (from nanoseconds to seconds) temporal dynamic range. Spatiotemporal information can be obtained even on complex dynamic processes whose time evolution is not forecast by simple Brownian diffusion. Our discussion of the most recent applications of image correlation spectroscopy to the study of anomalous sub- or superdiffusion suggests that this field still requires the development of multidimensional image analyses based on analytical models or numerical simulations. We focus in particular on the framework of spatiotemporal image correlation spectroscopy and examine the critical steps in getting information on anomalous diffusive processes from the correlation maps. We point out how a dual space-time correlative analysis, in both the direct and the Fourier space, can provide quantitative information on superdiffusional processes when these are analyzed through an empirical model based on intermittent active dynamics. We believe that this dual space-time analysis, potentially amenable to mathematical treatment and to the exact fit of experimental data, could be extended to include the rich phenomenology of subdiffusive processes, thereby quantifying relevant parameters for the various motivating biological problems of interest.

Spatiotemporal image correlation analysis of blood flow in branched vessel networks of zebrafish embryos

Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20  μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.

Development of an image Mean Square Displacement (iMSD)-based method as a novel approach to study the intracellular trafficking of nanoparticles

Fluorescence microscopy and spectroscopy techniques are commonly used to investigate complex and interacting biological systems (e.g. proteins and nanoparticles in living cells), since these techniques can explore intracellular dynamics with high time resolution at the nanoscale. Here we extended one of the Image Correlation Spectroscopy (ICS) methods, i.e. the image Mean Square Displacement, in order to study 2-dimensional diffusive and flow motion in confined systems, whose driving speed is uniformly distributed in a variable angular range. Although these conditions are not deeply investigated in the current literature, they can be commonly found in the intracellular trafficking of nanocarriers, which diffuse in the cytoplasm and/or may move along the cytoskeleton in different directions. The proposed approach could reveal the underlying system's symmetry using methods derived from fluorescence correlation concepts and could recover dynamic and geometric features which are commonly done by single particle analyses. Furthermore, it improves the characterization of low-speed flow motions, when compared to SpatioTemporal Image Correlation Spectroscopy (STICS). Although we present a specific example (lipoplexes in living cells), the emphasis is in the discussion of the method, its basic assumptions and its validation on numeric simulations.

STATEMENT OF SIGNIFICANCE

Recent advances in nanoparticle-based drug and gene delivery systems have pointed out the interactions at cellular and subcellular levels as key-factors for the efficiency of the adopted biomaterials. Such biochemical and biophysical interactions drive and affect the intracellular dynamics, that is commonly characterized by means of fluorescence microscopy and spectroscopy techniques. Here we present a novel Image Correlation Spectroscopy (ICS) method as a promising tool to capture the intracellular behavior of nanoparticles with high resolution and low background's sensitivity. This study overcomes some of the approximations adopted so far, by decoupling the flow terms of the investigated dynamics and thus recovering ensemble's information from specific single particle behaviors. Finally, relevant implications for nanoparticle-based drug delivery are shown.

Effective-medium approximation for lattice random walks with long-range jumps

We consider the random walk on a lattice with random transition rates and arbitrarily long-range jumps. We employ Bruggeman's effective-medium approximation (EMA) to find the disorder-averaged (coarse-grained) dynamics. The EMA procedure replaces the disordered system with a cleverly guessed reference system in a self-consistent manner. We give necessary conditions on the reference system and discuss possible physical mechanisms of anomalous diffusion. In the case of a power-law scaling between transition rates and distance, lattice variants of Lévy-flights emerge as the effective medium, and the problem is solved analytically, bearing the effective anomalous diffusivity. Finally, we discuss several example distributions and demonstrate very good agreement with numerical simulations.