Флуктуирующая флуоресценция одиночных центров окраски в кристаллах фторида лития

Single F2 and F3+- color centers in the LiF crystal were studied by confocal fluorescence microscopy. The time dependences of their fluorescence intensity were analyzed and statistically processed. Our studies show that, the F3+- color center, being photoexcited, is able enter the triplet state, while in ground (singlet) state it changes orientation with a frequency of 1.5 – 2 Hz at room temperature, due to reorientational diffusion, unlike the F2- center, which is reoriented only being in the triplet state. This subtype of rotational diffusion of the center does not lead to its translational diffusion.

The effects of protein crowders on small molecule drug diffusion

Crowded environments affect the pharmacokinetics of drug molecules. Here, we investigate how three macromolecular protein crowders, bovine serum albumin, hen egg-white lysozyme and myoglobin, influence the translational diffusion rates and interactions of four low molecular-weight drugs, fluorescein, doxorubicin, glycogen synthase kinase-3 inhibitor SB216763 and quinacrine. Using Fluorescence Recovery After Photo-bleaching in Line mode (Line FRAP), Brownian dynamics simulations and molecular docking, we find that the diffusive behavior of the small molecules is highly affected by self-aggregation, interactions with the proteins, and surface adhesion. Fluorescein diffusion is decreased by protein crowders due to their interactions. On the other hand, for doxorubicin, the presence of protein crowders increases diffusion by reducing surface interactions. SB216763 shows a third scenario, where BSA, but not myoglobin or lysozyme, reduces self-aggregation, resulting in faster diffusion. Quinacrine was the only small molecule whose diffusion was not affected by the presence of protein crowders. The mechanistic insights gained here into the effects of interactions of small molecules with proteins and surfaces on the translational diffusion of small molecules can assist in optimizing the design of compounds for higher mobility and lower occlusion in complex macromolecular environments.

A Lattice Model on the Rate of DNA Hybridization

We develop a lattice model on the rate of hybridization of the complementary single-stranded DNAs (c-ssDNAs). Upon translational diffusion mediated collisions, c-ssDNAs interpenetrate each other to form correct (cc), incorrect (icc) and trap-correct contacts (tcc) inside the reaction volume. Correct contacts are those with exact registry matches which leads to nucleation and zipping. Incorrect contacts are the mismatch contacts which are less stable compared to tcc which can occur in the repetitive c-ssDNAs. Although tcc possess registry match within the repeating sequences, they are incorrect contacts in the view of the whole c-ssDNAs. The nucleation rate (kN) is directly proportional to the collision rate and the average number of correct-contacts (<ncc>) formed when both the c-ssDNAs interpenetrate each other. Detailed lattice model simulations suggest that 〈n_cc 〉∝L⁄V where L is the length of c-ssDNAs and V is the reaction volume. Further numerical analysis revealed the scaling for the average radius of gyration of c-ssDNAs (Rg) with their length as R_g∝√L. Since the reaction space will be approximately a sphere with radius equals to 2Rg and V∝L^(3⁄2), one obtains k_N∝1/√L. When c-ssDNAs are nonrepetitive, then the overall renaturation rate becomes as k_R∝k_N L and one finally obtains k_R∝√L in line with the experimental observations. When c-ssDNAs are repetitive with a complexity of c, then earlier models suggested the scaling k_R∝√L/c which breaks down at c = L. This clearly suggested the existence of at least two different pathways of renaturation in case of repetitive c-ssDNAs viz. via incorrect contacts and trap correct contacts. The trap correct contacts can lead to the formation of partial duplexes which can keep the complementary strands in the close vicinity for a prolonged timescale. This is essential for the extended 1D slithering, inchworm movements and internal displacement mechanisms which can accelerate the searching for the correct contacts. Clearly, the extent of slithering dynamics will be inversely proportional to the complexity. When the complexity is close to the length of c-ssDNAs, then the pathway via incorrect contacts will dominate. When the complexity is much lesser than the length of c-ssDNA, then pathway via trap correct contacts would be the dominating one.

Dynamics of Water and Other Molecular Liquids Confined Within Voids and on Surface of Lignin Aggregates in Aging Bio Crude Oils

Neutron scattering methods were employed to study the microscopic structure and dynamics of Bio Crude Oils (BCOs) and their lignin fractions. The structure of the carbonaceous aggregates was investigated using Small Angle Neutron Scattering to reveal a fractal hierarchy as well as a growth of the aggregates as the aging of the BCO proceeds. Elastic Neutron Scattering measurements indicate that BCO liquid phase, comprised of water and other hydrogenated molecular liquids, is in a state of extreme confinement. Quasi-Elastic Neutron Scattering yields information on the molecular motions, indicating that long range translational diffusion is suppressed and only localized dynamics take place on the tens of picosecond time range. The obtained results provide quantitative information on the molecular activity, as aging proceed, in these reactive materials of relevance as potential renewable energy sources.

Solute Diffusion into Polymer Swollen by Supercritical CO2 by High-Pressure Electron Paramagnetic Resonance Spectroscopy and Chromatography

High-pressure electron paramagnetic resonance (EPR) was used to measure translational diffusion coefficients (Dtr) of a TEMPONE spin probe in poly(D,L-lactide) (PDLLA) and swollen in supercritical CO2. Dtr was measured on two scales: macroscopic scale (>1 μm), by measuring spin probe uptake by the sample; and microscopic scale (<10 nm), by using concentration-dependent spectrum broadening. Both methods yield similar translational diffusion coefficients (in the range 5–10 × 10−12 m2/s at 40–60 °C and 8–10 MPa). Swollen PDLLA was found to be homogeneous on the nanometer scale, although the TEMPONE spin probe in the polymer exhibited higher rotational mobility (τcorr = 6 × 10−11 s) than expected, based on its Dtr. To measure distribution coefficients of the solute between the swollen polymer and the supercritical medium, supercritical chromatography with sampling directly from the high-pressure vessel was used. A distinct difference between powder and bulk polymer samples was only observed at the start of the impregnation process.

Assessing the use of ellipsoidal microparticles for determining lipid membrane viscosity

The viscosity of lipid membranes sets the timescales of membrane-associated flows and therefore influences the dynamics of a wide range of cellular processes. Techniques to measure membrane viscosity remain sparse, however, and reported measurements to date, even of similar systems, give viscosity values that span orders of magnitude. To address this, we improve a method based on measuring both the rotational and translational diffusion of membrane-anchored microparticles and apply this approach and one based on tracking the motion of phase-separated lipid domains to the same system of phase-separated giant vesicles. We find good agreement between the two methods, with inferred viscosities within a factor of two of each other. Our technique uses ellipsoidal microparticles, and we show that the extraction of physically meaningful viscosity values from their motion requires consideration of their anisotropic shape. The validation of our method on phase-separated membranes makes possible its application to other systems, which we demonstrate by measuring the viscosity of bilayers composed of lipids with different chain lengths ranging from 14 to 20 carbon atoms, revealing a very weak dependence of two-dimensional viscosity on lipid size. The experimental and analysis methods described here should be generally applicable to a variety of membrane systems, both reconstituted and cellular.

A deep learning-based approach to model anomalous diffusion of membrane proteins: The case of the nicotinic acetylcholine receptor

We present a concatenated deep-learning multiple neural network system for the analysis of single-molecule trajectories. We apply this machine learning-based analysis to characterize the translational diffusion of the nicotinic acetylcholine receptor at the plasma membrane, experimentally interrogated using superresolution optical microscopy. The receptor protein displays a heterogeneous diffusion behavior that goes beyond the ensemble level, with individual trajectories exhibiting more than one diffusive state, requiring the optimization of the neural networks through a hyperparameter analysis for different numbers of steps and durations, especially for short trajectories (<50 steps) where the accuracy of the models is most sensitive to localization errors. We next use the statistical models to test for Brownian, continuous-time random walk, and fractional Brownian motion, and introduce and implement an additional, two-state model combining Brownian walks and obstructed diffusion mechanisms, enabling us to partition the two-state trajectories into segments, each of which is independently subjected to multiple analysis. The concatenated multi-network system evaluates and selects those physical models that most accurately describe the receptor’s translational diffusion. We show that the two-state Brownian-obstructed diffusion model can account for the experimentally observed anomalous diffusion (mostly subdiffusive) of the population and the heterogeneous single-molecule behavior, accurately describing the majority (72.5% to 88.7% for α-bungarotoxin-labeled receptor and between 73.5% and 90.3% for antibody-labeled molecules) of the experimentally observed trajectories, with only ∼15% of the trajectories fitting to the fractional Brownian motion model.