Fluorescence anisotropy decay study of self-association of bacterial luciferase intermediates

The fluorescence dynamics parameters of the fluorescent transient flavin-luciferase species from the typesVibrio fischeri andPhotobacterium leiognathi are presented. The fluorescence anisotropy decay is a single exponential function for both types. The correlation time is 70 ns for theP. leiognathi fluorescent transient intermediate (2°C, aqueous buffer, pH 7.0), consistent with the rotational correlation time of the luciferase macromolecule (77 kD) to which the flavin fluorophore is rigidly attached. In contrast, for theV. fischeri species the observed correlation time for the anisotropy decay function is 133 ns. This suggests that protein self-association occurs in theV. fischeri case and this is confirmed by filtration, where the fluorescent transient fromV. fischeri does not pass through a 100,000 molecular weight cutoff membrane, whereas theP. leiognathi species does. The filtration method also demonstrates self-association in the luciferase peroxyflavin and photoflavin fromV. fischeri. A monomer-dimer equilibrium also explains the previously reported high correlation times for theV. harveyi luciferase-flavin species. It is proposed that the self-association competes with the lumazine protein interaction in the bioluminescence reaction.     

TEM Imaging of Mass-selected Polymer Molecules

Polyethylene glycol (PEG) molecules with masses below 1300amu are electrosprayed (ES) from solution, mobility-selected at high resolution in a differential mobility analyzer (DMA), collected on a grid and imaged by transmission electron microscopy (ES–DMA–TEM). The DMA resolves individual n-mers, and selects only one out of the many present in the original sample. Ion identity is established from parallel mass spectra (ES-MS). The images reveal spherical particles 1.46nm in diameter, in good agreement with the known ion mass and bulk density. The DMA-selection technique opens new paths for the study of very small particles.     

The solid solutions Na3(1−x)Alx2xPO4: room temperature powder neutron diffraction studies of the two compositions x=0.025 and x=0.2

The crystal structures of the high-temperature modifications of sodium and silver orthophosphates have been determined using powder neutron diffraction (PND) data. II-Na₃PO₄ adopts the space group Fm3m with at 400°C. The PO³⁻₄ group is centered around the origin, but it shows high orientational disorder. The sodium ions occupy the and sites. II-Ag₃PO₄, at 650°C, is similar with . The structure of I-Ag₃PO₄ at room temperature

Full-size image (<1K)

has been re-examined by single-crystal X-ray diffraction. The derived model, with R=0.019 for 116 independent reflections, is in agreement with the latest work reported in the literature. The structure of I-Ag₃PO₄ at 375°C, as determined by PND, has , and displays no gross modifications from that observed at 25°C, although the anisotropic nature of the silver sites is markedly more pronounced at this higher temperature. The cation mobility is discussed in relation to the high-temperatures structures.     

Why Do Big Data and Machine Learning Entail the Fractional Dynamics?

Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks.     

High spatial and angular resolution diffusion-weighted imaging reveals forniceal damage related to memory impairment

Introduction

Diffusion tensor imaging (DTI) measures in patients with multiple sclerosis (MS), particularly those measures associated with a specific white matter pathway, have consistently shown correlations with function. This study sought to investigate correlations between DTI measures in the fornix and common cognitive deficits in MS patients, including episodic memory, working memory and attention.

Materials and Methods

Patients with MS and group age- and sex-matched controls underwent high-resolution diffusion scanning (1-mm isotropic voxels) and cognitive testing. Manually drawn forniceal regions of interest were applied to individual maps of tensor-derived measures, and mean values of transverse diffusivity (TD), mean diffusivity (MD), longitudinal diffusivity (LD) and fractional anisotropy (FA) were calculated.

Results

In 40 patients with MS [mean age±S.D.= 42.55±9.1 years; Expanded Disability Status Scale (EDSS)=2.0±1.2; Multiple Sclerosis Functional Composite (MSFC) score=0.38±0.46] and 20 healthy controls (mean age±S.D.= 41.35±9.7 years; EDSS=0.0±0; MSFC score=0.74±0.24), we found that FA, MD and TD values in the fornix were significantly different between groups (P< .03), and patient performance on the Brief Visuospatial Memory Test-Revised (BVMT-R) was correlated with DTI measures (P< .03).

Discussion

These results are consistent with findings of axonal degeneration in MS and support the use of DTI as an indicator of disease progression.     

The measurement of solid–liquid interfacial energy in colloidal suspensions using grain boundary grooves

Interfacial energy is a fundamental physiochemical property of any multi-phase system. Among the most direct approaches for determining solid–liquid interfacial energy is a technique based on measuring the shape of grain boundary grooves in specimens subjected to a linear temperature gradient. This technique was adapted to crystallizing colloids in a gravitational field. Such colloids exhibit a freezing–melting phase transition and are important not only as self-assembling precursors to photonic crystals, but also as physical models of atomic and molecular systems. The grain boundary groove technique was tested using suspensions of sterically stabilized poly(methyl methacrylate) spheres, which have been shown to closely approximate the hard sphere potential. Whereas isotropic models did not fit grain boundary groove data well, the capillary vector model, which is suitable for both isotropic and anisotropic surface energies, produced γ₁₁₀?=?0.58?±?0.05 k _B T/σ². This value of interfacial energy is in agreement with many of the published values for hard spheres, supporting the validity of our grain boundary groove technique adaptations to colloidal systems in a gravitational field. Finally, kinks observed in groove profiles suggest a minimum anisotropy parameter of ε?=?0.029 for hard spheres.     

Fifteenth International Conference on X-ray Absorption Fine Structure

The 15th International Conference on X-ray Absorption Fine Structure (XAFS15) was held at the Pullman Beijing West Wanda Hotel in Beijing, China, on July 22–28, 2012. The conference was chaired by Ziyu Wu (Chinese Academy of Sciences). In conjunction with XAFS15, the workshop “XAFS theory and nano particles” was held July 18–20, 2012, in Chiba, Japan, and chaired by T. Fujikawa.     

Programmable interferometry

The advent of automatic data-processing for interferometry greatly reduced the complexity of interferometric testing, thereby significantly increasing its usage both within and outside the optics community. A great many of these new applications require special data-processing and output data not normally used for testing lenses. To address these new measurement problems, many data-analysis programs were written, ranging from advanced analysis of wavefronts (i.e., Zernike polynominals, point-spread function, modulation-transfer function) to analysis of mechanical surfaces, such as Winchester-disk read/write heads. Some of these programs were very specific to a particular application, and some tried to be general and as such became cumbersome. Even with much of this software available for sale to the general public, most applications other than simple surface and lens measurements usually cannot be solved directly by using the available programs. In an attempt to solve this problem, we have developed software for interferometry that allows users to easily develop their own measurement routines. The solution was to take a version of the BASIC programming language and add the commands necessary to do interferometry. This software is resident in a processor that can easily be adapted to a large number of interferometry applications. By using this processor and its associated software with an appropriate interferometer, it is possible for the user to tailor the measurement to a particular application. This can be very useful in an optical-production shop, where each different testing application can have its own program. If the program is written properly, the operator will not have to set up any default conditions or format the output; the operation of the program can be reduced to the pushing of a single button, and the output will be formatted properly for that particular test. Examples of this system in actual optical shop-testing situations will be discussed.