Bayesian inference to identify crystalline structures for XRD

Crystalline phase structure is essential for understanding the performance and properties of a material. Therefore, this study identified and quantified the crystalline phase structure of a sample based on the diffraction pattern observed when the crystalline sample was irradiated with electromagnetic waves such as X-rays. Conventional analysis necessitates experienced and knowledgeable researchers to shorten the list from many candidate crystalline phase structures. However, the Conventional diffraction pattern analysis is highly analyst-dependent and not objective. Additionally, there is no established method for discussing the confidence intervals of the analysis results. Thus, this study aimed to establish a method for automatically inferring crystalline phase structures from diffraction patterns using Bayesian inference. Our method successfully identified true crystalline phase structures with a high probability from 50 candidate crystalline phase structures. Further, the mixing ratios of selected crystalline phase structures were estimated with a high degree of accuracy. This study provided reasonable results for well-crystallized samples that clearly identified the crystalline phase structures

Mapping of the local environmental changes in proteins by cysteine scanning

Protein conformational changes, which regulate the activity of proteins, are induced by the alternation of intramolecular interactions. Therefore, the detection of the local environmental changes around the key amino acid residues is essential to understand the activation mechanisms of functional proteins. Here we developed the methods to scan the local environmental changes using the vibrational band of cysteine S-H group. We validated the sensitivity of this method using bathorhodopsin, a photoproduct of rhodopsin trapped at liquid nitrogen temperature, which undergoes little conformational changes from the dark state as shown by the X-ray crystallography. The cysteine residues were individually introduced into 15 positions of Helix III, which contains several key amino acid residues for the light-induced conformational changes of rhodopsin. The shifts of S-H stretching modes of these cysteine residues and native cysteine residues upon the formation of bathorhodopsin were measured by Fourier transform infrared spectroscopy. While most of cysteine residues demonstrated no shift of S-H stretching mode, cysteine residues introduced at positions 117, 118, and 122, which are in the vicinity of the chromophore, demonstrated the significant changes. The current results are consistent with the crystal structure of bathorhodopsin, implying that the cysteine scanning is sensitive enough to detect the tiny conformational changes

Transparent Exopolymer Particles in Deep Oceans: Synthesis and Future Challenges

Transparent exopolymer particles (TEP) are a class of abundant gel-like particles that are omnipresent in seawater. While versatile roles of TEP in the regulation of carbon cycles have been studied extensively over the past three decades, investigators have only recently begun to find intriguing features of TEP distribution and processes in deep waters. The emergence of new research reflects the growing attention to ecological and biogeochemical processes in deep oceans, where large quantities of organic carbon are stored and processed. Here, we review recent research concerning the role of TEP in deep oceans. We discuss: (1) critical features in TEP distribution patterns, (2) TEP sources and sinks, and (3) contributions of TEP to the organic carbon inventory. We conclude that gaining a better understanding of TEP-mediated carbon cycling requires the effective application of gel theory and particle coagulation models for deep water settings. To achieve this goal, we need a better recognition and determination of the quantities, turnover, transport, chemical properties, and microbial processing of TEP