A stereoselective cobalt-containing nitrile hydratase

Nitrile hydratase from Pseudomonas putida NRRL-18668 has been purified and characterized. The purified enzyme catalyzes the hydration of 2(S)-(4'-chlorophenyl)-3-methylbutyronitrile at least fifty times faster than that of 2(R)-(4'-chlorophenyl)-3-methylbutyronitrile. This enzyme is a member of the class of nitrile hydratase that contains cobalt. Visible absorption and CD spectra suggest the cobalt exists as a non-corrin low-spin Co3+ ion in a tetragonally-distorted octahedral ligand field. Chemical reduction of the native enzyme results in a species with the EPR signature of a low-spin Co2+ complex. Like the other cobalt-containing nitrile hydratases, this enzyme is relatively stable, maintaining its activity below 35 degrees C, and it shows a broad activity optimum between pH 7.2 and 7.8. The structural genes for this enzyme have been cloned and sequenced. The deduced amino acid sequences for the alpha and beta subunits show 48-63% and 35-41% homology, respectively, to other sequenced nitrile hydratases. In particular, the cysteine residues in the alpha subunit that have been suggested to coordinate the metal ion in the iron-containing nitrile hydratases [Brennan, B. A., Cummings, J. G., Chase, D. B., Turner, I. M., Jr., & Nelson, M. J. (1996) Biochemistry 35, 10068-10077] are conserved in this enzyme, suggesting that this nitrile hydratase, like the enzyme from Rhodococcus rhodochrous J1, is a member of a newly described class of metalloenzymes with Co3+-thiolate ligation [Brennan, B. A., Alms, G., Nelson, M. J., Durney, L. T., & Scarrow, R. C. (1996) J. Am. Chem. Soc. 118, 9194-9195].     

Analysis of an interferometric optical fibre detection technique applied to silicon vibrating sensors

A simple and accurate analysis of a single-mode optical fibre interferometric displacement detection technique is resented. This analysis is in good agreement with experimental measurements, and shows that angular alignment between the fibre and the sensor is the most critical parameter.     

Turbulent Details Simulation for SPH Fluids via Vorticity Refinement

A major issue in smoothed particle hydrodynamics (SPH) approaches is the numerical dissipation during the projection process, especially under coarse discretizations. High‐frequency details, such as turbulence and vortices, are smoothed out, leading to unrealistic results. To address this issue, we introduce a vorticity refinement (VR) solver for SPH fluids with negligible computational overhead. In this method, the numerical dissipation of the vorticity field is recovered by the difference between the theoretical and the actual vorticity, so as to enhance turbulence details. Instead of solving the Biot‐Savart integrals, a stream function, which is easier and more efficient to solve, is used to relate the vorticity field to the velocity field. We obtain turbulence effects of different intensity levels by changing an adjustable parameter. Since the vorticity field is enhanced according to the curl field, our method can not only amplify existing vortices, but also capture additional turbulence. Our VR solver is straightforward to implement and can be easily integrated into existing SPH methods.     

A new approach to predict ulcerative colitis activity through standard clinical–biological parameters using a robust neural network model

Neural Computing and Applications - Colonoscopy is the “gold” standard for evaluating disease activity in ulcerative colitis (UC). An important area of research is finding a...     

Novel (Phenothiazinyl)Vinyl-Pyridinium Dyes and Their Potential Applications as Cellular Staining Agents

We report here the synthesis and structural characterization of novel cationic (phenothiazinyl)vinyl-pyridinium (PVP) dyes, together with optical (absorption/emission) properties and their potential applicability as fluorescent labels. Convective heating, ultrasound irradiation and mechanochemical synthesis were considered as alternative synthetic methodologies proficient for overcoming drawbacks such as long reaction time, nonsatisfactory yields or solvent requirements in the synthesis of novel dye (E)-1-(3-chloropropyl)-4-(2-(10-methyl-10H-phenothiazin-3-yl)vinyl)pyridin-1-ium bromide 3d and its N-alkyl-2-methylpyridinium precursor 1c. The trans geometry of the newly synthesized (E)-4-(2-(7-bromo-10-ethyl-10H-phenothiazin-3-yl)vinyl)-1-methylpyridin-1-ium iodide 3b and (E)-1-methyl-4-(2-(10-methyl-10H-phenothiazin-3-yl)vinyl)pyridin-1-ium tetrafluoroborate 3a′ was confirmed by single crystal X-ray diffraction. A negative solvatochromism of the dyes in polar solvents was highlighted by UV-Vis spectroscopy and explanatory insights were supported by molecular modeling which suggested a better stabilization of the lowest unoccupied molecular orbitals (LUMO). The photostability of the dye 3b was investigated by irradiation at 365 nm in different solvents, while the steady-state and time-resolved fluorescence properties of dye 3b and 3a′ in solid state were evaluated under one-photon excitation at 485 nm. The in vitro cytotoxicity of the new PVP dyes on B16-F10 melanoma cells was evaluated by WST-1 assay, while their intracellular localization was assessed by epi-fluorescence conventional microscopy imaging as well as one- and two-photon excited confocal fluorescence lifetime imaging microscopy (FLIM). PVP dyes displayed low cytotoxicity, good internalization inside melanoma cells and intense fluorescence emission inside the B16-F10 murine melanoma cells, making them suitable staining agents for imaging applications.     

Clustering based on median and closest string via rank distance with applications on DNA

This paper aims to present several clustering methods based on rank distance. Rank distance has applications in many different fields such as computational linguistics, biology and computer science. The K-means algorithm represents each cluster by a single mean vector. The mean vector is computed with respect to a distance measure. Two K-means algorithms based on rank distance are described in this paper. Hierarchical clustering builds models based on distance connectivity. This paper describes two hierarchical clustering techniques that use rank distance. Experiments using mitochondrial DNA sequences extracted from several mammals are performed to compare the results of the clustering methods. Results demonstrate the clustering performance and the utility of the proposed algorithms.