Determination of orientations of aromatic groups in self-assembled peptide fibrils by polarised Raman spectroscopy

In this paper we describe a novel combination of Raman spectroscopy, isotope editing and X-ray scattering as a powerful approach to give detailed structural information on aromatic side chains in peptide fibrils. The orientation of the tyrosine residues in fibrils of the peptide YTIAALLSPYS with respect to the fibril axis has been determined from a combination of polarised Raman spectroscopy and X-ray diffraction measurements. The Raman intensity of selected tyrosine bands collected at different polarisation geometries is related to the values and orientation of the Raman tensor for those specific vibrations. Using published Raman tensor values we solved the relevant expressions for both of the two tyrosine residues present in this peptide. Ring deuteration in one of the two tyrosine side chains allowed for the calculation to be performed individually for both, by virtue of the isotopic shift that eliminates band overlapping. Sample disorder was taken into account by obtaining the distribution of orientations of the samples from X-ray diffraction experiments. The results provide previously unavailable details about the molecular conformation of this peptide, and demonstrate the value of this approach for the study of amyloid fibrils.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

Impact of dietary polydextrose fiber on the human gut metabolome

The aim of the present study was to elucidate the impact of polydextrose PDX an soluble fiber, on the human fecal metabolome by high-resolution nuclear magnetic resonance (NMR) spectroscopy-based metabolomics in a dietary intervention study (n = 12). Principal component analysis (PCA) revealed a strong effect of PDX consumption on the fecal metabolome, which could be mainly ascribed to the presence of undigested fiber and oligosaccharides formed from partial degradation of PDX. Our results demonstrate that NMR-based metabolomics is a useful technique for metabolite profiling of feces and for testing compliance to dietary fiber intake in such trials. In addition, novel associations between PDX and the levels of the fecal metabolites acetate and propionate could be identified. The establishment of a correlation between the fecal metabolome and levels of Bifidobacterium (R2 = 0.66) and Bacteroides (R2 = 0.46) demonstrates the potential of NMR-based metabolomics to elucidate metabolic activity of bacteria in the gut.

New insights into the compressibility and high-pressure stability of Ni(CN)2: a combined study of neutron diffraction, Raman spectroscopy, and inelastic neutron scattering

Nickel cyanide is a layered material showing markedly anisotropic behaviour. High-pressure neutron diffraction measurements show that at pressures up to 20.1 kbar, compressibility is much higher in the direction perpendicular to the layers, c, than in the plane of the strongly chemically bonded metal-cyanide sheets. Detailed examination of the behaviour of the tetragonal lattice parameters, a and c, as a function of pressure reveal regions in which large changes in slope occur, for example, in c(P) at 1 kbar. The experimental pressure dependence of the volume data is fitted to a bulk modulus, B0, of 1050 (20) kbar over the pressure range 0–1 kbar, and to 124 (2) kbar over the range 1–20.1 kbar. Raman spectroscopy measurements yield additional information on how the structure and bonding in the Ni(CN)2 layers change with pressure and show that a phase change occurs at about 1 kbar. The new high-pressure phase, (Phase PII), has ordered cyanide groups with sheets of D4h symmetry containing Ni(CN)4 and Ni(NC)4 groups. The Raman spectrum of phase PII closely resembles that of the related layered compound, Cu1/2Ni1/2(CN)2, which has previously been shown to contain ordered C≡N groups. The phase change, PI to PII, is also observed in inelastic neutron scattering studies which show significant changes occurring in the phonon spectra as the pressure is raised from 0.3 to 1.5 kbar. These changes reflect the large reduction in the interlayer spacing which occurs as Phase PI transforms to Phase PII and the consequent increase in difficulty for out-of-plane atomic motions. Unlike other cyanide materials e.g. Zn(CN)2 and Ag3Co(CN)6, which show an amorphization and/or a decomposition at much lower pressures (~100 kbar), Ni(CN)2 can be recovered after pressurising to 200 kbar, albeit in a more ordered form.