Trans-Dominant Inhibition of Prion Propagation In Vitro Is Not Mediated by an Accessory Cofactor

Previous studies identified prion protein (PrP) mutants which act as dominant negative inhibitors of prion formation through a mechanism hypothesized to require an unidentified species-specific cofactor termed protein X. To study the mechanism of dominant negative inhibition in vitro, we used recombinant PrPC molecules expressed in Chinese hamster ovary cells as substrates in serial protein misfolding cyclic amplification (sPMCA) reactions. Bioassays confirmed that the products of these reactions are infectious. Using this system, we find that: (1) trans-dominant inhibition can be dissociated from conversion activity, (2) dominant-negative inhibition of prion formation can be reconstituted in vitro using only purified substrates, even when wild type (WT) PrPC is pre-incubated with poly(A) RNA and PrPSc template, and (3) Q172R is the only hamster PrP mutant tested that fails to convert into PrPSc and that can dominantly inhibit conversion of WT PrP at sub-stoichiometric levels. These results refute the hypothesis that protein X is required to mediate dominant inhibition of prion propagation, and suggest that PrP molecules compete for binding to a nascent seeding site on newly formed PrPSc molecules, most likely through an epitope containing residue 172

Protein Structure along the Order–Disorder Continuum

Thermal fluctuations cause proteins to adopt an ensemble of conformations wherein the relative stability of the different ensemble members is determined by the topography of the underlying energy landscape. “Folded” proteins have relatively homogeneous ensembles, while “unfolded” proteins have heterogeneous ensembles. Hence, the labels “folded” and “unfolded” represent attempts to provide a qualitative characterization of the extent of structural heterogeneity within the underlying ensemble. In this work, we introduce an information-theoretic order parameter to quantify this conformational heterogeneity. We demonstrate that this order parameter can be estimated in a straightforward manner from an ensemble and is applicable to both unfolded and folded proteins. In addition, a simple formula for approximating the order parameter directly from crystallographic B factors is presented. By applying these metrics to a large sample of proteins, we show that proteins span the full range of the order–disorder axis.National Institutes of Health (U.S.) (NIH Grant 5R21NS063185-02

Optical emission spectroscopy of electron-cyclotron-resonance-heated helium mirror plasmas

In this experiment emission spectroscopy in the 3000–5000 Å range has been utilized to determine the electron temperature (15–60 eV) and ion density (2–5 x 10 11 cm −3 ) of helium plasmas produced by the Michigan mirror machine (1) (MIMI). The plasma is generated and heated by whistler-mode electron-cyclotron resonance (ECR) waves at 7.43 GHz with 400–900 W power in 80-ms-long pulses. Gas fueling is provided at the midplane region by a leak valve with a range in pressure of 3 x 10 to 2 x 10 4 Torr. Emission line intensities are interpreted using a model of the important collisional and radiative processes occurring in the plasma. The model examines secondary processes such as radiation trapping, excitation transfer between levels of the carne principle quantum number, and excitation front metastable states for plasmas in the parameter range of MIMI ( n c = 1−6 x 10 11 cm −3 ). Front the analysis of line intensity ratios for neutral helium, the electron temperature is measured and its dependence upon the gas pressure and microwave power is determined. These temperatures agree with those obtained by Langmuir probe measurements. Art analysis of the line intensity ratio between singly ionized helium and neutral helium yields a measurement of the ion density which is in good agreement with electron density measurements made by a microwave interferometer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45473/1/11090_2005_Article_BF01447032.pd

Tutorial: Multivariate Classification for Vibrational Spectroscopy in Biological Samples

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental

Low Temperature Crystallization of TiNi Films by Ion Irradiation

TiNi films are well known as a typical shape memory alloy (SMA), and are expected to be promising materials for micro actuators. The film crystallization needed for making the shape memory property appear had been usually realized by high temperature (above 450 °C) annealing process during and/or after the sputtering deposition. As a special case, it was reported that the crystallization temperature could be lowered by enhancing the energies of sputtered particles with a single-target sputtering deposition. However, this method could not be applied to the multitarget sputtering deposition, which was essential to precisely controlling the TiNi film composition. Furthermore, it also had a difficulty in freely controlling the energies of sputtered particles. In order to resolve the problem we developed a new apparatus as well as a new process for lowering the crystallization temperature by using ion irradiation, and realized the crystallization at 200 °C of substrate temperature. The details of the film characteristics were reported in another paper. In order to further lower the crystallization temperature we try to improve the biasvoltage introduction into vacuum as well as to optimize the ion irradiation conditions. Resultantly, we have realized the low temperature crystallization at 150 °C of substrate temperature