Insight into the Impact of Oxidative Stress on the Barrier Properties of Lipid Bilayer Models

As a new field of oxidative stress-based therapy, cold physical plasma is a promising tool for several biomedical applications due to its potential to create a broad diversity of reactive oxygen and nitrogen species (RONS). Although proposed, the impact of plasma-derived RONS on the cell membrane lipids and properties is not fully understood. For this purpose, the changes in the lipid bilayer functionality under oxidative stress generated by an argon plasma jet (kINPen) were investigated by electrochemical techniques. In addition, liquid chromatography-tandem mass spectrometry was employed to analyze the plasma-induced modifications on the model lipids. Various asymmetric bilayers mimicking the structure and properties of the erythrocyte cell membrane were transferred onto a gold electrode surface by Langmuir-Blodgett/Langmuir-Schaefer deposition techniques. A strong impact of cholesterol on membrane permeabilization by plasma-derived species was revealed. Moreover, the maintenance of the barrier properties is influenced by the chemical composition of the head group. Mainly the head group size and its hydrogen bonding capacities are relevant, and phosphatidylcholines are significantly more susceptible than phosphatidylserines and other lipid classes, underlining the high relevance of this lipid class in membrane dynamics and cell physiology.     

One‐Step Formulation of Protein Microparticles with Tailored Properties: Hard Templating at Soft Conditions

Formulation of therapeutic proteins into particulate forms is a main strategy for site‐specific and prolonged protein delivery as well as for protection against degradation. Precise control over protein particle size, dispersity, purity, as well as mild preparation conditions and minimal processing steps are highly desirable. It is, however, hard to fit all these criteria with conventional preparation techniques. Here a one‐step hard‐templating synthesis of microparticles composed of functional, non‐denatured protein is reported. The method is based on filling porous CaCO₃ microtemplates with the protein near to its isoelectric point (pI) followed by pH‐ or EDTA‐mediated dissolution of the tempplates. In principle, a wide variety of proteins can be converted into microparticles using this approach. The main requirement is an overlap of the protein insolubility and a template solubility for a certain parameter (here pH or EDTA). Here the formulation of insulin particles is studied in detail and it is shown that particles consisting of high molecular weight protein (catalase) can also be prepared. In this context, the synthesis of CaCO₃ templates with controlled size, the mechanism of the protein microparticle formation and mechanical properties of the microparticles are discussed. For the first time, the fabrication of mesoporous monodispersed CaCO₃ microtemplates with identical porocity but tuned diameter from 3 to 20 μm is demonstrated. The protein particle diameter can be adjusted by choosing the appropriate template size that is critical for successful pulmonary delivery of insulin. As a first step towards insulin delivery, the in vitro release of insulin at physiological conditions is studied.     

PET: a proton/electron telescope for studies of magnetospheric,solar, and galactic particles

The proton/electron telescope (PET) on SAMPEX (Solar, Anomalous, and Magnetospheric Particle Explorer) is designed to provide measurements of energetic electrons and light nuclei from solar, Galactic, and magnetospheric sources. PET is an all solid-state system that will measure the differential energy spectra of electrons from ~1 to ~30 MeV and H and He nuclei from ~20 to ~300 MeV/nucleon, with isotope resolution of H and He extending from ~20 to ~80 MeV/nucleon. As SAMPEX scans all local times and geomagnetic cutoffs over the course of its near-polar orbit, PET will characterize precipitating relativistic electron events during periods of declining solar activity, and it will examine whether the production rate of odd nitrogen and hydrogen molecules in the middle atmosphere by precipitating electrons is sufficient to affect O₃ depletion. In addition, PET will complement studies of the elemental and isotopic composition of energetic heavy (Z>2) nuclei on SAMPEX by providing measurements of H, He, and electrons. Finally, PET has limited capability to identify energetic positrons from potential natural and man-made sources     

Constellation Rearrangement: Enhancement for Multilevel Modulation Formats and Transmit Diversity

Radio link adaptivity will be a key feature of the air interfaces of future mobile communication systems. This adaptivity includes techniques such as fast scheduling, hybrid ARQ, transmit diversity and adaptive modulation and coding. The performance of adaptive modulation generally suffers from the power inefficiencies of multilevel modulation formats. This is due to the variations in bit reliabilities caused by the bit-mapping onto the signal constellation. This article presents a concept, called constellation rearrangement (CoRe), which improves the multilevel modulation power efficiency by the joint application with transmit diversity schemes. It is shown by a theoretical analysis for 16-QAM that the presented concept can equalize variations in bit reliabilities by employing different mapping rules for the transmission over the diversity branches. This significantly improves the receiver block error rate performance and, hence, the performance of the adaptive modulation and coding. This is proven by simulations at link-level in a multicarrier CDMA system for AWGN and fading channels employing turbo coded transmission.     

Tracking ill-conditioning for the RLS-lattice algorithms

The numerical performance of lattice-based adaptive signal processing algorithms is shown to involve the conditioning of a 2×2 matrix whose off-diagonal elements contain reflection coefficients. Degraded algorithmic performance for the a posteriori recursive least squares lattice (RLSL) is shown to be attributed to the ill-conditioning of this matrix, Theoretical results are given which may be used to separate the conditioning of the underlying problem from issues concerning algorithmic stability. Although the results are not restricted to the all-pole case, for simplicity the authors make use of this well understood example since the condition number of the autocorrelation matrix will become arbitrarily close to singularity as the poles of an all-pole filter approach the unit circle. For a second-order prediction problem, four case studies of varying conditioning are provided which demonstrate the appropriateness of the theoretical bounds which analytically describe the sensitivity to perturbations in the residual update recursions. The paper illustrates the use of numerical linear algebra analysis techniques to better understand the numerical performance of algorithms in signal processing as well as emphasising that numerical performance is a function of the problem's conditioning as well as algorithmic stability     

Time-frequency spectral estimation of multichannel EEG using the Auto-SLEX method

In this paper, we apply a new time-frequency spectral estimation method for multichannel data to epileptiform electroencephalography (EEG). The method is based on the smooth localized complex exponentials (SLEX) functions which are time-frequency localized versions of the Fourier functions and, hence, are ideal for analyzing nonstationary signals whose spectral properties evolve over time. The SLEX functions are simultaneously orthogonal and localized in time and frequency because they are obtained by applying a projection operator rather than a window or taper. In this paper, we present the Auto-SLEX method which is a statistical method that 1) computes the periodogram using the SLEX transform, 2) automatically segments the signal into approximately stationary segments using an objective criterion that is based on log energy, and 3) automatically selects the optimal bandwidth of the spectral smoothing window. The method is applied to the intracranial EEG from a patient with temporal lobe epilepsy. This analysis reveals a reduction in average duration of stationarity in preseizure epochs of data compared to baseline. These changes begin up to hours prior to electrical seizure onset in this patient.     

3.2 Tbit/s (80 × 40 Gbit/s) phase-shaped binary transmissionover 3 × 100 km with 0.8 bit/s/Hz efficiency

50 GHz-spaced 80 × 40 Gbit/s WDM transmission over 300 km of TeraLight^TM fibre is demonstrated without polarisation demultiplexing, using the PSBT format. A record capacity of 3.2 Tbit/s is thus achieved over the C-band only, with a spectral efficiency of 0.8 bit/s/Hz     

Spatio-temporal fMRI analysis using Markov random fields

Functional magnetic resonance images (fMRI's) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activation areas involved in cognitive processes. To preserve the resolution of this noninvasive technique, refined methods are required in the analysis of the data. In this paper, we first discuss the widely used methods based on a statistical parameter map (SPM) analysis exposing the different shortcomings of this approach when considering high-resolution data. First, the often used Gaussian filtering results in a blurring effect and in delocalization of the activated area. Secondly, the SPM approach only considers false alarms due to noise but not rejections of activated voxels. We propose to embed the fMRI analysis problem into a Bayesian framework consisting of two steps: i) data restoration and ii) data analysis. We, therefore, propose two Markov random fields (MRF's) to solve these two problems. Results on three protocols (visual, motor and word recognition) are shown for two SPM approaches and compared with the proposed MRF approach.