Myelin-derived and putative molecular mimic peptides share structural properties in aqueous and membrane-like environments

Background: Despite intense research, the causes of various neurological diseases remain enigmatic to date. A role for viral or bacterial infection and associated molecular mimicry has frequently been suggested in the etiology of neurological diseases, including demyelinating autoimmune disorders, such as multiple sclerosis. Pathogen mimics of myelin-derived autoimmune peptides have been described in the literature and shown to induce myelin autoimmune responses in animal models. Methods: We carried out a structural study on myelin-derived peptides, and mimics thereof from various pathogens, in aqueous and membrane-like environments, using conventional and synchrotron radiation circular dichroism spectroscopy. A total of 13 peptides from the literature were studied, and 290 circular dichroism spectra were analysed. In addition, peptide structure predictions and vesicle aggregation assays were performed. Results: The results indicate a high level of similarity in the biophysical and folding properties of the peptides from either myelin proteins or proteins from pathogenic viruses or bacteria; essentially all of the studied peptides folded in the presence of lipid vesicles or under other membrane-mimicking conditions, which is a sign of membrane interaction. Many of the peptides presented remarkable similarities in their conformation in different environments. Conclusions: As most of the studied epitope segments in myelin proteins are associated with membrane-binding sites, our results support a view of molecular mimicry, involving lipid membrane interaction propensity and similar conformational properties, possibly playing a role in demyelinating disease. The results suggest mechanisms related to protein amphiphilicity and order-disorder transitions in the recognition of peptide epitopes in autoimmune demyelination.publishedVersio

Multicore Software-Defined Radio Architecture for GNSS Receiver Signal Processing

We describe a multicore Software-Defined Radio (SDR) architecture for Global Navigation Satellite System (GNSS) receiver implementation. A GNSS receiver picks up very low power signals from multiple satellites and then uses dedicated processing to demodulate and measure the exact timing of these signals from which the user's position, velocity, and time (PVT) can be estimated. Three GNSS SDR architectures are discussed. (1) A hardware-based SDR that is feasible for embedded devices but relatively expensive, (2) a pure SDR approach that has high level of flexibility and low bill of material, but is not yet suited for handheld applications, and (3) a novel architecture that uses a programmable array of multiple processing cores that exhibits both flexibility and potential for mobile devices. We present the CRISP project where the multicore architecture will be realized along with numerical analysis of application requirements of the platform's processing cores and network payload

Local Oscillator Phase Noise Effects on Phase Angle Component of GNSS Code Correlation

This paper demonstrates the effect of radio frequency (RF) front-end (FE) free-running local oscillator (FRO) phase noise (PN) on the phase component of the Global Navigation Satellite System (GNSS) code correlation product. It is observed that as FE PN increases, it adversely affects the stability of the phase component of the code correlation. The tracking loops in baseband processing of a GNSS receiver attempt to lock on to the frequency, delay and phase of the correlation product. Until these parameters are varying within acceptable bounds, set by the dynamics handling capability of the tracking loops, the tracking loops are able to successfully track the satellite signal. However, PN increases the variation in phase of the correlation product calculated over consecutive epochs and may also cause loss of tracking lock if these variations go beyond phase locked loop (PLL) pull-in range thresholds. This paper studies the relation between FRO PN and phase component of correlation through numerical analysis, and software simulations by artificially contaminating GNSS signal stream with PN of increasing variance and checking the result on the standard deviation (SD) of the phase component of correlation product. Based on these results, this paper recommends certain maximum limits on the FE PN in order to keep the SD of phase component below the onesigma phase error limits of the PLL used in typical GNSS tracking loops.Peer reviewe

Additional file 4: Figure S3. of Myelin-derived and putative molecular mimic peptides share structural properties in aqueous and membrane-like environments

CD spectra for a negative control peptide from the P. falciparum formin display no folding under membrane-mimicking conditions. The peptide sequence is KKIPAPPPFLLKKK. (TIF 25 kb

Additional file 2: Figure S1. of Myelin-derived and putative molecular mimic peptides share structural properties in aqueous and membrane-like environments

Helical wheel predictions of all peptides from this study. (PDF 1382 kb

Additional file 5: Table S2. of Myelin-derived and putative molecular mimic peptides share structural properties in aqueous and membrane-like environments

Results from CD spectrum deconvolution of all 290 samples, with two different algorithms. (PDF 66 kb

Additional file 1: Table S1. of Myelin-derived and putative molecular mimic peptides share structural properties in aqueous and membrane-like environments

Details of peptide properties. (PDF 60 kb

Blind sub-Nyquist GNSS signal detection

A satellite navigation receiver traditionally searches for positioning signals using an acquisition procedure. In situations, in which the required information is only a binary decision whether at least one positioning signal is present or absent, the procedure represents an unnecessarily complex solution. This paper presents a different approach for the binary detection problem with significantly reduced computational complexity. The approach is based on a novel decision metric which is utilized to design two binary detectors. The first detector operates under the theoretical assumption of additive white Gaussian noise and is evaluated by means of Receiver Operating Characteristics. The second one considers also additional interferences and is suitable to operate in a real environment. Its performance is verified using a signal captured by a receiver front-end