Differential use of signal peptides and membrane domains is a common occurrence in the protein output of transcriptional units

Membrane organization describes the orientation of a protein with respect to the membrane and can be determined by the presence, or absence, and organization within the protein sequence of two features: endoplasmic reticulum signal peptides and alpha-helical transmembrane domains. These features allow protein sequences to be classified into one of five membrane organization categories: soluble intracellular proteins, soluble secreted proteins, type I membrane proteins, type II membrane proteins, and multi- spanning membrane proteins. Generation of protein isoforms with variable membrane organizations can change a protein's subcellular localization or association with the membrane. Application of MemO, a membrane organization annotation pipeline, to the FANTOM3 Isoform Protein Sequence mouse protein set revealed that within the 8,032 transcriptional units ( TUs) with multiple protein isoforms, 573 had variation in their use of signal peptides, 1,527 had variation in their use of transmembrane domains, and 615 generated protein isoforms from distinct membrane organization classes. The mechanisms underlying these transcript variations were analyzed. While TUs were identified encoding all pairwise combinations of membrane organization categories, the most common was conversion of membrane proteins to soluble proteins. Observed within our highconfidence set were 156 TUs predicted to generate both extracellular soluble and membrane proteins, and 217 TUs generating both intracellular soluble and membrane proteins. The differential use of endoplasmic reticulum signal peptides and transmembrane domains is a common occurrence within the variable protein output of TUs. The generation of protein isoforms that are targeted to multiple subcellular locations represents a major functional consequence of transcript variation within the mouse transcriptome.

Identification of membrane-bound and secreted proteins from Echinococcus granulosus by signal sequence trap

The signal sequence trap technique was applied to identify genes coding for secreted and membrane bound proteins from Echinococcus granulosus, the etiologic agent of cystic hydatid disease. An E. granulosus protoscolex cDNA library was constructed in the AP-PST vector such that randomly primed cDNAs were fused with a placental alkaline phosphatase reporter gene lacking its endogenous signal peptide. E. granulosus cDNAs encoding a functional signal peptide were selected by their ability to rescue secretion of alkaline phosphatase by COS-7 cells that had been transfected with the cDNA library. Eighteen positive clones were identified and sequenced. Their deduced amino acid sequences showed significant similarity with amino acid transporters, Krebs cycle intermediates transporters, presenilins and vacuolar protein sorter proteins. Other cDNAs encoded secreted proteins without homologues. Three sequences were transcribed antisense to E. granulosus expressed sequence tags. All the mRNAs were expressed in protoscoleces and adult worms, but some of them were not found in oncospheres. The putative E. granulosus secreted and membrane bound proteins identified are likely to play important roles in the metabolism, development and survival in the host and represent potential targets for diagnosis, drugs and vaccines against E. granulosus. (c) 2005 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Low bit-rate speech encoding for digital mobile radio

The need for low bit-rate speech coding is the result of growing demand on the available radio bandwidth for mobile communications both for military purposes and for the public sector. To meet this growing demand it is required that the available bandwidth be utilized in the most economic way to accommodate more services. Two low bit-rate speech coders have been built and tested in this project. The two coders combine predictive coding with delta modulation, a property which enables them to achieve simultaneously the low bit-rate and good speech quality requirements. To enhance their efficiency, the predictor coefficients and the quantizer step size are updated periodically in each coder. This enables the coders to keep up with changes in the characteristics of the speech signal with time and with changes in the dynamic range of the speech waveform. However, the two coders differ in the method of updating their predictor coefficients. One updates the coefficients once every one hundred sampling periods and extracts the coefficients from input speech samples. This is known in this project as the Forward Adaptive Coder. Since the coefficients are extracted from input speech samples, these must be transmitted to the receiver to reconstruct the transmitted speech sample, thus adding to the transmission bit rate. The other updates its coefficients every sampling period, based on information of output data. This coder is known as the Backward Adaptive Coder. Results of subjective tests showed both coders to be reasonably robust to quantization noise. Both were graded quite good, with the Forward Adaptive performing slightly better, but with a slightly higher transmission bit rate for the same speech quality, than its Backward counterpart. The coders yielded acceptable speech quality of 9.6kbps for the Forward Adaptive and 8kbps for the Backward Adaptive.

Concurrent codes:a holographic-type encoding robust against noise and loss

Concurrent coding is an encoding scheme with 'holographic' type properties that are shown here to be robust against a significant amount of noise and signal loss. This single encoding scheme is able to correct for random errors and burst errors simultaneously, but does not rely on cyclic codes. A simple and practical scheme has been tested that displays perfect decoding when the signal to noise ratio is of order -18dB. The same scheme also displays perfect reconstruction when a contiguous block of 40% of the transmission is missing. In addition this scheme is 50% more efficient in terms of transmitted power requirements than equivalent cyclic codes. A simple model is presented that describes the process of decoding and can determine the computational load that would be expected, as well as describing the critical levels of noise and missing data at which false messages begin to be generated.

A theoretical analysis of eyewitness identification: Dual -process theory, signal detection theory and eyewitness confidence

Given the growing number of wrongful convictions involving faulty eyewitness evidence and the strong reliance by jurors on eyewitness testimony, researchers have sought to develop safeguards to decrease erroneous identifications. While decades of eyewitness research have led to numerous recommendations for the collection of eyewitness evidence, less is known regarding the psychological processes that govern identification responses. The purpose of the current research was to expand the theoretical knowledge of eyewitness identification decisions by exploring two separate memory theories: signal detection theory and dual-process theory. This was accomplished by examining both system and estimator variables in the context of a novel lineup recognition paradigm. Both theories were also examined in conjunction with confidence to determine whether it might add significantly to the understanding of eyewitness memory. ^ In two separate experiments, both an encoding and a retrieval-based manipulation were chosen to examine the application of theory to eyewitness identification decisions. Dual-process estimates were measured through the use of remember-know judgments (Gardiner & Richardson-Klavehn, 2000). In Experiment 1, the effects of divided attention and lineup presentation format (simultaneous vs. sequential) were examined. In Experiment 2, perceptual distance and lineup response deadline were examined. Overall, the results indicated that discrimination and remember judgments (recollection) were generally affected by variations in encoding quality and response criterion and know judgments (familiarity) were generally affected by variations in retrieval options. Specifically, as encoding quality improved, discrimination ability and judgments of recollection increased; and as the retrieval task became more difficult there was a shift toward lenient choosing and more reliance on familiarity. ^ The application of signal detection theory and dual-process theory in the current experiments produced predictable results on both system and estimator variables. These theories were also compared to measures of general confidence, calibration, and diagnosticity. The application of the additional confidence measures in conjunction with signal detection theory and dual-process theory gave a more in-depth explanation than either theory alone. Therefore, the general conclusion is that eyewitness identifications can be understood in a more complete manor by applying theory and examining confidence. Future directions and policy implications are discussed. ^

Sparse Signal Representation in Digital and Biological Systems

Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.

Bipolar Tribocharging Signal During Friction Force Fluctuations At Metal-insulator Interfaces.

Friction and triboelectrification of materials show a strong correlation during sliding contacts. Friction force fluctuations are always accompanied by two tribocharging events at metal-insulator [e.g., polytetrafluoroethylene (PTFE)] interfaces: injection of charged species from the metal into PTFE followed by the flow of charges from PTFE to the metal surface. Adhesion maps that were obtained by atomic force microscopy (AFM) show that the region of contact increases the pull-off force from 10 to 150 nN, reflecting on a resilient electrostatic adhesion between PTFE and the metallic surface. The reported results suggest that friction and triboelectrification have a common origin that must be associated with the occurrence of strong electrostatic interactions at the interface.

Association Of Single Nucleotide Polymorphisms In The Gene Encoding Glut1 And Diabetic Nephropathy In Brazilian Patients With Type 1 Diabetes Mellitus.

Mesangial cells subject to high extracellular glucose concentrations, as occur in hyperglycaemic states, are unable to down regulate glucose influx, resulting in intracellular activation of deleterious biochemical pathways. A high expression of GLUT1 participates in the development of diabetic glomerulopathy. Variants in the gene encoding GLUT1 (SLC2A1) have been associated to this diabetic complication. The aim of this study was to test whether polymorphisms in SLC2A1 confer susceptibility to diabetic nephropathy (DN) in Brazilian type 1 diabetes patients. Four polymorphisms (rs3820589, rs1385129, rs841847 and rs841848) were genotyped in a Brazilian cohort comprised of 452 patients. A prospective analysis was performed in 155 patients. Mean duration of follow-up was 5.6±2.4years and the incidence of renal events was 18.0%. The rs3820589 presented an inverse association with the prevalence of incipient DN (OR: 0.36, 95% CI: 0.16 - 0.80, p=0.01) and with progression to renal events (HR: 0.20; 95% CI: 0.03 - 0.70; p=0.009). AGGT and AGAC haplotypes were associated with the prevalence of incipient DN and the AGAC haplotype was also associated with the prevalence of established/advanced DN. In conclusion, rs3820589 in the SLC2A1 gene modulates the risk to DN in Brazilian patients with inadequate type 1 diabetes control.

Phylogenetic And Phylogeographic Mapping Of The Avian Coronavirus Spike Protein-encoding Gene In Wild And Synanthropic Birds.

The evolution and population dynamics of avian coronaviruses (AvCoVs) remain underexplored. In the present study, in-depth phylogenetic and Bayesian phylogeographic studies were conducted to investigate the evolutionary dynamics of AvCoVs detected in wild and synanthropic birds. A total of 500 samples, including tracheal and cloacal swabs collected from 312 wild birds belonging to 42 species, were analysed using molecular assays. A total of 65 samples (13%) from 22 bird species were positive for AvCoV. Molecular evolution analyses revealed that the sequences from samples collected in Brazil did not cluster with any of the AvCoV S1 gene sequences deposited in the GenBank database. Bayesian framework analysis estimated an AvCoV strain from Sweden (1999) as the most recent common ancestor of the AvCoVs detected in this study. Furthermore, the analysis inferred an increase in the AvCoV dynamic demographic population in different wild and synanthropic bird species, suggesting that birds may be potential new hosts responsible for spreading this virus.

Detection of metallo-'beta'-lactamases-encoding genes in environmental isolates of Aeromonas hydrophila and Aeromonas jandaei

Aims: To determine the prevalence and expression of metallo-beta-lactamases (MBL)-encoding genes in Aeromonas species recovered from natural water reservoirs in southeastern Brazil. Methods and Results: Eighty-seven Aeromonas isolates belonging to Aeromonas hydrophila (n = 41) and Aer. jandaei (n = 46) species were tested for MBL production by the combined disk test using imipenem and meropenem disks as substrates and EDTA or thioglycolic acid as inhibitors. The presence of MBL genes was investigated by PCR and sequencing using new consensus primer pairs designed in this study. The cphA gene was found in 97.6% and 100% of Aer. hydrophila and Aer. jandaei isolates, respectively, whereas the acquired MBL genes bla(IMP), bla(VIM) and bla(SPM-1) were not detected. On the other hand, production of MBL activity was detectable in 87.8% and 10.9% of the cphA-positive Aer. hydrophila and Aer. jandaei isolates respectively. Conclusions: Our results indicate that cphA seems to be intrinsic in the environmental isolates of Aer. hydrophila and Aer. jandaei in southeastern Brazil, although, based on the combined disk test, not all of them are apparently able to express the enzymatic activity. Significance and Impact of the Study: These data confirm the presence of MBL-producing Aeromonas species in natural water reservoirs. Risk of water-borne diseases owing to domestic and industrial uses of freshwater should be re-examined from the increase of bacterial resistance point of view

A Vaccine Encoding Conserved Promiscuous HIV CD4 Epitopes Induces Broad T Cell Responses in Mice Transgenic to Multiple Common HLA Class II Molecules

Current HIV vaccine approaches are focused on immunogens encoding whole HIV antigenic proteins that mainly elicit cytotoxic CD8+ responses. Mounting evidence points toward a critical role for CD4+ T cells in the control of immunodeficiency virus replication, probably due to cognate help. Vaccine-induced CD4+ T cell responses might, therefore, have a protective effect in HIV replication. In addition, successful vaccines may have to elicit responses to multiple epitopes in a high proportion of vaccinees, to match the highly variable circulating strains of HIV. Using rational vaccine design, we developed a DNA vaccine encoding 18 algorithm-selected conserved, ""promiscuous"" ( multiple HLA-DR-binding) B-subtype HIV CD4 epitopes - previously found to be frequently recognized by HIV-infected patients. We assessed the ability of the vaccine to induce broad T cell responses in the context of multiple HLA class II molecules using different strains of HLA class II-transgenic mice (-DR2, -DR4, -DQ6 and -DQ8). Mice displayed CD4+ and CD8+ T cell responses of significant breadth and magnitude, and 16 out of the 18 encoded epitopes were recognized. By virtue of inducing broad responses against conserved CD4+ T cell epitopes that can be recognized in the context of widely diverse, common HLA class II alleles, this vaccine concept may cope both with HIV genetic variability and increased population coverage. The vaccine may thus be a source of cognate help for HIV-specific CD8+ T cells elicited by conventional immunogens, in a wide proportion of vaccinees.

A DNA Vaccine Encoding Multiple HIV CD4 Epitopes Elicits Vigorous Polyfunctional, Long-Lived CD4(+) and CD8(+) T Cell Responses

T-cell based vaccines against HIV have the goal of limiting both transmission and disease progression by inducing broad and functionally relevant T cell responses. Moreover, polyfunctional and long-lived specific memory T cells have been associated to vaccine-induced protection. CD4(+) T cells are important for the generation and maintenance of functional CD8(+) cytotoxic T cells. We have recently developed a DNA vaccine encoding 18 conserved multiple HLA-DR-binding HIV-1 CD4 epitopes (HIVBr18), capable of eliciting broad CD4(+) T cell responses in multiple HLA class II transgenic mice. Here, we evaluated the breadth and functional profile of HIVBr18-induced immune responses in BALB/c mice. Immunized mice displayed high-magnitude, broad CD4(+)/CD8(+) T cell responses, and 8/18 vaccine-encoded peptides were recognized. In addition, HIVBr18 immunization was able to induce polyfunctional CD4(+) and CD8(+) T cells that proliferate and produce any two cytokines (IFN gamma/TNF alpha, IFN gamma/IL-2 or TNF alpha/IL-2) simultaneously in response to HIV-1 peptides. For CD4(+) T cells exclusively, we also detected cells that proliferate and produce all three tested cytokines simultaneously (IFN gamma/TNF alpha/IL-2). The vaccine also generated long-lived central and effector memory CD4(+) T cells, a desirable feature for T-cell based vaccines. By virtue of inducing broad, polyfunctional and long-lived T cell responses against conserved CD4(+) T cell epitopes, combined administration of this vaccine concept may provide sustained help for CD8(+) T cells and antibody responses-elicited by other HIV immunogens.

Expression of an activating mutation in the gene encoding the K(ATP) channel subunit Kir6.2 in mouse pancreatic beta cells recapitulates neonatal diabetes

Neonatal diabetes is a rare monogenic form of diabetes that usually presents within the first six months of life. It is commonly caused by gain-of-function mutations in the genes encoding the Kir6.2 and SUR1 subunits of the plasmalemmal ATP-sensitive K(+) (K(ATP)) channel. To better understand this disease, we generated a mouse expressing a Kir6.2 mutation (V59M) that causes neonatal diabetes in humans and we used Cre-lox technology to express the mutation specifically in pancreatic beta cells. These beta-V59M mice developed severe diabetes soon after birth, and by 5 weeks of age, blood glucose levels were markedly increased and insulin was undetectable. Islets isolated from beta-V59M mice secreted substantially less insulin and showed a smaller increase in intracellular calcium in response to glucose. This was due to a reduced sensitivity of K(ATP) channels in pancreatic beta cells to inhibition by ATP or glucose. In contrast, the sulfonylurea tolbutamide, a specific blocker of K(ATP) channels, closed K(ATP) channels, elevated intracellular calcium levels, and stimulated insulin release in beta-V59M beta cells, indicating that events downstream of K(ATP) channel closure remained intact. Expression of the V59M Kir6.2 mutation in pancreatic beta cells alone is thus sufficient to recapitulate the neonatal diabetes observed in humans. beta-V59M islets also displayed a reduced percentage of beta cells, abnormal morphology, lower insulin content, and decreased expression of Kir6.2, SUR1, and insulin mRNA. All these changes are expected to contribute to the diabetes of beta-V59M mice. Their cause requires further investigation.

Theory of small-signal ac response of a dielectric liquid containing two groups of ions

The analysis of Macdonald for electrolytes is generalized to the case in which two groups of ions are present. We assume that the electrolyte can be considered as a dispersion of ions in a dielectric liquid, and that the ionic recombination can be neglected. We present the differential equations governing the ionic redistribution when the liquid is subjected to an external electric field, describing the simultaneous diffusion of the two groups of ions in the presence of their own space charge fields. We investigate the influence of the ions on the impedance spectroscopy of an electrolytic cell. In the analysis, we assume that each group of ions have equal mobility, the electrodes perfectly block and that the adsorption phenomena can be neglected. In this framework, it is shown that the real part of the electrical impedance of the cell has a frequency dependence presenting two plateaux, related to a type of ambipolar and free diffusion coefficients. The importance of the considered problem on the ionic characterization performed by means of the impedance spectroscopy technique was discussed. (c) 2008 American Institute of Physics.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.