Optimal measurement of visual motion across spatial and temporal scales

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli

Attenuation of Helicobacter pylori-induced gastric inflammation by prior cag− strain (AM1) infection in C57BL/6 mice

Helicobacter pylori, colonize in stomach of ~50% of the world population. cag pathogenicity Island of H. pylori is one of the important virulent factors that attributed to gastric inflammation. Coinfection with H. pylori strain with different genetic makeup alters the degree of pathogenicity and susceptibility towards antibiotics. The present study investigates host immunomodulatory effects of H. pylori infection by both cag+ strain (SS1) and cag− strain (AM1). C57BL/6 mice were infected with AM1 or SS1 strain as well as AM1 followed by SS1 (AM1/SS1) and vice versa. Results: Mice infected with AM1/SS1 strain exhibited less gastric inflammation and reduced proMMP9 and proMMP3 activities in gastric tissues as compared to SS1/SS1 and SS1/AM1 infected groups. The expression of both MMP9 and MMP3 followed similar trend like activity in infected tissues. Both Th1 and Th17 responses were induced by SS1 strain more profoundly than AM1 strain infection which induced solely Th1 response in spleen and gastric tissues. Moreover, IFN-γ, TNF-α, IL-1β and IL-12 were significantly downregulated in mice spleen and gastric tissues infected by AM1/SS1 compared to SS1/SS1 but not with SS1/AM1 coinfection. Surprisingly, IL-17 level was dampened significantly in AM1/ SS1 compared to SS1/AM1 coinfected groups. Furthermore, number of Foxp3+ T-regulatory (Treg) cells and immunosuppressive cytokines like IL-10 and TGF-β were reduced in AM1/SS1 compared to SS1/SS1 and SS1/AM1 coinfected mice gastric tissues. Conclusions: These data suggested that prior H. pylori cag− strain infection attenuated the severity of gastric pathology induced by subsequent cag+ strain in C57BL/6 mice. Prior AM1 infection induced Th1 cytokine IFN-γ, which reduced the Th17 response induced by subsequent SS1 infection. The reduced gastritis in AM1/SS1-infected mice might also be due to enrichment of AM1- primed Treg cells in the gastric compartment which inhibit Th1 and Th17 responses to subsequent SS1 infection. In summary, prior infection by non-virulent H. pylori strain (AM1) causes reduction of subsequent virulent strain (SS1) infection by regulation of inflammatory cytokines and MMPs expressio

Hadamard upper bound on optimum joint decoding capacity of Wyner Gaussian cellular MAC

This article presents an original analytical expression for an upper bound on the optimum joint decoding capacity of Wyner circular Gaussian cellular multiple access channel (C-GCMAC) for uniformly distributed mobile terminals (MTs). This upper bound is referred to as Hadamard upper bound (HUB) and is a novel application of the Hadamard inequality established by exploiting the Hadamard operation between the channel fading matrix G and the channel path gain matrix Ω. This article demonstrates that the actual capacity converges to the theoretical upper bound under the constraints like low signal-to-noise ratios and limiting channel path gain among the MTs and the respective base station of interest. In order to determine the usefulness of the HUB, the behavior of the theoretical upper bound is critically observed specially when the inter-cell and the intra-cell time sharing schemes are employed. In this context, we derive an analytical form of HUB by employing an approximation approach based on the estimation of probability density function of trace of Hadamard product of two matrices, i.e., G and Ω. A closed form of expression has been derived to capture the effect of the MT distribution on the optimum joint decoding capacity of C-GCMAC. This article demonstrates that the analytical HUB based on the proposed approximation approach converges to the theoretical upper bound results in the medium to high signal to noise ratio regime and shows a reasonably tighter bound on optimum joint decoding capacity of Wyner GCMAC

Unsupervised feature selection for noisy data

Feature selection techniques are enormously applied in a variety of data analysis tasks in order to reduce the dimensionality. According to the type of learning, feature selection algorithms are categorized to: supervised or unsupervised. In unsupervised learning scenarios, selecting features is a much harder problem, due to the lack of class labels that would facilitate the search for relevant features. The selecting feature difficulty is amplified when the data is corrupted by different noises. Almost all traditional unsupervised feature selection methods are not robust against the noise in samples. These approaches do not have any explicit mechanism for detaching and isolating the noise thus they can not produce an optimal feature subset. In this article, we propose an unsupervised approach for feature selection on noisy data, called Robust Independent Feature Selection (RIFS). Specifically, we choose feature subset that contains most of the underlying information, using the same criteria as the Independent component analysis (ICA). Simultaneously, the noise is separated as an independent component. The isolation of representative noise samples is achieved using factor oblique rotation whereas noise identification is performed using factor pattern loadings. Extensive experimental results over divers real-life data sets have showed the efficiency and advantage of the proposed algorithm.We thankfully acknowledge the support of the Comision Interministerial de Ciencia y Tecnologa (CICYT) under contract No. TIN2015-65316-P which has partially funded this work.Peer ReviewedPostprint (author's final draft

Water-induced modulation of Helicobacter pylori virulence properties

While the influence of water in Helicobacter pylori culturability and membrane integrity has been extensively studied, there are little data concerning the effect of this environment on virulence properties. Therefore, we studied the culturability of water-exposed H. pylori and determined whether there was any relation with the bacterium’s ability to adhere, produce functional components of pathogenicity and induce inflammation and alterations in apoptosis in an experimental model of human gastric epithelial cells. H. pylori partially retained the ability to adhere to epithelial cells even after complete loss of culturability. However, the microorganism is no longer effective in eliciting in vitro host cell inflammation and apoptosis, possibly due to the non-functionality of the cag type IV secretion system. These H. pylori-induced host cell responses, which are lost along with culturability, are known to increase epithelial cell turnover and, consequently, could have a deleterious effect on the initial H. pylori colonisation process. The fact that adhesion is maintained by H. pylori to the detriment of other factors involved in later infection stages appears to point to a modulation of the physiology of the pathogen after water exposure and might provide the microorganism with the necessary means to, at least transiently, colonise the human stomach.FCT (SFRH/BD/24579/2005) (to NMG

Sphingomyelin Functions as a Novel Receptor for Helicobacter pylori VacA

The vacuolating cytotoxin (VacA) of the gastric pathogen Helicobacter pylori binds and enters epithelial cells, ultimately resulting in cellular vacuolation. Several host factors have been reported to be important for VacA function, but none of these have been demonstrated to be essential for toxin binding to the plasma membrane. Thus, the identity of cell surface receptors critical for both toxin binding and function has remained elusive. Here, we identify VacA as the first bacterial virulence factor that exploits the important plasma membrane sphingolipid, sphingomyelin (SM), as a cellular receptor. Depletion of plasma membrane SM with sphingomyelinase inhibited VacA-mediated vacuolation and significantly reduced the sensitivity of HeLa cells, as well as several other cell lines, to VacA. Further analysis revealed that SM is critical for VacA interactions with the plasma membrane. Restoring plasma membrane SM in cells previously depleted of SM was sufficient to rescue both toxin vacuolation activity and plasma membrane binding. VacA association with detergent-resistant membranes was inhibited in cells pretreated with SMase C, indicating the importance of SM for VacA association with lipid raft microdomains. Finally, VacA bound to SM in an in vitro ELISA assay in a manner competitively inhibited by lysenin, a known SM-binding protein. Our results suggest a model where VacA may exploit the capacity of SM to preferentially partition into lipid rafts in order to access the raft-associated cellular machinery previously shown to be required for toxin entry into host cells

Genome sequence analysis of Helicobacter pylori strains associated with gastric ulceration and gastric cancer

<p>Abstract</p> <p>Background</p> <p>Persistent colonization of the human stomach by <it>Helicobacter pylori </it>is associated with asymptomatic gastric inflammation (gastritis) and an increased risk of duodenal ulceration, gastric ulceration, and non-cardia gastric cancer. In previous studies, the genome sequences of <it>H. pylori </it>strains from patients with gastritis or duodenal ulcer disease have been analyzed. In this study, we analyzed the genome sequences of an <it>H. pylori </it>strain (98-10) isolated from a patient with gastric cancer and an <it>H. pylori </it>strain (B128) isolated from a patient with gastric ulcer disease.</p> <p>Results</p> <p>Based on multilocus sequence typing, strain 98-10 was most closely related to <it>H. pylori </it>strains of East Asian origin and strain B128 was most closely related to strains of European origin. Strain 98-10 contained multiple features characteristic of East Asian strains, including a type s1c <it>vacA </it>allele and a <it>cagA </it>allele encoding an EPIYA-D tyrosine phosphorylation motif. A core genome of 1237 genes was present in all five strains for which genome sequences were available. Among the 1237 core genes, a subset of alleles was highly divergent in the East Asian strain 98-10, encoding proteins that exhibited <90% amino acid sequence identity compared to corresponding proteins in the other four strains. Unique strain-specific genes were identified in each of the newly sequenced strains, and a set of strain-specific genes was shared among <it>H. pylori </it>strains associated with gastric cancer or premalignant gastric lesions.</p> <p>Conclusion</p> <p>These data provide insight into the diversity that exists among <it>H. pylori </it>strains from diverse clinical and geographic origins. Highly divergent alleles and strain-specific genes identified in this study may represent useful biomarkers for analyzing geographic partitioning of <it>H. pylori </it>and for identifying strains capable of inducing malignant or premalignant gastric lesions.</p

PatternLab for proteomics: a tool for differential shotgun proteomics

<p>Abstract</p> <p>Background</p> <p>A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu <it>et al</it>. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen <it>et al</it>. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.</p> <p>Results</p> <p>To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen <it>et al</it>. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine) because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies.</p> <p>Conclusion</p> <p>PatternLab offers an easy and unified access to a variety of feature selection and normalization strategies, each having its own niche. Additionally, graphing tools are available to aid in the analysis of high throughput experimental data. PatternLab is available at <url>http://pcarvalho.com/patternlab</url>.</p

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster

Epidemiology of reported Yersinia enterocolitica infections in Germany, 2001-2008

<p>Abstract</p> <p>Background</p> <p>Yersiniosis is the third most common zoonotic bacterial disease in Germany and the European Union. Sequelae of <it>Yersinia enterocolitica </it>infections, such as reactive arthritis, have been reported. Consumption of pork and its products, especially eaten raw or undercooked, is an important risk factor of yersiniosis. Infection with <it>Y. enterocolitica </it>is notifiable through the national surveillance system for infectious diseases in Germany and several thousands of cases are being reported each year. We present recent data on the epidemiology of reported yersiniosis in Germany.</p> <p>Methods</p> <p>Surveillance data on yersiniosis, accessed through the national level database (SurvNet), were analyzed with regard to time trends, demographical and geographical distribution, serotypes, and hospitalization, for the time period 2001-2008.</p> <p>Results</p> <p>A total of 47,627 cases of yersiniosis were reported. The mean annual incidence of yersiniosis was 7.2/100,000 population. A downward trend in the number of reportable cases has occurred since 2002. Almost all <it>Y. enterocolitica </it>infections were reported as single cases, i.e., with no apparent links to other cases. The number of reported infections showed substantially less seasonal variation than in other zoonotic enteric diseases. The incidence was highest in children under five years (58/100,000 population), in particular in one-year-old children (108/100,000 population). Almost 97% of infections were acquired domestically. High incidences occurred in the eastern German federal states Thuringia, Saxony, and Saxony-Anhalt. Differences in incidences across federal states were driven primarily by incidence differences in children under five years. Hospitalization was reported for 17% of cases, the proportion being highest among teenagers. Almost 90% of <it>Y. enterocolitica </it>strains were diagnosed as serotype O:3, which is the serotype most frequently isolated from pigs.</p> <p>Conclusions</p> <p>Yersiniosis is a zoonotic foodborne disease of relevance to public health in Germany because of its high incidence and risk for sequelae. The incidence of reported yersiniosis in Germany varies markedly from state to state, mainly due to incidence difference among young children. More research efforts should be directed towards the elucidation of risk factors of yersiniosis in this age group.</p