New multiple matched filter: design and experimental realization

A method of making a multiple matched filter which allows the recognition of different characters in successive planes in simple conditions is proposed. The generation of the filter is based on recording on the same plate the Fourier transforms of the different patterns to be recognized, each of which is affected by different spherical phase factors because the patterns have been placed at different distances from the lens. This is proved by means of experiments with a triple filter which allows satisfactory recognition of three characters.

Stochastic multiresonance

We present a class of systems for which the signal-to-noise ratio as a function of the noise level may display a multiplicity of maxima. This phenomenon, referred to as stochastic multiresonance, indicates the possibility that periodic signals may be enhanced at multiple values of the noise level, instead of at a single value which has occurred in systems considered up to now in the framework of stochastic resonance.

Respiratory chain dysfunction associated with multiple mitochondrial DNA deletions in antiretroviral therapy-related lipodystrophy.

Highly-active antiretroviral therapy (HAART) can induce a characteristic lipodystrophy syndrome characterized by peripheral fat wasting and central adiposity, usually associated with hyperlipidaemia and insulin resistance [1,2]. Indirect data have led some authors to propose that mitochondrial dysfunction could play a role in this syndrome [3,4].To date, as recently outlined by Kakuda et al. [5] in this journal, HIV-infected patients developing lipodystrophy have not been studied for mitochondrial changes or respiratory chain capacity...

Podocalyxin is a novel polysialylated neural adhesion protein with multiple roles in neural development and synapse formation

Neural development and plasticity are regulated by neural adhesion proteins, including the polysialylated form of NCAM (PSA-NCAM). Podocalyxin (PC) is a renal PSA-containing protein that has been reported to function as an anti-adhesin in kidney podocytes. Here we show that PC is widely expressed in neurons during neural development. Neural PC interacts with the ERM protein family, and with NHERF1/2 and RhoA/G. Experiments in vitro and phenotypic analyses of podxl-deficient mice indicate that PC is involved in neurite growth, branching and axonal fasciculation, and that PC loss-of-function reduces the number of synapses in the CNS and in the neuromuscular system. We also show that whereas some of the brain PC functions require PSA, others depend on PC per se. Our results show that PC, the second highly sialylated neural adhesion protein, plays multiple roles in neural development.

Multiple processes regulate long-term population dynamics of sea urchins on Mediterranean rocky reefs

We annually monitored the abundance and size structure of herbivorous sea urchin populations (Paracentrotus lividus and Arbacia lixula) inside and outside a marine reserve in the Northwestern Mediterranean on two distinct habitats (boulders and vertical walls) over a period of 20 years, with the aim of analyzing changes at different temporal scales in relation to biotic and abiotic drivers. P. lividus exhibited significant variability in density over time on boulder bottoms but not on vertical walls, and temporal trends were not significantly different between the protection levels. Differences in densities were caused primarily by variance in recruitment, which was less pronounced inside the MPA and was correlated with adult density, indicating density-dependent recruitment under high predation pressure, as well as some positive feedback mechanisms that may facilitate higher urchin abundances despite higher predator abundance. Populations within the reserve were less variable in abundance and did not exhibit the hyper-abundances observed outside the reserve, suggesting that predation effects maybe more subtle than simply lowering the numbers of urchins in reserves. A. lixula densities were an order of magnitude lower than P. lividus densities and varied within sites and over time on boulder bottoms but did not differ between protection levels. In December 2008, an exceptionally violent storm reduced sea urchin densities drastically (by 50% to 80%) on boulder substrates, resulting in the lowest values observed over the entire study period, which remained at that level for at least two years (up to the present). Our results also showed great variability in the biological and physical processes acting at different temporal scales. This study highlights the need for appropriate temporal scales for studies to fully understand ecosystem functioning, the concepts of which are fundamental to successful conservation and management.

Rockfall induced seismic signals: case study in Montserrat, Catalonia

After a rockfall event, a usual post event survey includes qualitative volume estimation, trajectory mapping and determination of departing zones. However, quantitative measurements are not usually made. Additional relevant quantitative information could be useful in determining the spatial occurrence of rockfall events and help us in quantifying their size. Seismic measurements could be suitable for detection purposes since they are non invasive methods and are relatively inexpensive. Moreover, seismic techniques could provide important information on rockfall size and location of impacts. On 14 February 2007 the Avalanche Group of the University of Barcelona obtained the seismic data generated by an artificially triggered rockfall event at the Montserrat massif (near Barcelona, Spain) carried out in order to purge a slope. Two 3 component seismic stations were deployed in the area about 200 m from the explosion point that triggered the rockfall. Seismic signals and video images were simultaneously obtained. The initial volume of the rockfall was estimated to be 75 m3 by laser scanner data analysis. After the explosion, dozens of boulders ranging from 10¿4 to 5 m3 in volume impacted on the ground at different locations. The blocks fell down onto a terrace, 120 m below the release zone. The impact generated a small continuous mass movement composed of a mixture of rocks, sand and dust that ran down the slope and impacted on the road 60 m below. Time, time-frequency evolution and particle motion analysis of the seismic records and seismic energy estimation were performed. The results are as follows: 1 ¿ A rockfall event generates seismic signals with specific characteristics in the time domain; 2 ¿ the seismic signals generated by the mass movement show a time-frequency evolution different from that of other seismogenic sources (e.g. earthquakes, explosions or a single rock impact). This feature could be used for detection purposes; 3 ¿ particle motion plot analysis shows that the procedure to locate the rock impact using two stations is feasible; 4 ¿ The feasibility and validity of seismic methods for the detection of rockfall events, their localization and size determination are comfirmed.

Resveratrol: A polyphenol with multiple effects

trans-Resveratrol (trans-3,5,4'-trihydroxystilbene) is a natural polyphenol that occurs in grapes, berries, peanuts, and several traditional medicines. A number of studies have demonstrated that this polyphenol holds promise against numerous age-associated diseases including cancer, diabetes, Alzheimer, cardiovascular and pulmonary diseases. In view of these studies, resveratrol's prospects for use in the clinics are rapidly accelerating. This review summarizes our work on the mechanisms involved in the intestinal absorption and its population pharmacokinetics. Finally, various targets of resveratrol and its therapeutic potential are described.

A nuclear defect in the 4p16 region predisposes to multiple mitochondrial DNA deletions in families with Wolfram syndrome.

Wolfram syndrome is a progressive neurodegenerative disorder transmitted in an autosomal recessive mode. We report two Wolfram syndrome families harboring multiple deletions of mitochondrial DNA. The deletions reached percentages as high as 85-90% in affected tissues such as the central nervous system of one patient, while in other tissues from the same patient and from other members of the family, the percentages of deleted mitochondrial DNA genomes were only 1-10%. Recently, a Wolfram syndrome gene has been linked to markers on 4p16. In both families linkage between the disease locus and 4p16 markers gave a maximum multipoint lod score of 3.79 at theta = 0 (Pi<0.03) with respect to D4S431. In these families, the syndrome was caused by mutations in this nucleus-encoded gene which deleteriously interacts with the mitochondrial genome. This is the first evidence of the implication of both genomes in a recessive disease.

A nuclear defect in the 4p16 region predisposes to multiple mitochondrial DNA deletions in families with Wolfram syndrome.

Wolfram syndrome is a progressive neurodegenerative disorder transmitted in an autosomal recessive mode. We report two Wolfram syndrome families harboring multiple deletions of mitochondrial DNA. The deletions reached percentages as high as 85-90% in affected tissues such as the central nervous system of one patient, while in other tissues from the same patient and from other members of the family, the percentages of deleted mitochondrial DNA genomes were only 1-10%. Recently, a Wolfram syndrome gene has been linked to markers on 4p16. In both families linkage between the disease locus and 4p16 markers gave a maximum multipoint lod score of 3.79 at theta = 0 (Pi<0.03) with respect to D4S431. In these families, the syndrome was caused by mutations in this nucleus-encoded gene which deleteriously interacts with the mitochondrial genome. This is the first evidence of the implication of both genomes in a recessive disease.

Automatic filtering and substantiation of drug safety signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions

Neutralizing antibodies in Multiple Sclerosis a model-based analysis of Interferon beta signaling pathway in macrophages

Multiple Sclerosis is the most common non-traumatic cause of neurologicaldisability in young people. There is no cure yet, and until recently, few long-termtherapies existed. Interferon beta (IFNβ) was the first treatment, and remains the mostcommonly prescribed. One of the most significant problems of IFNβ therapy is theproduction of drug specific antibodies. Up to 45% of patients develop neutralizingantibodies (NAbs) to IFNβ products. The neutralizing antibody binds to the biologicalagent preventing its interaction with its receptor, inhibiting the biological action of theprotein, which abrogates the clinical efficacy of IFNβ treatment. Interferon-betamediates its response by binding to its high affinity cell surface receptor and initiatingthe JAK/STAT signalling cascade. In this project we have analyzed the IFNβ signalingpathway in macrophages when neutralizing antibodies are present. The response tothis pathway after IFNβ stimulation shows a transient oscillatory rhythm of STAT1phosphorylation, which varies as NAbs concentration increases. To improve ourunderstanding of that behavior, we extended an existing mathematical model based onnonlinear ordinary differential equations of JAK/STAT pathway by including IFN-NAbassociation and IFN-activation receptor. Combining our theoretical model withexperimental data we could study the role of neutralizing antibodies on the molecularresponse and determine its lifetime after cytokine stimulation.

Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals

Background: oscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies. Oscillatory burst events should consequently play a specific functional role, distinct from background EEG activity – especially for cognitive tasks (e.g. working memory tasks), binding mechanisms and perceptual dynamics (e.g. visual binding), or in clinical contexts (e.g. effects of brain disorders). However extracting oscillatory events in single trials, with a reliable and consistent method, is not a simple task. Results: in this work we propose a user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals. The software is provided with a Matlab toolbox which can compute wavelet representations before calling automatically the stand-alone application. Conclusion: The tool is publicly available as a freeware at the address: http:// www.bsp.brain.riken.jp/bumptoolbox/toolbox_home.html

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.

Blind channel deconvolution of real world signals using source separation techniques

In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.