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...

Analog circuit for real-time computation of respiratory mechanical impedance in sleep studies

The aim of this work was to develop a low-cost circuit for real-time analog computation of the respiratory mechanical impedance in sleep studies. The practical performance of the circuit was tested in six patients with obstructive sleep apnea. The impedance signal provided by the analog circuit was compared with the impedance calculated simultaneously with a conventional computerized system. We concluded that the low-cost analog circuit developed could be a useful tool for facilitating the real-time assessment of airway obstruction in routine sleep studies.

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.

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

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

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.

Orchestration signals in the classroom: managing the jigsaw collaborative learning flow

The orchestration of collaborative learning processes in face-to-facephysical settings, such as classrooms, requires teachers to coordinate students indicating them who belong to each group, which collaboration areas areassigned to each group, and how they should distribute the resources or roles within the group. In this paper we present an Orchestration Signal system,composed of wearable Personal Signal devices and an Orchestration Signal manager. Teachers can configure color signals in the manager so that they are transmitted to the wearable devices to indicate different orchestration aspects.In particular, the paper describes how the system has been used to carry out a Jigsaw collaborative learning flow in a classroom where students received signals indicating which documents they should read, in which group they were and in which area of the classroom they were expected to collaborate. The evaluation results show that the proposed system facilitates a dynamic, visual and flexible orchestration.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Waveform-independent frame-timing acquisition for UWB signals

In this paper, the problem of frame-level symboltiming acquisition for UWB signals is addressed. The main goalis the derivation of a frame-level timing estimator which does notrequire any prior knowledge of neither the transmitted symbolsnor the received template waveform. The independence withrespect to the received waveform is of special interest in UWBcommunication systems, where a fast and accurate estimation ofthe end-to-end channel response is a challenging and computationallydemanding task. The proposed estimator is derived under theunconditional maximum likelihood criterion, and because of thelow power of UWB signals, the low-SNR assumption is adopted. Asa result, an optimal frame-level timing estimator is derived whichoutperforms existing acquisition methods in low-SNR scenarios.

Reversible mitochondrial respiratory chain impairment during symptomatic hyperlactatemia associated with antiretroviral therapy

Direct evidence confirming the hypothesis that a dysfunction of the mitochondrial respiratory chain (MRC) underlies the pathogenesis of hyperlactatemia associated with highly active antiretroviral therapy (HAART) is scarce. We studied mitochondrial DNA (mtDNA) content and MRC function in the skeletal muscle of an HIV-infected patient during an episode of symptomatic hyperlactatemia. Skeletal muscle biopsy was performed during the episode when the patient was symptomatic and 3 months later when the patient was clinically recovered. Assessment of mitochondria was performed using histological, polarographic, spectrophotometrical, and Southern blot and real time PCR DNA quantification methods. The histological study disclosed extensive mitochondrial impairment in the form of ragged-red fibers or equivalents on oxidative reactions. These findings were associated with an increase in mitochondrial content and a decrease in both mitochondrial respiratory capacity and MRC enzyme activities. Mitochondrial DNA content declined to 53% of control values. Mitochondrial abnormalities had almost disappeared later when the patient became asymptomatic. Our findings support the hypothesis that MRC dysfunction stands at the basis of HAART-related hyperlactatemia.

Reversible mitochondrial respiratory chain impairment during symptomatic hyperlactatemia associated with antiretroviral therapy

Direct evidence confirming the hypothesis that a dysfunction of the mitochondrial respiratory chain (MRC) underlies the pathogenesis of hyperlactatemia associated with highly active antiretroviral therapy (HAART) is scarce. We studied mitochondrial DNA (mtDNA) content and MRC function in the skeletal muscle of an HIV-infected patient during an episode of symptomatic hyperlactatemia. Skeletal muscle biopsy was performed during the episode when the patient was symptomatic and 3 months later when the patient was clinically recovered. Assessment of mitochondria was performed using histological, polarographic, spectrophotometrical, and Southern blot and real time PCR DNA quantification methods. The histological study disclosed extensive mitochondrial impairment in the form of ragged-red fibers or equivalents on oxidative reactions. These findings were associated with an increase in mitochondrial content and a decrease in both mitochondrial respiratory capacity and MRC enzyme activities. Mitochondrial DNA content declined to 53% of control values. Mitochondrial abnormalities had almost disappeared later when the patient became asymptomatic. Our findings support the hypothesis that MRC dysfunction stands at the basis of HAART-related hyperlactatemia.

Two distinct plant respiratory physiotypes might exist which correspond to fast-growing and slow-growing species

The origin of the carbon atoms in CO2 respired by leaves in the dark of several plant species has been studied using 13C/12C stable isotopes. This study was conducted using an open gas exchange system for isotope labeling that was coupled to an elemental analyser and further linked to an isotope ratio mass spectrometer (EA-IRMS) or coupled to a gas chromatography-combustion-isotope ratio mass spectrometer (GC-C-IRMS). We demonstrate here that the carbon, which is recently assimilated during photosynthesis, accounts for nearly ca. 50% of the carbon in the CO2 lost through dark respiration after illumination in fast-growing and cultivated plants and trees and, accounts for only ca. 10% in slow-growing plants. Moreover, our study shows that fast- growing plants, which had the largest percentages of newly fixed carbon of leaf-respired CO2 , were also those with the largest shoot/root ratios, whereas slow-growing plants showed the lowest shoot/root values.

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.