Smith Predictor Sliding Mode Closed-loop Glucose Controller in Type 1 Diabetes

Type 1 diabetic patients depend on external insulin delivery to keep their blood glucose within near-normal ranges. In this work, two robust closed-loop controllers for blood glucose regulation are developed to prevent the life-threatening hypoglycemia, as well as to avoid extended hyperglycemia. The proposed controllers are designed by using the sliding mode control technique in a Smith predictor structure. To improve meal disturbance rejection, a simple feedforward controller is added to inject meal-time insulin bolus. Simulations scenarios were used to test the controllers, and showed the controllers ability to maintain the glucose levels within the safe limits in the presence of errors in measurements, modeling and meal estimation

English grammar games in primary education

The purpose of this study was to analyse pupils’ English grammar acquisition from competitive and cooperative approaches. After searching a wide range of authors’ contribution to English language learning, grammar acquisition, classroom environment and language games. A hundred and twenty pupils from three schools; two from Ripoll and one from Campdevànol were enrolled in a specific grammar games intervention. This was imparted in three different phases: first of all, I interviewed the three teachers from the three schools, then I put into practice my competitive and cooperative games which I designed especially for this study (all the sessions were carried, assessed and registered by myself); finally, all pupils answered a questionnaire related to their experiences in my grammar games intervention. Analysis of teaching interventions showed that, in terms of English language acquisition, pupils used different strategies to show up understanding and achieve the objective of the game such as: recalling their background knowledge, expressing sentences influenced by their internal language and their mother tongue. Data collected revealed that most difficulties were founded in team work, even more in competitive games. The results also showed that team work is something which has to be developed step by step in order to achieve language learning and all pupils’ active participation successfully.

Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

Abstract Background: Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results: In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions: To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.

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.

First-passage and escape problems in the Feller process

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

Cross-validation of methods used for analysis of MTBE and other gasoline components in groundwater.

Head space gas chromatography with flame-ionization detection (HS-GC-FID), ancl purge and trap gas chromatography-mass spectrometry (P&T-GC-MS) have been used to determine methyl-tert-butyl ether (MTBE) and benzene, toluene, and the ylenes (BTEX) in groundwater. In the work discussed in this paper measures of quality, e.g. recovery (94-111%), precision (4.6 - 12.2%), limits of detection (0.3 - 5.7 I~g L 1 for HS and 0.001 I~g L 1 for PT), and robust-ness, for both methods were compared. In addition, for purposes of comparison, groundwater samples from areas suffering from odor problems because of fuel spillage and tank leakage were analyzed by use of both techniques. For high concentration levels there was good correlation between results from both methods.

Simultaneous determination of gross alpha, gross beta and Ra-226 in natural water by liquid scintillation counting.

The determination of gross alpha, gross beta and 226Ra activity in natural waters is useful in a wide range of environmental studies. Furthermore, gross alpha and gross beta parameters are included in international legislation on the quality of drinking water [Council Directive 98/83/EC].1 In this work, a low-background liquid scintillation counter (Wallac, Quantulus 1220) was used to simultaneously determine gross alpha, gross beta and 226Ra activity in natural water samples. Sample preparation involved evaporation to remove 222Rn and its short-lived decay daughters. The evaporation process concentrated the sample ten-fold. Afterwards, a sample aliquot of 8 mL was mixed with 12 mL of Ultima Gold AB scintillation cocktail in low-diffusion vials. In this study, a theoretical mathematical model based on secular equilibrium conditions between 226Ra and its short-lived decay daughters is presented. The proposed model makes it possible to determine 226Ra activity from two measurements. These measurements also allow determining gross alpha and gross beta simultaneously. To validate the proposed model, spiked samples with different activity levels for each parameter were analysed. Additionally, to evaluate the model's applicability in natural water, eight natural water samples from different parts of Spain were analysed. The eight natural water samples were also characterised by alpha spectrometry for the naturally occurring isotopes of uranium (234U, 235U and 238U), radium (224Ra and 226Ra), 210Po and 232Th. The results for gross alpha and 226Ra activity were compared with alpha spectrometry characterization, and an acceptable concordance was obtained.

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.

Quasi real-time Raman studies on the growth of Cu-In-S thin films

In this work annealing and growth of CuInS2 thin films is investigated with quasireal-time in situ Raman spectroscopy. During the annealing a shift of the Raman A1 mode towards lower wave numbers with increasing temperature is observed. A linear temperature dependence of the phonon branch of ¿2 cm¿1/100 K is evaluated. The investigation of the growth process (sulfurization of metallic precursors) with high surface sensitivity reveals the occurrence of phases which are not detected with bulk sensitive methods. This allows a detailed insight in the formation of the CuInS2 phases. Independent from stoichiometry and doping of the starting precursors the CuAu ordering of CuInS2 initially forms as the dominating ordering. The transformation of the CuAu ordering into the chalcopyrite one is, in contrast, strongly dependent on the precursor composition and requires high temperatures.

"In vitro" comparative experimental study of antimicrobial action of mouth washing products

Regular use of mouth rinses modifies the oral habitat, since bacterial populations are submitted to a high selective pressure during the treatment exercised by the active presence of the disinfectant. Mostly mouth rinses are based on the antibacterial effect of Chlorhexidine, Triclosan, essential oils and other antibacterials although other pharmaceutical characteristics can also affect their effectiveness. In this paper we compare"in vitro" the antibacterial effect of different oral rinsing solutions. Minimal Inhibitory Concentrations (MIC) and Minimal Bactericidal Concentrations (MBC) were determined as well as the kinetics of bacterial death in the presence of letal concentrations of the mouth rinses. MIC values expressed as Maximal Inhibitory Dilution (MID) of the mouth rinse ranged from 1 to 1/2048 depending on the microorganism and product, whereas Minimal Biocidal Concentration (MBC), expressed as Maximal Biocidal Dilution (MBD) ranged from 1 to 1/1024, being in general one dilution less than MIC. Maximal Biocidal Dilution is a good tool to measure the actual efficiency of mouth washing solutions. However, kinetics of death seems to be better in our work killing curves demonstrate that bacterial populations are mostly eliminated during the first minute after the contact of bacterial suspension and the mouth-washing solution. In all tested bacterial species mouth-washing solutions tested were able to reduce until suspension treated except 1 and 5

Validation study of the Spanish Version of the Work-Family Conflict Questionnaire (CCTF)

In this study, a brief Work-Family Conflict (WFC) Questionnaire in the Spanish language is proposed that takes into account the two directions commonly reported in the literature: work interference with family (WIF), and family interference with work (FIW). The results obtained through exploratory factor analyses (EFA) and confirmatory factor analyses (CFA) with two independent samples, carried out for women and men, showed acceptable validity and reliability. A copy of the instrument in Spanish language is provided, together with the Amos 4 syntax to perform the factor invariance analysis for women and men. The suggested Work-Family Conflict Questionnaire (in Spanish, abbreviated as CCTF) may be useful in studies performed in the work setting, considering the special relevance of the concept in this line of research.

Dissemination of periodic mammography and patterns of use, by birth cohort, in Catalonia (Spain)

Background: In Catalonia (Spain) breast cancer mortality has declined since the beginning of the 1990s. The dissemination of early detection by mammography and the introduction of adjuvant treatments are among the possible causes of this decrease, and both were almost coincident in time. Thus, understanding how these procedures were incorporated into use in the general population and in women diagnosed with breast cancer is very important for assessing their contribution to the reduction in breast cancer mortality. In this work we have modeled the dissemination of periodic mammography and described repeat mammography behavior in Catalonia from 1975 to 2006. Methods: Cross-sectional data from three Catalan Health Surveys for the calendar years 1994, 2002 and 2006 was used. The dissemination of mammography by birth cohort was modeled using a mixed effects model and repeat mammography behavior was described by age and survey year. Results: For women born from 1938 to 1952, mammography clearly had a period effect, meaning that they started to have periodic mammograms at the same calendar years but at different ages. The age at which approximately 50% of the women were receiving periodic mammograms went from 57.8 years of age for women born in 1938–1942 to 37.3 years of age for women born in 1963–1967. Women in all age groups experienced an increase in periodic mammography use over time, although women in the 50–69 age group have experienced the highest increase. Currently, the target population of the Catalan Breast Cancer Screening Program, 50–69 years of age, is the group that self-reports the highest utilization of periodic mammograms, followed by the 40–49 age group. A higher proportion of women of all age groups have annual mammograms rather than biennial or irregular ones. Conclusion: Mammography in Catalonia became more widely implemented during the 1990s. We estimated when cohorts initiated periodic mammograms and how frequently women are receiving them. These two pieces of information will be entered into a cost-effectiveness model of early detection in Catalonia.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Effect of cattle on Salmonella carriage, diversity and antimicrobial resistance in free-ranging wild boar (Sus scrofa) in northeastern Spain

Salmonella is distributed worldwide and is a pathogen of economic and public health importance. As a multi-host pathogen with a long environmental persistence, it is a suitable model for the study of wildlife-livestock interactions. In this work, we aim to explore the spill-over of Salmonella between free-ranging wild boar and livestock in a protected natural area in NE Spain and the presence of antimicrobial resistance. Salmonella prevalence, serotypes and diversity were compared between wild boars, sympatric cattle and wild boars from cattle-free areas. The effect of age, sex, cattle presence and cattle herd size on Salmonella probability of infection in wild boars was explored by means of Generalized Linear Models and a model selection based on the Akaike’s Information Criterion. Prevalence was higher in wild boars co-habiting with cattle (35.67%, CI 95% 28.19–43.70) than in wild boar from cattle-free areas (17.54%, CI 95% 8.74–29.91). Probability of a wild boar being a Salmonella carrier increased with cattle herd size but decreased with the host age. Serotypes Meleagridis, Anatum and Othmarschen were isolated concurrently from cattle and sympatric wild boars. Apart from serotypes shared with cattle, wild boars appear to have their own serotypes, which are also found in wild boars from cattle-free areas (Enteritidis, Mikawasima, 4:b:- and 35:r:z35). Serotype richness (diversity) was higher in wild boars co-habiting with cattle, but evenness was not altered by the introduction of serotypes from cattle. The finding of a S. Mbandaka strain resistant to sulfamethoxazole, streptomycin and chloramphenicol and a S. Enteritidis strain resistant to ciprofloxacin and nalidixic acid in wild boars is cause for public health concern.