Adherence to self-administered tuberculosis treatment in a high HIV-prevalence setting: a cross-sectional survey in Homa Bay, Kenya.

Good adherence to treatment is crucial to control tuberculosis (TB). Efficiency and feasibility of directly observed therapy (DOT) under routine program conditions have been questioned. As an alternative, Médecins sans Frontières introduced self-administered therapy (SAT) in several TB programs. We aimed to measure adherence to TB treatment among patients receiving TB chemotherapy with fixed dose combination (FDC) under SAT at the Homa Bay district hospital (Kenya). A second objective was to compare the adherence agreement between different assessment tools

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Evolutionary optimisation of neural network models for fish collective behaviours in mixed groups of robots and zebrafish

Animal and robot social interactions are interesting both for ethological studies and robotics. On the one hand, the robots can be tools and models to analyse animal collective behaviours, on the other hand, the robots and their artificial intelligence are directly confronted and compared to the natural animal collective intelligence. The first step is to design robots and their behavioural controllers that are capable of socially interact with animals. Designing such behavioural bio-mimetic controllers remains an important challenge as they have to reproduce the animal behaviours and have to be calibrated on experimental data. Most animal collective behavioural models are designed by modellers based on experimental data. This process is long and costly because it is difficult to identify the relevant behavioural features that are then used as a priori knowledge in model building. Here, we want to model the fish individual and collective behaviours in order to develop robot controllers. We explore the use of optimised black-box models based on artificial neural networks (ANN) to model fish behaviours. While the ANN may not be biomimetic but rather bio-inspired, they can be used to link perception to motor responses. These models are designed to be implementable as robot controllers to form mixed-groups of fish and robots, using few a priori knowledge of the fish behaviours. We present a methodology with multilayer perceptron or echo state networks that are optimised through evolutionary algorithms to model accurately the fish individual and collective behaviours in a bounded rectangular arena. We assess the biomimetism of the generated models and compare them to the fish experimental behaviours.Comment: 10 pages, 4 figure

How to Blend a Robot within a Group of Zebrafish: Achieving Social Acceptance through Real-time Calibration of a Multi-level Behavioural Model

We have previously shown how to socially integrate a fish robot into a group of zebrafish thanks to biomimetic behavioural models. The models have to be calibrated on experimental data to present correct behavioural features. This calibration is essential to enhance the social integration of the robot into the group. When calibrated, the behavioural model of fish behaviour is implemented to drive a robot with closed-loop control of social interactions into a group of zebrafish. This approach can be useful to form mixed-groups, and study animal individual and collective behaviour by using biomimetic autonomous robots capable of responding to the animals in long-standing experiments. Here, we show a methodology for continuous real-time calibration and refinement of multi-level behavioural model. The real-time calibration, by an evolutionary algorithm, is based on simulation of the model to correspond to the observed fish behaviour in real-time. The calibrated model is updated on the robot and tested during the experiments. This method allows to cope with changes of dynamics in fish behaviour. Moreover, each fish presents individual behavioural differences. Thus, each trial is done with naive fish groups that display behavioural variability. This real-time calibration methodology can optimise the robot behaviours during the experiments. Our implementation of this methodology runs on three different computers that perform individual tracking, data-analysis, multi-objective evolutionary algorithms, simulation of the fish robot and adaptation of the robot behavioural models, all in real-time.Comment: 9 pages, 3 figure

The inheritance of late blight resistance derived from Solanum habrochaites

Late blight caused by the oomycete Phytophthora infestans is a destructive disease of tomato in Brazil and other tropical and subtropical regions. The purpose of the present study was to analyses the inheritance of resistance to late blight and determine the genetic factors contributing to the resistance in the inbred line in '163A'. The Line '163A' resulted from interspecific cross between Solanum lycopersicum and S. habrochaites f. glabratum. Inoculated field with mixture isolates of pathogen with 1000 spores mL-1 and naturally infested field trials showed that the expression of '163A' against multiple isolates of the pathogen was stable. The genetic analysis supported the hypothesis of two recessive genes controlling the resistance. The scaling test of additive-dominance model showed that is a good fit for the data confirming the absence or neglect of epistasis

Electron acceleration in laboratory-produced turbulent collisionless shocks

Astrophysical collisionless shocks are among the most powerful particle accelerators in the Universe. Generated by violent interactions of supersonic plasma flows with the interstellar medium, supernova remnant shocks are observed to amplify magnetic fields and accelerate electrons and protons to highly relativistic speeds. In the well-established model of diffusive shock acceleration, relativistic particles are accelerated by repeated shock crossings. However, this requires a separate mechanism that pre-accelerates particles to enable shock crossing. This is known as the ‘injection problem’, which is particularly relevant for electrons, and remains one of the most important puzzles in shock acceleration. In most astrophysical shocks, the details of the shock structure cannot be directly resolved, making it challenging to identify the injection mechanism. Here we report results from laser-driven plasma flow experiments, and related simulations, that probe the formation of turbulent collisionless shocks in conditions relevant to young supernova remnants. We show that electrons can be effectively accelerated in a first-order Fermi process by small-scale turbulence produced within the shock transition to relativistic non-thermal energies, helping overcome the injection problem. Our observations provide new insight into electron injection at shocks and open the way for controlled laboratory studies of the physics underlying cosmic accelerators

Follow-Up of Patients with Multidrug Resistant Tuberculosis Four Years after Standardized First-Line Drug Treatment

Background: In 2004, an anti-tuberculosis (TB) drug resistance survey in Heilongjiang province, China, enrolled 1574 (79%) new and 421 (21%) retreatment patients. Multi-drug resistant (MDR) TB was detected in 7.2% of new and 30.4% of retreatment patients. All received treatment with standardized first-line drug (FLD) regimens. Methodology/Principal Findings: We report treatment outcomes of the 2004 cohort, and long-term outcomes as assessed in the second half of 2008. The reported cure rate for MDR-TB patients was 83% (94/113) among new and 66% (85/128) among retreatment patients (P<0.001). Ten of the 241 MDR-TB patients died during treatment. Of the remaining 231, 129 (56%) could be traced in 2008. The overall recurrence rates among new and retreatment cases were 46% and 66%, respectively (P=0.03). The overall death rates among new and retreatment cases were 25% and 46%, respectively (P=0.02). Forty percent of the traced new cases and 24% of the retreatment cases were alive and without recurrent TB (P=0.01). Of the 16 patients who failed or defaulted from treatment in 2004, only two patients were not re-diagnosed with TB by 2008. Of the 111 (86%) patients with an initial successful treatment outcome 63 (57%) had developed recurrent TB, 40 (36%) had died, 27 (24%) of them died of TB. The follow-up period of four years precluded follow-up of all patients. In a highly conservative sensitivity analysis in which we assumed that all non-included patients were alive and did not have recurrent TB, the recurrence and death rate were 33% and 21%. Conclusions/Significance: Documentation of cure based on conventional smear microscopy was a poor predictor of long term outcomes. MDR-TB patients in Heilongjiang province in China had high recurrence and death rates four years after treatment with standardized FLD regimens, reinforcing the need for early diagnosis and treatment of MDR-TB, including assessment of treatment outcomes with more sensitive laboratory method

Sleep disturbances in an arctic population: The Tromsø Study

<p>Abstract</p> <p>Background</p> <p>Prevalence estimates for insomnia range from 10 to 50% in the adult general population. Sleep disturbances cause great impairment in quality of life, which might even rival or exceed the impairment in other chronic medical disorders. The economic implications and use of health-care services related to chronic insomnia represent a clinical concern as well as a pronounced public health problem. Hypnotics are frequently prescribed for insomnia, but alcohol and over-the-counter sleep aids seem to be more widely used by insomniacs than prescription medications. Despite the complex relationship between insomnia and physical and mental health factors, the condition appears to be underrecognized and undertreated by health care providers, probably due to the generally limited knowledge of the causes and natural development of insomnia.</p> <p>Methods/Design</p> <p>The Tromsø Study is an ongoing population-based cohort study with five previous health studies undertaken between 1974 and 2001. This protocol outlines a planned study within the sixth Tromsø Study (Tromsø VI), aiming at; 1) describing sleep patterns in a community-based sample representative of the general population of northern Norway, and 2) examining outcome variables of sleep disturbances against possible explanatory and confounding variables, both within a cross-sectional approach, as well as retrospectively in a longitudinal study – exploring sleep patterns in subjects who have attended two or more of the previous Tromsø studies between 1974 and 2009. First, we plan to perform a simple screening in order to identify those participants with probable sleep disturbances, and secondly to investigate these sleep disturbances further, using an extensive sleep-questionnaire. We will also collect biological explanatory variables, i.e. blood samples, weight, height and blood pressure. We plan to merge data on an individual level from the Tromsø VI Study with data from the Norwegian Prescription Database (NorPD), which is a national registry including data for all prescription drugs issued at Norwegian pharmacies. Participants with sleep disturbances will be compared with pair-matched controls without sleep disturbances.</p> <p>Discussion</p> <p>Despite ongoing research, many challenges remain in the characterization of sleep disturbances and its correlates. Future mapping of the biological dimensions, natural history, as well as the behavioral and drug-related aspects of sleep disturbances in a representative population samples is clearly needed.</p

Rice-Map: a new-generation rice genome browser

<p>Abstract</p> <p>Background</p> <p>The concurrent release of rice genome sequences for two subspecies (<it>Oryza sativa </it>L. ssp. <it>japonica </it>and <it>Oryza sativa </it>L. ssp. <it>indica</it>) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively.</p> <p>Description</p> <p>More than one hundred annotation tracks (81 for <it>japonica </it>and 82 for <it>indica</it>) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria.</p> <p>Conclusions</p> <p>Rice-Map delivers abundant up-to-date <it>japonica </it>and <it>indica </it>annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at <url>http://www.ricemap.org/</url>, with all data available for free downloading.</p