A RAPID AND SENSITIVE HPLC METHOD FOR THE ANALYSIS OF PROGUNAIL AND CYCLOGUANIL IN PLASMA: APPLICATION TO SINGLE DOSE PHARMACOKINETIC STUDIES

A simple, sensitive cost-effective and reproducible reverse phase high performance liquidchromatographic (HPLC) method was developed to quantitate plasma levels of proguanil(PGN) and its active metabolite, cycloguanil (CGN) in order to conduct single dosepharmacokinetic studies. The drug and the internal standard were added to plasma samples,vortexed and rendered alkaline with 2 M NaoH and the samples extracted with ether,evaporated to dryness and the residue was reconstituted in methanol, whirlmixed beforeinjecting an aliquot onto the HPLC system. The calibration plots were linear over theconcentration range up to 4.0 μg /ml. The correlation coefficients (r) were of the order of 0.99and above for both PGN and CGN. The ion pair method was carried out on a 5 μ reversephase C-18 column, using perchlorate ion as the counter ion and ultra violet detection at 254nm. The method was reproducible with coefficient of variation for PGN and CGN, being lessthan 4.0 %. PGN was well resolved from its active metabolite, CGN, and the internalstandard, pyrimethamine. The limit of detection of PGN was 10 ng /ml and the recovery wasgreater than 95% in plasma. The analytical method therefore, exhibits good precision andsensitivity in detecting and quantifying PGN and CGN and has been demonstrated to besuitable for the pharmacokinetic studies of proguanil. The clinical applicability of the methodwas assessed by the preliminary pharmacokinetic study of PGN and CGN, in fifteen healthyvolunteers. The in vivo study was carried out according to a single dose randomized design

Bounded Verification with On-the-Fly Discrepancy Computation

Simulation-based verification algorithms can provide formal safety guarantees for nonlinear and hybrid systems. The previous algorithms rely on user provided model annotations called discrepancy function, which are crucial for computing reachtubes from simulations. In this paper, we eliminate this requirement by presenting an algorithm for computing piece-wise exponential discrepancy functions. The algorithm relies on computing local convergence or divergence rates of trajectories along a simulation using a coarse over-approximation of the reach set and bounding the maximal eigenvalue of the Jacobian over this over-approximation. The resulting discrepancy function preserves the soundness and the relative completeness of the verification algorithm. We also provide a coordinate transformation method to improve the local estimates for the convergence or divergence rates in practical examples. We extend the method to get the input-to-state discrepancy of nonlinear dynamical systems which can be used for compositional analysis. Our experiments show that the approach is effective in terms of running time for several benchmark problems, scales reasonably to larger dimensional systems, and compares favorably with respect to available tools for nonlinear models.Comment: 24 page

Simulation-based reachability analysis for nonlinear systems using componentwise contraction properties

A shortcoming of existing reachability approaches for nonlinear systems is the poor scalability with the number of continuous state variables. To mitigate this problem we present a simulation-based approach where we first sample a number of trajectories of the system and next establish bounds on the convergence or divergence between the samples and neighboring trajectories. We compute these bounds using contraction theory and reduce the conservatism by partitioning the state vector into several components and analyzing contraction properties separately in each direction. Among other benefits this allows us to analyze the effect of constant but uncertain parameters by treating them as state variables and partitioning them into a separate direction. We next present a numerical procedure to search for weighted norms that yield a prescribed contraction rate, which can be incorporated in the reachability algorithm to adjust the weights to minimize the growth of the reachable set

Approximate probabilistic verification of hybrid systems

Hybrid systems whose mode dynamics are governed by non-linear ordinary differential equations (ODEs) are often a natural model for biological processes. However such models are difficult to analyze. To address this, we develop a probabilistic analysis method by approximating the mode transitions as stochastic events. We assume that the probability of making a mode transition is proportional to the measure of the set of pairs of time points and value states at which the mode transition is enabled. To ensure a sound mathematical basis, we impose a natural continuity property on the non-linear ODEs. We also assume that the states of the system are observed at discrete time points but that the mode transitions may take place at any time between two successive discrete time points. This leads to a discrete time Markov chain as a probabilistic approximation of the hybrid system. We then show that for BLTL (bounded linear time temporal logic) specifications the hybrid system meets a specification iff its Markov chain approximation meets the same specification with probability $1$. Based on this, we formulate a sequential hypothesis testing procedure for verifying -approximately- that the Markov chain meets a BLTL specification with high probability. Our case studies on cardiac cell dynamics and the circadian rhythm indicate that our scheme can be applied in a number of realistic settings

Systematic and Realistic Testing in Simulation of Control Code for Robots in Collaborative Human-Robot Interactions

© Springer International Publishing Switzerland 2016. Industries such as flexible manufacturing and home care will be transformed by the presence of robotic assistants. Assurance of safety and functional soundness for these robotic systems will require rigorous verification and validation. We propose testing in simulation using Coverage-Driven Verification (CDV) to guide the testing process in an automatic and systematic way. We use a two-tiered test generation approach, where abstract test sequences are computed first and then concretized (e.g., data and variables are instantiated), to reduce the complexity of the test generation problem. To demonstrate the effectiveness of our approach, we developed a testbench for robotic code, running in ROS-Gazebo, that implements an object handover as part of a humanrobot interaction (HRI) task. Tests are generated to stimulate the robot’s code in a realistic manner, through stimulating the human, environment, sensors, and actuators in simulation. We compare the merits of unconstrained, constrained and model-based test generation in achieving thorough exploration of the code under test, and interesting combinations of human-robot interactions. Our results show that CDV combined with systematic test generation achieves a very high degree of automation in simulation-based verification of control code for robots in HRI

Implementation of behavioral systems

In this chapter, we study control by interconnection of a given linear differential system (the plant behavior) with a suitable controller. The problem formulations and their solutions are completely representation free, and specified only in terms of the system dynamics. A controller is a system that constrains the plant behavior through a certain set of variables. In this context, there are two main situations to be considered: either all the system variables are available for control, i.e., are control variables (full control) or only some of the variables are control variables (partial control). For systems evolving over a time domain (1D) the problems of implementability by partial (regular) interconnection are well understood. In this chapter, we study why similar results are not valid in themultidimensional (nD) case. Finally, we study two important classes of controllers, namely, canonical controllers and regular controllers

Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery.

BACKGROUND: The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation. NEW METHOD: We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously. RESULTS: We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimer's and Parkinson's diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes. COMPARISON WITH EXISTING METHODS: The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals. CONCLUSIONS: The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism

Multistep Inhibition of α-Synuclein Aggregation and Toxicity in Vitro and in Vivo by Trodusquemine.

The aggregation of α-synuclein, an intrinsically disordered protein that is highly abundant in neurons, is closely associated with the onset and progression of Parkinson's disease. We have shown previously that the aminosterol squalamine can inhibit the lipid induced initiation process in the aggregation of α-synuclein, and we report here that the related compound trodusquemine is capable of inhibiting not only this process but also the fibril-dependent secondary pathways in the aggregation reaction. We further demonstrate that trodusquemine can effectively suppress the toxicity of α-synuclein oligomers in neuronal cells, and that its administration, even after the initial growth phase, leads to a dramatic reduction in the number of α-synuclein inclusions in a Caenorhabditis elegans model of Parkinson's disease, eliminates the related muscle paralysis, and increases lifespan. On the basis of these findings, we show that trodusquemine is able to inhibit multiple events in the aggregation process of α-synuclein and hence to provide important information about the link between such events and neurodegeneration, as it is initiated and progresses. Particularly in the light of the previously reported ability of trodusquemine to cross the blood-brain barrier and to promote tissue regeneration, the present results suggest that this compound has the potential to be an important therapeutic candidate for Parkinson's disease and related disorders

Unexpected elevated alanine aminotransferase, asparte aminotransferase levels and hepatitis E virus infection among persons who work with pigs in accra, ghana

<p>Abstract</p> <p>Background</p> <p>Several studies have suggested that elevated serum alanine aminotransferase (ALT) and asparte aminotransferase (AST) may be markers of hepatitis E virus (HEV) infection. Thus, individuals with elevated ALT and AST may have ongoing subclinical infection of HEV. We estimated the prevalence of anti-HEV antibodies and serum ALT and AST levels among persons who work with pigs in Accra, Ghana.</p> <p>Results</p> <p>Three hundred and fifty- persons who work with pigs provided blood samples for unlinked anonymous testing for the presence of antibodies to HEV, ALT and AST levels. The median age of participants was 32.85 ± 11.38 years (range 15-70 years). HEV seroprevelance was 34.84%. Anti-HEV IgG was detected in 19.26% while anti-HEV IgM was detected in 15.58% of the persons who tested positive. On multivariate analysis, the independent determinants of HEV infection were, being employed on the farm for less than six months [odds ratio (OR) 8.96; 95% confidence interval (95% CI) 5.43-14.80], having piped water in the household and/or on the farm (OR 13.33; 95% CI 5.23-33.93) and consumption of alcohol (OR 4.91: 95% CI 2.65-9.10). Levels >3× the expected maximum were found for both ALT and AST among individuals who tested positive for anti-HEV IgG (ALT, 210.17 ± 11.64 U/L; AST, 127.18 ± 11.12 U/L) and anti-HEV IgM (ALT, 200.97 ± 10.76 U/L; AST, 120.00 ± 15.96 U/L).</p> <p>Conclusion</p> <p>Consistent with similar studies worldwide, the results of our studies revealed a high prevalence of HEV infection, ALT and AST values in pig handlers.</p