Leishmania Promastigotes Lack Phosphatidylserine but Bind Annexin V upon Permeabilization or Miltefosine Treatment

The protozoan parasite Leishmania is an intracellular pathogen infecting and replicating inside vertebrate host macrophages. A recent model suggests that promastigote and amastigote forms of the parasite mimic mammalian apoptotic cells by exposing phosphatidylserine (PS) at the cell surface to trigger their phagocytic uptake into host macrophages. PS presentation at the cell surface is typically analyzed using fluorescence-labeled annexin V. Here we show that Leishmania promastigotes can be stained by fluorescence-labeled annexin V upon permeabilization or miltefosine treatment. However, combined lipid analysis by thin-layer chromatography, mass spectrometry and 31 P nuclear magnetic resonance (NMR) spectroscopy revealed that Leishmania promastigotes lack any detectable amount of PS. Instead, we identified several other phospholipid classes such phosphatidic acid, phosphatidylethanolamine; phosphatidylglycerol and phosphatidylinositol as candidate lipids enabling annexin V staining.FAZIT (AW)Research Training Group 1121 of the German Research FoundationCarlsberg FoundationCenter for Synthetic Biology at Copenhagen UniversityUNIK research initiative of the Danish Ministry of Science, Technology and Innovatio

Transparency meets management: A monitoring and evaluating tool for governmental projects

The Brazilian government is maintaining several digital inclusion projects, providing computers and Internet connection to developing regions around the country. However, these projects can only succeed if they are constantly assessed; namely, the projects infrastructure deployment must be closely monitored and evaluated. In this paper, we introduce a system called SIMMC, which is currently monitoring and evaluating more than 4,500 computing devices from Brazilian digital inclusion projects. This system is innovative because, in addition to being used by the government for managing and expanding its projects, the collected data is also publicly available on a web page, allowing the citizens to follow the projects' deployment. We describe the SIMMC architecture, reporting some techniques used to optimize its data analysis processes, and describe how the information acquired and presented by the system has been used to enable public administration overhaul and improve efficiency on the project management, as well as its strategic use for security, theft, and defrauding

The application of a biometric identification technique for linking community and hospital data in rural Ghana

Background: The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Objective: Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. Design: A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. Results: A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Conclusions: Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information

Ionic liquids at electrified interfaces

Until recently, “room-temperature” (<100–150 °C) liquid-state electrochemistry was mostly electrochemistry of diluted electrolytes(1)–(4) where dissolved salt ions were surrounded by a considerable amount of solvent molecules. Highly concentrated liquid electrolytes were mostly considered in the narrow (albeit important) niche of high-temperature electrochemistry of molten inorganic salts(5-9) and in the even narrower niche of “first-generation” room temperature ionic liquids, RTILs (such as chloro-aluminates and alkylammonium nitrates).(10-14) The situation has changed dramatically in the 2000s after the discovery of new moisture- and temperature-stable RTILs.(15, 16) These days, the “later generation” RTILs attracted wide attention within the electrochemical community.(17-31) Indeed, RTILs, as a class of compounds, possess a unique combination of properties (high charge density, electrochemical stability, low/negligible volatility, tunable polarity, etc.) that make them very attractive substances from fundamental and application points of view.(32-38) Most importantly, they can mix with each other in “cocktails” of one’s choice to acquire the desired properties (e.g., wider temperature range of the liquid phase(39, 40)) and can serve as almost “universal” solvents.(37, 41, 42) It is worth noting here one of the advantages of RTILs as compared to their high-temperature molten salt (HTMS)(43) “sister-systems”.(44) In RTILs the dissolved molecules are not imbedded in a harsh high temperature environment which could be destructive for many classes of fragile (organic) molecules

Classification strategies in machine learning techniques predicting regime changes and durations in the Lorenz system

In this paper, we use machine learning strategies aiming to predict chaotic time series obtained from the Lorenz system. Such strategies prove to be successful in predicting the evolution of dynamical variables over a short period of time. Transitions between the regimes and their duration can be predicted with great accuracy by means of counting and classification strategies, for which we train multi-layer perceptron ensembles. Even for the longest regimes the occurrences and duration can be predicted. We also show the use of an echo state network to generate data of the time series with an accuracy of up to a few hundreds time steps. The ability of the classification technique to predict the regime duration of more than 11 oscillations corresponds to around 10 Lyapunov times

Emergence of multiagent spatial coordination strategies through artificial coevolution

This paper describe research investigating the evolution of coordination strategies in robot soccer teams. Each player (viewed as an agent) is provided with a common set of skills and is assigned to perform over a delimited area inside a soccer field. The idea is to optimize the whole team behavior by means of a spatial coadaptation process in which new players are selected in such a way to comply with the already existing ones. The main results show that, through coevolution, we progressively create teams whose members act on complementary areas of the playing field, being capable of prevailing over a standard opponent team with a fixed formation. (C) 2001 Elsevier Science Ltd. All rights reserved.2561013102

Hierarchical Evolution Of Heterogeneous Neural Networks

This paper describes a hierarchical evolutionary technique developed to design and train feedforward neural networks with different activation functions on their hidden-layer neurons (heterogeneous neural networks). At the upper level, a genetic algorithm is used to determine the number of neurons in the hidden layer and the type of the activation function of those neurons. At the second level, neural nets compete against each other across generations so that the nets with the lowest test errors survive. Finally, on the third level, a co-evolutionary approach is used to train each of the created networks by adjusting both the weights of the hidden-layer neurons and the parameters for their activation functions. © 2002 IEEE.217751780Coelho, A.L.V., Weingaertner, D., Von Zuben, F.J., Evolving heterogeneous neural networks for classification problems (2001) Procs. of Genetic and Evolutionary Compufalion Conference (GECCO-2001), pp. 266-273. , Morgan Kaufmann Publishers, JulyWhitehead, B., Choate, T., Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction (1996) IEEE Trans. on Neural Networks, 714, pp. 869-480Moriarty, D.E., Miikkulainen, R., Efficient reinforcement learning through symbiotic evolution (1996) Machine Learning, 22, pp. 11-33. , Kluwcr Academic Publishers, BostonMoriarty, D.E., Miikkulaincn, R., Hierarchical evolution of neural networks (1998) Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 428-433Whitley, D., Genetic algorithms and neural networks (1995) Genetic Algorithms in Engineering and Computer Science, , Periaux, J. and Winter, G. eds John Wiley & Sons LtdIyoda, E., Von Zuben, F., Evolutionary hybrid composition of activation functions in feedforward neural networks (1999) Procs. IJCNN, , article #396Ribeiro, J., Vasconcelos, G., An experimental evaluation of the cascade-correlation network in pattem recognition problems (1997) Proc. of ICONIP, pp. 1133-1136. , Springer-Verlag, New ZelandRibeiro, J., Vasconcelos, G., Constructive neural networks for pattern classification and verification (1999) Proc. of ICONIP, , Springer-VerlagPrechelt, L., (1994) Probeni: A Set of Neural Benchmarking Rules, , TR 21/94, Univcrstat KarlsruheZhao, Q., A coevolutionary algorithm for neural net learning (1997) Procs. of ICNN, 1, pp. 432-437Parekh, R., Yang, J., Honavar, V., (1998) Constructive Neural Network Leaming Algorithms for Multi-Category Real-valued Pattem Classification, pp. 97-06. , TR, Dep. of Computer Science, Iowa State UniversityReed, R., Pruning Algorithms - A Survey (1993) IEEE Trans. on Neural Networks, 45, pp. 740-747Haykin, S.S., (1998) Rleural Networks: A Comprehensive Foundation, , Prentice HallBack, T., Fogel, D.B., Michalewicz, T., (2000) Evolutionary Computation 1: Basic Algorithms and Operators, , Institute of Physics PublishingYao, X., A review of evolutionary artificial neural networks (1993) Int. J. Intell. Syst, 8 (4), pp. 539-567Liu, Y., Yao, X., Evolutionary design of artificial neural networks with different nodes (1996) Procs. of the Third IEEE International Con on Evolutionary Computation (CEC96), pp. 670-675. , Japan MayMichalewicz, Z., Nazhiyath, G., Michalewicz, M., A note on the usefulness of geometrical crossover for numerical optimization problems (1996) Proc. 5th Ann. Conf. on Evolutionary Programming, , MIT Pres