Identification of Toxin Inhibitors Using a Magnetic Nanosensor‐Based Assay

A magnetic nanosensor‐based method is described to screen a library of drugs for potential binding to toxins. Screening is performed by measuring changes in the magnetic relaxation signal of the nanosensors (bMR nanosensors) in aqueous suspension upon addition of the toxin. The Anthrax lethal factor (ALF) is selected as a model toxin to test the ability of our bMR nanosensor‐based screening method to identify potential inhibitors of the toxin. Out of 30 molecules screened, sulindac, naproxen and fusaric acid are found to bind LF, with dissociation constants in the low micromolar range. Further biological analysis of the free molecules in solution indicate that sulindac and its metabolic products inhibited LF cytotoxicity to macrophages with IC₅₀ values in the micromolar range. Meanwhile, fusaric acid is found to be less effective at inhibiting LF cytotoxicity, while naproxen does not inhibit LF toxicity. Most importantly, when the sulindac and fusaric acid‐bMR nanosensors themselves are tested as LF inhibitors, as opposed to the corresponding free molecules, they are stronger inhibitors of LF with IC₅₀ values in the nanomolar range. Taken together, these studies show that a bMR nanosensors‐based assay can be used to screen known drugs and other small molecules for inhibitor of toxins. The method can be easily modified to screen for inhibitors of other molecular interactions and not only the selected free molecule can be study as potential inhibitors but also the bMR nanosensors themselves achieving greater inhibitory potential.     

SIMULATING STRUCTURAL CHANGE IN ADAPTIVE ORGANIZATIONS

This paper presents an agent-based model of an organization. The model is made of a social network—composed of the different organization workers—and a knowledge network. Workers are assigned tasks, for which they have to use information in the knowledge network. We have modeled the quality of the information by assigning each information item a probability of being wrong. Agents can interact with other agents, who can recommend to them new information items in the knowledge network for the task to be performed. Workers are assigned different information-seeking behavior (passive, active, and learning), governing the way in which they interact with each other. Moreover, indirect interaction is also possible, as a publicly accessible knowledge base contains each agent's preferred information items.

The model was implemented in SDML, and its simulation shows that agents quickly learn to discern the better information items for the given task. However, group formation (agents' collaborating by exchanging information) takes longer to stabilize. Additionally, when the quality of items is changed, agents can quickly select the better new knowledge items, and organization performance improves again to a maximum that is only randomly disturbed.     

Growth performance,carcass and meat quality of the Celta pig crossbred with Duroc and Landrance genotypes

The Celta pig is a native breed adapted to the north of Spain and extensive production system. The objective was to study the effects of sex and crossbreeding on carcass characteristics and meat quality. Samples were taken from longissimus dorsi muscle of 52 pigs of three different groups [Celta pure breed (C), Celta crossed with Landrace (C × L) and Celta crossed with Duroc (C × D)].     

Comparison of different peeling systems for kiwifruit (Actinidia deliciosa,cv Hayward)

Galicia (N.W. Spain) produces 60% of Spanish kiwifruit (Actinidia deliciosa) and 5–20% of these are ‘destrío’ fruits, which do not reach market size and the appropriate form. These rejected fruits can be processed into products, thus increasing their added value. The processing of kiwifruit always includes a peeling operation, which can be performed by different systems. The most suitable conditions for caustic peeling and thermal peeling were established. Then, the two peeling systems were compared with manual peeling with the aim of selecting the best system to remove the peel of the ‘destrío’ kiwifruit. The fruits, once harvested, were stored in a cold chamber at 0 °C. Before processing or marketing kiwifruits, it is necessary to remove them from storage in cold chamber and storage at room temperature. In this study, different storage times at room temperature before peeling kiwifruits were also tested. The best system for peeling the kiwifruit was thermal peeling as this system resulted in the lowest weight loss and preserved the green colour characteristic of the kiwifruit. The best time for peeling the kiwifruit was after 8 days of storage at room temperature, after being removed from the cold chamber.     

Inverse material identification in coupled acoustic-structure interaction using a modified error in constitutive equation functional

This work focuses on the identification of heterogeneous linear elastic moduli in the context of frequency-domain, coupled acoustic-structure interaction (ASI), using either solid displacement or fluid pressure measurement data. The approach postulates the inverse problem as an optimization problem where the solution is obtained by minimizing a modified error in constitutive equation (MECE) functional. The latter measures the discrepancy in the constitutive equations that connect kinematically admissible strains and dynamically admissible stresses, while incorporating the measurement data as additional quadratic error terms. We demonstrate two strategies for selecting the MECE weighting coefficient to produce regularized solutions to the ill-posed identification problem: 1) the discrepancy principle of Morozov, and 2) an error-balance approach that selects the weight parameter as the minimizer of another functional involving the ECE and the data misfit. Numerical results demonstrate that the proposed methodology can successfully recover elastic parameters in 2D and 3D ASI systems from response measurements taken in either the solid or fluid subdomains. Furthermore, both regularization strategies are shown to produce accurate reconstructions when the measurement data is polluted with noise. The discrepancy principle is shown to produce nearly optimal solutions, while the error-balance approach, although not optimal, remains effective and does not need a priori information on the noise level.     

Strategic alignment and value maximization for IT project portfolios

Managing project portfolios has been a challenge to many IT organizations due to the size and complexity of their initiatives that are often cross-functional, fast changing, and transformational in nature. A governance process on project solicitation, evaluation, and monitoring is thus essential to ensure the resulting portfolio creates tangible values, balances across priorities, and supports business objectives. An optimization model to streamline the decision processes for IT portfolios and programs is proposed. We consider project characteristics such as the extent of strategic alignment, expected benefit, development cost, and cross-project synergy to maximize the portfolio value. We also consider team proficiency and resource availability to determine a project portfolio that could be implemented within the overall development time. The multi-objective model identifies the optimal mix among project types and the solution procedure efficiently produces recommendations that are superior to those found with current empirical techniques. We also describe an evolutionary algorithm to find approximate solutions to the optimization model. Possible extensions on how the optimization procedure can go beyond projects to also streamline decisions such as the renewal or replacement of in-flight applications is discussed.     

Epilactose production by 2 cellobiose 2-epimerases in natural milk

It was reported recently that cellobiose 2-epimerases (CE) from various aerobic microorganisms convert lactose to epilactose in defined buffer systems. In this study, we showed that CE from 2 mesophilic microorganisms, Flavobacterium johnsoniae and Pedobacter heparinus, were capable of converting lactose to prebiotic epilactose not only in buffer but also in a complex milk system. First, the 2 enzymes were separately cloned, recombinantly expressed in Escherichia coli, and purified by column chromatography. The production of F. johnsoniae CE was carried out in a stirred-tank reactor, indicating that future upscaling is possible. The bioconversions of milk lactose were carried out at an industrially relevant low temperature of 8°C to avoid undesired microbial contaminations or chemical side reactions. Both enzymes were reasonably active at this low temperature, because of their origin from mesophilic organisms. The enzymes showed different operational stabilities over a 24-h time-course. A conversion yield of about 30 to 33% epilactose was achieved with both enzymes. No side products were detected other than epilactose. Therefore, CE may introduce an added value for particular dairy products by in situ production of the prebiotic sugar epilactose.     

Data‐driven bounded‐error fault detection

In this paper, a new data‐driven fault‐detection method is proposed. This method is based on a new nonparametric system identification approach, which constitutes the principal contribution to this work. The fault‐detection method is a parametric model‐free approach that can be applied to nonlinear systems that work at various operating points. Not only can the fault‐detection process be applied to the steady state of each operating point, but it can also be applied to the transient state resulting from a change in the operating point. In order to detect faults, the proposed method uses an interval predictor based on bounded‐error techniques. The utilization of techniques based on bounded error enables system uncertainties to be included in an explicit way. This in turn leads to the possibility of obtaining interval predictions of the behaviour of the system, which include information on the reliability of the prediction itself. In order to show the effectiveness of the fault‐detection method, two examples are presented: in the form of a simulated process (counter‐flow shell‐and‐tube heat‐exchanger system) and an example of a real application (two‐tanks system). A comparison with two fault‐detection methods has also been included. Copyright © 2013 John Wiley & Sons, Ltd.     

Ozone as an Alternative for Disinfection of Explants during In Vitro Mass Plant Propagation

Ozone was used as an alternative for replacing sodium hypochlorite in the disinfection of yam nodal segments during the establishment stage for in vitro mass plant propagation. The purpose of this work was to evaluate the effect of ozone on disinfection of yam nodal segments in gaseous and aqueous phase in comparison to sodium hypochlorite. The immersion of yam nodal segments in water containing dissolved ozone with an ozone concentration of 1.0, 1.5 and 2.0 ppm during for 5 to 10 min gave the best results; 100% of yam nodal segments were free of microbial contamination. In terms of sprouting initiation (7.5 days), sprouting percentage (88%), and sprouts growth (4.81 cm), all were improved in comparison to the conventionally used sodium hypochlorite.