Design and synthesis of short antimicrobial peptides for plant protection. Study of their mode of action

Aquesta tesi doctoral està basada en el desenvolupament de nous agents antimicrobians derivats del pèptid híbrid cecropina A-melitina WKLFKKILKVL-NH2 (Pep3) que siguin sostenibles i útils per al control de malalties de plantes. Es van dissenyar i sintetitzar més de 133 anàlegs de Pep3 mitjançant química combinatòria. Es van obtenir anàlegs de Pep3 amb una elevada activitat contra fitopatògens i que presentaven baixa toxicitat. Els millors anàlegs van presentar eficàcies comparables amb pesticides de referència en la prevenció d'infeccions causades per fitopatògens. Es va estudiar el mecanisme d'acció de KKLFKKILKYL-NH2 (BP100) investigant la seva interacció amb models de membrana mitjançant tècniques espectroscòpiques. Es va observar la capacitat de BP100 a induir la permeabilització, la neutralització, i l'agregació de vesícules lipídiques aniòniques a una determinada concentració llindar. Es va deduir una equació que relaciona la CMI d'un pèptid antimicrobià amb la constant de partició i la concentració llindar en la membrana.

Fire blight (Erwinia amylovora) of rosaceous plants. Pathogen virulence and selection and characterization of biological control agents

El fuego bacteriano, causado por Erwinia amylovora, es una enfermedad muy importante a nivel comercial y económico porque afecta a plantas de la familia de las rosáceas y es especialmente agresiva en manzano (Pyrus malus) y peral (Pyrus communis), así como en plantas ornamentales (Crataegus, Cotoneaster o Pyracantha). Esta enfermedad está distribuida por todo el mundo en zonas climáticas templadas de Amércia del Norte, Nueva Zelanda, Japón, Israel, Turquí y Europa. En España, el fuego bacteriano fue detectado por primera vez en 1995 en el norte del País (Euskadi) y más tarde en nuevos focos aparecidos en otras áreas. La enfermedad puede ser controlada comercialmente mediante la aplicación de pesticidas quimicos (derivados de cobre, antibioticos). Sin embargo, muchos de los productos químicos presentan baja actividad o causan fitotoxicidad, y la estreptomicina, el producto más eficaz, esta prohibido en muchos países, incluyendo España. Por tanto, en ausencia de apropiados agentes químicos, el control biológico se contempla como una buena alternativa. En el presente trabajo, un agente de control biológico, Pseudomonas fluorescens EPS62e, ha sido seleccionada de entre 600 aislados de las especies P. fluorescens y Pantoea agglomerans obtenidos de flores, frutos y hojas de plantas de la familia de las rosáceas durante una prospección llevada a cabo en varias áreas geográficas de España. La cepa ha sido seleccionada por su capacidad de suprimir la infecciones producidas por E. amylovora frutos inmaduros, flores y brotes de peral en condiciones de ambiente controlado, presentando unos niveles de control similares a los obtenidos mediante el control químico usando derivados de cobre o antibióticos. La cepa además ha mostrado la capacidad de colonizar y sobrevivir en flores y heridas producidas en frutos inmaduros en condiciones de ambiento controlado pero también en flores en condiciones de campo. La exclusión de E. amylovora medinate la colonización de la superficie, el consumo de nutrientes, y la interacción entre las células del patógeno y del agente de biocontrol es la principal causa de la inhibición del fuego bacteriano por la cepa EPS62e. Estas características constituyen aspectos interesantes para un desarrollo efectivo de la cepa EPS62e como un agente de biocontrol del fuego bacteriano en condiciones comerciales.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

An exploration of the drivers to bio-security collective action among a sample of UK cattle and sheep farmers

At present, collective action regarding bio-security among UK cattle and sheep farmers is rare. Despite the occurrence of catastrophic livestock diseases such as bovine spongiform encephalopathy (BSE) and foot and mouth disease (FMD), within recent decades, there are few national or local farmer-led animal health schemes. To explore the reasons for this apparent lack of interest, we utilised a socio-psychological approach to disaggregate the cognitive, emotive and contextual factors driving bio-security behaviour among cattle and sheep farmers in the United Kingdom (UK). In total, we interviewed 121 farmers in South-West England and Wales. The main analytical tools included a content, cluster and logistic regression analysis. The results of the content analysis illustrated apparent 'dissonance' between bio-security attitudes and behaviour.(1) Despite the heavy toll animal disease has taken on the agricultural economy, most study participants were dismissive of the many measures associated with bio-security. Justification for this lack of interest was largely framed in relation to the collective attribution or blame for the disease threats themselves. Indeed, epidemic diseases were largely related to external actors and agents. Reasons for outbreaks included inadequate border control, in tandem with ineffective policies and regulations. Conversely, endemic livestock disease was viewed as a problem for 'bad' farmers and not an issue for those individuals who managed their stock well. As such, there was little utility in forming groups to address what was largely perceived as an individual problem. Further, we found that attitudes toward bio-security did not appear to be influenced by any particular source of information per se. While strong negative attitudes were found toward specific sources of bio-security information, e.g. government leaflets, these appear to simply reflect widely held beliefs. In relation to actual bio-security behaviours, the logistic regression analysis revealed no significant difference between in-scheme and out of scheme farmers. We concluded that in order to support collective action with regard to bio-security, messages need to be reframed and delivered from a neutral source. Efforts to support group formation must also recognise and address the issues relating to perceptions of social connectedness among the communities involved. (c) 2008 Elsevier B.V. All rights reserved.

Action following the discovery of a global association between the whole genome and adverse event risk in a clinical drug-development programme

Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non-sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to? determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright (C) 2008 John Wiley & Sons, Ltd.

Local roles of TGF-beta superfamily members in the control of ovarian follicle development

Members of the transforming growth factor-beta (TGF-beta) superfamily have wide-ranging influences on many tissue and organ systems including the ovary. Two recently discovered TGF-beta superfamily members, growth/differentiation factor-9 (GDF-9) and bone morphogenetic protein-15 (BMP-15; also designated as GDF-9B) are expressed in an oocyte-specific manner from a very early stage and play a key role in promoting follicle growth beyond the primary stage. Follicle growth to the small antral stage does not require gonadotrophins but appears to be driven by local autocrine/paracrine signals from both somatic cell types (granulosa and theca) and from the oocyte. TGF-beta superfamily members expressed by follicular cells and implicated in this phase of follicle development include TGF-beta, activin, GDF-9/9B and several BMPs. Acquisition of follicle-stimulating hormone (FSH) responsiveness is a pre-requisite for growth beyond the small antral stage and evidence indicates an autocrine role for granulosa-derived activin in promoting granulosa cell proliferation, FSH receptor expression and aromatase activity. Indeed, some of the effects of FSH on granulosa cells may be mediated by endogenous activin. At the same time, activin may act on theca cells to attenuate luteinizing hormone (LH)-dependent androgen production in small to medium-size antral follicles. Dominant follicle selection appears to depend on differential FSH sensitivity amongst a growing cohort of small antral follicles. Activin may contribute to this selection process by sensitizing those follicles with the highest "activin tone" to FSH. Production of inhibin, like oestradiol, increases in selected dominant follicles, in an FSH- and insulin-like growth factor-dependent manner and may exert a paracrine action on theca cells to upregulate LH-induced secretion of androgen, an essential requirement for further oestradiol secretion by the pre-ovulatory follicle. Like activin, BMP-4 and -7 (mostly from theca), and BMP-6 (mostly from oocyte), can enhance oestradiol and inhibin secretion by bovine granulosa cells while suppressing progesterone secretion; this suggests a functional role in delaying follicle luteinization and/or atresia. Follistatin, on the other hand, may favor luteinization and/or atresia by bio-neutralizing intrafollicular activin and BMPs. Activin receptors are expressed by the oocyte and activin may have a further intrafollicular role in the terminal stages of follicle differentiation to promote oocyte maturation and developmental competence. In a reciprocal manner, oocyte-derived GDF-9/9B may act on the surrounding cumulus granulosa cells to attenuate oestradiol output and promote progesterone and hyaluronic acid production, mucification and cumulus expansion.(C) 2003 Elsevier Science B.V. All rights reserved.

Identification of hepatic molecular mechanisms of action of alpha-tocopherol using global gene expression profile analysis in rats

The recent discovery that vitamin E (VE) regulates gene activity at the transcriptional level indicates that VE may exert part of its biological effects by mechanisms which may be independent of its well-recognised antioxidant function. The objective of this study was the identification of hepatic vitamin E-sensitive genes and examination of the effects of VE on their corresponding biological endpoints. Two groups of male rats were randomly assigned to either a VE-sufficient diet or to a control diet deficient in VE for 290 days. High-density oligonucleotide microarrays comprising over 7000 genes were used to assess the transcriptional response of the liver. Differential gene expression was monitored over a period of 9 months, at four different time-points, and rats were individually profiled. This experimental strategy identified several VE-sensitive genes, which were chronically altered by dietary VE. VE supplementation down-regulated scavenger receptor CD36, coagulation factor IX and 5-alpha-steroid reductase type 1 mRNA levels while hepatic gamma glutamyl-cysteinyl synthetase was significantly up-regulated. Measurement of the corresponding biological endpoints such as activated partial thromboplastin time, plasma dihydrotestosterone and hepatic glutathione substantiated the gene chip data which indicated that dietary VE plays an important role in a range of metabolic processes within the liver. (C) 2004 Elsevier B.V. All rights reserved.

Neural systems in the visual control of steering

Visual control of locomotion is essential for most mammals and requires coordination between perceptual processes and action systems. Previous research on the neural systems engaged by self-motion has focused on heading perception, which is only one perceptual subcomponent. For effective steering, it is necessary to perceive an appropriate future path and then bring about the required change to heading. Using function magnetic resonance imaging in humans, we reveal a role for the parietal eye fields (PEFs) in directing spatially selective processes relating to future path information. A parietal area close to PEFs appears to be specialized for processing the future path information itself. Furthermore, a separate parietal area responds to visual position error signals, which occur when steering adjustments are imprecise. A network of three areas, the cerebellum, the supplementary eye fields, and dorsal premotor cortex, was found to be involved in generating appropriate motor responses for steering adjustments. This may reflect the demands of integrating visual inputs with the output response for the control device.

Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping

The study of motor unit action potential (MUAP) activity from electrornyographic signals is an important stage on neurological investigations that aim to understand the state of the neuromuscular system. In this context, the identification and clustering of MUAPs that exhibit common characteristics, and the assessment of which data features are most relevant for the definition of such cluster structure are central issues. In this paper, we propose the application of an unsupervised Feature Relevance Determination (FRD) method to the analysis of experimental MUAPs obtained from healthy human subjects. In contrast to approaches that require the knowledge of a priori information from the data, this FRD method is embedded on a constrained mixture model, known as Generative Topographic Mapping, which simultaneously performs clustering and visualization of MUAPs. The experimental results of the analysis of a data set consisting of MUAPs measured from the surface of the First Dorsal Interosseous, a hand muscle, indicate that the MUAP features corresponding to the hyperpolarization period in the physisiological process of generation of muscle fibre action potentials are consistently estimated as the most relevant and, therefore, as those that should be paid preferential attention for the interpretation of the MUAP groupings.

Multiple-model fault tolerant control of terminal unites of HVAC Systems

In this work, a fault-tolerant control scheme is applied to a air handling unit of a heating, ventilation and air-conditioning system. Using the multiple-model approach it is possible to identify faults and to control the system under faulty and normal conditions in an effective way. Using well known techniques to model and control the process, this work focuses on the importance of the cost function in the fault detection and its influence on the reconfigurable controller. Experimental results show how the control of the terminal unit is affected in the presence a fault, and how the recuperation and reconfiguration of the control action is able to deal with the effects of faults.

Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning

This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Generative topographic mapping applied to clustering and visualization of motor unit action potentials

The identification and visualization of clusters formed by motor unit action potentials (MUAPs) is an essential step in investigations seeking to explain the control of the neuromuscular system. This work introduces the generative topographic mapping (GTM), a novel machine learning tool, for clustering of MUAPs, and also it extends the GTM technique to provide a way of visualizing MUAPs. The performance of GTM was compared to that of three other clustering methods: the self-organizing map (SOM), a Gaussian mixture model (GMM), and the neural-gas network (NGN). The results, based on the study of experimental MUAPs, showed that the rate of success of both GTM and SOM outperformed that of GMM and NGN, and also that GTM may in practice be used as a principled alternative to the SOM in the study of MUAPs. A visualization tool, which we called GTM grid, was devised for visualization of MUAPs lying in a high-dimensional space. The visualization provided by the GTM grid was compared to that obtained from principal component analysis (PCA). (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Shaking hands: Priming by social action effects

In a semi-naturalistic response-effect compatibility paradigm, participants were given the opportunity to learn that hand-shaking actions would be followed by social effects (human hand-shaking stimuli from a third-person perspective) or inanimate effects (block arrow stimuli). Relative to the actions, these effects appeared on the same or the opposite side of the screen (positional compatibility), and pointed towards or away from the response hand (directional compatibility). After learning, response times indicated a positional compatibility effect for both social and inanimate effects, but a directional compatibility effect occurred only for social action effects. These findings indicate that actions can be represented, not only by their effects on the inanimate world, but also by their effects on the actions of others. They are consistent with ideomotor theory, and with the view that actions are represented by bidirectional response-effect associations. They also have implications with respect to the origins and on-line control of imitation and the systems supporting imitation.

A hyperstable neural network for the modelling and control of nonlinear systems

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.