Mapping fibre orientation in complex-shaped biological systems with micrometre resolution by scanning X-ray microdiffraction

A fully automated procedure to extract and to image local fibre orientation in biological tissues from scanning X-ray diffraction is presented. The preferred chitin fibre orientation in the flow sensing system of crickets is determined with high spatial resolution by applying synchrotron radiation based X-ray microbeam diffraction in conjunction with advanced sample sectioning using a UV micro-laser. The data analysis is based on an automated detection of azimuthal diffraction maxima after 2D convolution filtering (smoothing) of the 2D diffraction patterns. Under the assumption of crystallographic fibre symmetry around the morphological fibre axis, the evaluation method allows mapping the three-dimensional orientation of the fibre axes in space. The resulting two-dimensional maps of the local fibre orientations - together with the complex shape of the flow sensing system - may be useful for a better understanding of the mechanical optimization of such tissues.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

Robust multivariable control of complex biological processes

This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.

Organization knowledge management change from a complex adaptive systems perpective with ability for ambidexeterity

We are working on the confluence of knowledge management, organizational memory and emergent knowledge with the lens of complex adaptive systems. In order to be fundamentally sustainable organizations search for an adaptive need for managing ambidexterity of day-to-day work and innovation. An organization is an entity of a systemic nature, composed of groups of people who interact to achieve common objectives, making it necessary to capture, store and share interactions knowledge with the organization, this knowledge can be generated in intra-organizational or inter-organizational level. The organizations have organizational memory of knowledge of supported on the Information technology and systems. Each organization, especially in times of uncertainty and radical changes, to meet the demands of the environment, needs timely and sized knowledge on the basis of tacit and explicit. This sizing is a learning process resulting from the interaction that emerges from the relationship between the tacit and explicit knowledge and which we are framing within an approach of Complex Adaptive Systems. The use of complex adaptive systems for building the emerging interdependent relationship, will produce emergent knowledge that will improve the organization unique developing.

New water-soluble Ruthenium(II) cytotoxic complex: biological activity and celular distribution

A novel water soluble organometallic compound, [RuCp(mTPPMSNa)(2,2'-bipy)][CF3SO3] (TM85, where Cp=eta(5)-cyclopentadienyl, mTPPMS = diphenylphosphane-benzene-3-sulfonate and 2,2'-bipy = 2,2'-bipyridine) is presented herein. Studies of interactions with relevant proteins were performed to understand the behavior and mode of action of this complex in the biological environment. Electrochemical and fluorescence studies showed that TM85 strongly binds to albumin. Studies carried out to study the formation of TM85 which adducts with ubiquitin and cytochrome c were performed by electrospray ionization mass spectrometry (ESI-MS). Antitumor activity was evaluated against a variety of human cancer cell lines, namely A2780, A2780cisR, MCF7, MDAMB231, HT29, PC3 and V79 non-tumorigenic cells and compared with the reference drug cisplatin. TM85 cytotoxic effect was reduced in the presence of endocytosis modulators at low temperatures, suggesting an energy-dependent mechanism consistent with endocytosis. Ultrastructural analysis by transmission electron microscopy (TEM) revealed that TM85 targets the endomembranar system disrupting the Golgi and also affects the mitochondria. Disruption of plasma membrane observed by flow cytometry could lead to cellular damage and cell death. On the whole, the biological activity evaluated herein combined with the water solubility property suggests that complex TM85 could be a promising anticancer agent. (C) 2013 Elsevier Inc. All rights reserved.

Hybrid systems biology: application to Escherichia coli

Dissertation presented to obtain a Master degree in Biotechnology

Integrated management systems as complex adaptive systems

It is a difficult task to avoid the “smart systems” topic when discussing smart prevention and, similarly, it is a difficult task to address smart systems without focusing their ability to learn. Following the same line of thought, in the current reality, it seems a Herculean task (or an irreparable omission) to approach the topic of certified occupational health and safety management systems (OHSMS) without discussing the integrated management systems (IMSs). The available data suggest that seldom are the OHSMS operating as the single management system (MS) in a company so, any statement concerning OHSMS should mainly be interpreted from an integrated perspective. A major distinction between generic systems can be drawn between those that learn, i.e., those systems that have “memory” and those that have not. These former systems are often depicted as adaptive since they take into account past events to deal with novel, similar and future events modifying their structure to enable success in its environment. Often, these systems, present a nonlinear behavior and a huge uncertainty related to the forecasting of some events. This paper seeks to portray, for the first time as we were able to find out, the IMSs as complex adaptive systems (CASs) by listing their properties and dissecting the features that enable them to evolve and self-organize in order to, holistically, fulfil the requirements from different stakeholders and thus thrive by assuring the successful sustainability of a company. Based on the revision of literature carried out, this is the first time that IMSs are pointed out as CASs which may develop fruitful synergies both for the MSs and for CASs communities. By performing a thorough revision of literature and based on some concepts embedded in the “DNA” of the subsystems implementation standards it is intended, specifically, to identify, determine and discuss the properties of a generic IMS that should be considered to classify it as a CAS.

Systems biology approaches for the design of novel Saccharomyces cerevisiae winemaking strains for enhanced flavour compounds synthesis

Tese de Doutoramento em Biologia Ambiental e Molecular

In-line rheo-optical microstructural characterization of complex polymer systems

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos.

Resonancia Magnética Nuclear aplicada al estudio de nuevos sistemas farmacéuticos y biológicos, complejos poliméricos y conjuntos de espines modelo. Nuclear Magnetic Resonance applied to the study of new pharmaceutical and biological systems, polymeric complexes and model spin clusters.

El presente proyecto plantea utilizar integralmente la técnica de Resonancia Magnética Nuclear en sólidos como un medio experimental que permite entender fenómenos de la física fundamental, como así también realizar aplicaciones de interés en el campo de la química, los desarrollos farmacéuticos y la biología. Novedosas técnicas experimentales serán empleadas, en conjunción con otras más tradicionales, en la caracterización de nuevas estructuras poliméricas acomplejadas a metales, membranas biológicas y compuestos de interés farmacéutico en vías de desarrollo, los cuales presentan el fenómeno de polimorfismo . Esto se llevará a cabo complementando los resultados de RMN en sólidos con técnicas tanto espectroscópicas como analíticas (Infrarrojo, Difracción de Rayos X, Calorimetría, RMN en solución) y trabajo interdisciplinario. Paralelamente al desarrollo de estos temas, profundizaremos mediante investigación básica, en la compresión de la dinámica cuántica y el surgimiento de la irreversibilidad en sistemas de espines nucleares. Observaremos en particular la generación, evolución y control de las coherencias cuánticas múltiples en sistemas cuánticos abiertos, lo cual nos da información sobre tamaño de clusters de espines. Esto permitirá la correcta implementación de secuencias de pulsos sofisticadas, como así también desarrollar nuevos métodos de medición aplicados a la caracterización estructural y a la dinámica molecular de sólidos complejos. Debemos resaltar que este proyecto está conectado con aspectos tanto básicos como aplicados de la RMN en sólidos como técnica experimental, la cual se desarrolla en el país únicamente en FaMAF-UNC. Se nutre además de trabajo multidisciplinario promoviendo la colaboración con investigadores y becarios de distintas áreas (física, química, farmacia, biología) provenientes de distintos puntos del país. Finalmente podemos afirmar que este plan impulsa la aplicación de la física básica proyectada a diferentes áreas del conocimiento, en el ámbito de la provincia de Córdoba. The aim of the present proyect is to use Nuclear Magnetic Resonance (NMR) as a complete techique that allows the understanding of fundamental physics phenomena and, at the same time, it leads to important applications in the fields of chemistry, pharmaceutical developments and biology. New experiments will be used together with traditional ones, in the characterization of new metal-polymer complexes, biological membranes and pharmaceutical compounds, some of them presenting polymorfism. NMR experiments will be complemented with diverse spectroscopic and analytical techniques: Infrared, X ray Diffraction, Thermal Analysis, solution NMR, as well as multidisciplinary investigation. Additionally, the present proyect plans to study in depth several aspects of quantum dynamics phenomena and decoherence in nuclear spin systems. The present proyect is connected with basic and applied aspects of the solid state NMR technique, developed in our country, only at FaMAF-UNC. It is is composed by multidisciplinary work and it promotes the collaboration with researchers and students coming from different fields (physics, chemistry, pharmaceutical developments, biology) and different points of our country.

New Radicals and new applications of Dynamic Nuclear Polarization of biological systems

Dynamic Nuclear Polarization (DNP) is an emerging technique that could revolutionize the NMR study of small molecules at very low concentrations by the increase in sensitivity that results from transfer of polarization between electronic and nuclear spins. Although the underlying physics has been known for a long time, in the last few years there has been a lot of excitement on the chemistry and biology NMR community caused by the demonstration that the highly polarized nuclei that are prepared in solid state at very low temperatures (1-2 K) could be rapidly transferred to liquid samples at room temperature and studied in solution by conventional NMR techniques. In favorable cases several order of magnitude increases in sensitivity have been achieved. The technique is now mature enough that a commercial instrument is available. The efficiency of DNP depends on two crucial aspects: i) the efficiency of the nuclear polarization process and ii) the efficiency of the transfer from the initial solid state to the fluid state in which NMR is measured. The preferred areas of application (iii) will be dictated by situations in which the low concentration of the sample or its intrinsic low receptivity are the limiting factors .

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.