Design and Characterization of Silicone and Surfactant Based Systems for Topical Drug Delivery

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development and in vitro skin delivery of dexamethasone acetate-loaded surfactant-based systems

Topical corticosteroids, e.g., dexamethasone acetate (DMA), are extensively used to treat cutaneous inflammatory disorders even though their use is correlated with potential local and systemic side effects. The objective of this study was to develop and test the topical delivery of DMA-loaded surfactant based systems in vitro; these studies could guarantee a suitable delivery and therapeutic efficacy, as well as minimize DMA's side effects. A phase diagram was constructed using polyoxypropylene (5) polyoxyethylene (20) cetyl alcohol as the surfactant (S), isopropyl myristate as the oil phase (O) and water (W). The systems were characterized using polarization light microscopy (PLM), as well as rheological and small angle X-ray scattering (SAXS) measurements. Depending on the concentration of the constituents, it was possible to obtain microemulsions (MEs) and liquid crystalline mesophases (lamellar and hexagonal). These types of arrangement were verified using PLM measurements. The SAXS results revealed that increasing the W/S ratio led to ME, as well as lamellar (LAM) and hexagonal (HEX) arrangements. The MEs displayed typical Newtonian behavior while the LAM and HEX phases exhibited pseudoplasticity and plasticity, respectively. The MEs displayed excellent drug solubilization that was approximately 10-fold higher than was observed with the individual components. The in vitro cutaneous permeation studies using pig ear skin and analysis of the mechanical parameters (hardness, compressibility, cohesiveness and adhesiveness) were carried out with a HEX phase and O/W emulsion. The HEX phase achieved better drug permeation and retention in the skin while its mechanical properties were suitable for skin administration. PPG-5-CETETH-20-based systems may be a promising platform delivering DMA and other topical corticosteroids through the skin.

Engineering knowledge-based variance-reduction simulation and G-dominance for structural frame robust optimization

[EN] This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variance reduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables.The simultaneous minimization of the constrained weight (adding structuralweight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including

Rheology and Fourier-transform rheology on water-based systems

The influence of shear fields on water-based systems was investigated within this thesis. The non-linear rheological behaviour of spherical and rod-like particles was examined with Fourier-Transform rheology under LAOS conditions. As a model system for spherical particles two different kinds of polystyrene dispersions, with a solid content higher than 0.3 each, were synthesised within this work. Due to the differences in polydispersity and Debye-length, differences were also found in the rheology. In the FT-rheology both kinds of dispersions showed a similar rise in the intensities of the magnitudes of the odd higher harmonics, which were predicted by a model. The in some cases additionally appearing second harmonics were not predicted. A novel method to analyse the time domain signal was developed, that splits the time domain signal up in four characteristic functions. Those characteristic functions correspond to rheological phenomena. In some cases the intensities of the Fourier components can interfere negatively. FD-virus particles were used as a rod-like model system, which already shows a highly non-linear behaviour at concentrations below 1. % wt. Predictions for the dependence of the higher harmonics from the strain amplitude described the non-linear behaviour well at large, but no so good at small strain amplitudes. Additionally the trends of the rheological behaviour could be described by a theory for rod-like particles. An existing rheo-optical set-up was enhanced by reducing the background birefringence by a factor of 20 and by increasing the time resolution by a factor of 24. Additionally a combination of FT-rheology and rheo-optics was achieved. The influence of a constant shear field on the crystallisation process of zinc oxide in the presence of a polymer was examined. The crystallites showed a reduction in length by a factor of 2. The directed addition of polymers in combination with a defined shear field can be an easy way for a defined change of the form of crystallites.

From lipid bilayers to synaptic vesicles: atomic force microscopy on lipid-based systems

The aim of this thesis was to apply the techniques of the atomic force microscope (AFM) to biological samples, namely lipid-based systems. To this end several systems with biological relevance based on self-assembly, such as a solid-supported membrane (SSM) based sensor for transport proteins, a bilayer of the natural lipid extract from an archaebacterium, and synaptic vesicles, were investigated by the AFM. For the characterization of transport proteins with SSM-sensors proteoliposomes are adsorbed that contain the analyte (transport protein). However the forces governing bilayer-bilayer interactions in solution should be repulsive under physiological conditions. I investigated the nature of the interaction forces with AFM force spectroscopy by mimicking the adsorbing proteoliposome with a cantilever tip, which was functionalized with charged alkane thiols. The nature of the interaction is indeed repulsive, but the lipid layers assemble in stacks on the SSM, which expose their unfavourable edges to the medium. I propose a model by which the proteoliposomes interact with these edges and fuse with the bilayer stacks, so forming a uniform layer on the SSM. Furthermore I characterized freestanding bilayers from a synthetic phospholipid with a phase transition at 41°C and from a natural lipid extract of the archaebacterium Methanococcus jannaschii. The synthetic lipid is in the gel-phase at room temperature and changes to the fluid phase when heated to 50°C. The bilayer of the lipid extract shows no phase transition when heated from room temperature to the growth temperature (~ 50°C) of the archeon. Synaptic vesicles are the containers of neurotransmitter in nerve cells and the synapsins are a family of extrinsic membrane proteins, that are associated with them, and believed to control the synaptic vesicle cycle. I used AFM imaging and force spectroscopy together with dynamic light scattering to investigate the influence of synapsin I on synaptic vesicles. To this end I used native, untreated synaptic vesicles and compared them to synapsin-depleted synaptic vesicles. Synapsin-depleted vesicles were larger in size and showed a higher tendency to aggregate compared to native vesicles, although their mechanical properties were alike. I also measured the aggregation kinetics of synaptic vesicles induced by synapsin I and found that the addition of synapsin I promotes a rapid aggregation of synaptic vesicles. The data indicate that synapsin I affects the stability and the aggregation state of synaptic vesicles, and confirm the physiological role of synapsins in the assembly and regulation of synaptic vesicle pools within nerve cells.

KNOWLEDGE-BASED MANUFACTURING STRATEGY AND METHODS FOR FOUNDRIES

The European foundry business is a traditional less RTD intensive industry which is dominated by SMEs and which forms a significant part of Europe’s manufacturing industry. The efficient design and manufacturing of cast components and corresponding tooling is a crucial success factor for these companies. To achieve this, information and knowledge around the design, planning and manufacturing of cast components needs to be accessible in a fast and structured way.

Knowledge-Based Task Structure Planning for an Information Gathering Agent

An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.

Exploiting Structured Linked Data in Enterprise Knowledge Management Systems: An Idea Management Case Study

In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems

A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach

In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach.

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

A knowledge based framework to support active aging at home based environments

Information and Communication Technologies can support Active Aging strategies in a scenario like the Smart Home. This paper details a person centered distributed framework, called TALISMAN+, whose aim is to promote personal autonomy by taking advantage of knowledge based technologies, sensors networks, mobile devices and internet. The proposed solution can support an elderly person to keep living alone at his house without being obliged to move to a residential center. The framework is composed by five subsystems: a reasoning module that is able to take local decisions at home in order to support active aging, a biomedical variables telemonitorisation platform running on a mobile device, a hybrid reasoning middleware aimed to assess cardiovascular risk in a remote way, a private vision based sensor subsystem, and a secure telematics solution that guarantees confidentiality for personal information. TALISMAN+ framework deployment is being evaluated at a real environment like the Accessible Digital Home.