910 resultados para mathematical modelling, controlled drug release, polymer micro-spheres, swelling, boundary problems


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The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

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Este estudo teve como objectivo compreender o desenvolvimento de tarefas de modelação, por parte de uma professora de Matemática e de uma professora de Física­ Química, no âmbito de trabalho colaborativo. Para tal foram formuladas três questões orientadoras: 1. Como é que os professores seleccionam e preparam as tarefas de modelação a colocar aos alunos em situação de sala de aula? Que características das tarefas de modelação se mostram fundamentais para a sua selecção? 2. como desenvolvem os professores as tarefas de modelação na sala de aula? Como gerem e dinamizam as aulas onde colocam tarefas de modelação aos alunos? Que papel reservam ao professor e ao aluno? 3. como exploram os professores as potencialidades das calculadoras gráficas no desenvolvimento das tarefas de modelação? Que questões se colocam à utilização de sensores? O estudo decorreu numa escola secundária, durante o ano lectivo de 2005/06, sob proposta e com a participação da investigadora, envolvendo uma professora de Matemática e uma professora de Física-Química de uma mesma turma de 100 ano. O grupo colaborativo reuniu regularmente e preparou e leccionou aulas com tarefas de modelação matemática, recorrendo a calculadoras gráficas e sensores, tarefas e tecnologias novas para ambas as professoras. A metodologia utilizada na investigação tem natureza qualitativa, tendo sido realizadas duas entrevistas longas a cada professora, uma no início e outra no fim do estudo, bem como entrevistas de curta duração às professoras após cada uma das aulas onde foram desenvolvidas as tarefas. Foram também recolhidos registos das sessões colectivas de trabalho e elaborado um "diário de bordo". O estudo permitiu formular as seguintes conclusões: - Quando as professoras seleccionavam as tarefas de modelação a propor aos seus alunos tinham em consideração o cumprimento dos programas, os conteúdos a abordar e a diversidade de questões que se podem formular sobre os mesmos e o interesse e significado da experiência para os alunos. - O tempo que é necessário para a preparação e execução das tarefas de modelação pareceu ser factor de grande peso na sua selecção. - O elevado número de alunos por turma pode ser factor um negativo para o desenvolvimento de tarefas de modelação na sala de aula. -Na opinião das professoras, o recurso à calculadora gráfica e aos sensores para realizar a recolha de dados relativos a uma tarefa de modelação tomou-as mais apelativas e ajudou os alunos a compreender a situação em causa assim como permitiu tomar mais nítida a relação entre a Matemática e a Física. ABSTRACT: This study aimed to understand the development of modelling tasks, by a Mathematics teacher and a Physics-Chemistry teacher, as part of collaborative work. For this study were formulated three guidelines: 1. How do teachers select and prepare the modelling tasks to present to the students in a classroom situation? What characteristics of these tasks are essential for their selection? 2. How do teachers develop the modelling tasks in the classroom? How do they manage and dynamize the classes where the modelling tasks took place? What role it's reserd to the teacher and the student? 3. How do teachers exploit the potential of graphics calculator in the development of the modelling tasks? What issues arise for the use of sensors? This study took place at a secundary school during the academic year 2005/06, as a suggestion and with the participation of the researcher, involving a Mathematics teacher and a Physics-Chemistry teacher of the same class (10th grade). The collaborative group had regular meetings and prepared and developed modellin tasks in the classroom using graphics calculator and sensors, which was a new activity for all the teachears. The methodology used has a qualitative nature. Two interviews were made to each teacher, one at baseline and another at the end of the study, fourteen work sections and three modelling tasks were explored in classroom context after which followed small interviews to the teacher that gave the class. ln addition records were also made in a small "log-book". This study allowed to reach the following conclusions: - When the teachers select the modelling tasks to offer its students they take into account the programs, the contents and the diversity of questions that can be made on it and the interest and significance of the experience for students. - The time needed for preparation and implementation of the modelling tasks is another factor of great weight in its selection. - The high number of student per class can be a negative factor for the development of modelling tasks in the classroom. Iii - ln the teacher’s opinion, the use of the graphics calculator and sensors to collect data on a modelling tasks makes its more attractive and helps students to understand the situation and makes clearer the link between Mathematics and Physics.

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We study the growth of a tissue construct in a perfusion bioreactor, focussing on its response to the mechanical environment. The bioreactor system is modelled as a two-dimensional channel containing a tissue construct through which a flow of culture medium is driven. We employ a multiphase formulation of the type presented by G. Lemon, J. King, H. Byrne, O. Jensen and K. Shakesheff in their study (Multiphase modelling of tissue growth using the theory of mixtures. J. Math. Biol. 52(2), 2006, 571–594) restricted to two interacting fluid phases, representing a cell population (and attendant extracellular matrix) and a culture medium, and employ the simplifying limit of large interphase viscous drag after S. Franks in her study (Mathematical Modelling of Tumour Growth and Stability. Ph.D. Thesis, University of Nottingham, UK, 2002) and S. Franks and J. King in their study Interactions between a uniformly proliferating tumour and its surrounding: Uniform material properties. Math. Med. Biol. 20, 2003, 47–89). The novel aspects of this study are: (i) the investigation of the effect of an imposed flow on the growth of the tissue construct, and (ii) the inclusion of a chanotransduction mechanism regulating the response of the cells to the local mechanical environment. Specifically, we consider the response of the cells to their local density and the culture medium pressure. As such, this study forms the first step towards a general multiphase formulation that incorporates the effect of mechanotransduction on the growth and morphology of a tissue construct. The model is analysed using analytic and numerical techniques, the results of which illustrate the potential use of the model to predict the dominant regulatory stimuli in a cell population.

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In this paper we describe the preparation poly (L-lactide) (PLA) nanocapsules as a drug delivery system for the local anesthetic benzocaine. The characterization and in vitro release properties of the system were investigated. The characterization results showed a polydispersity index of 0.14, an average diameter of 190.1± 3 nm, zeta potential of -38.5 mV and an entrapment efficiency of 73%. The release profile of Benzocaine loaded in PLA nanocapsules showed a significant different behavior than that of the pure anesthetic in solution. This study is important to characterize a drug release system using benzocaine for application in pain treatment.

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The 15-deoxy-(Delta 12,14)-PG J(2) (15d-PGJ(2)) has demonstrated excellent anti-inflammatory results in different experimental models. It can be used with a polymeric nanostructure system for modified drug release, which can change the therapeutic properties of the active principle, leading to increased stability and slower/prolonged release. The aim of the current study was to test a nano-technological formulation as a carrier for 15d-PGJ(2), and to investigate the immunomodulatory effects of this formulation in a mouse periodontitis model. Poly (D, L-lactide-coglycolide) nanocapsules (NC) were used to encapsulate 15d-PGJ(2). BALB/c mice were infected on days 0, 2, and 4 with Aggregatibacter actinomycetemcomitans and divided into groups (n = 5) that were treated daily during 15 d with 1, 3, or 10 mu g/kg 15d-PGJ(2)-NC. The animals were sacrificed, the submandibular lymph nodes were removed for FACS analysis, and the jaws were analyzed for bone resorption by morphometry. Immunoinflammatory markers in the gingival tissue were analyzed by reverse transcriptase-quantitative PCR, Western blotting, or ELISA. Infected animals treated with the 15d-PGJ(2)-NC presented lower bone resorption than infected animals without treatment (p < 0.05). Furthermore, infected animals treated with 10 mu g/kg 15d-PGJ(2)-NC had a reduction of CD4(+)CD25(+)FOXP3(+) cells and CD4/CD8 ratio in the submandibular lymph node (p < 0.05). Moreover, CD55 was upregulated, whereas RANKL was downregulated in the gingival tissue of the 10 mu g/kg treated group (p < 0.05). Several proinflammatory cytokines were decreased in the group treated with 10 mu g/kg 15d-PGJ(2)-NC, and high amounts of 15d-PGJ(2) were observed in the gingiva. In conclusion, the 15d-PGJ(2)-NC formulation presented immunomodulatory effects, decreasing bone resorption and inflammatory responses in a periodontitis mouse model. The Journal of Immunology, 2012, 189: 1043-1052.

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Purpose: To develop and optimise some variables that influence fluoxetine orally disintegrating tablets (ODTs) formulation. Methods: Fluoxetine ODTs tablets were prepared using direct compression method. Three-factor, 3- level Box-Behnken design was used to optimize and develop fluoxetine ODT formulation. The design suggested 15 formulations of different lubricant concentration (X1), lubricant mixing time (X2), and compression force (X3) and then their effect was monitored on tablet weight (Y1), thickness (Y2), hardness (Y3), % friability (Y4), and disintegration time (Y5). Results: All powder blends showed acceptable flow properties, ranging from good to excellent. The disintegration time (Y5) was affected directly by lubricant concentration (X1). Lubricant mixing time (X2) had a direct effect on tablet thickness (Y2) and hardness (Y3), while compression force (X3) had a direct impact on tablet hardness (Y3), % friability (Y4) and disintegration time (Y5). Accordingly, Box-Behnken design suggested an optimized formula of 0.86 mg (X1), 15.3 min (X2), and 10.6 KN (X3). Finally, the prediction error percentage responses of Y1, Y2, Y3, Y4, and Y5 were 0.31, 0.52, 2.13, 3.92 and 3.75 %, respectively. Formula 4 and 8 achieved 90 % of drug release within the first 5 min of dissolution test. Conclusion: Fluoxetine ODT formulation has been developed and optimized successfully using Box- Behnken design and has also been manufactured efficiently using direct compression technique.

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Purpose: To improve the effectiveness and reduce the systemic side effects of methylprednisolone in traumatic spinal injuries, its polymeric implants were prepared using chitosan and sodium alginate as the biocompatible polymers. Methods: Implants of methylprednisolone sodium succinate (MPSS) were prepared by molding the drug-loaded polymeric mass obtained after ionotropic gelation method. The prepared implants were evaluated for drug loading, in vitro drug release and in vivo performance in traumatic spinal-injury rat model with paraplegia. Results: All the implant formulations were light pale solid matrix with smooth texture. Implants showed 86.56 ± 2.07 % drug loading. Drug release was 89.29 ± 1.25 % at the end of 7 days. Motor function was evaluated in traumatic spinal injury-induced rats in terms of its movement on the horizontal bar. At the end of 7 days, the test group showed the activity score (4.75 ± 0.02) slightly higher than that of standard (4.62 ± 0.25), but the difference was not statistically different (p > 0.05). Conclusion: MPSS-loaded implants produces good recovery in traumatic spinal-injury rats.

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

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Despite the substantial body of research investigating the use of liposomes, niosomes and other bilayer vesicles for drug delivery, the translation of these systems into licensed products remains limited. Indeed, recent shortages in the supply of liposomal products demonstrate the need for new scalable production methods for liposomes. Therefore, the aim of our research has been to consider the application of microfluidics in the manufacture of liposomes containing either or both a water soluble and a lipid soluble drug to promote co-delivery of drugs. For the first time, we demonstrate the entrapment of a hydrophilic and a lipophilic drug (metformin and glipizide respectively) both individually, and in combination, using a scalable microfluidics manufacturing system. In terms of the operating parameters, the choice of solvents, lipid concentration and aqueous:solvent ratio all impact on liposome size with vesicle diameter ranging from ∼90 to 300 nm. In terms of drug loading, microfluidics production promoted high loading within ∼100 nm vesicles for both the water soluble drug (20–25% of initial amount added) and the bilayer embedded drug (40–42% of initial amount added) with co-loading of the drugs making no impact on entrapment efficacy. However, co-loading of glipizide and metformin within the same liposome formulation did impact on the drug release profiles; in both instances the presence of both drugs in the one formulation promoted faster (up to 2 fold) release compared to liposomes containing a single drug alone. Overall, these results demonstrate the application of microfluidics to prepare liposomal systems incorporating either or both an aqueous soluble drug and a bilayer loaded drug.

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In this thesis, we aim to discuss a simple mathematical model for the edge detection mechanism and the boundary completion problem in the human brain in a differential geometry framework. We describe the columnar structure of the primary visual cortex as the fiber bundle R2 × S1, the orientation bundle, and by introducing a first vector field on it, explain the edge detection process. Edges are detected through a lift from the domain in R2 into the manifold R2 × S1 and are horizontal to a completely non-integrable distribution. Therefore, we can construct a subriemannian structure on the manifold R2 × S1, through which we retrieve perceived smooth contours as subriemannian geodesics, solutions to Hamilton’s equations. To do so, in the first chapter, we illustrate the functioning of the most fundamental structures of the early visual system in the brain, from the retina to the primary visual cortex. We proceed with introducing the necessary concepts of differential and subriemannian geometry in chapters two and three. We finally implement our model in chapter four, where we conclude, comparing our results with the experimental findings of Heyes, Fields, and Hess on the existence of an association field.

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We give conditions on f involving pairs of lower and upper solutions which lead to the existence of at least three solutions of the two point boundary value problem y" + f(x, y, y') = 0, x epsilon [0, 1], y(0) = 0 = y(1). In the special case f(x, y, y') = f(y) greater than or equal to 0 we give growth conditions on f and apply our general result to show the existence of three positive solutions. We give an example showing this latter result is sharp. Our results extend those of Avery and of Lakshmikantham et al.

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Nine classes of integrable boundary conditions for the eight-state supersymmetric model of strongly correlated fermions are presented. The boundary systems are solved by using the coordinate Bethe ansatz method and the Bethe ansatz equations for all nine cases are given.

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alpha-Conotoxin MII, a 16-residue polypeptide from the venom of the piscivorous cone snail Conus magus, is a potent and highly specific blocker of mammalian neuronal nicotinic acetylcholine receptors composed of alpha 3 beta 2 subunits. The role of this receptor type in the modulation of neurotransmitter release and its relevance to the problems of addiction and psychosis emphasize the importance of a structural understanding of the mode of interaction of MII with the alpha 3 beta 2 interface. Here we describe the three-dimensional solution structure of MIT determined using 2D H-1 NMR spectroscopy. Structural restraints consisting of 376 interproton distances inferred from NOEs and 12 dihedral restraints derived from spin-spin coupling constants were used as input for simulated annealing calculations and energy minimization in the program X-PLOR. The final set of 20 structures is exceptionally well-defined with mean pairwise rms differences over the whole molecule of 0.07 Angstrom for the backbone atoms and 0.34 Angstrom for all heavy atoms. MII adopts a compact structure incorporating a central segment of alpha-helix and beta-turns at the N- and C-termini. The molecule is stabilized by two disulfide bonds, which provide cross-links between the N-terminus and both the middle and C-terminus of the structure. The susceptibility of the structure to conformational change was examined using several different solvent conditions. While the global fold of MII remains the same, the structure is stabilized in a more hydrophobic environment provided by the addition of acetonitrile or trifluoroethanol to the aqueous solution. The distribution of amino acid side chains in MII creates distinct hydrophobic and polar patches on its surface that may be important for the specific interaction with the alpha 3 beta 2 neuronal nAChR. A comparison of the structure of MII with other neuronal-specific alpha-conotoxins provides insights into their mode of interaction with these receptors.

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Integrable Kondo impurities in the one-dimensional supersymmetric U model of strongly correlated electrons are studied by means of the boundary graded quantum inverse scattering method. The boundary K-matrices depending on the local magnetic moments of the impurities are presented as non-trivial realizations of the reflection equation algebras in an impurity Hilbert space. Furthermore, the model Hamiltonian is diagonalized and the Bethe ansatz equations are derived. It is interesting to note that our model exhibits a free parameter in the bulk Hamiltonian but no free parameter exists on the boundaries. This is in sharp contrast to the impurity models arising from the supersymmetric t-J and extended Hubbard models where there is no free parameter in the bulk but there is a free parameter on each boundary.

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An integrable Kondo problem in the one-dimensional supersymmetric extended Hubbard model is studied by means of the boundary graded quantum inverse scattering method. The boundary K-matrices depending on the local moments of the impurities are presented as a non-trivial realization of the graded reflection equation algebras in a two-dimensional impurity Hilbert space. Further, the model is solved by using the algebraic Bethe ansatz method and the Bethe ansatz equations are obtained.