Novel strategy for encapsulation and targeted delivery of poorly water-soluble active substances

Carriers for targeted delivery and controlled release of poorly water-soluble active substances (PWSAS) are facing three challenges: (a) the encapsulation issues, (b) limitations of PWSAS water solubility, and (c) burst drug release which can be pharmacologically dangerous and economically inefficient. The present study brings a novel strategy for encapsulation and controlled release of PWSAS—caffeine in concentrations which are higher than its maximal water solubility without the possibility of burst effect. The modification of hydrophilic carrier based on poly(methacylic acid) was done using casein and liposomes. To further increase the maximal caffeine loading inside the carrier nicotinamide was used. The release study of the encapsulated PWSAS was elaborated with respect to morphology of the carriers and interactions that could be established between its structural components. The carriers swelling and the release of caffeine and nicotinamide were also investigated depending on caffeine concentration, the presence of different liposomal formulations and the volume ratio of liposomal formulation, in three media with different pH simulating the path of the carrier through the human gastrointestinal tract. The synthesized carriers are promising candidates for encapsulation of PWSAS in concentrations which are higher than its maximal water solubility and for the targeted delivery of those dosages.     

Predicting bleaching results with computer imaging

Vital bleaching can be a relatively unpredictable treatment. Photographs of previous cases and cosmetic imaging, although useful, may lead to unrealistic expectations on the part of the patient. The high-tech mystique of computer imaging and viewing one's own teeth has a significant impact on the dental patient. Whether imaged by the dentist or an auxiliary, patients must be aware of alternatives that may exist both before and during treatment. Cosmetic imaging should be used as an adjunct to, not as the prime motivator for, treatment planning in bleaching cases. Excellent communication between the practitioner and patient is the most important factor in assuring positive bleaching results and patient satisfaction.     

Nitric oxide synthase-immunoreactive neurons in human and porcine respiratory tract

The presence of nitric oxide synthase (NO-synthase), the enzyme responsible for the production of nitric oxide (NO) from L-arginine, is shown immunocytochemically in the intrinsic neurons of the human and porcine respiratory tract. NO-synthase immunoreactivity is demonstrated in a subpopulation of neurons of the microganglia present in the wall of the extra- and intrapulmonary bronchi as well as in the hilar region of the lung in relation to blood vessels. The immunostaining was also found in some nerve fibers of the respiratory nervous system. Human and porcine lung gave similar results. The possible involvement of NO in the nonadrenergic noncholinergic (NANC) nervous regulation of the lung is discussed.     

Towards a consolidated model for a collaborative courseware authoring system

Abstract In an effort to reduce the expensive resource requirements in courseware production and to allow effective management of, and communication and collaboration between authors, a model is needed to harmonize the diverse theoretical backgrounds such a process requires. To this end we look at five abstract models which where chosen for their apparent appropriateness within the general area of collaborative authoring and reuse of multimedia courseware. These models consist of a functional model of hypertext, an infrastructure model for an open collaborative authoring system, two object-oriented communication models, and a courseware production model. We attempt a consolidation of these models and ultimately make several conclusions, which are exposed during a conceptual harmonisation. The principal conclusion is that a hypermedia logical model is not by itself adequate to support collaboration and reuse. Our modeling conclusions have driven the design of a system which will be implemented and tested.     

Switching to Directional Antennas with Constant Increase in Radius and Hop Distance

For any angle α<2π, we show that any connected communication graph that is induced by a set P of n transceivers using omni-directional antennas of radius 1, can be replaced by a strongly connected communication graph, in which each transceiver in P is equipped with a directional antenna of angle α and radius r _dir, for some constant r _dir=r _dir(α). Moreover, the new communication graph is a c-spanner of the original graph, for some constant c=c(α), with respect to number of hops.     

Solid/liquid extraction and isolation by molecular distillation of hydroxytyrosol from Olea europaea L. leaves

Molecular distillation, or short‐path distillation (SPD), is particularly appropriate for processing of low‐volatility compounds, which are easily altered at high temperature. Olea europaea L. leaves constitute an olive tree by‐product very interesting for their natural antioxidants content. In this research, molecular distillation technology has been applied to obtain high‐value‐added compounds by the SPD fractionation of an olive tree leaf extract. The process consists of two stages: (a) ethanolic extraction of the olive leaves, followed by incorporation of the extract into glycerine and (b) molecular distillation of the glycerine enriched in olive leaf extract compounds (terpenic and phenolic compounds). Four molecular distillation tests under different conditions were carried out. Results showed that 80.9% 3,4‐dihydroxy‐phenylethanol (hydroxytyrosol) was recovered from the glycerine admixture under a pressure of 1.50–2.00 mbar, a temperature of 190 °C and a feed rate of 15 mL/min.     

An adaptive neuro‐fuzzy system for stock portfolio analysis

We propose an adaptive neuro‐fuzzy inference system (ANFIS) for stock portfolio return prediction. Previous work has shown that portfolio optimization can be improved by using predicted stock earnings rather than historical earnings. We show that predicted portfolio returns can be improved by using ANFIS and taking as input a variety of technical and fundamental attributes about various indices of the stock market. To generate membership functions, we use a robust noise rejection‐clustering algorithm. The neuro‐fuzzy model is tested on portfolios constituted from the Tehran Stock Exchange. In our experiments, the proposed method performs better in predicting the portfolio return than the classical Markowitz portfolio optimization method, a multiple regression, a neural network, and the Sugeno–Yasukawa method. © 2010 Wiley Periodicals, Inc.     

Advection‐Based Function Matching on Surfaces

A tangent vector field on a surface is the generator of a smooth family of maps from the surface to itself, known as the flow. Given a scalar function on the surface, it can be transported, or advected, by composing it with a vector field's flow. Such transport is exhibited by many physical phenomena, e.g., in fluid dynamics. In this paper, we are interested in the inverse problem: given source and target functions, compute a vector field whose flow advects the source to the target. We propose a method for addressing this problem, by minimizing an energy given by the advection constraint together with a regularizing term for the vector field. Our approach is inspired by a similar method in computational anatomy, known as LDDMM, yet leverages the recent framework of functional vector fields for discretizing the advection and the flow as operators on scalar functions. The latter allows us to efficiently generalize LDDMM to curved surfaces, without explicitly computing the flow lines of the vector field we are optimizing for. We show two approaches for the solution: using linear advection with multiple vector fields, and using non‐linear advection with a single vector field. We additionally derive an approximated gradient of the corresponding energy, which is based on a novel vector field transport operator. Finally, we demonstrate applications of our machinery to intrinsic symmetry analysis, function interpolation and map improvement.     

Discovery of Intrinsic Primitives on Triangle Meshes

The discovery of meaningful parts of a shape is required for many geometry processing applications, such as parameterization, shape correspondence, and animation. It is natural to consider primitives such as spheres, cylinders and cones as the building blocks of shapes, and thus to discover parts by fitting such primitives to a given surface. This approach, however, will break down if primitive parts have undergone almost‐isometric deformations, as is the case, for example, for articulated human models. We suggest that parts can be discovered instead by finding intrinsic primitives, which we define as parts that posses an approximate intrinsic symmetry. We employ the recently‐developed method of computing discrete approximate Killing vector fields (AKVFs) to discover intrinsic primitives by investigating the relationship between the AKVFs of a composite object and the AKVFs of its parts. We show how to leverage this relationship with a standard clustering method to extract k intrinsic primitives and remaining asymmetric parts of a shape for a given k. We demonstrate the value of this approach for identifying the prominent symmetry generators of the parts of a given shape. Additionally, we show how our method can be modified slightly to segment an entire surface without marking asymmetric connecting regions and compare this approach to state‐of‐the‐art methods using the Princeton Segmentation Benchmark.     

As‐Killing‐As‐Possible Vector Fields for Planar Deformation

Cartoon animation, image warping, and several other tasks in two‐dimensional computer graphics reduce to the formulation of a reasonable model for planar deformation. A deformation is a map from a given shape to a new one, and its quality is determined by the type of distortion it introduces. In many applications, a desirable map is as isometric as possible. Finding such deformations, however, is a nonlinear problem, and most of the existing solutions approach it by minimizing a nonlinear energy. Such methods are not guaranteed to converge to a global optimum and often suffer from robustness issues. We propose a new approach based on approximate Killing vector fields (AKVFs), first introduced in shape processing. AKVFs generate near‐isometric deformations, which can be motivated as direction fields minimizing an “as‐rigid‐as‐possible” (ARAP) energy to first order. We first solve for an AKVF on the domain given user constraints via a linear optimization problem and then use this AKVF as the initial velocity field of the deformation. In this way, we transfer the inherent nonlinearity of the deformation problem to finding trajectories for each point of the domain having the given initial velocities. We show that a specific class of trajectories — the set of logarithmic spirals — is especially suited for this task both in practice and through its relationship to linear holomorphic vector fields. We demonstrate the effectiveness of our method for planar deformation by comparing it with existing state‐of‐the‐art deformation methods.