Diphtheria toxoid conformation in the context of its nanoencapsulation within liposomal particles sandwiched by chitosan

Chitosan (alpha alpha-(1-4)-amino-2-deoxy-beta beta-D-glucan) is a deacetylated form of chitin, a polysaccharide from crustacean shells. Its unique characteristics, such as positive charge, biodegradability, biocompatibility, nontoxicity, and rigid structure, make this macromolecule ideal for an oral vaccine delivery system. We prepared reverse-phase evaporation vesicles (REVs) sandwiched by chitosan (Chi) and polyvinylic alcohol (PVA). However, in this method, there are still some problems to be circumvented related to protein stabilization. During the inverted micelle phase of protein nanoencapsulation, hydrophobic interfaces are expanded, leading to interfacial adsorption, followed by protein unfolding and aggregation. Here, spectroscopic and immunological techniques were used to ascertain the effects of the Hoffmeister series ions on diphtheria toxoid (Dtxd) stability during the inverted micelle phase. A correlation was established between the salts used in aqueous solutions and the changes in Dtxd solubility and conformation. Dtxd alpha alpha-helical content was quite stable, which led us to conclude that encapsulation occurred without protein aggregation or without exposition of hydrophobic residues. Dtxd aggregation was 98% avoided by the kosmotropic, PO

Dressing liposomal particles with chitosan and poly(vinylic alcohol) for oral vaccine delivery

Liposomes have been used as adjuvants since 1974. One major limitation for the use of liposomes in oral vaccines is the lipid structure instability caused by enzyme activities. Our aim was to combine liposomes that could encapsulate antigens (i.e., Dtxd, diphtheria toxoid) with chitosan, which protects the particles and promotes mucoadhesibility. We employed physical techniques to understand the process by which liposomes (SPC: Cho, 3: 1) can be sandwiched with chitosan (Chi) and stabilized by PVA (poly-vinylic alcohol), which are biodegradable, biocompatible polymers. Round, smooth-surfaced particles of REVs-Chi (reversed-phase vesicles sandwiched by Chi) stabilized by PVA were obtained. The REVs encapsulation efficiencies (Dtxd was used as the antigen) were directly dependent on the Chi and PVA present in the formulation. Chi adsorption on the REVs surface was accompanied by an increase of zeta-potential. In contrast, PVA adsorption on the REVs-Chi surface was accompanied by a decrease of zeta-potential. The presence of Dtxd increased the Chi surface-adsorption efficiency. The PVA affinity by mucine was 2,000 times higher than that observed with Chi alone and did not depend on the molecule being in solution or adsorbed on the liposomal surface. The liberation of encapsulated Dtxd was retarded by encapsulation within REVs-Chi-PVA. These results lead us to conclude that these new, stabilized particles were able to be adsorbed by intestinal surfaces, resisted degradation, and controlled antigen release. Therefore, REVs-Chi-PVA particles can be used as an oral delivery adjuvant.

Antimicrobial Particles from Cationic Lipid and Polyelectrolytes

Hybrid nanoparticles from cationic lipid and polymers were prepared and characterized regarding physical properties and antimicrobial activity. Carboxymethylcellulose (CMC) and polydiallyldimethylammonium chloride (PDDA) were sequentially added to cationic bilayer fragments (BF) prepared from ultrasonic dispersion in water of the synthetic and cationic lipid dioctadecyldimethylammonium bromide (DODAB). Particles thus obtained were characterized by dynamic light-scattering for determination of z-average diameter (Dz) and zeta-potential (zeta). Antimicrobial activity of the DODAB BF/CMC/PDDA particles against Pseudomonas aeruginosa or Staphylococcus aureus was determined by plating and CFU counting over a range of particle compositions. DODAB BF/CMC/PDDA particles exhibited sizes and zeta-potentials strictly dependent on DODAB, CM C, and PDDA concentrations. At 0.1 mM DODAB, 0.1 mg/mL CMC, and 0.1 mg/mL PDDA, small cationic particles with Dz = 100 nm and zeta = 30 mV were obtained. At 0.5 mM DODAB, 0.5 mg/mL CMC and 0.5 mg/mL PDDA, large cationic particles with Dz = 470 nm and zeta= 50 mV were obtained. Both particulates were highly reproducible regarding physical properties and yielded 0% of p. aeruginosa viability (10(7) CFU/mL) at 1 or 2 mu g/mL PDDA dissolved in solution or in form of particles, respectively. 99% of S. aureus cells died at 10 mu g/mL PDDA alone or in small or large DODAB BF/CMC/PDDA particles. The antimicrobial effect was dependent on the amount of positive charge on particles and independent of particle size. A high microbicide potency for PDDA over a range of nanomolar concentrations was disclosed. P. aeruginosa was more sensitive to all cationic assemblies than S. aureus.

Degradation and adsorption of AZO RR239 dye in aqueous solution by nanoscale zerovalent iron particles immobilized on sawdust

Carra sawdust pretrated with formaldehyde was used to adsorb RR239 (reactive azo dye) at varying pH and zerovalent iron (ZVI) dosage. Modeling of kinetic results shows that sorption process is best described by the pseudo-second-order model. Batch experiments suggest that the decolorization efficiency was strongly enhanced with the presence of ZVI and low solution pH. The kinetics of dye sorption by mixed sorbent (5 g of sawdust and 180 mg of ZVI) at pH 2.0 was rapid, reaching more than 90% of the total discoloration in three minutes.

PVP superabsorbent nanogels

Monomer free hydrogel nanoparticles (nanogels) were prepared by crosslinking preformed poly(N-vinyl-2-pyrrolidone) (PVP) entrapped in the aqueous pool of hexadecyltrimethylammonium bromide reverse micelles using the Fenton reaction. The PVP nanoparticles were spherical with a dry diameter of 27 nm. The diameter of the swollen particles was ten times higher, i.e., a swelling ratio, Q, above 900, characterizing this preparation as superabsorbent. PVP nanogel swelling was dependent on bound Fe(3+) and varied with pH and ionic strength. Nanogel deswelling by salt followed the anions lyotropic series, i.e., SCN(-) < HSO(3)(-) < NO(3)(-) < I(-) < Cl(-) < CH(3)COO(-) < CF(3)SO(3)(-). The value of Q reached 6,000 in iron-free PVP nanoparticles at low pH, making this nanogel one of the most efficient swelling systems so far described.

Under flow impedimetric measurements using magnetic particles for label-free detection affinity target

The necessity to adapt sensors based on electrochemical techniques for high throughput analysis control increases the interest to develop new analytical systems able to perform measurements under buffer now. In this report we explored the possibility of employing a new system to make impedimetric measurements to detect the interaction between proteins and small molecules. The well-known biotin-streptavidin interaction was adopted to evaluate the proposed assembly. This system allows us to perform experiments under flow. Magnetic beads functionalized with streptavidin were used and first characterized using AFM and FTIR. Non-faradic impedance spectroscopy allowed the detection of the biotin-streptavidin interaction. Using our new system and under a flow of PBS buffer, 5 10-5 M of biotin was detected with a stable signal. (c) 2007 Elsevier B.V. All rights reserved.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

Gravitational self-localization for spherical masses

In this work, I consider the center-of-mass wave function for a homogenous sphere under the influence of the self-interaction due to Newtonian gravity. I solve for the ground state numerically and calculate the average radius as a measure of its size. For small masses, M≲10−17 kg, the radial size is independent of density, and the ground state extends beyond the extent of the sphere. For masses larger than this, the ground state is contained within the sphere and to a good approximation given by the solution for an effective radial harmonic-oscillator potential. This work thus determines the limits of applicability of the point-mass Newton Schrödinger equations for spherical masses. In addition, I calculate the fringe visibility for matter-wave interferometry and find that in the low-mass case, interferometry can in principle be performed, whereas for the latter case, it becomes impossible. Based on this, I discuss this transition as a possible boundary for the quantum-classical crossover, independent of the usually evoked environmental decoherence. The two regimes meet at sphere sizes R≈10−7 m, and the density of the material causes only minor variations in this value.

Using Normative Markov Decision Processes for Evaluating Electronic Contracts: A Case Study in a Simulated Aerospace Aftermarket

Before signing electronic contracts, a rational agent should estimate the expected utilities of these contracts and calculate the violation risks related to them. In order to perform such pre-signing procedures, this agent has to be capable of computing a policy taking into account the norms and sanctions in the contracts. In relation to this, the contribution of this work is threefold. First, we present the Normative Markov Decision Process, an extension of the Markov Decision Process for explicitly representing norms. In order to illustrate the usage of our framework, we model an example in a simulated aerospace aftermarket. Second, we specify an algorithm for identifying the states of the process which characterize the violation of norms. Finally, we show how to compute policies with our framework and how to calculate the risk of violating the norms in the contracts by adopting a particular policy.