Microspheres as a vehicle for biomolecule delivery to neural stem cells

Neural stem cells (NSC) are a valuable model system for understanding the intrinsic and extrinsic controls for self-renewal and differentiation choice. They also offer a platform for drug screening and neurotoxicity studies, and hold promise for cell replacement therapies for the treatment of neurodegenerative diseases. Fully exploiting the potential of this experimental tool often requires the manipulation of intrinsic cues of interest using transfection methods, to which NSC are relatively resistant. In this paper, we show that mouse and human NSC readily take up polystyrene-based microspheres which can be loaded with a range of chemical or biological cargoes. This uptake can take place in the undifferentiated stage without affecting NSC proliferation and their capacity to give rise to neurons and glia. We demonstrate that ß-galactosidase-loaded microspheres could be efficiently introduced into NSC with no apparent toxic effect, thus providing proof-of-concept for the use of microspheres as an alternative biomolecule delivery system.

Reduction of Secondary Degeneration after Spinal Cord Injury by Acute Delivery of Proinflammatory Growth Factors

INTRODUCTION Inflammation is a protective attempt to facilitate the removal of damaged tissue and to initiate the healing response in other tissues. However, after spinal cord injury (SCI), this response is prolonged leading to secondary degeneration and glial scarring. Here, we investigate the potential of sustained delivery of pro-inflammatory factors vascular endothelial growth factor (VEGF) and platelet derived growth factor (PDGF) to increase early inflammatory events and promote inflammatory resolution. Method Animal ethics approval was obtained from the Queensland University of Technology. Adult Wistar-Kyoto rats (12-16 weeks old) were subjected to laminectomies and T10 hemisections. Animals were then randomised to treatment (implantation of osmotic pump (Alzet) loaded with 5ug VEGF & 5 ug PDGF) or control groups (lesion control or lesion plus pump delivering PBS). Rats were sacrificed at one month and the spinal cords were harvested and examined by immunohistology, using anti-neurofilament-200(NF200) and anti- ionized calcium binding adapter molecule 1 (Iba1). One way ANOVA was used for statistic analysis. Results At 1 month, active pump-treated cords showed a high level of axonal filament throughout the defects as compared to the control groups. The mean lesion size, as measured by NF200, was 0.47mm2 for the lesion control, 0.39mm2 for the vehicle control and 0.078mm2 for the active pump group. Significant differences were detected between the active pump group and the two control groups (AP vs LC p= 0.017 AG vs VC p= 0.004). Iba-1 staining also showed significant differences in the post-injury inflammatory response. Discussion We have shown that axons and activated microglia are co-located in the lesion of the treated cord. We hypothesise the delivery of VEGF/PDGF increases the local vessel permeability to inflammatory cells and activates these along with the resident microglia to threshold population, which ultimately resolved the prolonged inflammation. Here, we have shown that maintaining the inflammatory signals for at least 7 days improved the morphology of the injured cord. Conclusion This study has shown that boosting inflammation, by delivery VEGF/PDGF, in the early phase of SCI helps to reduce secondary degeneration and may promote inflammation resolution. This treatment may provide a platform for other neuro-regenrative therapies.

A test vehicle for compliance with resilience requirements in index-based e-health systems

Increasingly, national and international governments have a strong mandate to develop national e-health systems to enable delivery of much-needed healthcare services. Research is, therefore, needed into appropriate security and reliance structures for the development of health information systems which must be compliant with governmental and alike obligations. The protection of e-health information security is critical to the successful implementation of any e-health initiative. To address this, this paper proposes a security architecture for index-based e-health environments, according to the broad outline of Australia’s National E-health Strategy and National E-health Transition Authority (NEHTA)’s Connectivity Architecture. This proposal, however, could be equally applied to any distributed, index-based health information system involving referencing to disparate health information systems. The practicality of the proposed security architecture is supported through an experimental demonstration. This successful prototype completion demonstrates the comprehensibility of the proposed architecture, and the clarity and feasibility of system specifications, in enabling ready development of such a system. This test vehicle has also indicated a number of parameters that need to be considered in any national indexed-based e-health system design with reasonable levels of system security. This paper has identified the need for evaluation of the levels of education, training, and expertise required to create such a system.

Building Large Scale Traversability Maps Using Vehicle Experience

Traversability maps are a global spatial representation of the relative difficulty in driving through a local region. These maps support simple optimisation of robot paths and have been very popular in path planning techniques. Despite the popularity of these maps, the methods for generating global traversability maps have been limited to using a-priori information. This paper explores the construction of large scale traversability maps for a vehicle performing a repeated activity in a bounded working environment, such as a repeated delivery task.We evaluate the use of vehicle power consumption, longitudinal slip, lateral slip and vehicle orientation to classify the traversability and incorporate this into a map generated from sparse information.

Optimal planning of electric-vehicle charging stations in distribution systems

With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

Poly propyl ether imine (PETIM) dendrimer: A novel non-toxic dendrimer for sustained drug delivery

In the present study, an attempt was made to study the acute and sub-acute toxicity profile of G3-COOH Poly (propyl ether imine) PETIM] dendrimer and its use as a carrier for sustained delivery of model drug ketoprofen. Drug-dendrimer complex was prepared and characterized by FTIR, solubility and in vitro drug release study. PETIM dendrimer was found to have significantly less toxicity in A541 cells compared to Poly amido amine (PAMAM) dendrimer. Further, acute and 28 days sub-acute toxicity measurement in mice showed no mortality, hematological, biochemical or histopathological changes up to 80 mg/kg dose of PETIM dendrimer. The results of study demonstrated that G3-COOH PETIM dendrimer can be used as a safe and efficient vehicle for sustained drug delivery. (C) 2010 Elsevier Masson SAS. All rights reserved.

Vaginal delivery of the recombinant HIV-1 clade-C trimeric gp140 envelope protein CN54gp140 within novel rheologically structured vehicles elicits specific immune responses

Rheologically structured vehicle (RSV) gels were developed as delivery systems for vaginal mucosal vaccination with an HIV-1 envelope glycoprotein (CN54gp140). RSVs comprised a mucoadhesive matrix forming and vaginal fluid absorbing polymer. The mucoadhesive and rheological properties of the RSVs were evaluated in vitro, and the distribution, antigenicity and release of CN54gp140 were analysed by ELISA. CN54gp140 was uniformly distributed within the RSVs and continuously released in vitro in an antigenically intact form over 24 h. Vaginal administration to rabbits induced specific serum IgG, and IgG and IgA in genital tract secretions. The RSVs are a viable delivery modality for vaginal immunization.

An Evaluation of the Effectiveness of an FE/HE Partnership in the Delivery of a Preparation for Practice Module within an Undergraduate Social Work Degree Programme

The Preparation for Practice module at the University of Ulster is delivered to 170 first year students via a collaborative arrangement between higher and further education institutions. In each of the five sites, students receive large group and small group teaching facilitated by social work training agency workers and academic tutor dyads. An evaluation of the module sought the perceptions of the agency and academic facilitators regarding the overall collaborative arrangement and the model of co-teaching involving social work academics and agency partners. Respondents were asked to complete a semi-structured questionnaire, which generated data from a Likert scale and also invited qualitative commentary. The Likert scale data were analysed via SPSS and the qualitative information was scrutinised using a manual thematic analysis technique. Findings indicated that continuous communication, consistency in programme content and the acknowledgement of the differences in organisation resources were key to a successful collaborative arrangement. It was also noted that a co-teaching model should be viewed as a positive vehicle for achieving module objectives in a safe learning environment.

Graphene Nanoribbons as a Drug Delivery Agent for Lucanthone Mediated Therapy of Glioblastoma Multiforme

We report use of PEG-DSPE coated oxidized graphene nanoribbons (O-GNR-PEG-DSPE) as agent for delivery of anti-tumor drug Lucanthone (Luc) into Glioblastoma Multiformae (GBM) cells targeting base excision repair enzyme APE-1 (Apurinic endonuclease-1). Lucanthone, an endonuclease inhibitor of APE-1, was loaded onto O-GNR-PEG-DSPEs using a simple non-covalent method. We found its uptake by GBM cell line U251 exceeding 67% and 60% in APE-1-overexpressing U251, post 24 h. However, their uptake was ~ 38% and 29% by MCF-7 and rat glial progenitor cells (CG-4), respectively. TEM analysis of U251 showed large aggregates of O-GNR-PEG-DSPE in vesicles. Luc-O-GNR-PEG-DSPE was significantly toxic to U251 but showed little/no toxicity when exposed to MCF-7/CG-4 cells. This differential uptake effect can be exploited to use O-GNR-PEG-DSPEs as a vehicle for Luc delivery to GBM, while reducing nonspecific cytotoxicity to the surrounding healthy tissue. Cell death in U251 was necrotic, probably due to oxidative degradation of APE-1.

Graphical abstract

We used O-GNR-PEG-DSPE as a reliable, non-toxic vehicle for delivery of APE-1 inhibiting Lucanthone into GBM tumor cell lines. LUC-O-GNR-PEG-DSPE particles showed 60% or more uptake by CMV/U251 and A1-5/CMV/U251 where as the uptake by MCF7 and normal CG4 glial cells was much lower (38% and 29% respectively). Different concentrations of Luc (5–80 μM) loaded onto O-GNR-PEG-DSPE showed lower toxicity in the exposed cells compared to the free drug, due to possible slow release of the drug from this particle, which ensures minimum non-specific release of the drug from the particle once it is injected in vivo.
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Development and characterization of novel vehicles for topical drug delivery

Tese de doutoramento, Farmácia (Tecnologia Farmacêutica), Universidade de Lisboa, Faculdade de Farmácia, 2016

Heuristic solution methods for multi-attribute vehicle routing problems

Le Problème de Tournées de Véhicules (PTV) est une clé importante pour gérér efficacement des systèmes logistiques, ce qui peut entraîner une amélioration du niveau de satisfaction de la clientèle. Ceci est fait en servant plus de clients dans un temps plus court. En terme général, il implique la planification des tournées d'une flotte de véhicules de capacité donnée basée à un ou plusieurs dépôts. Le but est de livrer ou collecter une certain quantité de marchandises à un ensemble des clients géographiquement dispersés, tout en respectant les contraintes de capacité des véhicules. Le PTV, comme classe de problèmes d'optimisation discrète et de grande complexité, a été étudié par de nombreux au cours des dernières décennies. Étant donné son importance pratique, des chercheurs dans les domaines de l'informatique, de la recherche opérationnelle et du génie industrielle ont mis au point des algorithmes très efficaces, de nature exacte ou heuristique, pour faire face aux différents types du PTV. Toutefois, les approches proposées pour le PTV ont souvent été accusées d'être trop concentrées sur des versions simplistes des problèmes de tournées de véhicules rencontrés dans des applications réelles. Par conséquent, les chercheurs sont récemment tournés vers des variantes du PTV qui auparavant étaient considérées trop difficiles à résoudre. Ces variantes incluent les attributs et les contraintes complexes observés dans les cas réels et fournissent des solutions qui sont exécutables dans la pratique. Ces extensions du PTV s'appellent Problème de Tournées de Véhicules Multi-Attributs (PTVMA). Le but principal de cette thèse est d'étudier les différents aspects pratiques de trois types de problèmes de tournées de véhicules multi-attributs qui seront modélisés dans celle-ci. En plus, puisque pour le PTV, comme pour la plupart des problèmes NP-complets, il est difficile de résoudre des instances de grande taille de façon optimale et dans un temps d'exécution raisonnable, nous nous tournons vers des méthodes approcheés à base d’heuristiques.

Meta-heuristic Solution Methods for Rich Vehicle Routing Problems

Le problème de tournées de véhicules (VRP), introduit par Dantzig and Ramser en 1959, est devenu l'un des problèmes les plus étudiés en recherche opérationnelle, et ce, en raison de son intérêt méthodologique et de ses retombées pratiques dans de nombreux domaines tels que le transport, la logistique, les télécommunications et la production. L'objectif général du VRP est d'optimiser l'utilisation des ressources de transport afin de répondre aux besoins des clients tout en respectant les contraintes découlant des exigences du contexte d’application. Les applications réelles du VRP doivent tenir compte d’une grande variété de contraintes et plus ces contraintes sont nombreuse, plus le problème est difficile à résoudre. Les VRPs qui tiennent compte de l’ensemble de ces contraintes rencontrées en pratique et qui se rapprochent des applications réelles forment la classe des problèmes ‘riches’ de tournées de véhicules. Résoudre ces problèmes de manière efficiente pose des défis considérables pour la communauté de chercheurs qui se penchent sur les VRPs. Cette thèse, composée de deux parties, explore certaines extensions du VRP vers ces problèmes. La première partie de cette thèse porte sur le VRP périodique avec des contraintes de fenêtres de temps (PVRPTW). Celui-ci est une extension du VRP classique avec fenêtres de temps (VRPTW) puisqu’il considère un horizon de planification de plusieurs jours pendant lesquels les clients n'ont généralement pas besoin d’être desservi à tous les jours, mais plutôt peuvent être visités selon un certain nombre de combinaisons possibles de jours de livraison. Cette généralisation étend l'éventail d'applications de ce problème à diverses activités de distributions commerciales, telle la collecte des déchets, le balayage des rues, la distribution de produits alimentaires, la livraison du courrier, etc. La principale contribution scientifique de la première partie de cette thèse est le développement d'une méta-heuristique hybride dans la quelle un ensemble de procédures de recherche locales et de méta-heuristiques basées sur les principes de voisinages coopèrent avec un algorithme génétique afin d’améliorer la qualité des solutions et de promouvoir la diversité de la population. Les résultats obtenus montrent que la méthode proposée est très performante et donne de nouvelles meilleures solutions pour certains grands exemplaires du problème. La deuxième partie de cette étude a pour but de présenter, modéliser et résoudre deux problèmes riches de tournées de véhicules, qui sont des extensions du VRPTW en ce sens qu'ils incluent des demandes dépendantes du temps de ramassage et de livraison avec des restrictions au niveau de la synchronization temporelle. Ces problèmes sont connus respectivement sous le nom de Time-dependent Multi-zone Multi-Trip Vehicle Routing Problem with Time Windows (TMZT-VRPTW) et de Multi-zone Mult-Trip Pickup and Delivery Problem with Time Windows and Synchronization (MZT-PDTWS). Ces deux problèmes proviennent de la planification des opérations de systèmes logistiques urbains à deux niveaux. La difficulté de ces problèmes réside dans la manipulation de deux ensembles entrelacés de décisions: la composante des tournées de véhicules qui vise à déterminer les séquences de clients visités par chaque véhicule, et la composante de planification qui vise à faciliter l'arrivée des véhicules selon des restrictions au niveau de la synchronisation temporelle. Auparavant, ces questions ont été abordées séparément. La combinaison de ces types de décisions dans une seule formulation mathématique et dans une même méthode de résolution devrait donc donner de meilleurs résultats que de considérer ces décisions séparément. Dans cette étude, nous proposons des solutions heuristiques qui tiennent compte de ces deux types de décisions simultanément, et ce, d'une manière complète et efficace. Les résultats de tests expérimentaux confirment la performance de la méthode proposée lorsqu’on la compare aux autres méthodes présentées dans la littérature. En effet, la méthode développée propose des solutions nécessitant moins de véhicules et engendrant de moindres frais de déplacement pour effectuer efficacement la même quantité de travail. Dans le contexte des systèmes logistiques urbains, nos résultats impliquent une réduction de la présence de véhicules dans les rues de la ville et, par conséquent, de leur impact négatif sur la congestion et sur l’environnement.

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.

A flow control methodology for the rapid generation of vehicle traffic models

This paper presents a conveyor-based methodology to model complex vehicle flows common to factory and distribution warehouse facilities. The AGV and human path modelling techniques available in many commercial discrete event simulation packages require extensive knowledge and time to implement even the simplest flow control rules for multiple vehicle interaction. Although discrete event simulation is accepted as an effective tool to model vehicle delivery movements, human paths and delivery schedules for modern assembly lines, the time to generate accurate models is a significant limitation of existing simulation-based optimisation methodologies. The flow control method has been successfully implemented using two commercial simulation packages. It provides a realistic visual representation, as well as accurate statistical results, and reduces the model development process cost.

Microencapsulation of coupled folate and chitosan nanoparticles for targeted delivery of combination drugs to colon

Folate-chitosan nanoparticles, co-loaded with 5-fluourouacil (5-FU) and leucovorin (LV) and prepared by ionic gelation technology were physically microencapsulated by enteric polymer using a solvent evaporation method. Average particle size of the microencapsulated particles was in the range of 15 to 35 µm. High drug encapsulation efficiency was obtained for both 5-FU and LV in the microencapsulated particles. Both drugs were in amorphous state in the microencapsulated particles. By enteric coating, excellent pH-dependent release profile was achieved and no drug release was observed in simulated gastric and intestinal fluids. However, when the pH value reached the soluble threshold of Eudragit S-100, a constant and slow drug release was observed. The results indicated that these microencapsulated particles are a promising vehicle for selectively targeting drugs to colon in the chemotherapy of colon cancer.