Preparation and in vitro evaluation of a polymer based controlled release dry powder inhaler formulation for pulmonary delivery

This thesis described the synthesis of an L-leucine conjugate of the biodegradable polymer, chitosan and its potential application for the development of controlled release nanoparticulate dry powder inhaler (DPI) formulations. The study demonstrated that the physicochemical properties of conjugated chitosan nanoparticles had favourable effects on the dispersibility and controlled release profile of a model drug. The toxicity profile of the nanoparticulate formulation revealed promising outcome for its use in pulmonary delivery. The chitosan conjugate produced in this project would be useful for the application of polymer nanoparticulate systems for efficient lung delivery of drugs.

Adipose tissue engineering based on the controlled release of fibroblast growth factor-2 in a collagen matrix

Adipose tissue forms when basement membrane extract (Matrigel™) and fibroblast growth factor-2 (FGF-2) are added to our mouse tissue engineering chamber model. A mouse tumor extract, Matrigel is unsuitable for human clinical application, and finding an alternative to Matrigel is essential. In this study we generated adipose tissue in the chamber model without using Matrigel by controlled release of FGF-2 in a type I collagen matrix. FGF-2 was impregnated into biodegradable gelatin microspheres for its slow release. The chambers were filled with these microspheres suspended in 60 μL collagen gel. Injection of collagen containing free FGF-2 or collagen containing gelatin microspheres with buffer alone served as controls. When chambers were harvested 6 weeks after implantation, the volume and weight of the tissue obtained were higher in the group that received collagen and FGF-2 impregnated microspheres than in controls. Histologic analysis of tissue constructs showed the formation of de novo adipose tissue accompanied by angiogenesis. In contrast, control groups did not show extensive adipose tissue formation. In conclusion, this study has shown that de novo formation of adipose tissue can be achieved through controlled release of FGF-2 in collagen type I in the absence of Matrigel.

Controlled systemic release of interleukin-12 after gene electrotransfer to muscle for cancer gene therapy alone or in combination with ionizing radiation in murine sarcomas

Background: The present study aimed to evaluate the antitumor effectiveness of systemic interleukin (IL)-12 gene therapy in murine sarcoma models, and to evaluate its interaction with the irradiation of tumors and metastases. To avoid toxic side-effects of IL-12 gene therapy, the objective was to achieve the controlled release of IL-12 after intramuscular gene electrotransfer. Methods: Gene electrotransfer of the plasmid pORF-mIL12 was performed into the tibialis cranialis in A/J and C57BL/6 mice. Systemic release of the IL-12 was monitored in the serum of mice after carrying out two sets of intramuscular IL-12 gene electrotransfer of two different doses of plasmid DNA. The antitumor effectiveness of IL-12 gene electrotransfer alone or in combination with local tumor or lung irradiation with X-rays, was evaluated on subcutaneous SA-1 and LPB tumors, as well as on lung metastases. Results: A synergistic antitumor effect of intramuscular gene electrotransfer combined with local tumor irradiation was observed as a result of the systemic distribution of IL-12. The gene electrotransfer resulted in up to 28% of complete responses of tumors. In combination with local tumor irradiation, the curability was increased by up to 100%. The same effect was observed for lung metastases, where a potentiating factor of 1.3-fold was determined. The amount of circulating IL-12 was controlled by the number of repeats of gene electrotransfer and by the amount of the injected plasmid. Conclusions: The present study demonstrates the feasibility of treatment by IL-12 gene electrotransfer combined with local tumor or lung metastases irradiation on sarcoma tumors for translation into the clinical setting. Copyright © 2009 John Wiley & Sons, Ltd.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

Three-dimensional analysis of budding sites and released virus suggests a revised model for HIV-1 morphogenesis

Current models of HIV-1 morphogenesis hold that newly synthesized viral Gag polyproteins traffic to and assemble at the cell membrane into spherical protein shells. The resulting late-budding structure is thought to be released by the cellular ESCRT machinery severing the membrane tether connecting it to the producer cell. Using electron tomography and scanning transmission electron microscopy, we find that virions have a morphology and composition distinct from late-budding sites. Gag is arranged as a continuous but incomplete sphere in the released virion. In contrast, late-budding sites lacking functional ESCRT exhibited a nearly closed Gag sphere. The results lead us to propose that budding is initiated by Gag assembly, but is completed in an ESCRT-dependent manner before the Gag sphere is complete. This suggests that ESCRT functions early in HIV-1 release-akin to its role in vesicle formation-and is not restricted to severing the thin membrane tether.

Slaving and release in co-infection control

Background Animal and human infection with multiple parasite species is the norm rather than the exception, and empirical studies and animal models have provided evidence for a diverse range of interactions among parasites. We demonstrate how an optimal control strategy should be tailored to the pathogen community and tempered by species-level knowledge of drug sensitivity with use of a simple epidemiological model of gastro-intestinal nematodes. Methods We construct a fully mechanistic model of macroparasite co-infection and use it to explore a range of control scenarios involving chemotherapy as well as improvements to sanitation. Results Scenarios are presented whereby control not only releases a more resistant parasite from antagonistic interactions, but risks increasing co-infection rates, exacerbating the burden of disease. In contrast, synergisms between species result in their becoming epidemiologically slaved within hosts, presenting a novel opportunity for controlling drug resistant parasites by targeting co-circulating species. Conclusions Understanding the effects on control of multi-parasite species interactions, and vice versa, is of increasing urgency in the advent of integrated mass intervention programmes.

A simulation model of the within-host dynamics of Plasmodium vivax infection

Background The benign reputation of Plasmodium vivax is at odds with the burden and severity of the disease. This reputation, combined with restricted in vitro techniques, has slowed efforts to gain an understanding of the parasite biology and interaction with its human host. Methods A simulation model of the within-host dynamics of P. vivax infection is described, incorporating distinctive characteristics of the parasite such as the preferential invasion of reticulocytes and hypnozoite production. The developed model is fitted using digitized time-series’ from historic neurosyphilis studies, and subsequently validated against summary statistics from a larger study of the same population. The Chesson relapse pattern was used to demonstrate the impact of released hypnozoites. Results The typical pattern for dynamics of the parasite population is a rapid exponential increase in the first 10 days, followed by a gradual decline. Gametocyte counts follow a similar trend, but are approximately two orders of magnitude lower. The model predicts that, on average, an infected naïve host in the absence of treatment becomes infectious 7.9 days post patency and is infectious for a mean of 34.4 days. In the absence of treatment, the effect of hypnozoite release was not apparent as newly released parasites were obscured by the existing infection. Conclusions The results from the model provides useful insights into the dynamics of P. vivax infection in human hosts, in particular the timing of host infectiousness and the role of the hypnozoite in perpetuating infection.

A comprehensive mechanistic kinetic model for dilute acid hydrolysis of switchgrass cellulose to glucose, 5-HMF and levulinic acid

Switchgrass was treated by 1% (w/w) H₂SO₄in batch tube reactors at temperatures ranging from 140–220°C for up to 60 minutes. In this study, release patterns of glucose, 5-hydroxymethylfurfural (5-HMF), and levulinic acid from switchgrass cellulose were investigated through a mechanistic kinetic model. The predictions were consistent with the measured products of interest when new parameters reflecting the effects of reaction limitations, such as cellulose crystallinity, acid soluble lignin–glucose complex (ASL–glucose) and humins that cannot be quantitatively analyzed, were included. The new mechanistic kinetic model incorporating these parameters simulated the experimental data with R² above 0.97. Results showed that glucose yield was most sensitive to variations in the parameter regarding the cellulose crystallinity at low temperatures (140–180°C), while the impact of crystallinity on the glucose yield became imperceptible at elevated temperatures (200–220 °C). Parameters related to the undesired products (e.g. ASL–glucose and humins) were the most sensitive factors compared with rate constants and other additional parameters in impacting the levulinic acid yield at elevated temperatures (200–220°C), while their impacts were negligible at 140–180°C. These new findings provide a more rational explanation for the kinetic changes in dilute acid pretreatment performance and suggest that the influences of cellulose crystallinity and undesired products including ASL–glucose and humins play key roles in determining the generation of glucose, 5-HMF and levulinic acid from biomass-derived cellulose.

Soluble mediators in platelet concentrates modulate dendritic cell inflammatory responses in an experimental model of transfusion

The transfusion of platelet concentrates (PCs) is widely used to treat thrombocytopenia and severe trauma. Ex vivo storage of PCs is associated with a storage lesion characterized by partial platelet activation and the release of soluble mediators, such as soluble CD40 ligand (sCD40L), RANTES, and interleukin (IL)-8. An in vitro whole blood culture transfusion model was employed to assess whether mediators present in PC supernatants (PC-SNs) modulated dendritic cell (DC)-specific inflammatory responses (intracellular staining) and the overall inflammatory response (cytometric bead array). Lipopolysaccharide (LPS) was included in parallel cultures to model the impact of PC-SNs on cell responses following toll-like receptor-mediated pathogen recognition. The impact of both the PC dose (10%, 25%) and ex vivo storage period was investigated [day 2 (D2), day 5 (D5), day 7 (D7)]. PC-SNs alone had minimal impact on DC-specific inflammatory responses and the overall inflammatory response. However, in the presence of LPS, exposure to PC-SNs resulted in a significant dose associated suppression of the production of DC IL-12, IL-6, IL-1a, tumor necrosis factor-a (TNF-a), and macrophage inflammatory protein (MIP)-1b and storage-associated suppression of the production of DC IL-10, TNF-a, and IL-8. For the overall inflammatory response, IL-6, TNF-a, MIP-1a, MIP-1b, and inflammatory protein (IP)-10 were significantly suppressed and IL-8, IL-10, and IL-1b significantly increased following exposure to PC-SNs in the presence of LPS. These data suggest that soluble mediators present in PCs significantly suppress DC function and modulate the overall inflammatory response, particularly in the presence of an infectious stimulus. Given the central role of DCs in the initiation and regulation of the immune response, these results suggest that modulation of the DC inflammatory profile is a probable mechanism contributing to transfusion-related complications.

The introduction and release of Chiasmia inconspicua and C. assimilis (Lepidoptera: Geometridae) for the biological control of Acacia nilotica in Australia

Two geometrid moths Chiasmia inconspicua and Chiasmia assimilis, identified as potential biological control agents for prickly acacia Acacia nilotica subsp. indica, were collected in Kenya and imported into quarantine facilities in Australia where laboratory cultures were established. Aspects of the biologies of both insects were studied and CLIMEX® models indicating the climatically favourable areas of Australia were developed. Host range tests were conducted using an approved test list of 74 plant species and no-choice tests of neonate larvae placed on both cut foliage and potted plants. C. inconspicua developed through to adult on prickly acacia and, in small numbers, Acacia pulchella. C. assimilis developed through to adult on prickly acacia and also in very small numbers on A. pulchella, A. deanei, A. decurrens, and A. mearnsii. In all experiments, the response on prickly acacia could be clearly differentiated from the responses on the non-target species. Both insects were approved for release in Australia. Over a three-year period releases were made at multiple sites in north Queensland, almost all in inland areas. There was no evidence of either insect's establishment and both colonies were terminated. A new colony of C. assimilis was subsequently established from insects collected in South Africa and releases of C. assimilis from this new colony were made into coastal and inland infestations of prickly acacia. Establishment was rapid at one coastal site and the insect quickly spread to other infestations. Establishment at one inland area was also confirmed in early 2006. The establishment in coastal areas supported a CLIMEX model that indicated that the climate of coastal areas was more suitable than inland areas.

Accelerating Pseudo-Marginal MCMC using Gaussian Processes

Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

Time-dependent instantaneous mortality rates from multiple tagging experiments with exact times of release and recovery

Instantaneous natural mortality rates and a nonparametric hunting mortality function are estimated from a multiple-year tagging experiment with arbitrary, time-dependent fishing or hunting mortality. Our theory allows animals to be tagged over a range of times in each year, and to take time to mix into the population. Animals are recovered by hunting or fishing, and death events from natural causes occur but are not observed. We combine a long-standing approach based on yearly totals, described by Brownie et al. (1985, Statistical Inference from Band Recovery Data: A Handbook, Second edition, United States Fish and Wildlife Service, Washington, Resource Publication, 156), with an exact-time-of-recovery approach originated by Hearn, Sandland and Hampton (1987, Journal du Conseil International pour l'Exploration de la Mer, 43, 107-117), who modeled times at liberty without regard to time of tagging. Our model allows for exact times of release and recovery, incomplete reporting of recoveries, and potential tag shedding. We apply our methods to data on the heavily exploited southern bluefin tuna (Thunnus maccoyii).

Special Issue on Spatial Moment Techniques for Modelling Biological Processes

Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.

Modelling the movement of interacting cell populations: A moment dynamics approach

Mathematical models describing the movement of multiple interacting subpopulations are relevant to many biological and ecological processes. Standard mean-field partial differential equation descriptions of these processes suffer from the limitation that they implicitly neglect to incorporate the impact of spatial correlations and clustering. To overcome this, we derive a moment dynamics description of a discrete stochastic process which describes the spreading of distinct interacting subpopulations. In particular, we motivate our model by mimicking the geometry of two typical cell biology experiments. Comparing the performance of the moment dynamics model with a traditional mean-field model confirms that the moment dynamics approach always outperforms the traditional mean-field approach. To provide more general insight we summarise the performance of the moment dynamics model and the traditional mean-field model over a wide range of parameter regimes. These results help distinguish between those situations where spatial correlation effects are sufficiently strong, such that a moment dynamics model is required, from other situations where spatial correlation effects are sufficiently weak, such that a traditional mean-field model is adequate.