Plant-produced vaccines: promise and reality

Plant-produced vaccines are a much-hyped development of the past two decades, whose time to embrace reality may have finally come. Vaccines have been developed against viral, bacterial, parasite and allergenic antigens, for humans and for animals; a wide variety of plants have been used for stable transgenic expression as well as for transient expression via Agrobacterium tumefaciens and plant viral vectors. A great many products have shown significant immunogenicity; several have shown efficacy in target animals or in animal models. The realised potential of plant-produced vaccines is discussed, together with future prospects for production and registration. © 2008 Elsevier Ltd. All rights reserved.

Plant-made vaccines for humans and animals

Summary: The concept of using plants to produce high-value pharmaceuticals such as vaccines is 20 years old this year and is only now on the brink of realisation as an established technology. The original reliance on transgenic plants has largely given way to transient expression; proofs of concept for human and animal vaccines and of efficacy for animal vaccines have been established; several plant-produced vaccines have been through Phase I clinical trials in humans and more are scheduled; regulatory requirements are more clear than ever, and more facilities exist for manufacture of clinic-grade materials. The original concept of cheap edible vaccines has given way to a realisation that formulated products are required, which may well be injectable. The technology has proven its worth as a means of cheap, easily scalable production of materials: it now needs to find its niche in competition with established technologies. The realised achievements in the field as well as promising new developments will be reviewed, such as rapid-response vaccines for emerging viruses with pandemic potential and bioterror agents. © 2010 The Author. Journal compilation © 2010 Blackwell Publishing Ltd.

A protocol for the rapid isolation of full geminivirus genomes from dried plant tissue

A high-throughput method of isolating and cloning geminivirus genomes from dried plant material, by combining an Extract-n-Amp™-based DNA isolation technique with rolling circle amplification (RCA) of viral DNA, is presented. Using this method an attempt was made to isolate and clone full geminivirus genomes/genome components from 102 plant samples, including dried leaves stored at room temperature for between 6 months and 10 years, with an average hands-on-time to RCA-ready DNA of 15 min per 20 samples. While storage of dried leaves for up to 6 months did not appreciably decrease cloning success rates relative to those achieved with fresh samples, efficiency of the method decreased with increasing storage time. However, it was still possible to clone virus genomes from 47% of 10-year-old samples. To illustrate the utility of this simple method for high-throughput geminivirus diversity studies, six Maize streak virus genomes, an Abutilon mosaic virus DNA-B component and the DNA-A component of a previously unidentified New Word begomovirus species were fully sequenced. Genomic clones of the 69 other viruses were verified as such by end sequencing. This method should be extremely useful for the study of any circular DNA plant viruses with genome component lengths smaller than the maximum size amplifiable by RCA. © 2008 Elsevier B.V. All rights reserved.

Plant-produced cottontail rabbit papillomavirus L1 protein protects against tumor challenge : A proof-of-concept study

The native cottontail rabbit papillomavirus (CRPV) L1 capsid protein gene was expressed transgenically via Agrobacterium tumefaciens transformation and transiently via a tobacco mosaic virus (TMV) vector in Nicotiana spp. L1 protein was detected in concentrated plant extracts at concentrations up to 1.0 mg/kg in transgenic plants and up to 0.4 mg/kg in TMV-infected plants. The protein did not detectably assemble into viruslike particles; however, immunoelectron microscopy showed presumptive pentamer aggregates, and extracted protein reacted with conformation-specific and neutralizing monoclonal antibodies. Rabbits were injected with concentrated protein extract with Freund's incomplete adjuvant. All sera reacted with baculovirus-produced CRPV L1; however, they did not detectably neutralize infectivity in an in vitro assay. Vaccinated rabbits were, however, protected against wart development on subsequent challenge with live virus. This is the first evidence that a plant-derived papillomavirus vaccine is protective in an animal model and is a proof of concept for human papillomavirus vaccines produced in plants. Copyright © 2006, American Society for Microbiology. All Rights Reserved.

Third International Conference on plant-based vaccines and antibodies

This relatively new biennial meeting - the first was in Prague in 2005 - was chaired by Julian Ma (Guy's Hospital, London, UK), with Mario Pezzotti (University of Verona, Italy) as local organizer, and attracted approximately 180 delegates from 25 countries. The theme was 'Plant Expression Systems for Recombinant Pharmacologics': there were 46 talks gathered into two plenaries, 12 themed sessions and 72 posters. Topics covered included publicly funded and commercial developments, innovation, regulation and commercialization, competition with conventional technology, manufacture and new products. © 2009 Expert Reviews Ltd.

A particle-based micromechanics approach to simulate structural changes of plant cells during drying

This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

Understanding process behaviours in a large insurance company in Australia : a case study

Having a reliable understanding about the behaviours, problems, and performance of existing processes is important in enabling a targeted process improvement initiative. Recently, there has been an increase in the application of innovative process mining techniques to facilitate evidence-based understanding about organizations' business processes. Nevertheless, the application of these techniques in the domain of finance in Australia is, at best, scarce. This paper details a 6-month case study on the application of process mining in one of the largest insurance companies in Australia. In particular, the challenges encountered, the lessons learned, and the results obtained from this case study are detailed. Through this case study, we not only validated existing `lessons learned' from other similar case studies, but also added new insights that can be beneficial to other practitioners in applying process mining in their respective fields.

Towards a commercial lignocellulosic ethanol industry in Australia : the Mackay Renewable Biocommodities Pilot Plant

In 2007, the Queensland University of Technology (QUT) received funding from the Australian Government through the NCRIS program and from the then Queensland Government Department of State Development to construct a pilot research and development facility for the production of bioethanol and other renewable biocommodities from biomass including sugar cane bagasse. This facility is being constructed adjacent to the Racecourse Sugar Mill in Mackay and is known as the Mackay Renewable Biocommodities Pilot Plant (MRBPP). The MRBPP will be capable of processing biomass through a pressurised pretreatment reactor and includes equipment for enzymatic saccharification, fermentation and distillation to produce ethanol. Lignin and fermentation co-products will also be produced at a pilot scale for product development and testing.

An update on the Mackay Renewable Biocommodities Pilot Plant : preliminary trial results

THE Mackay Renewable Biocommodities Pilot Plant is a pilot scale facility owned and operated by QUT for research and demonstration of the conversion of lignocellulosic biomass such as sugarcane bagasse into biofuels. The pilot plant accommodates unique state-of-the-art equipment to process a wide range of feedstocks and is strategically located on the site of the Mackay Sugar Ltd Racecourse Mill. Major facilities include a biomass handling system, pre-treatment reactor, saccharification reactor, fermentors, distillation column and bioseparations equipment. This paper provides an update on the design, construction, commissioning and start-up of the facility. In addition, the paper provides results from preliminary facility trials on the pre-treatment of sugarcane bagasse for cellulosic ethanol production.

Application of a digital elevation model for flood modeling for the Pagsangaan River in Leyte

Flood related scientific and community-based data are rarely systematically collected and analysed in the Philippines. Over the last decades the Pagsangaan River Basin, Leyte, has experienced several flood events. However, documentation describing flood characteristics such as extent, duration or height of these floods are close to non-existing. To address this issue, computerized flood modelling was used to reproduce past events where there was data available for at least partial calibration and validation. The model was also used to provide scenario-based predictions based on A1B climate change assumptions for the area. The most important input for flood modelling is a Digital Elevation Model (DEM) of the river basin. No accurate topographic maps or Light Detection And Ranging (LIDAR)-generated data are available for the Pagsangaan River. Therefore, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM), Version 1, was chosen as the DEM. Although the horizontal spatial resolution of 30 m is rather desirable, it contains substantial vertical errors. These were identified, different correction methods were tested and the resulting DEM was used for flood modelling. The above mentioned data were combined with cross-sections at various strategic locations of the river network, meteorological records, river water level, and current velocity to develop the 1D-2D flood model. SOBEK was used as modelling software to create different rainfall scenarios, including historic flooding events. Due to the lack of scientific data for the verification of the model quality, interviews with local stakeholders served as the gauge to judge the quality of the generated flood maps. According to interviewees, the model reflects reality more accurately than previously available flood maps. The resulting flood maps are now used by the operations centre of a local flood early warning system for warnings and evacuation alerts. Furthermore these maps can serve as a basis to identify flood hazard areas for spatial land use planning purposes.

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

Systematic variation of the severity of motor vehicle accident-related traumatic brain injury vignettes produces different post-concussion symptom reports

This study investigated the specificity of the post-concussion syndrome (PCS) expectation-as-etiology hypothesis. Undergraduate students (n = 551) were randomly allocated to one of three vignette conditions. Vignettes depicted either a very mild (VMI), mild (MI), or moderate-to-severe (MSI) motor vehicle-related traumatic brain injury (TBI). Participants reported the PCS and PTSD symptoms that they imagined the depicted injury would produce. Secondary outcomes (knowledge of mild TBI, and the perceived undesirability of TBI) were also assessed. After data screening, the distribution of participants by condition was: VMI (n = 100), MI (n = 96), and MSI (n = 71). There was a significant effect of condition on PCS symptomatology, F(2, 264) = 16.55, p < .001. Significantly greater PCS symptomatology was expected in the MSI condition compared to the other conditions (MSI > VMI; medium effect, r = .33; MSI > MI; small-to-medium effect, r = .22). The same pattern of group differences was found for PTSD symptoms, F(2, 264) = 17.12, p < .001. Knowledge of mild TBI was not related to differences in expected PCS symptoms by condition; and the perceived undesirability of TBI was only associated with reported PCS symptomatology in the MSI condition. Systematic variation in the severity of a depicted TBI produces different PCS and PTSD symptom expectations. Even a very mild TBI vignette can elicit expectations of PCS symptoms.

"Please touch the plant on your way up the stairs..."

We are aware of global concerns of sustainability and are encouraged on many fronts to modify our behaviour to save the planet but sometimes this understanding is more intellectual than motivated. An opportunity was identified within the university environment to activate a pilot study to investigate the level of voluntary student engagement in saving energy if a plant/digital interface were introduced. We postulate that people may be more inclined to participate in a "green" activity if they are more directly aware of the benefits. This project also seeks to discover if the introduction of nature (green plants) as the interface would encourage users to increase participation in socially responsive activities. Using plants as the interface offers an immediate sensory connection between the participants and the outcome of their chosen actions. This may generate a deeper awareness of the environment by enabling the participant to realise that their one small action in an ordinary day can contribute positively to larger global issues.

Does legal heritage affect obesity? The channel of motor vehicle dependence

We find a robust relationship between motor vehicle ownership, its interaction with legal heritage and obesity in OECD countries. Our estimates indicate that an increase of 100 motor vehicles per thousand residents is associated with about a 6% point increase in obesity in common law countries, whereas it has a much smaller or insignificant impact in civil law countries. These relations hold whether we examine trend data and simple correlations, or conduct cross-section or panel data regression analysis. Our results suggest that obesity rises with motor vehicle ownership in countries following a common law tradition where individual liberty is encouraged, whereas the link is small or statistically non-existent in countries with a civil law background where the rights of the individual tend to be circumscribed by the power of the state.

Power system sensitivity analysis considering induction motor loads

Power system operation and planning are facing increasing uncertainties especially with the deregulation process and increasing demand for power. Probabilistic power system stability assessment and probabilistic power system planning have been identified by EPRI as one of the important trends in power system operations and planning. Probabilistic small signal stability assessment studies the impact of system parameter uncertainties on system small disturbance stability characteristics. Researches in this area have covered many uncertainties factors such as controller parameter uncertainties and generation uncertainties. One of the most important factors in power system stability assessment is load dynamics. In this paper, composite load model is used to consider the uncertainties from load parameter uncertainties impact on system small signal stability characteristics. The results provide useful insight into the significant stability impact brought to the system by load dynamics. They can be used to help system operators in system operation and planning analysis.