Optimising yeast as a host for recombinant protein production (review)

Having access to suitably stable, functional recombinant protein samples underpins diverse academic and industrial research efforts to understand the workings of the cell in health and disease. Synthesising a protein in recombinant host cells typically allows the isolation of the pure protein in quantities much higher than those found in the protein's native source. Yeast is a popular host as it is a eukaryote with similar synthetic machinery to the native human source cells of many proteins of interest, while also being quick, easy, and cheap to grow and process. Even in these cells the production of some proteins can be plagued by low functional yields. We have identified molecular mechanisms and culture parameters underpinning high yields and have consolidated our findings to engineer improved yeast cell factories. In this chapter, we provide an overview of the opportunities available to improve yeast as a host system for recombinant protein production.

Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

The Subclassing Anomaly in Compiler Evolution

Subclassing in collections of related classes may require re-implementation of otherwise valid classes just because they utilize outdated parent classes, a phenomenon that is referred to as the subclassing anomaly. The subclassing anomaly is a serious problem since it can void the benefits of code reuse altogether. This paper offers an analysis of the subclassing anomaly in an evolving object-oriented compiler. The paper also outlines a solution for the subclassing anomaly that is based on alternative code reuse mechanism, named class overriding.

Optimising Pichia pastoris induction

A common method for inducing the production of recombinant proteins in Pichia pastoris is through the use of methanol. However, the by-products of methanol metabolism are toxic to yeast cells and therefore its addition to recombinant cultures must be controlled and monitored throughout the process in order to maximise recombinant protein yields. Described here are online and off-line methods to monitor and control methanol addition to bench-top-scale bioreactors. © 2012 Springer Science+business Media, LLC.

Optimising QoE distribution for video applications through LTE-WiFi interworking

Mobile WiFi devices are becoming increasingly popular in non-seamless and user-controlled mobile traffic offloading alongside the standard WiFi hotspots. Unlike the operator-controlled hotspots, a mobile WiFi device relies on the capacity of the macro-cell for the data rate allocated to it. This type of devices can help offloading data traffic from the macro-cell base station and serve the end users within a closer range, but will change the pattern of resource distributions operated by the base station. We propose a resource allocation scheme that aims to optimize user quality of experience (QoE) when accessing video services in the environment where traffic offloading is taking place through interworking between a mobile communication system and low range wireless LANs. In this scheme, a rate redistribution algorithm is derived to perform scheduling which is controlled by a no-reference quality assessment metric in order to achieve the desired trade-offs between efficiency and fairness. We show the performance of this algorithm in terms of the distribution of the allocated data rates throughout the macro-cell investigated and the service coverage offered by the WiFi access point.

Optimising the diagnostic performance of the Geriatric Depression Scale

The aim of this work is to empirically generate a shortened version of the Geriatric Depression Scale (GDS), with the intention of maximising the diagnostic performance in the detection of depression compared with previously GDS validated versions, while optimizing the size of the instrument. A total of 233 individuals (128 from a Day Hospital, 105 randomly selected from the community) aged 60 or over completed the GDS and other measures. The 30 GDS items were entered in the Day Hospital sample as independent variables in a stepwise logistic regression analysis predicting diagnosis of Major Depression. A final solution of 10 items was retained, which correctly classified 97.4% of cases. The diagnostic performance of these 10 GDS items was analysed in the random sample with a receiver operating characteristic (ROC) curve. Sensitivity (100%), specificity (97.2%), positive (81.8%) and negative (100%) predictive power, and the area under the curve (0.994) were comparable with values for GDS-30 and higher compared with GDS-15, GDS-10 and GDS-5. In addition, the new scale proposed had excellent fit when testing its unidimensionality with CFA for categorical outcomes (e.g., CFI=0.99). The 10-item version of the GDS proposed here, the GDS-R, seems to retain the diagnostic performance for detecting depression in older adults of the GDS-30 items, while increasing the sensitivity and predictive values relative to other shortened versions.

Multi-Tenant Virtual GPUs for Optimising Performance of a Financial Risk Application

Graphics Processing Units (GPUs) are becoming popular accelerators in modern High-Performance Computing (HPC) clusters. Installing GPUs on each node of the cluster is not efficient resulting in high costs and power consumption as well as underutilisation of the accelerator. The research reported in this paper is motivated towards the use of few physical GPUs by providing cluster nodes access to remote GPUs on-demand for a financial risk application. We hypothesise that sharing GPUs between several nodes, referred to as multi-tenancy, reduces the execution time and energy consumed by an application. Two data transfer modes between the CPU and the GPUs, namely concurrent and sequential, are explored. The key result from the experiments is that multi-tenancy with few physical GPUs using sequential data transfers lowers the execution time and the energy consumed, thereby improving the overall performance of the application.

Pharmaceutical strategies towards optimising polypharmacy in older people

This paper focuses on the issue of polypharmacy in older people and potential pharmaceutical strategies to optimize the use of multiple medicines. Although polypharmacy has long been viewed negatively, increasing emphasis is being placed on the difference between appropriate and inappropriate polypharmacy. This is largely being driven by the increasing prevalence of multimorbidity and the use of evidence-based guidelines. In this paper, we outline a number of key considerations that are pertinent to optimizing polypharmacy, notably prescribing appropriate polypharmacy, pharmaceutical formulations, the involvement of older people in clinical trials and patient adherence.

Optimising power take-off of an oscillating wave surge converter using high fidelity numerical simulations

Oscillating wave surge converters are a promising technology to harvest ocean wave energy in the near shore region. Although research has been going on for many years, the characteristics of the wave action on the structure and especially the phase relation between the driving force and wave quantities like velocity or surface elevation have not been investigated in detail. The main reason for this is the lack of suitable methods. Experimental investigations using tank tests do not give direct access to overall hydrodynamic loads, only damping torque of a power take off system can be measured directly. Non-linear computational fluid dynamics methods have only recently been applied in the research of this type of devices. This paper presents a new metric named wave torque, which is the total hydrodynamic torque minus the still water pitch stiffness at any given angle of rotation. Changes in characteristics of that metric over a wave cycle and for different power take off settings are investigated using computational fluid dynamics methods. Firstly, it is shown that linearised methods cannot predict optimum damping in typical operating states of OWSCs. We then present phase relationships between main kinetic parameters for different damping levels. Although the flap seems to operate close to resonance, as predicted by linear theory, no obvious condition defining optimum damping is found.

Multilevel mesh partitioning for optimising domain shape

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut-edge weight in the graph with the aim of minimising the parallel communication overhead. However it has been shown that for certain classes of problem, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. In this paper therefore, we modify the multilevel algorithms in order to optimise a cost function based on aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Multilevel mesh partitioning for optimising subdomain aspect ratio

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut-edge weight in the graph with the aim of minimising the parallel communication overhead. However it has been shown that for certain classes of problem, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. In this paper therefore, we modify the multilevel algorithms in order to optimise a cost function based on aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Optimising plant bed performance through adaptive research with the Australian sweetpotato industry

A key driver of Australian sweetpotato productivity improvements and consumer demand has been industry adoption of disease-free planting material systems. On a farm isolated from main Australian sweetpotato areas, virus-free germplasm is annually multiplied, with subsequent 'pathogen-tested' (PT) sweetpotato roots shipped to commercial Australian sweetpotato growers. They in turn plant their PT roots into specially designated plant beds, commencing in late winter. From these beds, they cut sprouts as the basis for their commercial fields. Along with other intense agronomic practices, this system enables Australian producers to achieve worldRSQUOs highest commercial yields (per hectare) of premium sweetpotatoes. Their industry organisation, ASPG (Australian Sweetpotato Growers Inc.), has identified productivity of mother plant beds as a key driver of crop performance. Growers and scientists are currently collaborating to investigate issues such as catastrophic plant beds losses; optimisation of irrigation and nutrient addition; rapidity and uniformity of initial plant bed harvests; optimal plant bed harvest techniques; virus re-infection of plant beds; and practical longevity of plant beds. A survey of 50 sweetpotato growers in Queensland and New South Wales identified a substantial diversity in current plant bed systems, apparently influenced by growing district, scale of operation, time of planting, and machinery/labour availability. Growers identified key areas for plant bed research as: optimising the size and grading specifications of PT roots supplied for the plant beds; change in sprout density, vigour and performance through sequential cuttings of the plant bed; optimal height above ground level to cut sprouts to maximise commercial crop and plant bed performance; and use of structures and soil amendments in plant bed systems. Our ongoing multi-disciplinary research program integrates detailed agronomic experiments, grower adaptive learning sites, product quality and consumer research, to enhance industry capacity for inspired innovation and commercial, sustainable practice change.

Ad hoc procedure for optimising agreement between observational records

Observational studies in the field of sport are complicated by the added difficulty of having to analyse multiple, complex events or behaviours that may last just a fraction of a second. In this study, we analyse three aspects related to the reliability of data collected in such a study. The first aim was to analyse and compare the reliability of data sets assessed quantitatively (calculation of kappa statistic) and qualitatively (consensus agreement method). The second aim was to describe how, by ensuring the alignment of events, we calculated the kappa statistic for the order parameter using SDIS-GSEQ software (version 5.1) for data sets containing different numbers of sequences. The third objective was to describe a new consultative procedure designed to remove the confusion generated by discordant data sets and improve the reliability of the data. The procedure is called "consultative" because it involves the participation of a new observer who is responsible for consulting the existing observations and deciding on the definitive result.

Effectiveness of Depression-Suicidal Behaviour Gatekeeper training among police officers in three European regions: outcomes of the Optimising Suicide Prevention Programmes and their Implementation in Europe (OSPI-Europe) study

Background: Gatekeeper training for community facilitators, to identify and respond to those at risk of suicide, forms an important part of multi-level community-based suicide prevention programmes. Aims: This study examined the effects of gatekeeper training on attitudes, knowledge and confidence of police officers in dealing with persons at risk of suicide. Methods: A total of 828 police officers across three European regions participated in a 4-hour training programme which addressed the epidemiology of depression and suicidal behaviour, symptoms of depression, warning signs and risk factors associated with suicidal behaviour, motivating help-seeking behaviour, dealing with acute suicidal crisis and informing bereaved relatives. Participants completed internationally validated questionnaires assessing stigmatising attitudes, knowledge about depression and confidence in dealing with suicidal persons pre- and post-training. Results: There were significant differences among countries in terms of previous exposure to suicidal persons and extent of previous training. Post-training evaluation demonstrated significant improvements in stigmatising attitudes, knowledge and confidence in all three countries. Conclusion: The consistently positive effects of gatekeeper training of police officers across different regions support inclusion of this type of training as a fundamental part of multi-level community-based suicide prevention programmes and roll-out, nationally and internationally.

A framework for fully decentralised cycle stealing

Ordinary desktop computers continue to obtain ever more resources – in-creased processing power, memory, network speed and bandwidth – yet these resources spend much of their time underutilised. Cycle stealing frameworks harness these resources so they can be used for high-performance computing. Traditionally cycle stealing systems have used client-server based architectures which place significant limits on their ability to scale and the range of applica-tions they can support. By applying a fully decentralised network model to cycle stealing the limits of centralised models can be overcome. Using decentralised networks in this manner presents some difficulties which have not been encountered in their previous uses. Generally decentralised ap-plications do not require any significant fault tolerance guarantees. High-performance computing on the other hand requires very stringent guarantees to ensure correct results are obtained. Unfortunately mechanisms developed for traditional high-performance computing cannot be simply translated because of their reliance on a reliable storage mechanism. In the highly dynamic world of P2P computing this reliable storage is not available. As part of this research a fault tolerance system has been created which provides considerable reliability without the need for a persistent storage. As well as increased scalability, fully decentralised networks offer the ability for volunteers to communicate directly. This ability provides the possibility of supporting applications whose tasks require direct, message passing style communication. Previous cycle stealing systems have only supported embarrassingly parallel applications and applications with limited forms of communication so a new programming model has been developed which can support this style of communication within a cycle stealing context. In this thesis I present a fully decentralised cycle stealing framework. The framework addresses the problems of providing a reliable fault tolerance sys-tem and supporting direct communication between parallel tasks. The thesis includes a programming model for developing cycle stealing applications with direct inter-process communication and methods for optimising object locality on decentralised networks.