Bridging the gap: Exploring the barriers to using economic evidence in healthcare decision making and strategies for improving uptake

Evidence from economic evaluations is often not used to inform healthcare policy despite being well regarded by policy makers and physicians. This article employs the accessibility and acceptability framework to review the barriers to using evidence from economic evaluation in healthcare policy and the strategies used to overcome these barriers. Economic evaluations are often inaccessible to policymakers due to the absence of relevant economic evaluations, the time and cost required to conduct and interpret economic evaluations, and lack of expertise to evaluate quality and interpret results. Consistently reported factors that limit the translation of findings from economic evaluations into healthcare policy include poor quality of research informing economic evaluations, assumptions used in economic modelling, conflicts of interest, difficulties in transferring resources between sectors, negative attitudes to healthcare rationing, and the absence of equity considerations. Strategies to overcome these barriers have been suggested in the literature, including training, structured abstract databases, rapid evaluation, reporting checklists for journals, and considering factors other than cost effectiveness in economic evaluations, such as equity or budget impact. The factors that prevent or encourage decision makers to use evidence from economic evaluations have been identified, but the relative importance of these factors to decision makers is uncertain.

What’s driving the uptake of prefabricated housing in Australia?

Prefabrication has been promoted as a means to improve the efficiency of the Australian house building industry. Issues affecting the uptake of prefabrication were identified through interviews with small and medium sized building companies. Prefabrication’s specific impact on housing construction and smaller organisations has not been frequently investigated. Similar past research has been conducted without the use of a clear theoretical grounding guiding the identification of relevant issues. The current study is guided by a combination of the Theory of Planned Behaviour (TPB) and the Technology Acceptance Model (TAM). This allowed the identification of a broad range of issues across attitudinal, normative, behavioural control and technology adaptation domains. Results revealed improved quality was often offset against practical cost implications. While a high quality of prefabricated products was reported, key technical challenges included coordinating the transporting of modules, and balancing standardisation and product flexibility. Resistance from traditional industry stakeholders regarding build methods, financing, and openness to encouraging prefabrication was commonly reported. The key role of government decision making in facilitating greater demand and competitiveness of prefabricated businesses in the consumer marketplace was also highlighted. Further research is currently being undertaken by the authors, which builds on the exploratory results of the current study through confirmatory, quantitative surveying.

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

N,N'-Carbonyldiimidazole-mediated functionalization of superparamagnetic nanoparticles as vaccine carrier

Particulates with specific sizes and characteristics can induce potent immune responses by promoting antigen uptake of appropriate immuno-stimulatory cell types. Magnetite (Fe3O4) nanoparticles have shown many potential bioapplications due to their biocompatibility and special characteristics. Here, superparamagnetic Fe3O4 nanoparticles (SPIONs) with high magnetization value (70emug-1) were stabilized with trisodium citrate and successfully conjugated with a model antigen (ovalbumin, OVA) via N,N'-carbonyldiimidazole (CDI) mediated reaction, to achieve a maximum conjugation capacity at approximately 13μgμm-2. It was shown that different mechanisms governed the interactions between the OVA molecules and magnetite nanoparticles at different pH conditions. We evaluated as-synthesized SPION against commercially available magnetite nanoparticles. The cytotoxicity of these nanoparticles was investigated using mammalian cells. The reported CDI-mediated reaction can be considered as a potential approach in conjugating biomolecules onto magnetite or other biodegradable nanoparticles for vaccine delivery.

Preparation of macroporous methacrylate monolithic material with convective flow properties for bioseparation : Investigating the kinetics of pore formation and hydrodynamic performance

The preparation of macroporous methacrylate monolithic material with controlled pore structures can be carried out in an unstirred mould through careful and precise control of the polymerisation kinetics and parameters. Contemporary synthesis conditions of methacrylate monolithic polymers are based on existing polymerisation schemes without an in-depth understanding of the dynamics of pore structure and formation. This leads to poor performance in polymer usage thereby affecting final product recovery and purity, retention time, productivity and process economics. The unique porosity of methacrylate monolithic polymer which propels its usage in many industrial applications can be controlled easily during its preparation. Control of the kinetics of the overall process through changes in reaction time, temperature and overall composition such as cross-linker and initiator contents allow the fine tuning of the macroporous structure and provide an understanding of the mechanism of pore formation within the unstirred mould. The significant effect of temperature of the reaction kinetics serves as an effectual means to control and optimise the pore structure and allows the preparation of polymers with different pore size distributions from the same composition of the polymerisation mixture. Increasing the concentration of the cross-linking monomer affects the composition of the final monoliths and also decreases the average pore size as a result of pre-mature formation of highly cross-linked globules with a reduced propensity to coalesce. The choice and concentration of porogen solvent is also imperative. Different porogens and porogen mixtures present different pore structure output. Example, larger pores are obtained in a poor solvent due to early phase separation.

Reconceptualizing green infrastructure for climate change adaptation: Barriers to adoption and drivers for uptake by spatial planners

Urban green infrastructure can help cities adapt to climate change. Spatial planning can play an important role in utilizing green infrastructure for adaptation. Yet climate change risks represent a different sort of challenge for planning institutions. This paper aims to address two issues arising from this challenge. First, it defines the concept of green infrastructure within the context of climate adaptation. Second, it identifies and puts into perspective institutional barriers to adopting green infrastructure for climate adaptation, including path dependence. We begin by arguing that there is growing confusion among planners and policy makers about what constitutes green infrastructure. Definitional ambiguity may contribute to inaction on climate change adaptation, because it muddies existing programs and initiatives that are to do with green-space more broadly, which in turn feeds path dependency. We then report empirical findings about how planners perceive the institutional challenge arising from climate change and the adoption of green infrastructure as an adaptive response. The paper concludes that spatial planners generally recognize multiple rationales associated with green infrastructure. However they are not particularly keen on institutional innovation and there is a tendency for path dependence. We propose a conceptual model that explicitly recognizes such institutional factors. This paper contributes to the literature by showing that agency and institutional dimensions are a limiting factor in advancing the concept of green infrastructure within the context of climate change adaptation.

Reduced intensity conditioning for allogeneic hematopoietic stem cell transplant determines the kinetics of acute Graft-Versus-Host Disease

Background Preparative myeloablative conditioning regimens for allogeneic hematopoietic stem-cell transplantation (HSCT) may control malignancy and facilitate engraftment but also contribute to transplant related mortality, cytokine release, and acute graft-versus-host disease (GVHD). Reduced intensity conditioning (RIC) regimens have decreased transplant related mortality but the incidence of acute GVHD, while delayed, remains unchanged. There are currently no in vivo allogeneic models of RIC HSCT, limiting studies into the mechanism behind RIC-associated GVHD. Methods We developed two RIC HSCT models that result in delayed onset GVHD (major histocompatibility complex mismatched (UBI-GFP/BL6 [H-2b]→BALB/c [H-2d]) and major histocompatibility complex matched, minor histocompatibility mismatched (UBI-GFP/BL6 [H-2b]→BALB.B [H-2b])) enabling the effect of RIC on chimerism, dendritic cell (DC) chimerism, and GVHD to be investigated. Results In contrast with myeloablative conditioning, we observed that RIC-associated delayed-onset GVHD is characterized by low production of tumor necrosis factor-α, maintenance of host DC, phenotypic DC activation, increased T-regulatory cell numbers, and a delayed emergence of activated donor DC. Furthermore, changes to the peritransplant milieu in the recipient after RIC lead to the altered activation of DC and the induction of T-regulatory responses. Reduced intensity conditioning recipients suffer less early damage to GVHD target organs. However, as donor cells engraft, activated donor DC and rising levels of tumor necrosis factor-α are associated with a later onset of severe GVHD. Conclusions Delineating the mechanisms underlying delayed onset GVHD in RIC HSCT recipients is vital to improve the prediction of disease onset and allow more targeted interventions for acute GVHD.

Impact of technology uptake on an Australian electricity distribution network

This paper presents simulation results for future electricity grids using an agent-based model developed with MODAM (MODular Agent-based Model). MODAM is introduced and its use demonstrated through four simulations based on a scenario that expects a rise of on-site renewable generators and electric vehicles (EV) usage. The simulations were run over many years, for two areas in Townsville, Australia, capturing variability in space of the technology uptake, and for two charging methods for EV, capturing people's behaviours and their impact on the time of the peak load. Impact analyses of these technologies were performed over the areas, down to the distribution transformer level, where greater variability of their contribution to the assets peak load was observed. The MODAM models can be used for different purposes such as impact of renewables on grid sizing, or on greenhouse gas emissions. The insights gained from using MODAM for technology assessment are discussed.

Effect of functionalized kaolinite on the curing kinetics of cycloaliphatic epoxy/anhydride system

Silane grafted kaolinite (KGS) was prepared through grinding kaolinite and then grafting with 3-aminopropyltriethoxysilane. The influence of KGS on the curing kinetics of cycloaliphatic epoxy resin was studied by non-isothermal differential scanning calorimetry at different heating rates. The reaction activation energy (Ea) was determined based on the Flynn–Wall–Ozawa method. The results of dynamic differential scanning calorimetry (DSC) kinetic analysis show that the surface hydroxyl groups of clay decreases the Ea from 70.6 kJ mol− 1 to 62.8 kJ mol− 1 and accelerates the curing reaction of the epoxy resin. The silane grafting reactions consume the surface hydroxyl groups of kaolinite and lead to a decrease in the catalytic efficiency of KGS in the curing of epoxy resin.

Uptake of influenza vaccination in pregnancy amongst Australian Aboriginal and Torres Strait Islander women: A mixed-methods pilot study

Background Influenza infection during pregnancy is associated with significant morbidity and mortality. Immunisation against influenza is recommended during pregnancy in several countries but uptake of vaccine is poor. There are limited data on vaccine uptake, and the determinants of vaccination, in Australian Aboriginal and/or Torres Islander women during pregnancy. This study aimed to establish an appropriate methodology and collect pilot data on vaccine uptake and attitudes towards, and perceptions of, maternal influenza vaccination in that population in order to inform the development of larger studies. Methods A mixed-methods study comprised of a cross-sectional survey and yarning circles (focus groups) amongst Aboriginal and Torres Strait Islander women attending two primary health care services. The women were between 28 weeks gestation and less than 16 weeks post-birth. These data were supplemented by data collected in an ongoing national Australian study of maternal influenza vaccination. Aboriginal research officers collected community data and data from the yarning circles which were based on a narrative enquiry framework. Descriptive statistics were used to analyse quantitative data and thematic analyses were applied to qualitative data. Results Quantitative data were available for 53 women and seven of these women participated in the yarning circles. The proportion of women who reported receipt of an influenza vaccine during their pregnancy was 9/53. Less than half of the participants (21/53) reported they had been offered the vaccine in pregnancy. Forty-three percent reported they would get a vaccine if they became pregnant again. Qualitative data suggested perceived benefits to themselves and their infants were important factors in the decision to be vaccinated but there was insufficient information available to women to make that choice. Conclusions The rates of influenza immunisation may continue to remain low for Aboriginal and/or Torres Strait Islander women during pregnancy. Access to services and recommendations by a health care worker may be factors in the lower rates. Our findings support the need for larger studies directed at monitoring and understanding the determinants of maternal influenza vaccine uptake during pregnancy in Australian Aboriginal and Torres Strait Islander women. This research will best be achieved using methods that account for the social and cultural contexts of Aboriginal and Torres Strait Islander communities in Australia.

Kinematics and kinetics of the Nordic hamstring curl

This thesis describes, for the first time, the forces involved in the Nordic hamstring exercise, its reliability and the biomechanical effects of extra loading during the movement. The results provide practitioners with valuable information to enhance hamstring injury prevention and rehabilitation programs.

Targeting ASCT2-mediated glutamine uptake blocks prostate cancer growth and tumour development

Glutamine is conditionally essential in cancer cells, being utilized as a carbon and nitrogen source for macromolecule production, as well as for anaplerotic reactions fuelling the tricarboxylic acid (TCA) cycle. In this study, we demonstrated that the glutamine transporter ASCT2 (SLC1A5) is highly expressed in prostate cancer patient samples. Using LNCaP and PC-3 prostate cancer cell lines, we showed that chemical or shRNA-mediated inhibition of ASCT2 function in vitro decreases glutamine uptake, cell cycle progression through E2F transcription factors, mTORC1 pathway activation and cell growth. Chemical inhibition also reduces basal oxygen consumption and fatty acid synthesis, showing that downstream metabolic function is reliant on ASCT2-mediated glutamine uptake. Furthermore, shRNA knockdown of ASCT2 in PC-3 cell xenografts significantly inhibits tumour growth and metastasis in vivo, associated with the down-regulation of E2F cell cycle pathway proteins. In conclusion, ASCT2-mediated glutamine uptake is essential for multiple pathways regulating the cell cycle and cell growth, and is therefore a putative therapeutic target in prostate cancer.

Stochastic linear multistep methods for the simulation of chemical kinetics

In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the tau-leaping framework to past information. Using the theta-trapezoidal tau-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k >= 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.

Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method

Background Biochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need for numerical methods that are both fast and accurate. The Bulirsch-Stoer method is an established method for solving ordinary differential equations that possesses both of these qualities. Results In this paper, we present the Stochastic Bulirsch-Stoer method, a new numerical method for simulating discrete chemical reaction systems, inspired by its deterministic counterpart. It is able to achieve an excellent efficiency due to the fact that it is based on an approach with high deterministic order, allowing for larger stepsizes and leading to fast simulations. We compare it to the Euler τ-leap, as well as two more recent τ-leap methods, on a number of example problems, and find that as well as being very accurate, our method is the most robust, in terms of efficiency, of all the methods considered in this paper. The problems it is most suited for are those with increased populations that would be too slow to simulate using Gillespie’s stochastic simulation algorithm. For such problems, it is likely to achieve higher weak order in the moments. Conclusions The Stochastic Bulirsch-Stoer method is a novel stochastic solver that can be used for fast and accurate simulations. Crucially, compared to other similar methods, it better retains its high accuracy when the timesteps are increased. Thus the Stochastic Bulirsch-Stoer method is both computationally efficient and robust. These are key properties for any stochastic numerical method, as they must typically run many thousands of simulations.