An electrospun polycaprolactone–collagen membrane for the resurfacing of cartilage defects

A polycaprolactone (PCL)–collagen electrospun mesh is proposed as a novel alternative to the conventional periosteal graft in autologous chondrocyte implantation. This is the first known attempt in designing a cartilage resurfacing membrane using a mechanically resilient PCL mesh with a weight-average molecular weight of 139 300 that is enhanced with bioactive collagen. PCL–collagen 10, 20 and 40% electrospun meshes (Coll-10, Coll-20 and Coll-40) were evaluated and it was discovered that the retention of surface collagen could only be achieved in Coll-20 and Coll-40. Furthermore Coll-20 was stiffer and stronger than Coll-40 and it satisfied the mechanical demands at the cartilage implant site. When seeded with mesenchymal stem cells (MSCs), the cells adhered on the surface of the Coll-20 mesh and they remained viable over a period of 28 days; however, they were unable to infiltrate through the dense meshwork. Cell compatibility was also noted in the chondrogenic environment as the MSCs differentiated into chondrocytes with the expression of Sox9, aggrecan and collagen II. More importantly, the mesh did not induce a hypertrophic response from the cells. The current findings support the use of Coll-20 as a cartilage patch, and future implantation studies are anticipated.

James Street market, Brisbane : a subtropical retail case study

Climate change mitigation is driving demand for energy-efficient and environmentally conscious commercial buildings in Australia. In the Australian subtropics, high rainfall, warm weather and humidity present unique challenges and opportunities for the architects tasked with designing eco-sensitive projects. The case of the James Street Market in Brisbane’s Fortitude Valley shows that climate-responsive design is an effective approach for reducing the environmental impact of commercial developments. The James Street Market combines climate-responsiveness, environmentally sensitive design strategies and smart planning to create a more sustainable retail precinct. This paper details the design strategies featured in the James Street Market, the project that kicked off a renaissance in climate-responsive commercial building design in Brisbane.

Potential of St John's Wort for the treatment of depression : the economic perspective

The burden of rising health care expenditures has created a demand for information regarding the clinical and economic outcomes associated with complementary and alternative medicines. Meta-analyses of randomized controlled trials have found Hypericum perforatum preparations to be superior to placebo and similarly effective as standard antidepressants in the acute treatment of mild to moderate depression. A clear advantage over antidepressants has been demonstrated in terms of the reduced frequency of adverse effects and lower treatment withdrawal rates, low rates of side effects and good compliance, key variables affecting the cost-effectiveness of a given form of therapy. The most important risk associated with use is potential interactions with other drugs, but this may be mitigated by using extracts with low hyperforin content. As the indirect costs of depression are greater than five times direct treatment costs, given the rising cost of pharmaceutical antidepressants, the comparatively low cost of Hypericum perforatum extract makes it worthy of consideration in the economic evaluation of mild to moderate depression treatments.

Linking ambulance, emergency department and hospital admissions data : understanding the emergency journey

Objective: to assess the accuracy of data linkage across the spectrum of emergency care in the absence of a unique patient identifier, and to use the linked data to examine service delivery outcomes in an emergency department setting. Design: automated data linkage and manual data linkage were compared to determine their relative accuracy. Data were extracted from three separate health information systems: ambulance, ED and hospital inpatients, then linked to provide information about the emergency journey of each patient. The linking was done manually through physical review of records and automatically using a data linking tool (Health Data Integration) developed by the CSIRO. Match rate and quality of the linking were compared. Setting: 10, 835 patient presentations to a large, regional teaching hospital ED over a two month period (August-September 2007). Results: comparison of the manual and automated linkage outcomes for each pair of linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of between 75% and 99%; and a positive predictive value of between 88% and 95%. Conclusions: Our results indicate that automated linking provides a sound basis for health service analysis, even in the absence of a unique patient identifier. The use of an automated linking tool yields accurate data suitable for planning and service delivery purposes and enables the data to be linked regularly to examine service delivery outcomes.

Computing in performing arts education and practice

The performing arts have traditionally made limited use of and showed limited acceptance of computing technology. There are cognitive, physical, environmental, and social influences on the use of computers in performing arts. This paper will examine those influences on the practice of computers in the performing arts and their implications for education in those areas. These implications for the learning environment include infrastructure, interface design, industrial design, and software functionality. Although many of the issues raised in this paper are common to all visual and performing arts, there are significant differences between them which require abstraction of the concepts presented in this paper beyond the more practical focus intended. In particular there are differences in the ways humans are involved in the presentation of a work, and the transitory verses static nature of time in art products.

Adaptive Bayesian compound designs for dose finding studies

We consider the problem of how to efficiently and safely design dose finding studies. Both current and novel utility functions are explored using Bayesian adaptive design methodology for the estimation of a maximum tolerated dose (MTD). In particular, we explore widely adopted approaches such as the continual reassessment method and minimizing the variance of the estimate of an MTD. New utility functions are constructed in the Bayesian framework and are evaluated against current approaches. To reduce computing time, importance sampling is implemented to re-weight posterior samples thus avoiding the need to draw samples using Markov chain Monte Carlo techniques. Further, as such studies are generally first-in-man, the safety of patients is paramount. We therefore explore methods for the incorporation of safety considerations into utility functions to ensure that only safe and well-predicted doses are administered. The amalgamation of Bayesian methodology, adaptive design and compound utility functions is termed adaptive Bayesian compound design (ABCD). The performance of this amalgamation of methodology is investigated via the simulation of dose finding studies. The paper concludes with a discussion of results and extensions that could be included into our approach.

Defending the sanctity of life principle : a reply to John Keown

This article is a response to Professor Keown’s criticism of my paper “Finding a Way Through the Ethical and Legal Maze: Withdrawal of Medical Treatment and Euthanasia” (2005) 13 (3) Medical Law Review 357. The article takes up and responds to a number of criticisms raised by Keown in an attempt to further the debate concerning the moral and legal status of withdrawing life-sustaining measures, its distinction from euthanasia, and the implications of the lawfulness of withdrawal for the principle of the sanctity of life.

Functional role of cell surface CUB domain-containing protein 1 in tumour cell dissemination

The function of CUB domain-containing protein 1 (CDCP1), a recently described transmembrane protein expressed on the surface of hematopoietic stem cells and normal and malignant cells of different tissue origin, is not well defined. The contribution of CDCP1 to tumor metastasis was analyzed by using HeLa carcinoma cells overexpressing CDCP1 (HeLa-CDCP1) and a high-disseminating variant of prostate carcinoma PC-3 naturally expressing high levels of CDCP1 (PC3-hi/diss). CDCP1 expression rendered HeLa cells more aggressive in experimental metastasis in immunodeficient mice. Metastatic colonization by HeLa-CDCP1 was effectively inhibited with subtractive immunization-generated, CDCP1-specific monoclonal antibody (mAb) 41-2, suggesting that CDCP1 facilitates relatively late stages of the metastatic cascade. In the chick embryo model, time- and dose-dependent inhibition of HeLa-CDCP1 colonization by mAb 41-2 was analyzed quantitatively to determine when and where CDCP1 functions during metastasis. Quantitative PCR and immunohistochemical analyses indicated that CDCP1 facilitated tumor cell survival soon after vascular arrest. Live cell imaging showed that the function-blocking mechanism of mAb 41-2 involved enhancement of tumor cell apoptosis, confirmed by attenuation of mAb 41-2–mediated effects with the caspase inhibitor z-VAD-fmk. Under proapoptotic conditions in vitro, CDCP1 expression conferred HeLa-CDCP1 cells with resistance to doxorubicin-induced apoptosis, whereas ligation of CDCP1 with mAb 41-2 caused additional enhancement of the apoptotic response. The functional role of naturally expressed CDCP1 was shown by mAb 41-2–mediated inhibition of both experimental and spontaneous metastasis of PC3-hi/diss. These findings confirm that CDCP1 functions as an antiapoptotic molecule and indicate that during metastasis CDCP1 facilitates tumor cell survival likely during or soon after extravasation.

Design of experiments for bivariate binary responses modelled by Copula functions

Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

A profluorescent azaphenalene nitroxide for nitroxide-mediated polymerization

A novel nitroxide-mediated polymerization (NMP) control agent; 1,1,3,3-tetramethyl-2,3-dihydro-2-azaphenalen-2-yloxyl (TMAO), was used in the free-radical polymerization of styrene. The conversion of styrene during NMP was studied using FT-Raman spectroscopy and the effectiveness of TMAO as a NMP control agent was assessed by GPC analysis. Fidelity of the TMAO-alkoxyamine end-group on the synthesized polymers was confirmed by GPC, UV-Vis and fluorescence spectroscopic analyses. Comparison to the well known NMP control agent, TEMPO was made. TMAO showed control of molecular weight approaching that of TEMPO. Attempts to improve the properties of TMAO as an NMP control agent by synthesizing an analogue with bulkier substituents around the nitroxide did not generate the target molecule but demonstrated some of the interesting chemistry of the azaphenalene ring system

Robust designs for Poisson regression models

We consider the problem of how to construct robust designs for Poisson regression models. An analytical expression is derived for robust designs for first-order Poisson regression models where uncertainty exists in the prior parameter estimates. Given certain constraints in the methodology, it may be necessary to extend the robust designs for implementation in practical experiments. With these extensions, our methodology constructs designs which perform similarly, in terms of estimation, to current techniques, and offers the solution in a more timely manner. We further apply this analytic result to cases where uncertainty exists in the linear predictor. The application of this methodology to practical design problems such as screening experiments is explored. Given the minimal prior knowledge that is usually available when conducting such experiments, it is recommended to derive designs robust across a variety of systems. However, incorporating such uncertainty into the design process can be a computationally intense exercise. Hence, our analytic approach is explored as an alternative.