Edaravone containing isoindoline nitroxides for the potential treatment of cardiovascular ischaemia

A novel antioxidant for the potential treatment of ischaemia was designed by incorporating an isoindoline nitroxide into the framework of the free radical scavenger edaravone. 5-(3-Methyl-pyrazol-5-ol-1-yl)-1,1,3,3-tetramethylisoindolin-2-yloxyl 7 was prepared by N-arylation of 3-methyl-5-pyrazolone with 5-iodo-1,1,3,3-tetramethylisoindoline-2-yloxyl 8 in the presence of catalytic copper(I)iodide. Evaluation of 7, its methoxyamine derivative 10 and 5-carboxy-1,1,3,3-tetramethylisoindolin-2-yloxyl (CTMIO) against edaravone 1 in ischaemic rat atrial cardiomyocytes revealed significant decreases in cell death after prolonged ischaemia for each agent; however the protective effect of the novel antioxidant 7 (showing greater than 85% reduction in cell death at 100 μM) was significantly enhanced over that of edaravone 1 alone. Furthermore, the activity for 7 was found to be equal to or greater than the potent cardioprotective agent N6-cyclopentyladenosine (CPA). The methoxyamine adduct 10 and edaravone 1 showed no difference between the extent of reduction in cell death whilst CTMIO had only a modest protective effect.

Designing for engagement towards healthier lifestyles through food image sharing : the case of I8DAT

This paper introduces the underlying design concepts of I8DAT, a food image sharing application that has been developed as part of a three-year research project – Eat, Cook, Grow: Ubiquitous Technology for Sustainable Food Culture in the City (http://www.urbaninformatics .net/projects/food) – exploring urban food practices to engage people in healthier, more environmentally and socially sustainable eating, cooking, and growing food in their everyday lives. The key aim of the project is to produce actionable knowledge, which is then applied to create and test several accessible, user-centred interactive design solutions that motivate user-engagement through playful and social means rather than authoritative information distribution. Through the design and implementation processes we envisage to integrate these design interventions to create a sustainable food network that is both technical and socio-cultural in nature (technosocial). Our primary research locale is Brisbane, Australia, with additional work carried out in three reference cities with divergent geographic, socio-cultural, and technological backgrounds: Seoul, South Korea, for its global leadership in ubiquitous technology, broadband access, and high population density; Lincoln, UK, for the regional and peri-urban dimension it provides, and Portland, Oregon, US, for its international standing as a hub of the sustainable food movement.

Disclosure, conservatism and the cost of equity capital : a review of the foundation literature

In this review piece, we survey the literature on the cost of equity capital implications of corporate disclosure and conservative accounting policy choice decisions with the principle objective of providing insights into the design and methodological issues, which underlie the empirical investigations. We begin with a review of the analytical studies most typically cited in the empirical research as providing a theoretical foundation. We then turn to consider literature that offers insights into the selection of proxies for each of our points of interest, cost of equity capital, disclosure quality and accounting conservatism. As a final step, we review selected empirical studies to illustrate the relevant evidence found within the literature. Based on our review, we interpret the literature as providing the researcher with only limited direct guidance on the appropriate choice of measure for each of the constructs of interest. Further, we view the literature as raising questions about both the interpretation of empirical findings in the face of measurement concerns and the suitability of certain theoretical arguments to the research setting. Overall, perhaps the message which is most clear is that one of the most controversial and fundamental issues underlying the literature is the issue of the diversifiability or nondiversifiability of information effects.

The 2008 Tibet riots : perspectives, divided group protests and divergent media narratives

Awareness of the power of the mass media to communicate images of protest to global audiences and, in so doing, to capture space in global media discourses is a central feature of the transnational protest movement. A number of protest movements have formed around opposition to concepts and practices that operate beyond national borders, such as neoliberal globalization or threats to the environment. However, transnational protests also involve more geographically discreet issues such as claims to national independence or greater religious or political freedom by groups within specific national contexts. Appealing to the international community for support is a familiar strategy for communities who feel that they are being discriminated against or ignored by a national government.

The impact of software-as-a-service on business models of leading software vendors : experiences from three exploratory case studies

The number of software vendors offering ‘Software-as-a-Service’ has been increasing in recent years. In the Software-as-a-Service model software is operated by the software vendor and delivered to the customer as a service. Existing business models and industry structures are challenged by the changes to the deployment and pricing model compared to traditional software. However, the full implications on the way companies create, deliver and capture value are not yet sufficiently analyzed. Current research is scattered on specific aspects, only a few studies provide a more holistic view of the impact from a business model perspective. For vendors it is, however, crucial to be aware of the potentially far reaching consequences of Software-as-a-Service. Therefore, a literature review and three exploratory case studies of leading software vendors are used to evaluate possible implications of Software-as-a-Service on business models. The results show an impact on all business model building blocks and highlight in particular the often less articulated impact on key activities, customer relationship and key partnerships for leading software vendors and show related challenges, for example, with regard to the integration of development and operations processes. The observed implications demonstrate the disruptive character of the concept and identify future research requirements.

Partial protection against chlamydial reproductive tract infection by a recombinant major outer membrane protein/CpG/cholera toxin intranasal vaccine in the guinea pig Chlamydia cavaie model

Chlamydia trachomatis is a major cause of sexually transmitted diseases worldwide. There currently is no vaccine to protect against chlamydial infection of the female reproductive tract. Vaccine development has predominantly involved using the murine model, however infection of female guinea pigs with Chlamydia caviae more closely resembles chlamydial infection of the human female reproductive tract, and presents a better model to assess potential human chlamydial vaccines. We immunised female guinea pigs intranasally with recombinant major outer membrane protein (r-MOMP) combined with CpG-10109 and cholera toxin adjuvants. Both systemic and mucosal immune responses were elicited in immunised animals. MOMP-specific IgG and IgA were present in the vaginal mucosae, and high levels of MOMP-specific IgG were detected in the serum of immunised animals. Antibodies from the vaginal mucosae were also shown to be capable of neutralising C. caviae in vitro. Following immunisation, animals were challenged intravaginally with a live C. caviae infection of 102 inclusion forming units. We observed a decrease in duration of infection and a significant (p<0.025) reduction in infection load in r-MOMP immunised animals, compared to animals immunised with adjuvant only. Importantly, we also observed a marked reduction in upper reproductive tract (URT) pathology in r-MOMP immunised animals. Intranasal immunisation of female guinea pigs with r-MOMP was able to provide partial protection against C. caviae infection, not only by reducing chlamydial burden but also URT pathology. This data demonstrates the value of using the guinea pig model to evaluate potential chlamydial vaccines for protection against infection and disease pathology caused by C. trachomatis in the female reproductive tract.

A comparison of the effects of a chlamydial vaccine administered during or after a C. muridarum urogenital infection of female mice

There are approximately 92 million new chlamydial infections of the genital tract in humans diagnosed each year, costing health care systems billions of dollars in treatment not only of acute infections, but also of associated inflammatory sequelae, such as pelvic inflammatory disease (PID) and ectopic pregnancy. These numbers are increasing at a steady rate and, due to the asymptomatic nature of infections, the incidence may be underestimated and the costs of treatment therefore higher. Over the previous few decades there has been a large amount of research into the development of an efficacious vaccine against genital tract chlamydial infections. The majority of this research has focused on females, due to the high rate of development of associated diseases, including PID, which can lead to ectopic pregnancy and infertility. In light of the increasing infection rates that have occurred despite the availability of antibiotics, and the asymptomatic nature of chlamydial infections, it is imperative that an efficacious vaccine that protects against infection and associated pathology be developed.

On the consistency of multiclass classification methods

Binary classification methods can be generalized in many ways to handle multiple classes. It turns out that not all generalizations preserve the nice property of Bayes consistency. We provide a necessary and sufficient condition for consistency which applies to a large class of multiclass classification methods. The approach is illustrated by applying it to some multiclass methods proposed in the literature.

On the optimality of sample-based estimates of the expectation of the empirical minimizer

We study sample-based estimates of the expectation of the function produced by the empirical minimization algorithm. We investigate the extent to which one can estimate the rate of convergence of the empirical minimizer in a data dependent manner. We establish three main results. First, we provide an algorithm that upper bounds the expectation of the empirical minimizer in a completely data-dependent manner. This bound is based on a structural result due to Bartlett and Mendelson, which relates expectations to sample averages. Second, we show that these structural upper bounds can be loose, compared to previous bounds. In particular, we demonstrate a class for which the expectation of the empirical minimizer decreases as O(1/n) for sample size n, although the upper bound based on structural properties is Ω(1). Third, we show that this looseness of the bound is inevitable: we present an example that shows that a sharp bound cannot be universally recovered from empirical data.

Correction to “The Importance of Convexity in Learning With Squared Loss” [Sep 98 1974-1980]

The paper "the importance of convexity in learning with squared loss" gave a lower bound on the sample complexity of learning with quadratic loss using a nonconvex function class. The proof contains an error. We show that the lower bound is true under a stronger condition that holds for many cases of interest.

Shouting from the rooftops : Queer digital storytelling for social impact

This chapter explores some of the practical and theoretical obstacles and opportunities for self-expression experienced by a group of Queer Dig- ital Storytellers who primarily make and distribute their stories online. “Queer” in this chapter encompasses a diverse range of gender and sexual identities and perspectives on same, including the heterosexual children of queer parents and heterosexual parents of queer children. As such it is also used as a unifying moniker by participants in the Rainbow Family Tree case study that is examined in this chapter. The Digital Storytellers in this case study are largely motivated by a desire to have an impact on social attitudes towards gender and sexuality, both in their personal province of friends and family, and in public domains constituted of unknown or invisible audiences. The privacy and publicity dilemmas that will be considered arise out of positioning personal stories in the public domain and the quandaries that emerge from an activist desire to speak truth to power that is located across a wide cross section of audiences.

On the consistency of multiclass classification methods

Binary classification is a well studied special case of the classification problem. Statistical properties of binary classifiers, such as consistency, have been investigated in a variety of settings. Binary classification methods can be generalized in many ways to handle multiple classes. It turns out that one can lose consistency in generalizing a binary classification method to deal with multiple classes. We study a rich family of multiclass methods and provide a necessary and sufficient condition for their consistency. We illustrate our approach by applying it to some multiclass methods proposed in the literature.

Closing the gap between bandit and full-information online optimization : high-probability regret bound

We demonstrate a modification of the algorithm of Dani et al for the online linear optimization problem in the bandit setting, which allows us to achieve an O( \sqrt{T ln T} ) regret bound in high probability against an adaptive adversary, as opposed to the in expectation result against an oblivious adversary of Dani et al. We obtain the same dependence on the dimension as that exhibited by Dani et al. The results of this paper rest firmly on those of Dani et al and the remarkable technique of Auer et al for obtaining high-probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

Developing the atlas of cancer in Queensland : methodological issues

Background: Achieving health equity has been identified as a major challenge, both internationally and within Australia. Inequalities in cancer outcomes are well documented, and must be quantified before they can be addressed. One method of portraying geographical variation in data uses maps. Recently we have produced thematic maps showing the geographical variation in cancer incidence and survival across Queensland, Australia. This article documents the decisions and rationale used in producing these maps, with the aim to assist others in producing chronic disease atlases. Methods: Bayesian hierarchical models were used to produce the estimates. Justification for the cancers chosen, geographical areas used, modelling method, outcome measures mapped, production of the adjacency matrix, assessment of convergence, sensitivity analyses performed and determination of significant geographical variation is provided. Conclusions: Although careful consideration of many issues is required, chronic disease atlases are a useful tool for assessing and quantifying geographical inequalities. In addition they help focus research efforts to investigate why the observed inequalities exist, which in turn inform advocacy, policy, support and education programs designed to reduce these inequalities.