Differential Uptake of Gold Nanoparticles by 2 Species of Tadpole, the Wood Frog (Lithobates Sylvaticus) and the Bullfrog (Lithobates Catesbeianus)

Engineered nanoparticles are aquatic contaminants of emerging concern that exert ecotoxicological effects on a wide variety of organisms. We exposed cetyltrimethylammonium bromide–capped spherical gold nanoparticles to wood frog and bullfrog tadpoles with conspecifics and in combination with the other species continuously for 21 d, then measured uptake and localization of gold. Wood frog tadpoles alone and in combination with bullfrog tadpoles took up significantly more gold than bullfrogs. Bullfrog tadpoles in combination with wood frogs took up significantly more gold than controls. The rank order of weight-normalized gold uptake was wood frogs in combination \u3e wood frogs alone \u3e bullfrogs in combination \u3e bullfrogs alone \u3e controls. In all gold-exposed groups of tadpoles, gold was concentrated in the anterior region compared with the posterior region of the body. The concentration of gold nanoparticles in the anterior region of wood frogs both alone and in combination with bullfrogs was significantly higher than the corresponding posterior regions. We also measured depuration time of gold in wood frogs. After 21 d in a solution of gold nanoparticles, tadpoles lost \u3e83% of internalized gold when placed in gold-free water for 5 d. After 10 d in gold-free water, tadpoles lost 94% of their gold. After 15 d, gold concentrations were below the level of detection. Our finding of differential uptake between closely related species living in similar habitats with overlapping geographical distributions argues against generalizing toxicological effects of nanoparticles for a large group of organisms based on measurements in only one species

Statistical pairwise interaction model of stock market

Financial markets are a classical example of complex systems as they comprise many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or others are agent-based models with rules designed in order to recover some empirical behaviours. Here we show that the pairwise model is actually a statistically consistent model with observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach based only on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviours, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.Comment: 11 pages, 8 figure

U.S. stock market interaction network as learned by the Boltzmann Machine

We study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented analysis shows that binarization preserves market correlation structure. Properties of distributions of external fields and couplings as well as industry sector clustering structure are studied for different historical dates and moving window sizes. We found that a heavy positive tail in the distribution of couplings is responsible for the sparse market clustering structure. We also show that discrepancies between the model parameters might be used as a precursor of financial instabilities.Comment: 15 pages, 17 figures, 1 tabl

Contribution of positron emission tomography in pleural disease.

INTRODUCTION: Positron emission tomography (PET) now plays a clear role in oncology, especially in chest tumours. We discuss the value of metabolic imaging in characterising pleural pathology in the light of our own experience and review the literature. BACKGROUND: PET is particularly useful in characterising malignant pleural pathologies and is a factor of prognosis in mesothelioma. Metabolic imaging also provides clinical information for staging lung cancer, in researching the primary tumour in metastatic pleurisy and in monitoring chronic or recurrent pleural pathologies. CONCLUSIONS: PET should therefore be considered as a useful tool in the diagnosis of liquid or solid pleural pathologies

Evaluating Lifeworld as an emancipatory methodology

Disability research is conducted within a highly politicised ‘hotbed’ of competing paradigms and principles. New researchers, who want to work within the social model, are soon faced with complex and challenging methodological and philosophical dilemmas. The social model advocates research agendas that are focused on the emancipation and empowerment of disabled people but, in reality, these are rarely achieved. To be successful researchers need to engage with innovative and creative methodologies and to share their experiences of these within environments that welcome challenge and debate. This paper focuses on Lifeworld and assesses its value as a tool for emancipatory research. Using examples from a study with parents, whose children were in the process of being labelled as having autism, the paper illustrates how the principles that ‘underpin’ the methodology offered a supportive framework for a novice researcher

Doing narrative research? Thinking through the narrative process

Across social science disciplines there has been a growth in narrative research—the so called ‘narrative turn’. This turn echoes broader shifts associated with more complex social worlds, epistemological challenges and feminist responses. Narrative research typically involves exploring individual, subjective experiences through interview-based research, but can also range across researching group and organisational dynamics to document-based analysis. In this chapter the question of what constitutes narrative research is explored and illuminated using data from a qualitative longitudinal study on transition to first-time motherhood. The importance of developing a theoretical rationale when choosing a narrative research approach, together with suggested ways of analysing data once collected, is noted. Researching individual accounts of subjective experience and transitions as a feminist researcher provides opportunities, but challenges too

Biographical interviews and imagined futures essay writing: users of two methods in conversation

This article reports on a conversation between users of two research methods, biographical interviews and imagined futures essay writing. A dialogue form is used to discuss these methods and their potential to be combined. The value of comparing research methods is discussed, and then the two methods are described and points of connection and contrast are explored. Although one method emphasises looking back while the other looks forward, the two have much in common, including the exercise of imagination, and discussion of individual agency and structural constraint. Both involve the construction of narratives that help understanding of people’s lives as individual trajectories set in broader social and historical contexts. The two methods are quite different but complementary, and possibilities for their combination in one project are identified. The article ends by reflecting on the benefits and drawbacks of using dialogue to consider how research methods sit alongside each other

Rethinking the patient: using Burden of Treatment Theory to understand the changing dynamics of illness

<b>Background</b> In this article we outline Burden of Treatment Theory, a new model of the relationship between sick people, their social networks, and healthcare services. Health services face the challenge of growing populations with long-term and life-limiting conditions, they have responded to this by delegating to sick people and their networks routine work aimed at managing symptoms, and at retarding - and sometimes preventing - disease progression. This is the new proactive work of patient-hood for which patients are increasingly accountable: founded on ideas about self-care, self-empowerment, and self-actualization, and on new technologies and treatment modalities which can be shifted from the clinic into the community. These place new demands on sick people, which they may experience as burdens of treatment.<p></p> <b>Discussion</b> As the burdens accumulate some patients are overwhelmed, and the consequences are likely to be poor healthcare outcomes for individual patients, increasing strain on caregivers, and rising demand and costs of healthcare services. In the face of these challenges we need to better understand the resources that patients draw upon as they respond to the demands of both burdens of illness and burdens of treatment, and the ways that resources interact with healthcare utilization.<p></p> <b>Summary</b> Burden of Treatment Theory is oriented to understanding how capacity for action interacts with the work that stems from healthcare. Burden of Treatment Theory is a structural model that focuses on the work that patients and their networks do. It thus helps us understand variations in healthcare utilization and adherence in different healthcare settings and clinical contexts

Local niche differences predict genotype associations in sister taxa of desert tortoise

Aims: To investigate spatial congruence between ecological niches and genotype in two allopatric species of desert tortoise that are species of conservation concern. Location: Mojave and Sonoran Desert ecoregions; California, Nevada, Arizona, Utah, USA. Methods: We compare ecological niches of Gopherus agassizii and Gopherus morafkai using species distribution modelling (SDM) and then calibrate a pooled-taxa distribution model to explore local differences in species-environment relationships based on the spatial residuals of the pooled-taxa model. We use multiscale geographically weighted regression (MGWR) applied to those residuals to estimate local species-environment relationships that can vary across the landscape. We identify multivariate clusters in these local species-environment relationships and compare them against models of (a) a geographically based taxonomic designation for two sister species and (b) an environmental ecoregion designation, with respect to their ability to predict a genotype association index for these two species. Results: We find non-identical niches for these species, with differences that span physiographic and vegetation niche dimensions. We find evidence for two distinct clusters of local species-environment relationships that when mapped, predict an index of genotype association for the two sister taxa better than did either the geographically based taxonomic designation or an environmental ecoregion designation. Main conclusions: Exploring local species-environment relationships by coupling SDM and MGWR can benefit studies of biogeography and conservation. We find that niche separation in habitat selection conforms to genotypic differences between sister taxa of tortoise in a recent secondary contact zone. This result may inform decision making by agencies with regulatory or land management authority for the two sister taxa addressed here.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Magnetic fluctuations in the classical XY model: the origin of an exponential tail in a complex system

We study the probability density function for the fluctuations of the magnetic order parameter in the low temperature phase of the XY model of finite size. In two-dimensions this system is critical over the whole of the low temperature phase. It is shown analytically and without recourse to the scaling hypothesis that, in this case, the distribution is non-Gaussian and of universal form, independent of both system size and critical exponent $\eta$. An exact expression for the generating function of the distribution is obtained, which is transformed and compared with numerical data from high resolution molecular dynamics and Monte Carlo simulations. The calculation is extended to general dimension and an exponential tail is found in all dimensions less than four, despite the fact that critical fluctuations are limited to D=2. These results are discussed in the light of similar behaviour observed in models of interface growth and for dissipative systems driven into a non-equilibrium steady state.Comment: 32 pages, 13 figures, 1 table. Few changes. To appear in Phys. Rev.