Carbon stable isotope analysis of cereal remains as a way to reconstruct water availability: preliminary results

Reconstructing past water availability, both as rainfall and irrigation, is important to answer questions about the way society reacts to climate and its changes and the role of irrigation in the development of social complexity. Carbon stable isotope analysis of archaeobotanical remains is a potentially valuable method for reconstructing water availability. To further define the relationship between water availability and plant carbon isotope composition and to set up baseline values for the Southern Levant, grains of experimentally grown barley and sorghum were studied. The cereal crops were grown at three stations under five different irrigation regimes in Jordan. Results indicate that a positive but weak relationship exists between irrigation regime and total water input of barley grains, but no relationship was found for sorghum. The relationship for barley is site-specific and inter-annual variation was present at Deir ‘Alla, but not at Ramtha and Khirbet as-Samra

Diagnosis and Management of Infected Total Knee Arthroplasty§

Infection following total knee arthroplasty can be difficult to diagnose and treat. Diagnosis is multifactorial and relies on the clinical picture, radiographs, bone scans, serologic tests, synovial fluid examination, intra-operative culture and histology. Newer techniques including ultrasonication and molecular diagnostic studies are playing an expanded role. Two-stage exchange arthroplasty with antibiotic cement and 4-6 weeks of intravenous antibiotic treatment remains the most successful intervention for infection eradication. There is no consensus on the optimum type of interval antibiotic cement spacer. There is a limited role for irrigation and debridement, direct one-stage exchange, chronic antibiotic suppression and salvage procedures like arthrodesis and amputation. We examine the literature on each of the diagnostic modalities and treatment options in brief and explain their current significance

Leveraging H1N1 infection transmission modeling with proximity sensor microdata

<p>Abstract</p> <p>Background</p> <p>The contact networks between individuals can have a profound impact on the evolution of an infectious outbreak within a network. The impact of the interaction between contact network and disease dynamics on infection spread has been investigated using both synthetic and empirically gathered micro-contact data, establishing the utility of micro-contact data for epidemiological insight. However, the infection models tied to empirical contact data were highly stylized and were not calibrated or compared against temporally coincident infection rates, or omitted critical non-network based risk factors such as age or vaccination status.</p> <p>Methods</p> <p>In this paper we present an agent-based simulation model firmly grounded in disease dynamics, incorporating a detailed characterization of the natural history of infection, and 13 weeks worth of micro-contact and participant health and risk factor information gathered during the 2009 H1N1 flu pandemic.</p> <p>Results</p> <p>We demonstrate that the micro-contact data-based model yields results consistent with the case counts observed in the study population, derive novel metrics based on the logarithm of the time degree for evaluating individual risk based on contact dynamic properties, and present preliminary findings pertaining to the impact of internal network structures on the spread of disease at an individual level.</p> <p>Conclusions</p> <p>Through the analysis of detailed output of Monte Carlo ensembles of agent based simulations we were able to recreate many possible scenarios of infection transmission using an empirically grounded dynamic contact network, providing a validated and grounded simulation framework and methodology. We confirmed recent findings on the importance of contact dynamics, and extended the analysis to new measures of the relative risk of different contact dynamics. Because exponentially more time spent with others correlates to a linear increase in infection probability, we conclude that network dynamics have an important, but not dominant impact on infection transmission for H1N1 transmission in our study population.</p

Partnerships for the Design, Conduct, and Analysis of Effectiveness, and Implementation Research: Experiences of the Prevention Science and Methodology Group

What progress prevention research has made comes through strategic partnerships with communities and institutions that host this research, as well as professional and practice networks that facilitate the diffusion of knowledge about prevention. We discuss partnership issues related to the design, analysis, and implementation of prevention research and especially how rigorous designs, including random assignment, get resolved through a partnership between community stakeholders, institutions, and researchers. These partnerships shape not only study design, but they determine the data that can be collected and how results and new methods are disseminated. We also examine a second type of partnership to improve the implementation of effective prevention programs into practice. We draw on social networks to studying partnership formation and function. The experience of the Prevention Science and Methodology Group, which itself is a networked partnership between scientists and methodologists, is highlighted

Enhancing Dissemination and Implementation Research Using Systems Science Methods

PURPOSE: Dissemination and implementation (D&I) research seeks to understand and overcome barriers to adoption of behavioral interventions that address complex problems; specifically interventions that arise from multiple interacting influences crossing socio-ecological levels. It is often difficult for research to accurately represent and address the complexities of the real world, and traditional methodological approaches are generally inadequate for this task. Systems science methods, expressly designed to study complex systems, can be effectively employed for an improved understanding about dissemination and implementation of evidence-based interventions. METHODS: Case examples of three systems science methods – system dynamics modeling, agent-based modeling, and network analysis – are used to illustrate how each method can be used to address D&I challenges. RESULTS: The case studies feature relevant behavioral topical areas: chronic disease prevention, community violence prevention, and educational intervention. To emphasize consistency with D&I priorities, the discussion of the value of each method is framed around the elements of the established Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. CONCLUSIONS: Systems science methods can help researchers, public health decision makers and program implementers to understand the complex factors influencing successful D&I of programs in community settings, and to identify D&I challenges imposed by system complexity

DNA dispose, but subjects decide. Learning and the extended synthesis

Adaptation by means of natural selection depends on the ability of populations to maintain variation in heritable traits. According to the Modern Synthesis this variation is sustained by mutations and genetic drift. Epigenetics, evodevo, niche construction and cultural factors have more recently been shown to contribute to heritable variation, however, leading an increasing number of biologists to call for an extended view of speciation and evolution. An additional common feature across the animal kingdom is learning, defined as the ability to change behavior according to novel experiences or skills. Learning constitutes an additional source for phenotypic variation, and change in behavior may induce long lasting shifts in fitness, and hence favor evolutionary novelties. Based on published studies, I demonstrate how learning about food, mate choice and habitats has contributed substantially to speciation in the canonical story of Darwin’s finches on the Galapagos Islands. Learning cannot be reduced to genetics, because it demands decisions, which requires a subject. Evolutionary novelties may hence emerge both from shifts in allelic frequencies and from shifts in learned, subject driven behavior. The existence of two principally different sources of variation also prevents the Modern Synthesis from self-referring explanations.publishedVersio