allows reconnection to occur at small {theta} and high V{sub A} leads to exhaust jets that are fast enough relative to the surrounding solar wind to be readily identified. Very small-{theta} current sheets are common in the solar wind at 1 AU, but typically are not associated with particularly low plasma {beta} or high V{sub A}. On the other hand, small-{theta} current sheets should be common in the lower solar corona, a plasma regime of extremely low {beta} and extremely high V{sub A}. Our observations lend credence to models that predict that reconnection at small-{theta} current sheets is primarily responsible for coronal heating.

Representatives from the US and Canadian Government will present updates from the Joint US and Canada Dietary Reference Intake (DRI) Working Group on activities conducted to work toward updating the sodium and potassium DRIs. The Governments of the United States and Canada have jointly undertaken the development of the Dietary Reference Intakes since the mid‐1990s. Federal DRI committees from each country work collaboratively to identify DRI needs, prioritize nutrient reviews and advance work to resolve any methodological issues that could impede new reviews. The commission of a systematic review for nutrients under review is now an integral part of the DRI process. Recently the DRI Working Group sponsored an evidence review by the Agency for Health Care Research and Quality (AHRQ) on sodium and potassium to inform the update of the sodium and potassium DRIs by the National Academy of Medicine (NAM). The AHRQ review will be completed in 2017. Additionally, the DRI steering committees jointly decided that prior to undertaking a nutrient review, the scientific framework for setting DRIs needed to be adapted to include a framework for including data on chronic disease risk reduction. Thus, a scientific expert panel was convened to review and critically evaluate evidentiary, dose response, and process issues related to the use of chronic disease endpoints and develop options for their incorporation into future DRI reviews. The Joint US/Canadian‐sponsored Working Group's report ‘Options for Basing DRIs on Chronic Disease Endpoints’ will inform the NAM committee that will develop guiding principles for inclusion of chronic disease endpoints to be used by committees setting future DRIs. In summary, the US and Canadian Governments are working collaboratively to adapt the methods for updating the DRIs utilizing rigorous systematic evidence reviews and a chronic disease endpoint framework.Support or Funding InformationUnited States Department of Health and Human Services, United States Department of Agriculture, and Health Canada.

Aims To examine the effect of rounding of visual acuity data on estimates of surgical performance. Method In this observational study, the distribution of 1-year Snellen visual acuity data from 606 endothelial keratoplasties from the NHSBT UK transplant database was analysed. A curve was fitted to the data and used to estimate the frequencies of partly read Snellen lines. The estimates were used to create a virtual database of grafts with Snellen acuities that included individual letter scores. The virtual database was then sampled to produce datasets for 10 virtual surgeons. Various acuity analysis methods were then applied to simulate possible effects of surgeons rounding their data. Results Rounding of acuity data was found to have a notable effect on estimates of surgeons’ success rates. When a criterion of 6/12 or better was applied, the success rates ranged from 62% to 80% using a conservative method of estimation but ranged from 80% to 94% using a less conservative method. Conclusions Rounding of visual acuity scores is an important potential bias in outcome data and should be avoided. If rounding is required we recommend that it is carried out conservatively, giving credit only for lines read completely.

To determine whether diesel exhaust particles (DEPs) could be a toxic agent to the bladder, rats were exposed to different concentrations of DEPs for one month or three months. When the rats were sacrificed, morphologic changes of the urothelium were investigated. The antioxidase activity and the levels of lipid peroxidation in the bladder were assayed. In the three-month group, DEPs at doses of 21.03 μg/μl insulted the structural integrity of surface glycosaminoglycans, widened the gap between urothelial cells, increased levels of lipid peroxidation, and decreased antioxidase activities in the urinary bladder (p<0.05). Furthermore, DEPs at a dose of 5.61 μg/μl decreased glutathione, catalase, and glutathione peroxidase activities (p<0.05). These results led to the conclusion that DEPs were a toxic agent in the bladder. The toxic effects might be attributed to oxidative damage mediated by pro-oxidant/antioxidant imbalance or excessive free radicals.

Hamiltonian dynamics can be used to produce distant proposals for the Metropolis algorithm, thereby avoiding the slow exploration of the state space that results from the diffusive behaviour of simple random-walk proposals. Though originating in physics, Hamiltonian dynamics can be applied to most problems with continuous state spaces by simply introducing fictitious “momentum” variables. A key to its usefulness is that Hamiltonian dynamics preserves volume, and its trajectories can thus be used to define complex mappings without the need to account for a hard-to-compute Jacobian factor — a property that can be exactly maintained even when the dynamics is approximated by discretizing time. In this review, I discuss theoretical and practical aspects of Hamiltonian Monte Carlo, and present some of its variations, including using windows of states for deciding on acceptance or rejection, computing trajectories using fast approximations, tempering during the course of a trajectory to handle isolated modes, and short-cut methods that prevent useless trajectories from taking much computation time.

At JSM this summer, John Kimmel from Chapman and Hall/CRC Press gave me a copy of the Handbook of Markov Chain Monte Carlo, as I had not received an author's copy. This handbook is edited by Steve ...

Phylogeographic methods have attracted a lot of attention in recent years, stressing the need to provide a solid statistical framework for many existing methodologies so as to draw statistically reliable inferences. Here, we take a flexible fully Bayesian approach by reducing the problem to a clustering framework, whereby the population distribution can be explained by a set of migrations, forming geographically stable population clusters. These clusters are such that they are consistent with a fixed number of migrations on the corresponding (unknown) subdivided coalescent tree. Our methods rely upon a clustered population distribution, and allow for inclusion of various covariates (such as phenotype or climate information) at little additional computational cost. We illustrate our methods with an example from weevil mitochondrial DNA sequences from the Iberian peninsula.

In this paper we consider the problem of model choice for a set of insurance loss ratios. We use a reversible jump algorithm for our model discrimination and show how the vanilla reversible jump algorithm can be improved on using recent methodological advances in reversible jump computation.

Hamiltonian dynamics can be used to produce distant proposals for the Metropolis algorithm, thereby avoiding the slow exploration of the state space that results from the diffusive behaviour of simple random-walk proposals.Though originating in physics, Hamiltonian dynamics can be applied to most problems with continuous state spaces by simply introducing fictitious "momentum" variables.A key to its usefulness is that Hamiltonian dynamics preserves volume, and its trajectories can thus be used to define complex mappings without the need to account for a hard-to-compute Jacobian factor -a property that can be exactly maintained even when the dynamics is approximated by discretizing time.In this review, I discuss theoretical and practical aspects of Hamiltonian Monte Carlo, and present some of its variations, including using windows of states for deciding on acceptance or rejection, computing trajectories using fast approximations, tempering during the course of a trajectory to handle isolated modes, and short-cut methods that prevent useless trajectories from taking much computation time.

Fibroblasts are a dominant cell type in most human solid tumors. The possibility that fibroblasts have the capacity to interact with and modulate the function of tumor-associated T lymphocytes makes them a potential therapeutic target. To address this question, primary cultures of fibroblasts derived from human lung tumors were established and cultured with T cells derived from the same tumor. The tumor fibroblasts significantly enhance the production of IFN-gamma and IL-17A by the tumor-associated T cells following a CD3/CD28-induced activation of the T cells. This enhancement was fibroblast cell dose-dependent and did not require direct contact between the two cell types. Tumor-associated fibroblast-conditioned media similarly enhanced both IFN-gamma and IL-17A in activated T cells, and this enhancement was significantly reduced by Abs to IL-6. Conditioned media derived from activated lymphocyte cultures significantly enhanced IL-6 production by tumor fibroblasts. A similar enhancement of IFN-gamma and IL-17A was observed when activated T cells from a normal donor were cultivated with skin fibroblasts derived from the same donor. These results establish that fibroblasts and autologous lymphocytes, whether derived from the tumor microenvironment or from nonmalignant tissues, have the capacity to reciprocally interact and modulate function. In contrast to other reports, fibroblasts are shown to have an immunostimulatory effect upon activated T lymphocytes. The ability of fibroblasts to enhance two T cell cytokines known to have an impact upon tumor progression suggests that fibroblasts play an important role in tumor pathogenesis that could be exploited therapeutically.

Individual Level Models (ILMs), a new class of models, are being applied to infectious epidemic data to aid in the understanding of the spatio-temporal dynamics of infectious diseases. These models are highly flexible and intuitive, and can be parameterised under a Bayesian framework via Markov chain Monte Carlo (MCMC) methods. Unfortunately, this parameterisation can be difficult to implement due to intense computational requirements when calculating the full posterior for large, or even moderately large, susceptible populations, or when missing data are present. Here we detail a methodology that can be used to estimate parameters for such large, and/or incomplete, data sets. This is done in the context of a study of the UK 2001 foot-and-mouth disease (FMD) epidemic.

In the previous chapter, a sequence of matrices was used to model the sequence of subprocesses, birth, survival, movement, etc., which characterize population dynamics. We find this building block perspective attractive for at least two reasons: (1) it allows one to mentally "divide and conquer" sometimes complicated population dynamics processes; (2) the resulting product of matrices is a generalization of Leslie and Lefkovitch matrices, something familiar to many biologists.