Beta-binomial model for meta-analysis of odds ratios

In meta-analysis of odds ratios ({\OR}s), heterogeneity between the studies is usually modelled via the additive random effects model (REM). An alternative, multiplicative random effects model for {\OR}s uses overdispersion. The multiplicative factor in this overdispersion model (ODM) can be interpreted as an intra-class correlation (ICC) parameter. This model naturally arises when the probabilities of an event in one or both arms of a comparative study are themselves beta-distributed, resulting in beta-binomial distributions. We propose two new estimators of the ICC for meta-analysis in this setting. One is based on the inverted Breslow-Day test, and the other on the improved gamma approximation by Kulinskaya and Dollinger (2015, p. 26) to the distribution of Cochran's $Q$. The performance of these and several other estimators of ICC on bias and coverage is studied by simulation. Additionally, the Mantel-Haenszel approach to estimation of odds ratios is extended to the beta-binomial model, and we study performance of various ICC estimators when used in the Mantel-Haenszel or the inverse-variance method to combine odds ratios in meta-analysis. The results of the simulations show that the improved gamma-based estimator of ICC is superior for small sample sizes, and the Breslow-Day-based estimator is the best for $n\geq100$. The Mantel-Haenszel-based estimator of {\OR} is very biased and is not recommended. The inverse-variance approach is also somewhat biased for {\OR}s\neq1, but this bias is not very large in practical settings. Developed methods and R programs, provided in the Web Appendix, make the beta-binomial model a feasible alternative to the standard REM for meta-analysis of odds ratios

Functional biodiversity in the agricultural landscape: relationships between weeds and arthropod fauna

We reviewed studies aimed at understanding functional relationships between weeds and arthropods in agroecosystems as influenced by biodiversity at different scales, with the main goal of highlighting gaps in knowledge, research methods and approaches. We first addressed: (i) the regulation of arthropod communities by weed diversity at genetic, species and habitat levels, (ii) the regulation of weed communities by arthropods through seed predation and dispersal and (iii) belowground weed-insect interactions. We then focussed on methodologies to study weed–arthropod interactions in agricultural landscapes and discuss techniques potentially available for data analysis and the importance of joint weed–arthropod trend detection. Lastly, we discuss the implications of research findings for biodiversity conservation policies (agri-environmental schemes) and suggest some priorities for future work. Results showed that to date research has largely ignored weed–arthropod interactions in agricultural landscapes. No information is available on the role of weed genetic diversity as driver of weed–arthropod interactions, whereas studies on effects of species and habitat diversity often lack a functional perspective and ⁄ or a spatial component. Also, information on how management of the wider agricultural biotope might express positive weed– arthropod functional interactions is scarce. Another area worth being explored is the relationship between weed-leaf ⁄ root herbivores and beneficial arthropods. Tools for spatial data analysis might be useful for elucidating weed–arthropod interactions in agricultural landscapes, but some methodological aspects, e.g. the definition of the most appropriate experimental design and sampling scale ⁄ frequency, must be refined. New studies on weed–arthropod interactions should encompass an explicit spatial component; this knowledge is particularly important for improving IPM ⁄IWM systems and designing more targeted agri-environmental schemes

Host-plant genotypic diversity and community genetic interactions mediate aphid spatial distribution.

Genetic variation in plants can influence the community structure of associated species, through both direct and indirect interactions. Herbivorous insects are known to feed on a restricted range of plants, and herbivore preference and performance can vary among host plants within a species due to genetically based traits of the plant (e.g., defensive compounds). In a natural system, we expect to find genetic variation within both plant and herbivore communities and we expect this variation to influence species interactions. Using a three-species plant-aphid model system, we investigated the effect of genetic diversity on genetic interactions among the community members. Our system involved a host plant (Hordeum vulgare) that was shared by an aphid (Sitobion avenae) and a hemi-parasitic plant (Rhinanthus minor). We showed that aphids cluster more tightly in a genetically diverse host-plant community than in a genetic monoculture, with host-plant genetic diversity explaining up to 24% of the variation in aphid distribution. This is driven by differing preferences of the aphids to the different plant genotypes and their resulting performance on these plants. Within the two host-plant diversity levels, aphid spatial distribution was influenced by an interaction among the aphid's own genotype, the genotype of a competing aphid, the origin of the parasitic plant population, and the host-plant genotype. Thus, the overall outcome involves both direct (i.e., host plant to aphid) and indirect (i.e., parasitic plant to aphid) interactions across all these species. These results show that a complex genetic environment influences the distribution of herbivores among host plants. Thus, in genetically diverse systems, interspecific genetic interactions between the host plant and herbivore can influence the population dynamics of the system and could also structure local communities. We suggest that direct and indirect genotypic interactions among species can influence community structure and processes

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Islands of change in Palau : church, school, and elected government, 1891-1981

Ed.D. University of Hawaii at Manoa 1982Includes bibliographical references (leaves 417-429).Ed.D