Understanding GPU programming for statistical computation: Studies in massively parallel massive mixtures

This article describes advances in statistical computation for large-scale data analysis in structured Bayesian mixture models via graphics processing unit (GPU) programming. The developments are partly motivated by computational challenges arising in fitting models of increasing heterogeneity to increasingly large datasets. An example context concerns common biological studies using high-throughput technologies generating many, very large datasets and requiring increasingly high-dimensional mixture models with large numbers of mixture components.We outline important strategies and processes for GPU computation in Bayesian simulation and optimization approaches, give examples of the benefits of GPU implementations in terms of processing speed and scale-up in ability to analyze large datasets, and provide a detailed, tutorial-style exposition that will benefit readers interested in developing GPU-based approaches in other statistical models. Novel, GPU-oriented approaches to modifying existing algorithms software design can lead to vast speed-up and, critically, enable statistical analyses that presently will not be performed due to compute time limitations in traditional computational environments. Supplementalmaterials are provided with all source code, example data, and details that will enable readers to implement and explore the GPU approach in this mixture modeling context. © 2010 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play.

Interactions between natural selection and environmental change are well recognized and sit at the core of ecology and evolutionary biology. Reciprocal interactions between ecology and evolution, eco-evolutionary feedbacks, are less well studied, even though they may be critical for understanding the evolution of biological diversity, the structure of communities and the function of ecosystems. Eco-evolutionary feedbacks require that populations alter their environment (niche construction) and that those changes in the environment feed back to influence the subsequent evolution of the population. There is strong evidence that organisms influence their environment through predation, nutrient excretion and habitat modification, and that populations evolve in response to changes in their environment at time-scales congruent with ecological change (contemporary evolution). Here, we outline how the niche construction and contemporary evolution interact to alter the direction of evolution and the structure and function of communities and ecosystems. We then present five empirical systems that highlight important characteristics of eco-evolutionary feedbacks: rotifer-algae chemostats; alewife-zooplankton interactions in lakes; guppy life-history evolution and nutrient cycling in streams; avian seed predators and plants; and tree leaf chemistry and soil processes. The alewife-zooplankton system provides the most complete evidence for eco-evolutionary feedbacks, but other systems highlight the potential for eco-evolutionary feedbacks in a wide variety of natural systems.

Using decision analysis to improve malaria control policy making.

Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets (ITNs) and artemesinin combination therapies (ACTs) for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases.

Rain dances in the dry season: overcoming the religious congruence fallacy

Religious congruence refers to consistency among an individual’s religious beliefs and attitudes, consistency between religious ideas and behavior, and religious ideas, identities, or schemas that are chronically salient and accessible to individuals across contexts and situations. Decades of anthropological, sociological, and psychological research establish that religious congruence is rare, but much thinking about religion presumes that it is common. The religious congruence fallacy occurs when interpretations or explanations unjustifiably presume religious congruence. I illustrate the ubiquity of religious incongruence, show how the religious congruence fallacy distorts thinking about religion, and outline an approach to help overcome the fallacy.

5-α reductase inhibitors and prostate cancer prevention: where do we turn now?

With the lifetime risk of being diagnosed with prostate cancer so great, an effective chemopreventive agent could have a profound impact on the lives of men. Despite decades of searching for such an agent, physicians still do not have an approved drug to offer their patients. In this article, we outline current strategies for preventing prostate cancer in general, with a focus on the 5-α-reductase inhibitors (5-ARIs) finasteride and dutasteride. We discuss the two landmark randomized, controlled trials of finasteride and dutasteride, highlighting the controversies stemming from the results, and address the issue of 5-ARI use, including reasons why providers may be hesitant to use these agents for chemoprevention. We further discuss the recent US Food and Drug Administration ruling against the proposed new indication for dutasteride and the change to the labeling of finasteride, both of which were intended to permit physicians to use the drugs for chemoprevention. Finally, we discuss future directions for 5-ARI research.

A dimensionless number for understanding the evolutionary dynamics of antigenically variable RNA viruses.

Antigenically variable RNA viruses are significant contributors to the burden of infectious disease worldwide. One reason for their ubiquity is their ability to escape herd immunity through rapid antigenic evolution and thereby to reinfect previously infected hosts. However, the ways in which these viruses evolve antigenically are highly diverse. Some have only limited diversity in the long-run, with every emergence of a new antigenic variant coupled with a replacement of the older variant. Other viruses rapidly accumulate antigenic diversity over time. Others still exhibit dynamics that can be considered evolutionary intermediates between these two extremes. Here, we present a theoretical framework that aims to understand these differences in evolutionary patterns by considering a virus's epidemiological dynamics in a given host population. Our framework, based on a dimensionless number, probabilistically anticipates patterns of viral antigenic diversification and thereby quantifies a virus's evolutionary potential. It is therefore similar in spirit to the basic reproduction number, the well-known dimensionless number which quantifies a pathogen's reproductive potential. We further outline how our theoretical framework can be applied to empirical viral systems, using influenza A/H3N2 as a case study. We end with predictions of our framework and work that remains to be done to further integrate viral evolutionary dynamics with disease ecology.

Considering the role of social dynamics and positional behavior in gestural communication research.

While the hominin fossil record cannot inform us on either the presence or extent of social and cognitive abilities that may have paved the way for the emergence of language, studying non-vocal communication among our closest living relatives, the African apes, may provide valuable information about how language originated. Although much has been learned from gestural signaling in non-human primates, we have not yet established how and why gestural repertoires vary across species, what factors influence this variation, and how knowledge of these differences can contribute to an understanding of gestural signaling's contribution to language evolution. In this paper, we review arguments surrounding the theory that language evolved from gestural signaling and suggest some important factors to consider when conducting comparative studies of gestural communication among African apes. Specifically, we propose that social dynamics and positional behavior are critical components that shape the frequency and nature of gestural signaling across species and we argue that an understanding of these factors could shed light on how gestural communication may have been the basis of human language. We outline predictions for the influence of these factors on the frequencies and types of gestures used across the African apes and highlight the importance of including these factors in future gestural communication research with primates.

Neuroimaging assessment of early and late neurobiological sequelae of traumatic brain injury: implications for CTE.

Traumatic brain injury (TBI) has been increasingly accepted as a major external risk factor for neurodegenerative morbidity and mortality. Recent evidence indicates that the resultant chronic neurobiological sequelae following head trauma may, at least in part, contribute to a pathologically distinct disease known as Chronic Traumatic Encephalopathy (CTE). The clinical manifestation of CTE is variable, but the symptoms of this progressive disease include impaired memory and cognition, affective disorders (i.e., impulsivity, aggression, depression, suicidality, etc.), and diminished motor control. Notably, mounting evidence suggests that the pathology contributing to CTE may be caused by repetitive exposure to subconcussive hits to the head, even in those with no history of a clinically evident head injury. Given the millions of athletes and military personnel with potential exposure to repetitive subconcussive insults and TBI, CTE represents an important public health issue. However, the incidence rates and pathological mechanisms are still largely unknown, primarily due to the fact that there is no in vivo diagnostic tool. The primary objective of this manuscript is to address this limitation and discuss potential neuroimaging modalities that may be capable of diagnosing CTE in vivo through the detection of tau and other known pathological features. Additionally, we will discuss the challenges of TBI research, outline the known pathology of CTE (with an emphasis on Tau), review current neuroimaging modalities to assess the potential routes for in vivo diagnosis, and discuss the future directions of CTE research.