LYMESIM 2.0: An Updated Simulation of Blacklegged Tick (Acari: Ixodidae) Population Dynamics and Enzootic Transmission of \u3ci\u3eBorrelia burgdorferi\u3c/i\u3e (Spirochaetales: Spirochaetaceae)

Lyme disease is the most commonly reported vector-borne disease in the United States, and the number of cases reported each year continues to rise. The complex nature of the relationships between the pathogen (Borrelia burgdorferi sensu stricto), the tick vector (Ixodes scapularis Say), multiple vertebrate hosts, and numerous environmental factors creates challenges for understanding and predicting tick population and pathogen transmission dynamics. LYMESIM is a mechanistic model developed in the late 1990s to simulate the life-history of I. scapularis and transmission dynamics of B. burgdorferi s.s. Here we present LYMESIM 2.0, a modernized version of LYMESIM, that includes several modifications to enhance the biological realism of the model and to generate outcomes that are more readily measured under field conditions. The model is tested for three geographically distinct locations in New York, Minnesota, and Virginia. Model-simulated timing and densities of questing nymphs, infected nymphs, and abundances of nymphs feeding on hosts are consistent with field observations and reports for these locations. Sensitivity analysis highlighted the importance of temperature in host finding for the density of nymphs, the importance of transmission from small mammals to ticks on the density of infected nymphs, and temperature-related tick survival for both density of nymphs and infected nymphs. A key challenge for accurate modeling of these metrics is the need for regionally representative inputs for host populations and their fluctuations. LYMESIM 2.0 is a useful public health tool that downstream can be used to evaluate tick control interventions and can be adapted for other ticks and pathogens

Imperial divides: race, nation, security and the U.S.-Mexico border, 1940-1955

Imperial Divides explores the history of border policing between the United States and Mexico from the 1940s to the 1950s. I examine the links between international security and the early efforts to militarize the U.S.-Mexico border, focusing on the cultural production of a boundary cast in perpetual crisis. This project traces the construction of the U.S.-Mexico border as a global security threat and examines how it was enforced in both countries. It studies the relationship between warfare, migration, and boundary enforcement, arguing that the deep anxieties concerning the United States’ inability to exercise complete control over its southern boundary during World War II and the Cold War were crucial in transforming the U.S.-Mexico border into a national security imperative. I contend that public spectacles of border enforcement were crafted in large part in response to global warfare, beginning with Axis nationals in the years leading up to World War II, and then shifting to Mexican nationals during the Cold War. Just as significantly, this dissertation draws attention to the opposition of the early efforts to militarize the U.S.-Mexico border. For radical artists, intellectuals, and activists, the joint policing of the border, and the Mexican state’s close cooperation with the United States during the first decade of the Cold War signaled a troubling rightward shift in the nation. As the presidential administrations of Ávila Camacho (1940-46), Miguel Alemán Valdés (1946-52), and Adolfo Ruiz Cortines (1952-58) sought greater political, economic, and security ties with the United States, a creative flurry of radical opposition emerged, insisting that the sovereignty of the Mexican nation was being undermined by its imperial neighbor

Modeling the Geographic Distribution of \u3ci\u3eIxodes scapularis\u3c/i\u3e and \u3ci\u3eIxodes pacificus\u3c/i\u3e (Acari: Ixodidae) in the Contiguous United States

In addition to serving as vectors of several other human pathogens, the black-legged tick, Ixodes scapularis Say, and western black-legged tick, Ixodes pacificus Cooley and Kohls, are the primary vectors of the spirochete (Borrelia burgdorferi) that causes Lyme disease, the most common vector-borne disease in the United States. Over the past two decades, the geographic range of I. pacificus has changed modestly while, in contrast, the I. scapularis range has expanded substantially, which likely contributes to the concurrent expansion in the distribution of human Lyme disease cases in the Northeastern, North-Central and Mid-Atlantic states. Identifying counties that contain suitable habitat for these ticks that have not yet reported established vector populations can aid in targeting limited vector surveillance resources to areas where tick invasion and potential human risk are likely to occur. We used county-level vector distribution information and ensemble modeling to map the potential distribution of I. scapularis and I. pacificus in the contiguous United States as a function of climate, elevation, and forest cover. Results show that I. pacificus is currently present within much of the range classified by our model as suitable for establishment. In contrast, environmental conditions are suitable for I. scapularis to continue expanding its range into northwestern Minnesota, central and northern Michigan, within the Ohio River Valley, and inland from the southeastern and Gulf coasts. Overall, our ensemble models show suitable habitat for I. scapularis in 441 eastern counties and for I. pacificus in 11 western counties where surveillance records have not yet supported classification of the counties as established

The use of error-category mapping in pharmacokinetic model analysis of dynamic contrast-enhanced MRI data.

This study introduces the use of 'error-category mapping' in the interpretation of pharmacokinetic (PK) model parameter results derived from dynamic contrast-enhanced (DCE-) MRI data. Eleven patients with metastatic renal cell carcinoma were enrolled in a multiparametric study of the treatment effects of bevacizumab. For the purposes of the present analysis, DCE-MRI data from two identical pre-treatment examinations were analysed by application of the extended Tofts model (eTM), using in turn a model arterial input function (AIF), an individually-measured AIF and a sample-average AIF. PK model parameter maps were calculated. Errors in the signal-to-gadolinium concentration ([Gd]) conversion process and the model-fitting process itself were assigned to category codes on a voxel-by-voxel basis, thereby forming a colour-coded 'error-category map' for each imaged slice. These maps were found to be repeatable between patient visits and showed that the eTM converged adequately in the majority of voxels in all the tumours studied. However, the maps also clearly indicated sub-regions of low Gd uptake and of non-convergence of the model in nearly all tumours. The non-physical condition ve ≥ 1 was the most frequently indicated error category and appeared sensitive to the form of AIF used. This simple method for visualisation of errors in DCE-MRI could be used as a routine quality-control technique and also has the potential to reveal otherwise hidden patterns of failure in PK model applications.This work was supported by GlaxoSmithKline UK, Wellcome Trust, Cambridge NIHR Biomedical Research Centre, Cambridge Experimental Cancer Medicine Centre, Cancer Research UKThis is the published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0730725X1400321X

Democracy Playbook 2021: 10 Commitments for Advancing Democracy

This special edition of our Democracy Playbook updates our 2019 compendium of evidence-based democracy best practices with the research and developments of the eventful past two years. Most importantly, we here extract from that rich body of knowledge ten proposed pro-democracy commitments for consideration by participants in the upcoming first Summit for Democracy on December 9–10, 2021, and the subsequent year of action. We break down each of the ten commitments into a series of specific and measurable steps that all stakeholders can undertake to renew and strengthen democracy, fight democratic backsliding, and usher in an era of improved governance. After the Summit, we will update the Playbook again with the best of the learnings from that gathering for use as we build towards the 2022 follow-up event a year from now

Mauve Assembly Metrics

Summary: High-throughput DNA sequencing technologies have spurred the development of numerous novel methods for genome assembly. With few exceptions, these algorithms are heuristic and require one or more parameters to be manually set by the user. One approach to parameter tuning involves assembling data from an organism with an available high-quality reference genome, and measuring assembly accuracy using some metrics

Common genetic risk of major depression and nicotine dependence: The contribution of antisocial traits in a United States veteran male twin cohort

Many studies that found associations between depression and nicotine dependence have ignored possible shared genetic influences associated with antisocial traits. The present study examined the contribution of genetic and environmental effects associated with conduct disorder (CD) and antisocial personality disorder (ASPD) to the comorbidity of major depression (MD) and nicotine dependence (ND). A telephone diagnostic interview, the Diagnostic Interview Schedule-III-R, was administered to eligible twins from the Vietnam Era Twin (VET) Registry in 1992. Multivariate genetic models were fitted to 3360 middle-aged and predominantly white twin pairs (1868 monozygotic, 1492 dizygotic pairs) of which both members completed the pertinent diagnostic interview sections. Genetic influences on CD accounted for 100%, 68%, and 50% of the total genetic variance in risk for ASPD, MD and ND, respectively. After controlling for genetic influences on CD, the partial genetic correlation between MD and ND was no longer statistically significant. Nonshared environmental contributions to the comorbidity among these disorders were not significant. This study not only demonstrates that the comorbidity between ND and MD is influenced by common genetic risk factors, but also further suggests that the common genetic risk factors overlapped with those for antisocial traits such as CD and ASPD in men

Normalized Affymetrix expression data are biased by G-quadruplex formation

Probes with runs of four or more guanines (G-stacks) in their sequences can exhibit a level of hybridization that is unrelated to the expression levels of the mRNA that they are intended to measure. This is most likely caused by the formation of G-quadruplexes, where inter-probe guanines form Hoogsteen hydrogen bonds, which probes with G-stacks are capable of forming. We demonstrate that for a specific microarray data set using the Human HG-U133A Affymetrix GeneChip and RMA normalization there is significant bias in the expression levels, the fold change and the correlations between expression levels. These effects grow more pronounced as the number of G-stack probes in a probe set increases. Approximately 14 of the probe sets are directly affected. The analysis was repeated for a number of other normalization pipelines and two, FARMS and PLIER, minimized the bias to some extent. We estimate that ∼15 of the data sets deposited in the GEO database are susceptible to the effect. The inclusion of G-stack probes in the affected data sets can bias key parameters used in the selection and clustering of genes. The elimination of these probes from any analysis in such affected data sets outweighs the increase of noise in the signal. © 2011 The Author(s)