Comparison of Trees and Grasses for Rhizoremediation of Petroleum Hydrocarbons

Rhizoremediation of petroleum contaminants is a phytoremediation process that depends on interactions among plants, microbes, and soils. Trees and grasses are commonly used for phytoremediation, with trees typically being chosen for remediation of BTEX while grasses are more commonly used for remediation of PAHs and total petroleum hydrocarbons. The objective of this review was to compare the effectiveness of trees and grasses for rhizoremediation of hydrocarbons and address the advantages of each vegetation type. Grasses were more heavily represented in the literature and therefore demonstrated a wider range of effectiveness. However, the greater biomass and depth of tree roots may have greater potential for promoting environmental conditions that can improve rhizoremediation, such as increased metabolizable organic carbon, oxygen, and water. Overall, we found little difference between grasses and trees with respect to average reduction of hydrocarbons for studies that compared planted treatments with a control. Additional detailed investigations into plant attributes that most influence hydrocarbon degradation rates should provide data needed to determine the potential for rhizoremediation with trees or grasses for a given site and identify which plant characteristics are most important.     

Catalytic and Functional Roles of Conserved Amino Acids in the SET Domain of the S. cerevisiae Lysine Methyltransferase Set1

In S. cerevisiae, the lysine methyltransferase Set1 is a member of the multiprotein complex COMPASS. Set1 catalyzes mono-, di- and trimethylation of the fourth residue, lysine 4, of histone H3 using methyl groups from S-adenosylmethionine, and requires a subset of COMPASS proteins for this activity. The methylation activity of COMPASS regulates gene expression and chromosome segregation in vivo. To improve understanding of the catalytic mechanism of Set1, single amino acid substitutions were made within the SET domain. These Set1 mutants were evaluated in vivo by determining the levels of K4-methylated H3, assaying the strength of gene silencing at the rDNA and using a genetic assessment of kinetochore function as a proxy for defects in Dam1 methylation. The findings indicate that no single conserved active site base is required for H3K4 methylation by Set1. Instead, our data suggest that a number of aromatic residues in the SET domain contribute to the formation of an active site that facilitates substrate binding and dictates product specificity. Further, the results suggest that the attributes of Set1 required for trimethylation of histone H3 are those required for Pol II gene silencing at the rDNA and kinetochore function.     

A Hybrid Likelihood Model for Sequence-Based Disease Association Studies

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.     

Trauma History and Depression Predict Incomplete Adherence to Antiretroviral Therapies in a Low Income Country

Background

As antiretroviral therapy (ART) for HIV becomes increasingly available in low and middle income countries (LMICs), understanding reasons for lack of adherence is critical to stemming the tide of infections and improving health. Understanding the effect of psychosocial experiences and mental health symptomatology on ART adherence can help maximize the benefit of expanded ART programs by indicating types of services, which could be offered in combination with HIV care.

Methodology

The Coping with HIV/AIDS in Tanzania (CHAT) study is a longitudinal cohort study in the Kilimanjaro Region that included randomly selected HIV-infected (HIV+) participants from two local hospital-based HIV clinics and four free-standing voluntary HIV counselling and testing sites. Baseline data were collected in 2008 and 2009; this paper used data from 36 month follow-up interviews (N = 468). Regression analyses were used to predict factors associated with incomplete self-reported adherence to ART.

Results

Incomplete ART adherence was significantly more likely to be reported amongst participants who experienced a greater number of childhood traumatic events: sexual abuse prior to puberty and the death in childhood of an immediate family member not from suicide or homicide were significantly more likely in the non-adherent group and other negative childhood events trended toward being more likely. Those with incomplete adherence had higher depressive symptom severity and post-traumatic stress disorder (PTSD). In multivariable analyses, childhood trauma, depression, and financial sacrifice remained associated with incomplete adherence.

Discussion

This is the first study to examine the effect of childhood trauma, depression and PTSD on HIV medication adherence in a low income country facing a significant burden of HIV. Allocating spending on HIV/AIDS toward integrating mental health services with HIV care is essential to the creation of systems that enhance medication adherence and maximize the potential of expanded antiretroviral access to improve health and reduce new infections.     

MuPIT interactive: webserver for mapping variant positions to annotated, interactive 3D structures

Mutation position imaging toolbox (MuPIT) interactive is a browser-based application for single-nucleotide variants (SNVs), which automatically maps the genomic coordinates of SNVs onto the coordinates of available three-dimensional (3D) protein structures. The application is designed for interactive browser-based visualization of the putative functional relevance of SNVs by biologists who are not necessarily experts either in bioinformatics or protein structure. Users may submit batches of several thousand SNVs and review all protein structures that cover the SNVs, including available functional annotations such as binding sites, mutagenesis experiments, and common polymorphisms. Multiple SNVs may be mapped onto each structure, enabling 3D visualization of SNV clusters and their relationship to functionally annotated positions. We illustrate the utility of MuPIT interactive in rationalizing the impact of selected polymorphisms in the PharmGKB database, somatic mutations identified in the Cancer Genome Atlas study of invasive breast carcinomas, and rare variants identified in the exome sequencing project. MuPIT interactive is freely available for non-profit use at http://mupit.icm.jhu.edu.     

Estimating population size by spatially explicit capture–recapture

The number of animals in a population is conventionally estimated by capture–recapture without modelling the spatial relationships between animals and detectors. Problems arise with non‐spatial estimators when individuals differ in their exposure to traps or the target population is poorly defined. Spatially explicit capture–recapture (SECR) methods devised recently to estimate population density largely avoid these problems. Some applications require estimates of population size rather than density, and population size in a defined area may be obtained as a derived parameter from SECR models. While this use of SECR has potential benefits over conventional capture–recapture, including reduced bias, it is unfamiliar to field biologists and no study has examined the precision and robustness of the estimates. We used simulation to compare the performance of SECR and conventional estimators of population size with respect to bias and confidence interval coverage for several spatial scenarios. Three possible estimators for the sampling variance of realised population size all performed well. The precision of SECR estimates was nearly the same as that of the null‐model conventional population estimator. SECR estimates of population size were nearly unbiased (relative bias 0–10%) in all scenarios, including surveys in randomly generated patchy landscapes. Confidence interval coverage was near the nominal level. We used SECR to estimate the population of a species of skink Oligosoma infrapunctatum from pitfall trapping. The estimated number in the area bounded by the outermost traps differed little between a homogeneous density model and models with a quadratic trend in density or a habitat effect on density, despite evidence that the latter models fitted better. Extrapolation of trend models to a larger plot may be misleading. To avoid extrapolation, a large region of interest should be sampled throughout, either with one continuous trapping grid or with clusters of traps dispersed widely according to a probability‐based and spatially representative sampling design.     

Ethnic divisions and public goods provision,revisited

A considerable amount of recent work in political science and economics builds from the hypothesis that ethnic heterogeneity leads to poor provision of public goods, a key component of poor governance. Much of this work cites Alesina, Baqir and Easterly as providing empirical proof. This paper argues that the findings of this article have been significantly overstated. Through a simple re-analysis of the data, it shows that ethnic diversity does not straightforwardly undermine public goods provision. Rather, at least in these data, the relationship is mixed for different public goods: ethnic diversity is related to lower provision of some public goods and to higher provision of others. In some cases, there is no clear relationship. The differences between the findings presented here and those of the original article are arguably subtle, but are worth noting because of Alesina, et al.'s important contribution to the literature.