41 research outputs found

    Food Insecurity and Sexual Risk in an HIV Endemic Community in Uganda

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    Food insecurity has been linked to high-risk sexual behavior in sub-Saharan Africa, but there are limited data on these links among people living with HIV/AIDS, and on the mechanisms for how food insecurity predisposes individuals to risky sexual practices. We undertook a series of in-depth open-ended interviews with 41 individuals living with HIV/AIDS to understand the impact of food insecurity on sexual-risk behaviors. Participants were recruited from the Immune Suppression Clinic at the Mbarara University of Science and Technology in Mbarara, Uganda. Interviews were recorded, transcribed verbatim, translated, and coded following the strategy of grounded theory. Four major themes emerged from the interview data: the relationship between food insecurity and transactional sex for women; the impact of a husband\u27s death from HIV on worsening food insecurity among women and children; the impact of food insecurity on control over condom use, and the relationship between food insecurity and staying in violent/abusive relationships. Food insecurity led to increased sexual vulnerability among women. Women were often compelled to engage in transactional sex or remain in violent or abusive relationships due to their reliance on men in their communities to provide food for themselves and their children. There is an urgent need to prioritize food security programs for women living with HIV/AIDS and address broader gender-based inequities that are propelling women to engage in risky sexual behaviors based on hunger. Such interventions will play an important role in improving the health and well-being of people living with HIV/AIDS, and preventing HIV transmission

    Food Insecurity and Sexual Risk in an HIV Endemic Community in Uganda

    Get PDF
    Food insecurity has been linked to high-risk sexual behavior in sub-Saharan Africa, but there are limited data on these links among people living with HIV/AIDS, and on the mechanisms for how food insecurity predisposes individuals to risky sexual practices. We undertook a series of in-depth open-ended interviews with 41 individuals living with HIV/AIDS to understand the impact of food insecurity on sexual-risk behaviors. Participants were recruited from the Immune Suppression Clinic at the Mbarara University of Science and Technology in Mbarara, Uganda. Interviews were recorded, transcribed verbatim, translated, and coded following the strategy of grounded theory. Four major themes emerged from the interview data: the relationship between food insecurity and transactional sex for women; the impact of a husband’s death from HIV on worsening food insecurity among women and children; the impact of food insecurity on control over condom use, and the relationship between food insecurity and staying in violent/abusive relationships. Food insecurity led to increased sexual vulnerability among women. Women were often compelled to engage in transactional sex or remain in violent or abusive relationships due to their reliance on men in their communities to provide food for themselves and their children. There is an urgent need to prioritize food security programs for women living with HIV/AIDS and address broader gender-based inequities that are propelling women to engage in risky sexual behaviors based on hunger. Such interventions will play an important role in improving the health and well-being of people living with HIV/AIDS, and preventing HIV transmission

    Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change

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    Understanding the process interactions and feedbacks among water, porous geological media, microbes, and vascular plants is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated coevolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled laboratory and uncontrollable field studies, the University of Arizona built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO comprises three replicated, heavily instrumented, hillslope-scale model landscapes within the environmentally controlled Biosphere 2 facility. The model landscapes were designed to initially be simple and purely abiotic, enabling scientists to observe each step in the landscapes’ evolution as they undergo physical, chemical, and biological changes over many years. This chapter describes the model systems and associated research facilities and illustrates how LEO allows for tracking of multiscale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and soil coring data are already providing insights into the tight linkages between water flow, weathering, and microbial community development. These interacting processes are anticipated to drive the model systems to increasingly complex states and will be impacted by the introduction of vascular plants and changes in climatic regimes over the years to come. By intensively monitoring the evolutionary trajectory, integrating data with mathematical models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked, and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change

    Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes.

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    INTRODUCTION: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates. RESULTS: We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB. CONCLUSION: Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study

    HIV Promoter Integration Site Primarily Modulates Transcriptional Burst Size Rather Than Frequency

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    Mammalian gene expression patterns, and their variability across populations of cells, are regulated by factors specific to each gene in concert with its surrounding cellular and genomic environment. Lentiviruses such as HIV integrate their genomes into semi-random genomic locations in the cells they infect, and the resulting viral gene expression provides a natural system to dissect the contributions of genomic environment to transcriptional regulation. Previously, we showed that expression heterogeneity and its modulation by specific host factors at HIV integration sites are key determinants of infected-cell fate and a possible source of latent infections. Here, we assess the integration context dependence of expression heterogeneity from diverse single integrations of a HIV-promoter/GFP-reporter cassette in Jurkat T-cells. Systematically fitting a stochastic model of gene expression to our data reveals an underlying transcriptional dynamic, by which multiple transcripts are produced during short, infrequent bursts, that quantitatively accounts for the wide, highly skewed protein expression distributions observed in each of our clonal cell populations. Interestingly, we find that the size of transcriptional bursts is the primary systematic covariate over integration sites, varying from a few to tens of transcripts across integration sites, and correlating well with mean expression. In contrast, burst frequencies are scattered about a typical value of several per cell-division time and demonstrate little correlation with the clonal means. This pattern of modulation generates consistently noisy distributions over the sampled integration positions, with large expression variability relative to the mean maintained even for the most productive integrations, and could contribute to specifying heterogeneous, integration-site-dependent viral production patterns in HIV-infected cells. Genomic environment thus emerges as a significant control parameter for gene expression variation that may contribute to structuring mammalian genomes, as well as be exploited for survival by integrating viruses
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