When Death Comes

after Mary Oliver When death comes like the dentist, sticking her hand into your mouth

The Sir

The Sir is a novel about a directionless college graduate who takes a fourth grade teaching position at a country school in the Rio Grande Valley of South Texas. David Walsh is taken by the exoticness of his surroundings, as well as a newfound sense of purpose as he tries to break down the walls of authority, culture, and class that divide him from his academically struggling students. He forms close relationships with two students in particular: Ramon Garza, a child prodigy, and Eddie Santos, a troublemaker from a broken family. The planting of a garden in the school\u27s vegetation-less courtyard symbolizes David\u27s hopes for an edenic community, but as the school year wears on, his efforts at becoming a co-learner devolve into ethical tangles, violence, and personal crisis. The novel ends six years later as David, now married and with his wife expecting a child, travels back to the Valley after receiving a disturbing letter from Ramon. He returns in an attempt to redeem his past failures, only to confront once again his own demons

Restoring the Duality between Principal Components of a Distance Matrix and Linear Combinations of Predictors, with Application to Studies of the Microbiome.

Appreciation of the importance of the microbiome is increasing, as sequencing technology has made it possible to ascertain the microbial content of a variety of samples. Studies that sequence the 16S rRNA gene, ubiquitous in and nearly exclusive to bacteria, have proliferated in the medical literature. After sequences are binned into operational taxonomic units (OTUs) or species, data from these studies are summarized in a data matrix with the observed counts from each OTU for each sample. Analysis often reduces these data further to a matrix of pairwise distances or dissimilarities; plotting the first two or three principal components (PCs) of this distance matrix often reveals meaningful groupings in the data. However, once the distance matrix is calculated, it is no longer clear which OTUs or species are important to the observed clustering; further, the PCs are hard to interpret and cannot be calculated for subsequent observations. We show how to construct approximate decompositions of the data matrix that pair PCs with linear combinations of OTU or species frequencies, and show how these decompositions can be used to construct biplots, select important OTUs and partition the variability in the data matrix into contributions corresponding to PCs of an arbitrary distance or dissimilarity matrix. To illustrate our approach, we conduct an analysis of the bacteria found in 45 smokeless tobacco samples

Correlation between values for each method.

<p>Correlation between values for each method.</p

Scree plots for variance explained by each component.

<p>For each method, the contribution of the first 20 (of 44) components plotted. Note the change of scale for unconstrained regression. Components are ordered by decreasing eigenvalue of the Unifrac distance matrix.</p

Percent of variation in <i>X</i> explained and <i>R</i>² for prediction of <i>B</i>_⋅1 through <i>B</i>_⋅9 for the Tobacco data.

<p>Percent of variation in <i>X</i> explained and <i>R</i>² for prediction of <i>B</i>_⋅1 through <i>B</i>_⋅9 for the Tobacco data.</p

Biplot for second and third component of tobacco bacterial data.

<p>Points are colored by type (blue = dry, red = moist, green = toombak) and samples corresponding to replicates of the same product are plotted with the same symbol. The taxonomic families corresponding to the OTUs shown are <i>Staphylococcaceae</i> (4312974), <i>Aerococcaceae</i> (52399), <i>Lactobacillaceae</i> (4379247), <i>Enterococcaceae</i> (29012) and <i>Corynebacteriaceae</i> (810425). The scale on bottom and left corresponds to coordinates of samples, scale on right and top to coordinates of OTUs.</p

Characterization of Bacterial Communities in Selected Smokeless Tobacco Products Using 16S rDNA Analysis

<div><p>The bacterial communities present in smokeless tobacco (ST) products have not previously reported. In this study, we used Next Generation Sequencing to study the bacteria present in U.S.-made dry snuff, moist snuff and Sudanese toombak. Sample diversity and taxonomic abundances were investigated in these products. A total of 33 bacterial families from four phyla, Actinobacteria, Firmicutes, Proteobacteria and Bacteroidetes, were identified. U.S.-produced dry snuff products contained a diverse distribution of all four phyla. Moist snuff products were dominated by Firmicutes. Toombak samples contained mainly Actinobacteria and Firmicutes (<i>Aerococcaceae</i>, <i>Enterococcaceae</i>, <i>and Staphylococcaceae</i>). The program PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) was used to impute the prevalence of genes encoding selected bacterial toxins, antibiotic resistance genes and other pro-inflammatory molecules. PICRUSt also predicted the presence of specific nitrate reductase genes, whose products can contribute to the formation of carcinogenic nitrosamines. Characterization of microbial community abundances and their associated genomes gives us an indication of the presence or absence of pathways of interest and can be used as a foundation for further investigation into the unique microbiological and chemical environments of smokeless tobacco products.</p></div