Pale Moon : An Indian Love Song

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Equivalence of histogram equalization, histogram matching and the Nyul algorithm for intensity standardization in MRI

Intensity standardization is an important preprocessing step in automatedanalysis of MRI. A popular method by Nyul et al. uses apiece-wise linear approximation of histogram matching. We showthat this method is a non-uniform trapezoidal Riemann approximationof the ideal histogram matching operation, and suggest thathistogram matching is no better than histogram equalization for intensitystandardization in MRI. Experimental results are derived usingsynthetic data

Ribosomal RNA diversity predicts genome diversity in gut bacteria and their relatives

The mammalian gut is an attractive model for exploring the general question of how habitat impacts the evolution of gene content. Therefore, we have characterized the relationship between 16 S rRNA gene sequence similarity and overall levels of gene conservation in four groups of species: gut specialists and cosmopolitans, each of which can be divided into pathogens and non-pathogens. At short phylogenetic distances, specialist or cosmopolitan bacteria found in the gut share fewer genes than is typical for genomes that come from non-gut environments, but at longer phylogenetic distances gut bacteria are more similar to each other than are genomes at equivalent evolutionary distances from non-gut environments, suggesting a pattern of short-term specialization but long-term convergence. Moreover, this pattern is observed in both pathogens and non-pathogens, and can even be seen in the plasmids carried by gut bacteria. This observation is consistent with the finding that, despite considerable interpersonal variation in species content, there is surprising functional convergence in the microbiome of different humans. Finally, we observe that even within bacterial species or genera 16S rRNA divergence provides useful information about average conservation of gene content. The results described here should be useful for guiding strain selection to maximize novel gene discovery in large-scale genome sequencing projects, while the approach could be applied in studies seeking to understand the effects of habitat adaptation on genome evolution across other body habitats or environment types

Non-bloat legumes alter pasture soil greenhouse gas fluxes, nutrient cycling rates, & microbial community structure

Non-Peer ReviewedPasture grazing systems can act as both sources and sinks for greenhouse gases (GHGs) — cattle emit enteric methane (CH4), while soil microorganisms emit nitrous oxide (N2O) and consume ambient CH4. Producers seed non-bloat legumes into pasture forage to increase cattle protein uptake and decrease enteric CH4 emissions, but with undetermined impacts on soil N cycling and N2O emissions. While the introduction of legumes to a grass system can shift soil microbial community structure, it remains unclear how non-bloat legumes affect soil microbial community structure, nutrient cycling rates, and GHG fluxes. To answer this, a two-year survey of microbial community structure, enzyme activity, and GHG emissions was conducted within pastures containing a grass control treatment and two non-bloat legume treatments consisting of sod-seeded Astragalus cicer (cicer milkvetch) and Onobrychis viciifolia (common sainfoin). Seasonal changes and precipitation had the largest effect on microbial community structure, while including non-bloat legumes was responsible for 5% of the community variation, partially through increased soil nitrate levels. Structural equation models (SEMs) revealed that cicer milkvetch lowered soil nitrogen cycling rates and decreased arbuscular mycorrhizal fungi (AMF) abundance, which was associated with higher N2O emissions. Soil moisture was the strongest predictor of N2O emissions but did not guarantee a large N2O flux. While cicer milkvetch increases soil nitrate and potential N2O emissions, this must be weighed against the expected benefits of reduced cattle CH4 emissions

The RNA Ontology (RNAO): An ontology for integrating RNA sequence and structure data

Biomedical Ontologies are intended to integrate diverse biomedical data to enable intelligent data-mining and facilitate translation of basic research into useful clinical knowledge. We present the first version of RNAO, an ontology for integrating RNA 3D structural, biochemical and sequence data. While each 3D data file depicts the structure of a specific molecule, such data have broader significance as representatives of classes of homologous molecules, which, while differing in sequence, generally share core structural features of functional importance. Thus, 3D structure data gain value by being linked to homologous sequences in genomic data and databases of sequence alignments. Likewise genomic data can increase in value by annotation of shared structural features, especially when these can be linked to specific functions. The RNAO is being developed in line with the developing standards of the Open Biomedical Ontologies (OBO) Consortium

Human-Associated Microbial Signatures: Examining Their Predictive Value

SummaryHost-associated microbial communities are unique to individuals, affect host health, and correlate with disease states. Although advanced technologies capture detailed snapshots of microbial communities, high within- and between-subject variation hampers discovery of microbial signatures in diagnostic or forensic settings. We suggest turning to machine learning and discuss key directions toward harnessing human-associated microbial signatures

The mind-body-microbial continuum

Our understanding of the vast collection of microbes that live on and inside us (microbiota) and their collective genes (microbiome) has been revolutionized by culture-independent “metagenomic” techniques and DNA sequencing technologies. Most of our microbes live in our gut, where they function as a metabolic organ and provide attributes not encoded in our human genome. Metagenomic studies are revealing shared and distinctive features of microbial communities inhabiting different humans. A central question in psychiatry is the relative role of genes and environment in shaping behavior. The human microbiome serves as the interface between our genes and our history of environmental exposures; explorations of our microbiomes thus offer the possibility of providing new insights into our neurodevelopment and our behavioral phenotypes by affecting complex processes such as inter- and intra personal variations in cognition, personality, mood, sleep, and eating behavior, and perhaps even a variety of neuropsychiatric diseases ranging from affective disorders to autism. Better understanding of microbiome-encoded pathways for xenobiotic metabolism also has important implications for improving the efficacy of pharmacologic interventions with neuromodulator agents

Pale Moon

Out of my lodge at eventide to thy love forsaken, Thy spirit mantle throw Ere thou the great white dawn awaken, And to the sea thou swingest low Then to the West I’ll follow Across the deep lagoon Swift as a flying arrow, To thy abode, Pale Moon, Pale Moon

The arithmetical hierarchy in the setting of ω1\omega_1

We continue work from (Greenberg and Knight) on computable structure theory in the setting of $\omega_1$, where the countable ordinals play the role of natural numbers, and countable sets play the role of finite sets. In the present paper, we define the arithmetical hierarchy through all countable levels (not just the finite levels). We consider two different ways of doing this—one based on the standard definition of the hyperarithmetical hierarchy, and the other based on the standard definition of the effective Borel hierarchy. For each definition, we define computable infinitary formulas through all countable levels, and we obtain analogues of the well-known results from (Ash and Knight, 1989) and (Chisholm, 1990) saying that a relation is relatively intrinsically $\Sigma^0_\alpha$ just in case it is definable by a computable $\Sigma_\alpha$ formula. Although we obtain the same results for the two definitions of the arithmetical hierarchy, we conclude that the definition resembling the standard definition of the hyperarithmetical hierarchy seems preferable