398 research outputs found

    Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset.

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    Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1-10 cameras), and (2) by total season length (1-365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species

    Categorical Dimensions of Human Odor Descriptor Space Revealed by Non-Negative Matrix Factorization

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    In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain unclear. Here, we use non-negative matrix factorization (NMF) – a dimensionality reduction technique – to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor dimensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner. We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures

    Continuous increase of cardiovascular diseases, diabetes, and non-HIV related cancers as causes of death in HIV-infected individuals in Brazil: An analysis of nationwide data

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    Introduction: After antiretroviral therapy (ART) became available, there was a decline in the number of deaths in persons infected with HIV. Thereafter, there was a decrease in the proportion of deaths attributed to opportunistic infections and an increase in the proportion of deaths attributed to chronic comorbidities. Herein we extend previous observations from a nationwide survey on temporal trends in causes of death in HIV-infected patients in Brazil. Methods: We describe temporal trends in causes of death among adults who had HIV/AIDS listed in the death certificate to those who did not. All death certificates issued in Brazil from 1999 to 2011 and listed in the national mortality database were included. Generalized linear mixed-effects logistic models were used to study temporal trends in proportions. Results: In the HIV-infected population, there was an annual adjusted average increase of 6.0%, 12.0%, 4.0% and 4.1% for cancer, external causes, cardiovascular diseases (CVD) and diabetes mellitus (DM), respectively, compared to 3.0%, 4.0%, 1.0% and 3.9%, in the non-HIV group. For tuberculosis (TB), there was an adjusted average increase of 0.3%/year and a decrease of 3.0%/year in the HIV and the non-HIV groups, respectively. Compared to 1999, the odds ratio (OR) for cancer, external causes, CVD, DM, or TB in the HIV group were, respectively, 2.31, 4.17, 1.76, 2.27 and 1.02, while for the non-HIV group, the corresponding OR were 1.31, 1.63, 1.14, 1.62 and 0.67. Interactions between year as a continuous or categorical variable and HIV were significant (p <0.001) for all conditions, except for DM when year was considered as a continuous variable (p = 0.76). Conclusions: Non HIV-related co-morbidities continue to increase more rapidly as causes of death among HIV-infected individuals than in those without HIV infection, highlighting the need for targeting prevention measures and surveillance for chronic diseases among those patients. © 2014 Paula et al

    Control of intestinal stem cell function and proliferation by mitochondrial pyruvate metabolism.

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    Most differentiated cells convert glucose to pyruvate in the cytosol through glycolysis, followed by pyruvate oxidation in the mitochondria. These processes are linked by the mitochondrial pyruvate carrier (MPC), which is required for efficient mitochondrial pyruvate uptake. In contrast, proliferative cells, including many cancer and stem cells, perform glycolysis robustly but limit fractional mitochondrial pyruvate oxidation. We sought to understand the role this transition from glycolysis to pyruvate oxidation plays in stem cell maintenance and differentiation. Loss of the MPC in Lgr5-EGFP-positive stem cells, or treatment of intestinal organoids with an MPC inhibitor, increases proliferation and expands the stem cell compartment. Similarly, genetic deletion of the MPC in Drosophila intestinal stem cells also increases proliferation, whereas MPC overexpression suppresses stem cell proliferation. These data demonstrate that limiting mitochondrial pyruvate metabolism is necessary and sufficient to maintain the proliferation of intestinal stem cells

    Stop the Top Background of the Stop Search

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    The main background for the supersymmetric stop direct production search comes from Standard Model ttbar events. For the single-lepton search channel, we introduce a few kinematic variables to further suppress this background by focusing on its dileptonic and semileptonic topologies. All are defined to have end points in the background, but not signal distributions. They can substantially improve the stop signal significance and mass reach when combined with traditional kinematic variables such as the total missing transverse energy. Among them, our variable M^W_T2 has the best overall performance because it uses all available kinematic information, including the on-shell mass of both W's. We see 20%-30% improvement on the discovery significance and estimate that the 8 TeV LHC run with 20 fb-1 of data would be able to reach an exclusion limit of 650-700 GeV for direct stop production, as long as the stop decays dominantly to the top quark and a light stable neutralino. Most of the mass range required for the supersymmetric solution of the naturalness problem in the standard scenario can be covered.Comment: 16 pages, 5 figure

    Rule-based Procedural Generation of Item in Role-playing Game

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    This paper demonstrates the significance of rule-based procedural generation of item in role-playing game. The main aims of this project are to: implement rule-based randomized algorithm and totally randomized algorithm in generating item procedurally in Role-Playing Game (RPG), and compare the advantage of rule-based randomized algorithm against totally randomized algorithm in item drop mechanism. Experimental results demonstrate success with all aims: rule-based randomized algorithm is proven to be a better game changing factor in procedural generation of item as it can control the prolific generation of strong items in the early stage of the game. This helps to balance the game and prevents any snow-balling effect as the game progresses

    Strong Ultraviolet Pulse From a Newborn Type Ia Supernova

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    Type Ia supernovae are destructive explosions of carbon oxygen white dwarfs. Although they are used empirically to measure cosmological distances, the nature of their progenitors remains mysterious, One of the leading progenitor models, called the single degenerate channel, hypothesizes that a white dwarf accretes matter from a companion star and the resulting increase in its central pressure and temperature ignites thermonuclear explosion. Here we report observations of strong but declining ultraviolet emission from a Type Ia supernova within four days of its explosion. This emission is consistent with theoretical expectations of collision between material ejected by the supernova and a companion star, and therefore provides evidence that some Type Ia supernovae arise from the single degenerate channel.Comment: Accepted for publication on the 21 May 2015 issue of Natur

    A direct physical interaction between Nanog and Sox2 regulates embryonic stem cell self-renewal

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    Embryonic stem (ES) cell self-renewal efficiency is determined by the Nanog protein level. However, the protein partners of Nanog that function to direct self-renewal are unclear. Here, we identify a Nanog interactome of over 130 proteins including transcription factors, chromatin modifying complexes, phosphorylation and ubiquitination enzymes, basal transcriptional machinery members, and RNA processing factors. Sox2 was identified as a robust interacting partner of Nanog. The purified Nanog–Sox2 complex identified a DNA recognition sequence present in multiple overlapping Nanog/Sox2 ChIP-Seq data sets. The Nanog tryptophan repeat region is necessary and sufficient for interaction with Sox2, with tryptophan residues required. In Sox2, tyrosine to alanine mutations within a triple-repeat motif (S X T/S Y) abrogates the Nanog–Sox2 interaction, alters expression of genes associated with the Nanog-Sox2 cognate sequence, and reduces the ability of Sox2 to rescue ES cell differentiation induced by endogenous Sox2 deletion. Substitution of the tyrosines with phenylalanine rescues both the Sox2–Nanog interaction and efficient self-renewal. These results suggest that aromatic stacking of Nanog tryptophans and Sox2 tyrosines mediates an interaction central to ES cell self-renewal

    MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets

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    Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology (‘MCAM’) employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.National Institutes of Health (U.S.) (NIH-U54-CA112967 )National Institutes of Health (U.S.) (NIH-R01-CA096504
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