649 research outputs found
Lessons Learned About Societal Responses to Emerging Technologies Perceived as Risky
Presented at the 180-Minute Symposium Biofuels Ablaze, organized by Susan E Cozzens, Georgia Institute of Technology, Atlanta, GA.This presentation will present results from a research project that asks whether past experience in the United States with technologies associated in the public mind with risk, along with relevant social-scientific literatures, can inform strategies for bio-energy technologies.Research sponsored by the Program on Ethical, Legal, and Societal Implications
(ELSI) of Research on Alternative Bioenergy Technologies, Synthetic Genomics, or Nanotechnologies, Office of Science, U.S. Department of Energ
Supernatural explanations across the globe are more common for Natural than social pnenomena
Supernatural beliefs are common in every human society, and people frequently invoke the supernatural to explain natural (e.g., storms, disease outbreaks) and social (e.g., murder, warfare) events. However, evolutionary and psychological theories of religion raise competing hypotheses about whether supernatural explanations should more commonly focus on natural or social phenomena. Here we test these hypotheses with a global analysis of supernatural explanations in 109 geographically and culturally diverse societies. We find that supernatural explanations are more prevalent for natural phenomena than for social phenomena, an effect that generalizes across regions and subsistence styles and cannot be reduced to the frequency of natural vs. social phenomena or common cultural ancestry. We also find that supernatural explanations of social phenomena only occur in societies that also have supernatural explanations of natural phenomena. This evidence is consistent with theories that ground the origin of supernatural belief in a human tendency to perceive intent and agency in nature.Method Results - Prevalence of Supernatural Explanations. - Prevalence of Supernatural Explanations by World Region and Subsistence Style. - Frequency of Phenomena and Frequency of Supernatural Explanation. - Sources of Variability in Supernatural Explanations. Discussion Supplemental Material
A Monte Carlo-based framework enhances the discovery and interpretation of regulatory sequence motifs
Abstract
Background
Discovery of functionally significant short, statistically overrepresented subsequence patterns (motifs) in a set of sequences is a challenging problem in bioinformatics. Oftentimes, not all sequences in the set contain a motif. These non-motif-containing sequences complicate the algorithmic discovery of motifs. Filtering the non-motif-containing sequences from the larger set of sequences while simultaneously determining the identity of the motif is, therefore, desirable and a non-trivial problem in motif discovery research.
Results
We describe MotifCatcher, a framework that extends the sensitivity of existing motif-finding tools by employing random sampling to effectively remove non-motif-containing sequences from the motif search. We developed two implementations of our algorithm; each built around a commonly used motif-finding tool, and applied our algorithm to three diverse chromatin immunoprecipitation (ChIP) data sets. In each case, the motif finder with the MotifCatcher extension demonstrated improved sensitivity over the motif finder alone. Our approach organizes candidate functionally significant discovered motifs into a tree, which allowed us to make additional insights. In all cases, we were able to support our findings with experimental work from the literature.
Conclusions
Our framework demonstrates that additional processing at the sequence entry level can significantly improve the performance of existing motif-finding tools. For each biological data set tested, we were able to propose novel biological hypotheses supported by experimental work from the literature. Specifically, in Escherichia coli, we suggested binding site motifs for 6 non-traditional LexA protein binding sites; in Saccharomyces cerevisiae, we hypothesize 2 disparate mechanisms for novel binding sites of the Cse4p protein; and in Halobacterium sp. NRC-1, we discoverd subtle differences in a general transcription factor (GTF) binding site motif across several data sets. We suggest that small differences in our discovered motif could confer specificity for one or more homologous GTF proteins. We offer a free implementation of the MotifCatcher software package at
http://www.bme.ucdavis.edu/facciotti/resources_data/software/
.http://deepblue.lib.umich.edu/bitstream/2027.42/112965/1/12859_2012_Article_5570.pd
Uric acid and thiocyanate as competing substrates of lactoperoxidase
The physiological function of urate is poorly understood. It
may act as a danger signal, an antioxidant, or a substrate for
heme peroxidases. Whether it reacts sufficiently rapidly with
lactoperoxidase (LPO) to act as a physiological substrate remains unknown. LPO is a mammalian peroxidase that plays a
key role in the innate immune defense by oxidizing thiocyanate
to the bactericidal and fungicidal agent hypothiocyanite. We
now demonstrate that urate is a good substrate for bovine LPO
The Sunyaev-Zel'dovich Infrared Experiment: A Millimeter-wave Receiver for Cluster Cosmology
Measurements of the Sunyaev-Zel'dovich (S-Z) effect towards distant clusters
of galaxies can be used to determine the Hubble constant and the radial
component of cluster peculiar velocities. Determination of the cluster peculiar
velocity requires the separation of the two components of the S-Z effect, which
are due to the thermal and bulk velocities of the intracluster plasma. The two
components can be separated practically only at millimeter (mm) wavelengths.
Measurements of the S-Z effect at mm wavelengths are subject to minimal
astrophysical confusion and, therefore, provide an important test of results
obtained at longer wavelengths. We describe the instrument used to make the
first significant detections of the S-Z effect at millimeter wavelengths. This
instrument employs new filter, detector, and readout technologies to produce
sensitive measurements of differential sky brightness stable on long time
scales. These advances allow drift scan observations which achieve high
sensitivity while minimizing common sources of systematic error.Comment: 19 pages, 15 postscript figures, LaTeX(aaspptwo.sty), ApJ(in press
MicroRNA and messenger RNA profiling reveals new biomarkers and mechanisms for RDX induced neurotoxicity
Background
RDX is a well-known pollutant to induce neurotoxicity. MicroRNAs (miRNA) and messenger RNA (mRNA) profiles are useful tools for toxicogenomics studies. It is worthy to integrate MiRNA and mRNA expression data to understand RDX-induced neurotoxicity.
Results
Rats were treated with or without RDX for 48 h. Both miRNA and mRNA profiles were conducted using brain tissues. Nine miRNAs were significantly regulated by RDX. Of these, 6 and 3 miRNAs were up- and down-regulated respectively. The putative target genes of RDX-regulated miRNAs were highly nervous system function genes and pathways enriched. Fifteen differentially genes altered by RDX from mRNA profiles were the putative targets of regulated miRNAs. The induction of miR-71, miR-27ab, miR-98, and miR-135a expression by RDX, could reduce the expression of the genes POLE4, C5ORF13, SULF1 and ROCK2, and eventually induce neurotoxicity. Over-expression of miR-27ab, or reduction of the expression of unknown miRNAs by RDX, could up-regulate HMGCR expression and contribute to neurotoxicity. RDX regulated immune and inflammation response miRNAs and genes could contribute to RDX- induced neurotoxicity and other toxicities as well as animal defending reaction response to RDX exposure.
Conclusions
Our results demonstrate that integrating miRNA and mRNA profiles is valuable to indentify novel biomarkers and molecular mechanisms for RDX-induced neurological disorder and neurotoxicity.published_or_final_versio
Shape-based peak identification for ChIP-Seq
We present a new algorithm for the identification of bound regions from
ChIP-seq experiments. Our method for identifying statistically significant
peaks from read coverage is inspired by the notion of persistence in
topological data analysis and provides a non-parametric approach that is robust
to noise in experiments. Specifically, our method reduces the peak calling
problem to the study of tree-based statistics derived from the data. We
demonstrate the accuracy of our method on existing datasets, and we show that
it can discover previously missed regions and can more clearly discriminate
between multiple binding events. The software T-PIC (Tree shape Peak
Identification for ChIP-Seq) is available at
http://math.berkeley.edu/~vhower/tpic.htmlComment: 12 pages, 6 figure
Virtual patients design and its effect on clinical reasoning and student experience : a protocol for a randomised factorial multi-centre study
Background
Virtual Patients (VPs) are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent) and structured clinical reasoning feedback (present or absent).
Methods/Design
This is a multi-centre randomised 2x2 factorial design study evaluating two independent variables of VP design, branching (present or absent), and structured clinical reasoning feedback (present or absent).The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded.
In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for both primary outcomes
A new approach to construct pathway connected networks and its application in dose responsive gene expression profiles of rat liver regulated by 2,4DNT
<p>Abstract</p> <p>Background</p> <p>Military and industrial activities have lead to reported release of 2,4-dinitrotoluene (2,4DNT) into soil, groundwater or surface water. It has been reported that 2,4DNT can induce toxic effects on humans and other organisms. However the mechanism of 2,4DNT induced toxicity is still unclear. Although a series of methods for gene network construction have been developed, few instances of applying such technology to generate pathway connected networks have been reported.</p> <p>Results</p> <p>Microarray analyses were conducted using liver tissue of rats collected 24h after exposure to a single oral gavage with one of five concentrations of 2,4DNT. We observed a strong dose response of differentially expressed genes after 2,4DNT treatment. The most affected pathways included: long term depression, breast cancer regulation by stathmin1, WNT Signaling; and PI3K signaling pathways. In addition, we propose a new approach to construct pathway connected networks regulated by 2,4DNT. We also observed clear dose response pathway networks regulated by 2,4DNT.</p> <p>Conclusions</p> <p>We developed a new method for constructing pathway connected networks. This new method was successfully applied to microarray data from liver tissue of 2,4DNT exposed animals and resulted in the identification of unique dose responsive biomarkers in regards to affected pathways.</p
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