Human hypocretin and melanin-concentrating hormone levels are linked to emotion and social interaction.

The neurochemical changes underlying human emotions and social behaviour are largely unknown. Here we report on the changes in the levels of two hypothalamic neuropeptides, hypocretin-1 and melanin-concentrating hormone, measured in the human amygdala. We show that hypocretin-1 levels are maximal during positive emotion, social interaction and anger, behaviours that induce cataplexy in human narcoleptics. In contrast, melanin-concentrating hormone levels are minimal during social interaction, but are increased after eating. Both peptides are at minimal levels during periods of postoperative pain despite high levels of arousal. Melanin-concentrating hormone levels increase at sleep onset, consistent with a role in sleep induction, whereas hypocretin-1 levels increase at wake onset, consistent with a role in wake induction. Levels of these two peptides in humans are not simply linked to arousal, but rather to specific emotions and state transitions. Other arousal systems may be similarly emotionally specialized

Conservation of resources theory and research use in health systems

<p>Abstract</p> <p>Background</p> <p>Health systems face challenges in using research evidence to improve policy and practice. These challenges are particularly evident in small and poorly resourced health systems, which are often in locations (in Canada and globally) with poorer health status. Although organizational resources have been acknowledged as important in understanding research use resource theories have not been a focus of knowledge translation (KT) research. What resources, broadly defined, are required for KT and how does their presence or absence influence research use?</p> <p>In this paper, we consider conservation of resources (COR) theory as a theoretical basis for understanding the capacity to use research evidence in health systems. Three components of COR theory are examined in the context of KT. First, resources are required for research uptake. Second, threat of resource loss fosters resistance to research use. Third, resources can be optimized, even in resource-challenged environments, to build capacity for KT.</p> <p>Methods</p> <p>A scan of the KT literature examined organizational resources needed for research use. A multiple case study approach examined the three components of COR theory outlined above. The multiple case study consisted of a document review and key informant interviews with research team members, including government decision-makers and health practitioners through a retrospective analysis of four previously conducted applied health research studies in a resource-challenged region.</p> <p>Results</p> <p>The literature scan identified organizational resources that influence research use. The multiple case study supported these findings, contributed to the development of a taxonomy of organizational resources, and revealed how fears concerning resource loss can affect research use. Some resources were found to compensate for other resource deficits. Resource needs differed at various stages in the research use process.</p> <p>Conclusions</p> <p>COR theory contributes to understanding the role of resources in research use, resistance to research use, and potential strategies to enhance research use. Resources (and a lack of them) may account for the observed disparities in research uptake across health systems. This paper offers a theoretical foundation to guide further examination of the COR-KT ideas and necessary supports for research use in resource-challenged environments.</p

Supra-subduction Zone Pyroxenites from San Jorge and Santa Isabel (Solomon Islands)

Peridotites associated with pyroxenites (with rare olivine and spinel) are exposed on the islands of San Jorge and Santa Isabel in the Solomon Islands. Orthopyroxenite occurs in large outcrops (≤100 m2) whereas websterite and clinopyroxenite occur as l

Genome-Scale Mapping of <i>Escherichia coli</i> σ⁵⁴ Reveals Widespread, Conserved Intragenic Binding

<div><p>Bacterial RNA polymerases must associate with a σ factor to bind promoter DNA and initiate transcription. There are two families of σ factor: the σ⁷⁰ family and the σ⁵⁴ family. Members of the σ⁵⁴ family are distinct in their ability to bind promoter DNA sequences, in the context of RNA polymerase holoenzyme, in a transcriptionally inactive state. Here, we map the genome-wide association of <i>Escherichia coli</i> σ⁵⁴, the archetypal member of the σ⁵⁴ family. Thus, we vastly expand the list of known σ⁵⁴ binding sites to 135. Moreover, we estimate that there are more than 250 σ⁵⁴ sites in total. Strikingly, the majority of σ⁵⁴ binding sites are located inside genes. The location and orientation of intragenic σ⁵⁴ binding sites is non-random, and many intragenic σ⁵⁴ binding sites are conserved. We conclude that many intragenic σ⁵⁴ binding sites are likely to be functional. Consistent with this assertion, we identify three conserved, intragenic σ⁵⁴ promoters that drive transcription of mRNAs with unusually long 5ʹ UTRs.</p></div

Distribution of σ⁵⁴ binding sites relative to gene position.

<p><b>(A)</b> (Top) Schematic representing the four possible classes of σ⁵⁴ binding site relative to a gene. (Bottom) The distribution of each class of σ⁵⁴ binding site in <i>E</i>. <i>coli</i>. <b>(B)</b> Cumulative frequency of the distance from intergenic (blue), intragenic (red) and all (purple) σ⁵⁴ binding sites to the next available gene start. The cumulative frequency distribution of the distances between 4000 random positions and the next available gene start is also indicated (grey).</p

ChIP-seq identifies σ⁵⁴ binding sites on a genomic scale.

<p><b>(A)</b> Examples of σ⁵⁴ and RNAP (β) binding. Schematics depict the local genomic environment surrounding selected σ⁵⁴ binding sites identified by ChIP-seq. Grey arrows represent genes. Grey arrows with dotted lines indicate that only a portion of the gene is shown. Bent, black arrows indicate the location and direction of σ⁵⁴ binding motifs associated with identified ChIP-seq peaks. Histograms show mapped sequence reads from σ⁵⁴ (blue) and β (black) ChIP-seq experiments. Percentages indicate relative scale on the y-axis. <b>(B)</b> Consensus motif derived from 135 σ⁵⁴ ChIP-seq peaks, determined with MEME (E-value = 1.8e^-213). The established σ⁵⁴ consensus sequence [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.ref006" target="_blank">6</a>] is shown beneath the logo. Nucleotides in bold, underlined text are those most important for σ⁵⁴ binding [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.ref006" target="_blank">6</a>]. <b>(C)</b> Centrimo analysis of σ⁵⁴ motifs identified by MEME, showing the position of the motifs relative to the ChIP-seq peak centers. The graph indicates the average density of motif position for all 135 motif-containing regions, using 10 bp bins from position -75 to +75 relative to the σ⁵⁴ ChIP-seq peak.</p

ChIP-seq enrichment represents genuine σ⁵⁴ binding.

<p><b>(A)</b> Targeted validation of σ⁵⁴ binding sites. ChIP-qPCR measurement of σ⁵⁴ binding at putative sites identified by ChIP-seq in wild-type (MG1655; black bars) and Δ<i>rpoN</i> (RPB146; white bars) <i>E</i>. <i>coli</i> strains. The cognate promoter IDs and the fold above threshold (FAT; see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#sec018" target="_blank">Methods</a>) scores (Tables <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.t001" target="_blank">1</a> & <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.t002" target="_blank">2</a>) are indicated in parentheses and below the gene name, respectively. Gene names for “outside sense” (OS) and “outside antisense” (OA) binding sites correspond to the first gene downstream of the binding site (downstream relative to the orientation of the binding site). Gene names for “inside sense” (IS) and “inside antisense” (IA) binding sites correspond to the gene that contains the binding site. Occupancy units represent background-subtracted enrichment of target regions relative to a control region within the transcriptionally silent gene <i>bglB</i>. Error bars represent the standard deviation from three independent biological replicates. Significant differences between wild-type and Δ<i>rpoN</i> values are indicated (*<i>p</i> ≤ 0.05, **<i>p</i> ≤ 0.01, ***<i>p</i> ≤ 0.001). <b>(B)</b> Correlation of ChIP-qPCR and ChIP-seq data. Values obtained from ChIP-qPCR (occupancy units) and ChIP-seq (FAT) using the σ⁵⁴ antibody in <i>E</i>. <i>coli</i> were compared.</p

Conservation analysis of σ⁵⁴ binding sites.

<p>Heat-maps depicting the match to the σ⁵⁴ consensus binding site for each <b>(A)</b> canonical and <b>(B)</b> non-canonical σ⁵⁴ binding site across a range of bacterial species. Genera are listed across the top, binding site ID numbers, and fold above threshold (FAT) scores in parentheses are listed to the left of the heat-map. For σ⁵⁴ binding sites in panel A, the gene immediately downstream of each binding site is indicated to the right of the heat-map. <b>(C)</b> Comparison of the level of σ⁵⁴ binding, as indicated by FAT score (Tables <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.t001" target="_blank">1</a> & <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.t002" target="_blank">2</a>), versus Motif Score (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.s011" target="_blank">S5 Table</a>) for <i>E</i>. <i>coli</i> only. Different classes of binding site are indicated by color.</p

Genome-wide σ⁵⁴-dependent changes in gene expression.

<p>Relative RNA levels, determined by RNA-seq, for all genes in cells transiently overexpressing <i>rpoN</i> (MG1655 <i>ΔrpoN</i> + pRpoN; RPB149) or control cells containing empty vector (MG1655 <i>ΔrpoN</i> + pBAD24; RPB152). Relative RNA levels were calculated using Rockhopper [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005552#pgen.1005552.ref065" target="_blank">65</a>]. Each gene is indicated by a grey data point. Genes immediately downstream of intergenic σ⁵⁴ sites (blue), or genes containing intragenic σ⁵⁴ sites (red) are highlighted.</p