Galactic and Extragalactic Samples of Supernova Remnants: How They Are Identified and What They Tell Us

Supernova remnants (SNRs) arise from the interaction between the ejecta of a supernova (SN) explosion and the surrounding circumstellar and interstellar medium. Some SNRs, mostly nearby SNRs, can be studied in great detail. However, to understand SNRs as a whole, large samples of SNRs must be assembled and studied. Here, we describe the radio, optical, and X-ray techniques which have been used to identify and characterize almost 300 Galactic SNRs and more than 1200 extragalactic SNRs. We then discuss which types of SNRs are being found and which are not. We examine the degree to which the luminosity functions, surface-brightness distributions and multi-wavelength comparisons of the samples can be interpreted to determine the class properties of SNRs and describe efforts to establish the type of SN explosion associated with a SNR. We conclude that in order to better understand the class properties of SNRs, it is more important to study (and obtain additional data on) the SNRs in galaxies with extant samples at multiple wavelength bands than it is to obtain samples of SNRs in other galaxiesComment: Final 2016 draft of a chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin. Final version available at https://doi.org/10.1007/978-3-319-20794-0_90-

Transformation and scattering activities of the receptor tyrosine kinase RON/Stk in rodent fibroblasts and lack of regulation by the jaagsiekte sheep retrovirus receptor, Hyal2

BACKGROUND: The envelope (Env) protein of jaagsiekte sheep retrovirus (JSRV) can transform cells in culture and is likely to be the main factor responsible for lung cancer induction by JSRV in animals. A recent report indicates that the epithelial-cell transforming activity of JSRV Env depends on activation of the cell-surface receptor tyrosine kinase Mst1r (called RON for the human and Stk for the rodent orthologs). In the immortalized line of human epithelial cells used (BEAS-2B cells), the virus receptor Hyal2 was found to bind to and suppress the activity of RON. When Env was expressed it bound to Hyal2 causing its degradation, release of RON activity from Hyal2 suppression, and activation of pathways resulting in cell transformation. METHODS: Due to difficulty with reproducibility of the transformation assay in BEAS-2B cells, we have used more tractable rodent fibroblast models to further study Hyal2 modulation of RON/Stk transforming activity and potential effects of Hyal2 on RON/Stk activation by its natural ligand, macrophage stimulating protein (MSP). RESULTS: We did not detect transformation of NIH 3T3 cells by plasmids expressing RON or Stk, but did detect transformation of 208F rat fibroblasts by these plasmids at a very low rate. We were able to isolate 208F cell clones that expressed RON or Stk and that showed changes in morphology indicative of transformation. The parental 208F cells did not respond to MSP but 208F cells expressing RON or Stk showed obvious increases in scattering/transformation in response to MSP. Human Hyal2 had no effect on the basal or MSP-induced phenotypes of RON-expressing 208F cells, and human, mouse or rat Hyal2 had no effect on the basal or MSP-induced phenotypes of Stk-expressing 208F cells. CONCLUSIONS: We have shown that RON or Stk expression in 208F rat fibroblasts results in a transformed phenotype that is enhanced by addition of the natural ligand for these proteins, MSP. Hyal2 does not directly modulate the basal or MSP-induced RON/Stk activity, although it is possible that adaptor proteins might mediate such signaling in other cell types

Gene Expression Variability within and between Human Populations and Implications toward Disease Susceptibility

Variations in gene expression level might lead to phenotypic diversity across individuals or populations. Although many human genes are found to have differential mRNA levels between populations, the extent of gene expression that could vary within and between populations largely remains elusive. To investigate the dynamic range of gene expression, we analyzed the expression variability of ∼18, 000 human genes across individuals within HapMap populations. Although ∼20% of human genes show differentiated mRNA levels between populations, our results show that expression variability of most human genes in one population is not significantly deviant from another population, except for a small fraction that do show substantially higher expression variability in a particular population. By associating expression variability with sequence polymorphism, intriguingly, we found SNPs in the untranslated regions (5′ and 3′UTRs) of these variable genes show consistently elevated population heterozygosity. We performed differential expression analysis on a genome-wide scale, and found substantially reduced expression variability for a large number of genes, prohibiting them from being differentially expressed between populations. Functional analysis revealed that genes with the greatest within-population expression variability are significantly enriched for chemokine signaling in HIV-1 infection, and for HIV-interacting proteins that control viral entry, replication, and propagation. This observation combined with the finding that known human HIV host factors show substantially elevated expression variability, collectively suggest that gene expression variability might explain differential HIV susceptibility across individuals

Target Gene Analysis by Microarrays and Chromatin Immunoprecipitation Identifies HEY Proteins as Highly Redundant bHLH Repressors

HEY bHLH transcription factors have been shown to regulate multiple key steps in cardiovascular development. They can be induced by activated NOTCH receptors, but other upstream stimuli mediated by TGFß and BMP receptors may elicit a similar response. While the basic and helix-loop-helix domains exhibit strong similarity, large parts of the proteins are still unique and may serve divergent functions. The striking overlap of cardiac defects in HEY2 and combined HEY1/HEYL knockout mice suggested that all three HEY genes fulfill overlapping function in target cells. We therefore sought to identify target genes for HEY proteins by microarray expression and ChIPseq analyses in HEK293 cells, cardiomyocytes, and murine hearts. HEY proteins were found to modulate expression of their target gene to a rather limited extent, but with striking functional interchangeability between HEY factors. Chromatin immunoprecipitation revealed a much greater number of potential binding sites that again largely overlap between HEY factors. Binding sites are clustered in the proximal promoter region especially of transcriptional regulators or developmental control genes. Multiple lines of evidence suggest that HEY proteins primarily act as direct transcriptional repressors, while gene activation seems to be due to secondary or indirect effects. Mutagenesis of putative DNA binding residues supports the notion of direct DNA binding. While class B E-box sequences (CACGYG) clearly represent preferred target sequences, there must be additional and more loosely defined modes of DNA binding since many of the target promoters that are efficiently bound by HEY proteins do not contain an E-box motif. These data clearly establish the three HEY bHLH factors as highly redundant transcriptional repressors in vitro and in vivo, which explains the combinatorial action observed in different tissues with overlapping expression

Electrophysiological correlates of associative learning in smokers: a higher-order conditioning experiment

Background: Classical conditioning has been suggested to play an important role in the development, maintenance, and relapse of tobacco smoking. Several studies have shown that initially neutral stimuli that are directly paired with smoking are able to elicit conditioned responses. However, there have been few human studies that demonstrate the contribution of higher-order conditioning to smoking addiction, although it is assumed that higher-order conditioning predominates learning in the outside world. In the present study a higher-order conditioning task was designed in which brain responses of smokers and non-smokers were conditioned by pairing smoking-related and neutral stimuli (CS1smokeand CS1neutral) with two geometrical figures (CS2smokeand CS2neutral). ERPs were recorded to all CSs.Results: Data showed that the geometrical figure that was paired with smoking stimuli elicited significantly larger P2 and P3 waves than the geometrical figure that was paired with neutral stimuli. During the first half of the experiment this effect was only present in smokers whereas non-smokers displayed no significant differences between both stimuli, indicating that neutral cues paired with motivationally relevant smoking-related stimuli gain more motivational significance even though they were never paired directly with smoking. These conclusions are underscored by self-reported evidence of enhanced second-order conditioning in smokers.Conclusions: It can be concluded that smokers show associative learning for higher-order smoking-related stimuli. The present study directly shows the contribution of higher-order conditioning to smoking addiction and is the first to reveal its electrophysiological correlates. Although results are preliminary, they may help in understanding the etiology of smoking addiction and its persistence

14-3-3 Mediates Histone Cross-Talk during Transcription Elongation in Drosophila

Post-translational modifications of histone proteins modulate the binding of transcription regulators to chromatin. Studies in Drosophila have shown that the phosphorylation of histone H3 at Ser10 (H3S10ph) by JIL-1 is required specifically during early transcription elongation. 14-3-3 proteins bind H3 only when phosphorylated, providing mechanistic insights into the role of H3S10ph in transcription. Findings presented here show that 14-3-3 functions downstream of H3S10ph during transcription elongation. 14-3-3 proteins localize to active genes in a JIL-1–dependent manner. In the absence of 14-3-3, levels of actively elongating RNA polymerase II are severely diminished. 14-3-3 proteins interact with Elongator protein 3 (Elp3), an acetyltransferase that functions during transcription elongation. JIL-1 and 14-3-3 are required for Elp3 binding to chromatin, and in the absence of either protein, levels of H3K9 acetylation are significantly reduced. These results suggest that 14-3-3 proteins mediate cross-talk between histone phosphorylation and acetylation at a critical step in transcription elongation

The relationships between workaholism and symptoms of psychiatric disorders: a large-scale cross-sectional study

Despite the many number of studies examining workaholism, large-scale studies have been lacking. The present study utilized an open web-based cross-sectional survey assessing symptoms of psychiatric disorders and workaholism among 16,426 workers (Mage = 37.3 years, SD = 11.4, range = 16–75 years). Participants were administered the Adult ADHD Self-Report Scale, the Obsession-Compulsive Inventory-Revised, the Hospital Anxiety and Depression Scale, and the Bergen Work Addiction Scale, along with additional questions examining demographic and work-related variables. Correlations between workaholism and all psychiatric disorder symptoms were positive and significant. Workaholism comprised the dependent variable in a three-step linear multiple hierarchical regression analysis. Basic demographics (age, gender, relationship status, and education) explained 1.2% of the variance in workaholism, whereas work demographics (work status, position, sector, and annual income) explained an additional 5.4% of the variance. Age (inversely) and managerial positions (positively) were of most importance. The psychiatric symptoms (ADHD, OCD, anxiety, and depression) explained 17.0% of the variance. ADHD and anxiety contributed considerably. The prevalence rate of workaholism status was 7.8% of the present sample. In an adjusted logistic regression analysis, all psychiatric symptoms were positively associated with being a workaholic. The independent variables explained between 6.1% and 14.4% in total of the variance in workaholism cases. Although most effect sizes were relatively small, the study’s findings expand our understanding of possible psychiatric predictors of workaholism, and particularly shed new insight into the reality of adult ADHD in work life. The study’s implications, strengths, and shortcomings are also discussed