XMM-Newton Archival Study of the ULX Population in Nearby Galaxies

We present the results of an archival XMM-Newton study of the bright X-ray point sources (L_X > 10^38 erg/s) in 32 nearby galaxies. From our list of approximately 100 point sources, we attempt to determine if there is a low-state counterpart to the Ultraluminous X-ray (ULX) population, searching for a soft-hard state dichotomy similar to that known for Galactic X-ray binaries and testing the specific predictions of the IMBH hypothesis. To this end, we searched for "low-state" objects, which we defined as objects within our sample which had a spectrum well fit by a simple absorbed power law, and "high-state" objects, which we defined as objects better fit by a combined blackbody and a power law. Assuming that ``low-state'' objects accrete at approximately 10% of the Eddington luminosity (Done & Gierlinski 2003) and that "high-state" objects accrete near the Eddington luminosity we further divided our sample of sources into low and high state ULX sources. We classify 16 sources as low-state ULXs and 26 objects as high-state ULXs. As in Galactic black hole systems, the spectral indices, Gamma, of the low-state objects, as well as the luminosities, tend to be lower than those of the high-state objects. The observed range of blackbody temperatures for the high state is 0.1-1 keV, with the most luminous systems tending toward the lowest temperatures. We therefore divide our high-state ULXs into candidate IMBHs (with blackbody temperatures of approximately 0.1 keV) and candidate stellar mass BHs (with blackbody temperatures of approximately 1.0 keV). A subset of the candidate stellar mass BHs have spectra that are well-fit by a Comptonization model, a property similar of Galactic BHs radiating in the "very-high" state near the Eddington limit.Comment: 54 pages, submitted to ApJ (March 2005), accepted (May 2006); changes to organization of pape

Elemental Abundances of Nearby Galaxies through High Signal-to-Noise XMM-Newton Observations of ULXs

(abridged) In this paper, we examined XMM Newton EPIC spectra of 14 ultra-luminous X-ray sources (ULXs)in addition to the XMM RGS spectra of two sources (Holmberg II X-1 and Holmberg IX X-1). We determined oxygen and iron abundances of the host galaxy's interstellar medium (ISM) using K-shell (O) and L-shell (Fe) X-ray photo-ionization edges towards these ULXs. We found that the oxygen abundances closely matched recent solar abundances for all of our sources, implying that ULXs live in similar local environments despite the wide range of galaxy host properties. Also, we compare the X-ray hydrogen column densities (n_H) for 8 ULX sources with column densities obtained from radio H I observations. The X-ray model n_H values are in good agreement with the H I n_H values, implying that the hydrogen absorption towards the ULXs is not local to the source (with the exception of the source M81 XMM1). In order to obtain the column density and abundance values, we fit the X-ray spectra of the ULXs with a combined power law and one of several accretion disk models. We tested the abundances obtained from the XSPEC models bbody, diskbb, grad, and diskpn along with a power law, finding that the abundances were independent of the thermal model used. We comment on the physical implications of these different model fits. We also note that very deep observations allow a breaking of the degeneracy noted by Stobbart et al. (2006) favoring a high mass solution for the absorbed grad + power law model.Comment: 18 pages, accepted to Ap

The Swift BAT-detected Seyfert 1 Galaxies: X-ray Broadband Properties and Warm Absorbers

We present results from an analysis of the broad-band, 0.3-195 keV, X-ray spectra of 48 Seyfert 1-1.5 sources detected in the very hard X-rays with the Swift Burst Alert Telescope (BAT). This sample is selected in an all-sky survey conducted in the 14-195 keV band. Therefore, our sources are largely unbiased towards both obscuration and host galaxy properties. Our detailed and uniform model fits to Suzaku/BAT and XMM-Newton/BAT spectra include the neutral absorption, direct power-law, reflected emission, soft excess, warm absorption, and narrow Fe K-alpha emission properties for the entire sample. We significantly detect O VII and O VIII edges in 52% of our sample. The strength of these detections are strongly correlated with the neutral column density measured in the spectrum. Among the strongest detections, X-ray grating and UV observations, where available, indicate outflowing material. The ionized column densities of sources with O VII and O VIII detections are clustered in a narrow range with N$_{\rm warm} \sim 10^{21}$\,cm$^{-2}$, while sources without strong detections have column densities of ionized gas an order of magnitude lower. Therefore, we note that sources without strong detections likely have warm ionized outflows present but at low column densities that are not easily probed with current X-ray observations. Sources with strong complex absorption have a strong soft excess, which may or may not be due to difficulties in modeling the complex spectra of these sources. Still, the detection of a flat Gamma ~ 1 and a strong soft excess may allow us to infer the presence of strong absorption in low signal-to-noise AGN spectra. Additionally, we include a useful correction from the Swift BAT luminosity to bolometric luminosity, based on a comparison of our spectral fitting results with published spectral energy distribution fits from 33 of our sources.Comment: 60 pages (pre-print format), 14 figures, accepted to Ap

Fighting the flinch : experimentally induced compassion makes a difference in healthcare providers

Objectives: Although healthcare providers are required to sustain care in difficult circumstances, some patients challenge this principle. Evoking compassion seems likely to be helpful in such situations. This research aimed to evaluate whether inducing compassion in healthcare providers might mitigate disengagement with patients who have challenging presenting features such as those with disgusting symptoms and/or are to blame for their own health problems. Design: An online experimental study with clinical healthcare providers. Methods: Medical students (n=219) and qualified healthcare professionals (n=108) took part in an online experiment. Participants were randomised to view a slideshow of either neutral images (control) or compassion-inducing images (compassion condition) and were then presented with a series of patient vignettes where presenting problems systematically varied on patient responsibility and disgusting symptoms. Engagement was assessed by asking participants how caring they felt, how much they would want to help, how challenging it would be, and whether they would wear a mask. Results: Participants reported less engagement with patients who were responsible for their illness and who presented with disgusting symptoms. Induced compassion offset disengagement and qualified health professionals were more caring and willing to help patients than medical students. The compassion induction eliminated some differences between experienced and trainee clinicians. Conclusions: This research demonstrates that disgust and patient responsibility impacts clinical engagement and that medical students are more impacted by such scenarios than qualified health providers. Inducing compassion may help to mitigate these differences and further investigation into strategies that foster engagement with difficult patients is warranted

Drug Adverse Event Detection in Health Plan Data Using the Gamma Poisson Shrinker and Comparison to the Tree-based Scan Statistic

Background: Drug adverse event (AE) signal detection using the Gamma Poisson Shrinker (GPS) is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan). Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds

Structure-Activity Studies Of 7-Heteroaryl-3-Azabicyclo[3.3.1]Non-6-Enes: A Novel Class Of Highly Potent Nicotinic Receptor Ligands

The potential for nicotinic ligands with affinity for the α4β2 or α7 subtypes to treat such diverse diseases as nicotine addiction, neuropathic pain, and neurodegenerative and cognitive disorders has been exhibited clinically for several compounds while preclinical activity in relevant in vivo models has been demonstrated for many more. For several therapeutic programs, we sought nicotinic ligands with various combinations of affinity and function across both subtypes, with an emphasis on dual α4β2-α7 ligands, to explore the possibility of synergistic effects. We report here the structure-activity relationships (SAR) for a novel series of 7-heteroaryl-3-azabicyclo[3.3.1]non-6-enes and characterize many of the analogues for activity at multiple nicotinic subtypes. © 2012 American Chemical Society

Epigenetic alterations differ in phenotypically distinct human neuroblastoma cell lines

<p>Abstract</p> <p>Background</p> <p>Epigenetic aberrations and a CpG island methylator phenotype have been shown to be associated with poor outcomes in children with neuroblastoma (NB). Seven cancer related genes (<it>THBS-1, CASP8, HIN-1, TIG-1, BLU, SPARC</it>, and <it>HIC-1</it>) that have been shown to have epigenetic changes in adult cancers and play important roles in the regulation of angiogenesis, tumor growth, and apoptosis were analyzed to investigate the role epigenetic alterations play in determining NB phenotype.</p> <p>Methods</p> <p>Two NB cell lines (tumorigenic LA1-55n and non-tumorigenic LA1-5s) that differ in their ability to form colonies in soft agar and tumors in nude mice were used. Quantitative RNA expression analyses were performed on seven genes in LA1-5s, LA1-55n and 5-Aza-dC treated LA1-55n NB cell lines. The methylation status around <it>THBS-1, HIN-1, TIG-1 </it>and <it>CASP8 </it>promoters was examined using methylation specific PCR. Chromatin immunoprecipitation assay was used to examine histone modifications along the <it>THBS-1 </it>promoter. Luciferase assay was used to determine <it>THBS-1 </it>promoter activity. Cell proliferation assay was used to examine the effect of 5-Aza-dC on NB cell growth. The soft agar assay was used to determine the tumorigenicity.</p> <p>Results</p> <p>Promoter methylation values for <it>THBS-1</it>, <it>HIN-1</it>, <it>TIG-1</it>, and <it>CASP8 </it>were higher in LA1-55n cells compared to LA1-5s cells. Consistent with the promoter methylation status, lower levels of gene expression were detected in the LA1-55n cells. Histone marks associated with repressive chromatin states (H3K9Me3, H3K27Me3, and H3K4Me3) were identified in the <it>THBS-1 </it>promoter region in the LA1-55n cells, but not the LA1-5s cells. In contrast, the three histone codes associated with an active chromatin state (acetyl H3, acetyl H4, and H3K4Me3) were present in the <it>THBS-1 </it>promoter region in LA1-5s cells, but not the LA1-55n cells, suggesting that an accessible chromatin structure is important for <it>THBS-1 </it>expression. We also show that 5-Aza-dC treatment of LA1-55n cells alters the DNA methylation status and the histone code in the <it>THBS-1 </it>promoter modifies cell morphology, and inhibits their ability to form colonies in soft agar.</p> <p>Conclusion</p> <p>Our results suggest that epigenetic aberrations contribute to NB phenotype, and that tumorigenic properties can be inhibited by reversing the epigenetic changes with 5-Aza-dC.</p

The molecular portraits of breast tumors are conserved acress microarray platforms

Background Validation of a novel gene expression signature in independent data sets is a critical step in the development of a clinically useful test for cancer patient risk-stratification. However, validation is often unconvincing because the size of the test set is typically small. To overcome this problem we used publicly available breast cancer gene expression data sets and a novel approach to data fusion, in order to validate a new breast tumor intrinsic list. Results A 105-tumor training set containing 26 sample pairs was used to derive a new breast tumor intrinsic gene list. This intrinsic list contained 1300 genes and a proliferation signature that was not present in previous breast intrinsic gene sets. We tested this list as a survival predictor on a data set of 311 tumors compiled from three independent microarray studies that were fused into a single data set using Distance Weighted Discrimination. When the new intrinsic gene set was used to hierarchically cluster this combined test set, tumors were grouped into LumA, LumB, Basal-like, HER2+/ER-, and Normal Breast-like tumor subtypes that we demonstrated in previous datasets. These subtypes were associated with significant differences in Relapse-Free and Overall Survival. Multivariate Cox analysis of the combined test set showed that the intrinsic subtype classifications added significant prognostic information that was independent of standard clinical predictors. From the combined test set, we developed an objective and unchanging classifier based upon five intrinsic subtype mean expression profiles (i.e. centroids), which is designed for single sample predictions (SSP). The SSP approach was applied to two additional independent data sets and consistently predicted survival in both systemically treated and untreated patient groups. Conclusion This study validates the breast tumor intrinsic subtype classification as an objective means of tumor classification that should be translated into a clinical assay for further retrospective and prospective validation. In addition, our method of combining existing data sets can be used to robustly validate the potential clinical value of any new gene expression profile

The molecular portraits of breast tumors are conserved across microarray platforms

BACKGROUND: Validation of a novel gene expression signature in independent data sets is a critical step in the development of a clinically useful test for cancer patient risk-stratification. However, validation is often unconvincing because the size of the test set is typically small. To overcome this problem we used publicly available breast cancer gene expression data sets and a novel approach to data fusion, in order to validate a new breast tumor intrinsic list. RESULTS: A 105-tumor training set containing 26 sample pairs was used to derive a new breast tumor intrinsic gene list. This intrinsic list contained 1300 genes and a proliferation signature that was not present in previous breast intrinsic gene sets. We tested this list as a survival predictor on a data set of 311 tumors compiled from three independent microarray studies that were fused into a single data set using Distance Weighted Discrimination. When the new intrinsic gene set was used to hierarchically cluster this combined test set, tumors were grouped into LumA, LumB, Basal-like, HER2+/ER-, and Normal Breast-like tumor subtypes that we demonstrated in previous datasets. These subtypes were associated with significant differences in Relapse-Free and Overall Survival. Multivariate Cox analysis of the combined test set showed that the intrinsic subtype classifications added significant prognostic information that was independent of standard clinical predictors. From the combined test set, we developed an objective and unchanging classifier based upon five intrinsic subtype mean expression profiles (i.e. centroids), which is designed for single sample predictions (SSP). The SSP approach was applied to two additional independent data sets and consistently predicted survival in both systemically treated and untreated patient groups. CONCLUSION: This study validates the "breast tumor intrinsic" subtype classification as an objective means of tumor classification that should be translated into a clinical assay for further retrospective and prospective validation. In addition, our method of combining existing data sets can be used to robustly validate the potential clinical value of any new gene expression profile