Pahs, Ionized Gas, and Molecular Hydrogen in Brightest Cluster Galaxies of Cool Core Clusters of Galaxies

We present measurements of 5-25 {\mu}m emission features of brightest cluster galaxies (BCGs) with strong optical emission lines in a sample of 9 cool-core clusters of galaxies observed with the Infrared Spectrograph on board the Spitzer Space Telescope. These systems provide a view of dusty molecular gas and star formation, surrounded by dense, X-ray emitting intracluster gas. Past work has shown that BCGs in cool-core clusters may host powerful radio sources, luminous optical emission line systems, and excess UV, while BCGs in other clusters never show this activity. In this sample, we detect polycyclic aromatic hydrocarbons (PAHs), extremely luminous, rotationally-excited molecular hydrogen line emission, forbidden line emission from ionized gas ([Ne II] and [Ne III]), and infrared continuum emission from warm dust and cool stars. We show here that these BCGs exhibit more luminous forbidden neon and H2 rotational line emission than star-forming galaxies with similar total infrared luminosities, as well as somewhat higher ratios of 70 {\mu}m / 24 {\mu}m luminosities. Our analysis suggests that while star formation processes dominate the heating of the dust and PAHs, a heating process consistent with suprathermal electron heating from the hot gas, distinct from star formation, is heating the molecular gas and contributing to the heating of the ionized gas in the galaxies. The survival of PAHs and dust suggests that dusty gas is somehow shielded from significant interaction with the X-ray gas.Comment: 27 preprint pages, 18 figures, accepted by Astrophysical Journa

Linkage and related analyses of Barrett's esophagus and its associated adenocarcinomas

BACKGROUND: Familial aggregation and segregation analysis studies have provided evidence of a genetic basis for esophageal adenocarcinoma (EAC) and its premalignant precursor, Barrett's esophagus (BE). We aim to demonstrate the utility of linkage analysis to identify the genomic regions that might contain the genetic variants that predispose individuals to this complex trait (BE and EAC). METHODS: We genotyped 144 individuals in 42 multiplex pedigrees chosen from 1000 singly ascertained BE/EAC pedigrees, and performed both model‐based and model‐free linkage analyses, using S.A.G.E. and other software. Segregation models were fitted, from the data on both the 42 pedigrees and the 1000 pedigrees, to determine parameters for performing model‐based linkage analysis. Model‐based and model‐free linkage analyses were conducted in two sets of pedigrees: the 42 pedigrees and a subset of 18 pedigrees with female affected members that are expected to be more genetically homogeneous. Genome‐wide associations were also tested in these families. RESULTS: Linkage analyses on the 42 pedigrees identified several regions consistently suggestive of linkage by different linkage analysis methods on chromosomes 2q31, 12q23, and 4p14. A linkage on 15q26 is the only consistent linkage region identified in the 18 female‐affected pedigrees, in which the linkage signal is higher than in the 42 pedigrees. Other tentative linkage signals are also reported. CONCLUSION: Our linkage study of BE/EAC pedigrees identified linkage regions on chromosomes 2, 4, 12, and 15, with some reported associations located within our linkage peaks. Our linkage results can help prioritize association tests to delineate the genetic determinants underlying susceptibility to BE and EAC

Predicting Barrett's Esophagus in Families: An Esophagus Translational Research Network (BETRNet) Model Fitting Clinical Data to a Familial Paradigm

Barrett’s esophagus (BE) is often asymptomatic and only a small portion of BE patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with BE. Familial aggregation of BE and esophageal adenocarcinoma (EAC), and the increased risk of EAC for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well-developed

BVRI Light Curves for 29 Type Ia Supernovae

BVRI light curves are presented for 27 Type Ia supernovae discovered during the course of the Calan/Tololo Survey and for two other SNe Ia observed during the same period. Estimates of the maximum light magnitudes in the B, V, and I bands and the initial decline rate parameter m15(B) are also given.Comment: 17 pages, figures and tables are not included (contact first author if needed), to appear in the Astronomical Journa

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD

Formal and Informal Financing Decisions of Small Businesses

This study investigates small businesses’ financing decisions. Drawing upon asymmetric information theory, institutional theory and relevant literature on cognitive financial constraints, human capital and social capital, we propose a theoretical framework in which financing determinants come from three dimensions: entrepreneurs’ individual factors, organisational (firm-level) factors and contextual (institutional) factors. We employ this model to distinguish four types of firms: (1) firms that use no external finance, (2) firms that use informal finance only, (3) firms that use formal finance only and (4) firms that use both formal and informal finance. An empirical test on Vietnamese small businesses shows that factors from all three dimensions are important in understanding small businesses’ financing decisions

New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients

<p>Abstract</p> <p>Background</p> <p>Current practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.</p> <p>Methods</p> <p>We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.</p> <p>Results</p> <p>285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.</p> <p>Conclusion</p> <p>We present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets. </p

Genome Scan of M. tuberculosis Infection and Disease in Ugandans

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is an enduring public health problem globally, particularly in sub-Saharan Africa. Several studies have suggested a role for host genetic susceptibility in increased risk for TB but results across studies have been equivocal. As part of a household contact study of Mtb infection and disease in Kampala, Uganda, we have taken a unique approach to the study of genetic susceptibility to TB, by studying three phenotypes. First, we analyzed culture confirmed TB disease compared to latent Mtb infection (LTBI) or lack of Mtb infection. Second, we analyzed resistance to Mtb infection in the face of continuous exposure, defined by a persistently negative tuberculin skin test (PTST-); this outcome was contrasted to LTBI. Third, we analyzed an intermediate phenotype, tumor necrosis factor-alpha (TNFα) expression in response to soluble Mtb ligands enriched with molecules secreted from Mtb (culture filtrate). We conducted a full microsatellite genome scan, using genotypes generated by the Center for Medical Genetics at Marshfield. Multipoint model-free linkage analysis was conducted using an extension of the Haseman-Elston regression model that includes half sibling pairs, and HIV status was included as a covariate in the model. The analysis included 803 individuals from 193 pedigrees, comprising 258 full sibling pairs and 175 half sibling pairs. Suggestive linkage (p<10−3) was observed on chromosomes 2q21-2q24 and 5p13-5q22 for PTST-, and on chromosome 7p22-7p21 for TB; these findings for PTST- are novel and the chromosome 7 region contains the IL6 gene. In addition, we replicated recent linkage findings on chromosome 20q13 for TB (p = 0.002). We also observed linkage at the nominal α = 0.05 threshold to a number of promising candidate genes, SLC11A1 (PTST- p = 0.02), IL-1 complex (TB p = 0.01), IL12BR2 (TNFα p = 0.006), IL12A (TB p = 0.02) and IFNGR2 (TNFα p = 0.002). These results confirm not only that genetic factors influence the interaction between humans and Mtb but more importantly that they differ according to the outcome of that interaction: exposure but no infection, infection without progression to disease, or progression of infection to disease. Many of the genetic factors for each of these stages are part of the innate immune system