Bostonia: The Boston University Alumni Magazine. Volume 33

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs

SN 2006bp: Probing the Shock Breakout of a Type II-P Supernova

HET optical spectroscopy and unfiltered ROTSE-III photometry spanning the first 11 months since explosion of the Type II-P SN 2006bp are presented. Flux limits from the days before discovery combined with the initial rapid brightening suggest the supernova was first detected just hours after shock breakout. Optical spectra obtained about 2 days after breakout exhibit narrow emission lines corresponding to HeII 4200, HeII 4686, and CIV 5805 in the rest frame, and these features persist in a second observation obtained 5 hours later; however, these emission lines are not detected the following night nor in subsequent observations. We suggest that these lines emanate from material close to the explosion site, possibly in the outer layers of the progenitor that have been ionized by the high energy photons released at shock breakout. A P-Cygni profile is observed around 4450 A in the +2 and +3 day spectra. Previous studies have attributed this feature to high velocity H-beta, but we discuss the possibility that this profile is instead due to HeII 4687. Further HET observations (14 nights in total) covering the spectral evolution across the photometric plateau up to 73 days after breakout and during the nebular phase around day +340 are presented, and expansion velocities are derived for key features. The measured decay slope for the unfiltered light curve is 0.0073 +/- 0.0004 mag/day between days +121 and +335, which is significantly slower than the decay of rate 56Co. We combine our HET measurements with published X-ray, UV, and optical data to obtain a quasi-bolometric light curve through day +60. We see a slow cooling over the first 25 days, but no sign of an early sharp peak; any such feature from the shock breakout must have lasted less than ~1 day.[ABRIDGED]Comment: ApJ accepted, 43 page

Extensive Liquid Meltwater Storage in Firn Within the Greenland Ice Sheet

The accelerating loss of mass from the Greenland ice sheet is a major contribution to current sea level rise. Increased melt water runoff is responsible for half of Greenlands mass loss increase. Surface melt has been increasing in extent and intensity, setting a record for surface area melt and runoff in 2012. The mechanisms and timescales involved in allowing surface melt water to reach the ocean where it can contribute to sea level rise are poorly understood. The potential capacity to store this water in liquid or frozen form in the firn (multi-year snow layer) is significant, and could delay its sea-level contribution. Here we describe direct observation of water within a perennial firn aquifer persisting throughout the winter in the southern ice sheet,where snow accumulation and melt rates are high. This represents a previously unknown storagemode for water within the ice sheet. Ice cores, groundairborne radar and a regional climatemodel are used to estimate aquifer area (70 plue or minus 10 x 10(exp 3) square kilometers ) and water table depth (5-50 m). The perennial firn aquifer represents a new glacier facies to be considered 29 in future ice sheet mass 30 and energy budget calculations

Molecular epidemiological analysis of Escherichia coli sequence type ST131 (O25:H4) and bla CTX-M-15among extended-spectrum-β- lactamase-producing E. coli from the United States, 2000 to 2009

Escherichia coli sequence type ST131 (from phylogenetic group B2), often carrying the extended-spectrum-β-lactamase (ESBL) gene bla , is an emerging globally disseminated pathogen that has received comparatively little attention in the United States. Accordingly, a convenience sample of 351 ESBL-producing E. coli isolates from 15 U.S. centers (collected in 2000 to 2009) underwent PCR-based phylotyping and detection of ST131 and bla . A total of 200 isolates, comprising 4 groups of 50 isolates each that were (i) bla negative non-ST131, (ii) bla positive non-ST131, (iii) bla negative ST131, or (iv) bla positive ST131, also underwent virulence genotyping, antimicrobial susceptibility testing, and pulsed-field gel electrophoresis (PFGE). Overall, 201 (57%) isolates exhibited bla , whereas 165 (47%) were ST131. ST131 accounted for 56% of bla -positive-versus 35% of bla -negative isolates (

Accuracy of methods for detecting an irregular pulse and suspected atrial fibrillation: A systematic review and meta-analysis

Background: Pulse palpation has been recommended as the first step of screening to detect atrial fibrillation. We aimed to determine and compare the accuracy of different methods for detecting pulse irregularities caused by atrial fibrillation. Methods: We systematically searched MEDLINE, EMBASE, CINAHL and LILACS until 16 March 2015. Two reviewers identified eligible studies, extracted data and appraised quality using the QUADAS-2 instrument. Meta-analysis, using the bivariate hierarchical random effects method, determined average operating points for sensitivities, specificities, positive and negative likelihood ratios (PLR, NLR); we constructed summary receiver operating characteristic plots. Results: Twenty-one studies investigated 39 interventions (n = 15,129 pulse assessments) for detecting atrial fibrillation. Compared to 12-lead electrocardiography (ECG) diagnosed atrial fibrillation, blood pressure monitors (BPMs; seven interventions) and non-12-lead ECGs (20 interventions) had the greatest accuracy for detecting pulse irregularities attributable to atrial fibrillation (BPM: sensitivity 0.98 (95% confidence interval (CI) 0.92–1.00), specificity 0.92 (95% CI 0.88–0.95), PLR 12.1 (95% CI 8.2–17.8) and NLR 0.02 (95% CI 0.00–0.09); non-12-lead ECG: sensitivity 0.91 (95% CI 0.86–0.94), specificity 0.95 (95% CI 0.92–0.97), PLR 20.1 (95% CI 12–33.7), NLR 0.09 (95% CI 0.06–0.14)). There were similar findings for smartphone applications (six interventions) although these studies were small in size. The sensitivity and specificity of pulse palpation (six interventions) were 0.92 (95% CI 0.85–0.96) and 0.82 (95% CI 0.76–0.88), respectively (PLR 5.2 (95% CI 3.8–7.2), NLR 0.1 (95% CI 0.05–0.18)). Conclusions: BPMs and non-12-lead ECG were most accurate for detecting pulse irregularities caused by atrial fibrillation; other technologies may therefore be pragmatic alternatives to pulse palpation for the first step of atrial fibrillation screening

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment