Effect of Layer-Stacking on the Electronic Structure of Graphene Nanoribbons

The evolution of electronic structure of graphene nanoribbons (GNRs) as a function of the number of layers stacked together is investigated using \textit{ab initio} density functional theory (DFT) including interlayer van der Waals interactions. Multilayer armchair GNRs (AGNRs), similar to single-layer AGNRs, exhibit three classes of band gaps depending on their width. In zigzag GNRs (ZGNRs), the geometry relaxation resulting from interlayer interactions plays a crucial role in determining the magnetic polarization and the band structure. The antiferromagnetic (AF) interlayer coupling is more stable compared to the ferromagnetic (FM) interlayer coupling. ZGNRs with the AF in-layer and AF interlayer coupling have a finite band gap while ZGNRs with the FM in-layer and AF interlayer coupling do not have a band gap. The ground state of the bi-layer ZGNR is non-magnetic with a small but finite band gap. The magnetic ordering is less stable in multilayer ZGNRs compared to single-layer ZGNRs. The quasipartcle GW corrections are smaller for bilayer GNRs compared to single-layer GNRs because of the reduced Coulomb effects in bilayer GNRs compared to single-layer GNRs.Comment: 10 pages, 5 figure

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

An Early-Time Infrared and Optical Study of the Type Ia Supernova 1998bu in M96

We present first-season infrared (IR) and optical photometry and spectroscopy of the Type Ia Supernova 1998bu in M96. We also report optical polarimetry of this event. SN1998bu is one of the closest type Ia Supernovae of modern times and the distance of its host galaxy is well-determined. We find that SN1998bu is both photometrically and spectroscopically normal. However, the extinction to this event is unusually high, with Av=1.0 +/-0.11. We find that SN1998bu peaked at an intrinsic Mv=-19.37 +/-0.23. Adopting a distance modulus of 30.25 (Tanvir et al. 1999) and using Phillips et al.'s (1999) relations for the Hubble constant we obtain Ho=70.4 +/-4.3 km/s/Mpc. Combination of our IR photometry with those of Jha et al. (1999) provides one of the most complete early-phase IR light curves for a SN Ia published so far. In particular, SN 1998bu is the first normal SN Ia for which good pre-maximum (in the B band) IR coverage has been obtained. It reveals that the J, H and K light curves peak about 5 days earlier than the flux in the B-band curve.Comment: 22 pages, 9 figues, accepted for publication by MNRA

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented

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

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

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

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