Mn3O4-Graphene Hybrid as a High Capacity Anode Material for Lithium Ion Batteries

We developed two-step solution-phase reactions to form hybrid materials of Mn3O4 nanoparticles on reduced graphene oxide (RGO) sheets for lithium ion battery applications. Mn3O4 nanoparticles grown selectively on RGO sheets over free particle growth in solution allowed for the electrically insulating Mn3O4 nanoparticles wired up to a current collector through the underlying conducting graphene network. The Mn3O4 nanoparticles formed on RGO show a high specific capacity up to ~900mAh/g near its theoretical capacity with good rate capability and cycling stability, owing to the intimate interactions between the graphene substrates and the Mn3O4 nanoparticles grown atop. The Mn3O4/RGO hybrid could be a promising candidate material for high-capacity, low-cost, and environmentally friendly anode for lithium ion batteries. Our growth-on-graphene approach should offer a new technique for design and synthesis of battery electrodes based on highly insulating materials.Comment: JACS in pres

Radio and mid-infrared identification of BLAST source counterparts in the Chandra Deep Field South

We have identified radio and/or mid-infrared counterparts to 198 out of 350 sources detected at >=5 sigma over ~ 9 square degrees centered on the Chandra Deep Field South (CDFS) by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST) at 250, 350 and 500 um. We have matched 114 of these counterparts to optical sources with previously derived photometric redshifts and fitted SEDs to the BLAST fluxes and fluxes at 70 and 160 um acquired with the Spitzer Space Telescope. In this way, we have constrained dust temperatures, total far-infrared/sub-millimeter luminosities and star formation rates for each source. Our findings show that on average, the BLAST sources lie at significantly lower redshifts and have significantly lower rest-frame dust temperatures compared to submm sources detected in surveys conducted at 850 um. We demonstrate that an apparent increase in dust temperature with redshift in our sample arises as a result of selection effects. Finally, we provide the full multi-wavelength catalog of >= 5 sigma BLAST sources contained within the complete ~ 9 square degree survey area.Comment: Published in the Astrophysical Journal: 2009, ApJ, 703, 285. 23 pages, 13 figures. Data available at http://blastexperiment.inf

Graphene-Wrapped Sulfur Particles as a Rechargeable Lithium-Sulfur-Battery Cathode Material with High Capacity and Cycling Stability

We report the synthesis of a graphene-sulfur composite material by wrapping polyethyleneglycol (PEG) coated submicron sulfur particles with mildly oxidized graphene oxide sheets decorated by carbon black nanoparticles. The PEG and graphene coating layers are important to accommodating volume expansion of the coated sulfur particles during discharge, trapping soluble polysulfide intermediates and rendering the sulfur particles electrically conducting. The resulting graphene-sulfur composite showed high and stable specific capacities up to ~600mAh/g over more than 100 cycles, representing a promising cathode material for rechargeable lithium batteries with high energy density.Comment: published in Nano Letter

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

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

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