Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey II: Multiwavelength Classification

We describe the application of the `shapelet' linear decomposition of galaxy images to multi-wavelength morphological classification using the $u,g,r,i,$ and $z$-band images of 1519 galaxies from the Sloan Digital Sky Survey. We utilize elliptical shapelets to remove to first-order the effect of inclination on morphology. After decomposing the galaxies we perform a principal component analysis on the shapelet coefficients to reduce the dimensionality of the spectral morphological parameter space. We give a description of each of the first ten principal component's contribution to a galaxy's spectral morphology. We find that galaxies of different broad Hubble type separate cleanly in the principal component space. We apply a mixture of Gaussians model to the 2-dimensional space spanned by the first two principal components and use the results as a basis for classification. Using the mixture model, we separate galaxies into three classes and give a description of each class's physical and morphological properties. We find that the two dominant mixture model classes correspond to early and late type galaxies, respectively. The third class has, on average, a blue, extended core surrounded by a faint red halo, and typically exhibits some asymmetry. We compare our method to a simple cut on $u-r$ color and find the shapelet method to be superior in separating galaxies. Furthermore, we find evidence that the $u-r=2.22$ decision boundary may not be optimal for separation between early and late type galaxies, and suggest that the optimal cut may be $u-r \sim 2.4$.Comment: 42 pages, 18 figs, revised version in press at AJ. Some modification to the technique, more discussion, addition/deletion/modification of several figures, color figures have been added. A high resolution version may be obtained at http://bllac.as.arizona.edu/~bkelly/shapelets/shapelets_ugriz.ps.g

CD32-RNA Co-localizes with HIV-RNA in CD3+ Cells Found within Gut Tissues from Viremic and ART-Suppressed Individuals.

BackgroundIdentifying biomarkers for cells harboring replication-competent HIV is a major research priority. Recently, there have been mixed reports addressing the possibility that CD32-expressing T cells are enriched for HIV. There is growing evidence that CD32 expression increases with cellular activation that may be related to, but not necessarily specific for, infection with HIV. However, the relationship of CD32 expression to HIV-infection in subtypes of tissue-resident leukocytes is unclear.MethodsFirst, we used duplex chromogenic in situ hybridization to identify cells actively transcribing RNA for both CD32 and HIV on human gut tissues. Then we performed multiplexed immunofluorescence and in situ hybridization (mIFISH) on sections from the same tissues to determine the phenotype of individual cells co-expressing HIV-RNA and CD32-RNA.ResultsHIV-RNA+ cells were more abundant in tissues from viremic individuals than in those receiving suppressive anti-retroviral therapy (ART). However, staining by both methods indicated that a higher proportion of HIV-RNA+ cells co-expressed CD32-RNA in ART-suppressed individuals than in those with viremia. The majority of HIV-RNA+ cells were CD3+.ConclusionsOur data suggest that the transcription of CD32-RNA is correlated with HIV transcriptional activity in CD3+ cells found within human gut tissue. Whether or not up-regulation of CD32-RNA is a direct result of HIV transcription or more global T-cell activation remains unclear

Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey

We describe application of the `shapelet' linear decomposition of galaxy images to morphological classification using images of $\sim$ 3000 galaxies from the Sloan Digital Sky Survey. After decomposing the galaxies we perform a principal component analysis to reduce the number of dimensions of the shapelet space to nine. We find that each of these nine principal components contains unique morphological information, and give a description of each principal component's contribution to a galaxy's morphology. We find that galaxies of differing Hubble type separate cleanly in the shapelet space. We apply a Gaussian mixture model to the 9-dimensional space spanned by the principal components and use the results as a basis for classification. Using the mixture model, we separate galaxies into seven classes and give a description of each class's physical and morphological properties. We find that several of the mixture model classes correlate well with the traditional Hubble types both in their morphology and their physical parameters (e.g., color, velocity dispersions, etc.). In addition, we find an additional class of late-type morphology but with high velocity dispersions and very blue color; most of these galaxies exhibit post-starburst activity. This method provides an objective and quantitative alternative to traditional and subjective visual classification.Comment: 21 pages, 16 figures, accepted by AJ, minor changes per the referee's comment

Regulatory Approved Monoclonal Antibodies Contain Framework Mutations Predicted From Human Antibody Repertoires

Monoclonal antibodies (mAbs) are an important class of therapeutics used to treat cancer, inflammation, and infectious diseases. Identifying highly developable mAb sequences in silico could greatly reduce the time and cost required for therapeutic mAb development. Here, we present position-specific scoring matrices (PSSMs) for antibody framework mutations developed using baseline human antibody repertoire sequences. Our analysis shows that human antibody repertoire-based PSSMs are consistent across individuals and demonstrate high correlations between related germlines. We show that mutations in existing therapeutic antibodies can be accurately predicted solely from baseline human antibody sequence data. We find that mAbs developed using humanized mice had more human-like FR mutations than mAbs originally developed by hybridoma technology. A quantitative assessment of entire framework regions of therapeutic antibodies revealed that there may be potential for improving the properties of existing therapeutic antibodies by incorporating additional mutations of high frequency in baseline human antibody repertoires. In addition, high frequency mutations in baseline human antibody repertoires were predicted in silico to reduce immunogenicity in therapeutic mAbs due to the removal of T cell epitopes. Several therapeutic mAbs were identified to have common, universally high-scoring framework mutations, and molecular dynamics simulations revealed the mechanistic basis for the evolutionary selection of these mutations. Our results suggest that baseline human antibody repertoires may be useful as predictive tools to guide mAb development in the future. &nbsp;</p

Prostate cancer incidence across stage, NCCN risk groups, and age before and after USPSTF Grade D recommendations against prostateâ specific antigen screening in 2012

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153721/1/cncr32604.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153721/2/cncr32604_am.pd

ARC: A compact, high-field, fusion nuclear science facility and demonstration power plant with demountable magnets

The affordable, robust, compact (ARC) reactor is the product of a conceptual design study aimed at reducing the size, cost, and complexity of a combined fusion nuclear science facility (FNSF) and demonstration fusion Pilot power plant. ARC is a ∼200–250 MWe tokamak reactor with a major radius of 3.3 m, a minor radius of 1.1 m, and an on-axis magnetic field of 9.2 T. ARC has rare earth barium copper oxide (REBCO) superconducting toroidal field coils, which have joints to enable disassembly. This allows the vacuum vessel to be replaced quickly, mitigating first wall survivability concerns, and permits a single device to test many vacuum vessel designs and divertor materials. The design point has a plasma fusion gain of Q[subscript p] ≈ 13.6, yet is fully non-inductive, with a modest bootstrap fraction of only ∼63%. Thus ARC offers a high power gain with relatively large external control of the current profile. This highly attractive combination is enabled by the ∼23 T peak field on coil achievable with newly available REBCO superconductor technology. External current drive is provided by two innovative inboard RF launchers using 25 MW of lower hybrid and 13.6 MW of ion cyclotron fast wave power. The resulting efficient current drive provides a robust, steady state core plasma far from disruptive limits. ARC uses an all-liquid blanket, consisting of low pressure, slowly flowing fluorine lithium beryllium (FLiBe) molten salt. The liquid blanket is low-risk technology and provides effective neutron moderation and shielding, excellent heat removal, and a tritium breeding ratio ≥ 1.1. The large temperature range over which FLiBe is liquid permits an output blanket temperature of 900 K, single phase fluid cooling, and a high efficiency helium Brayton cycle, which allows for net electricity generation when operating ARC as a Pilot power plant.United States. Department of Energy (Grant DE-FG02-94ER54235)United States. Department of Energy (Grant DE-SC008435)United States. Department of Energy. Office of Fusion Energy Sciences (Grant DE-FC02-93ER54186)National Science Foundation (U.S.) (Grant 1122374

Conservative management of lowâ risk prostate cancer among young versus older men in the United States: Trends and outcomes from a novel national database

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151903/1/cncr32332.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151903/2/cncr32332_am.pd

Network Brain-Computer Interface (nBCI): An Alternative Approach for Cognitive Prosthetics

Brain computer interfaces (BCIs) have been applied to sensorimotor systems for many years. However, BCI technology has broad potential beyond sensorimotor systems. The emerging field of cognitive prosthetics, for example, promises to improve learning and memory for patients with cognitive impairment. Unfortunately, our understanding of the neural mechanisms underlying these cognitive processes remains limited in part due to the extensive individual variability in neural coding and circuit function. As a consequence, the development of methods to ascertain optimal control signals for cognitive decoding and restoration remains an active area of inquiry. To advance the field, robust tools are required to quantify time-varying and task-dependent brain states predictive of cognitive performance. Here, we suggest that network science is a natural language in which to formulate and apply such tools. In support of our argument, we offer a simple demonstration of the feasibility of a network approach to BCI control signals, which we refer to as network BCI (nBCI). Finally, in a single subject example, we show that nBCI can reliably predict online cognitive performance and is superior to certain common spectral approaches currently used in BCIs. Our review of the literature and preliminary findings support the notion that nBCI could provide a powerful approach for future applications in cognitive prosthetics

Genomic and clinical characterization of stromal infiltration markers in prostate cancer

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154519/1/cncr32688_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154519/2/cncr32688.pd

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy