133 research outputs found
Role of Metalloproteases in the Release of the IL-1 type II Decoy Receptor
The IL-1 type II receptor (decoy RII) is a nonsignaling molecule the only established function of which is to capture IL-1 and prevent it from interacting with signaling receptor. The decoy RII is released in a regulated way from the cell surface. Here, we reported that hydroxamic acid inhibitors of matrix metalloproteases inhibit different pathways of decoy RII release, including the following: (a) the slow (18 h) gene expression-dependent release from monocytes and polymorphonuclear cells exposed to dexamethasone; (b) rapid release (minutes) from myelomonocytic cells exposed to tumor necrosis factor, chemoattractants, or phorbol myristate acetate; (c) phorbol myristate acetate-induced release from decoy RII-transfected fibroblasts and B cells. Inhibition of release was associated with increased surface expression of decoy RII. Inhibitors of other protease classes did not substantially affect release. However, serine protease inhibitors increased the molecular mass of the decoy RII released from polymorphonuclear cells from 45 to 60 kDa. Thus, irrespective of the pathway responsible for release and of the cellular context, matrix metalloproteases, rather than differential splicing, play a key role in production of soluble decoy RII
Phylogeography of Japanese encephalitis virus:genotype is associated with climate
The circulation of vector-borne zoonotic viruses is largely determined by the overlap in the geographical distributions of virus-competent vectors and reservoir hosts. What is less clear are the factors influencing the distribution of virus-specific lineages. Japanese encephalitis virus (JEV) is the most important etiologic agent of epidemic encephalitis worldwide, and is primarily maintained between vertebrate reservoir hosts (avian and swine) and culicine mosquitoes. There are five genotypes of JEV: GI-V. In recent years, GI has displaced GIII as the dominant JEV genotype and GV has re-emerged after almost 60 years of undetected virus circulation. JEV is found throughout most of Asia, extending from maritime Siberia in the north to Australia in the south, and as far as Pakistan to the west and Saipan to the east. Transmission of JEV in temperate zones is epidemic with the majority of cases occurring in summer months, while transmission in tropical zones is endemic and occurs year-round at lower rates. To test the hypothesis that viruses circulating in these two geographical zones are genetically distinct, we applied Bayesian phylogeographic, categorical data analysis and phylogeny-trait association test techniques to the largest JEV dataset compiled to date, representing the envelope (E) gene of 487 isolates collected from 12 countries over 75 years. We demonstrated that GIII and the recently emerged GI-b are temperate genotypes likely maintained year-round in northern latitudes, while GI-a and GII are tropical genotypes likely maintained primarily through mosquito-avian and mosquito-swine transmission cycles. This study represents a new paradigm directly linking viral molecular evolution and climate
Multi-Grid Monte Carlo via Embedding. II. Two-Dimensional Principal Chiral Model
We carry out a high-precision simulation of the two-dimensional
principal chiral model at correlation lengths up to ,
using a multi-grid Monte Carlo (MGMC) algorithm and approximately one year of
Cray C-90 CPU time. We extrapolate the finite-volume Monte Carlo data to
infinite volume using finite-size-scaling theory, and we discuss carefully the
systematic and statistical errors in this extrapolation. We then compare the
extrapolated data to the renormalization-group predictions. The deviation from
asymptotic scaling, which is at , decreases to
at . We also analyze the dynamic critical
behavior of the MGMC algorithm using lattices up to , finding
the dynamic critical exponent
(subjective 68% confidence interval). Thus, for this asymptotically free model,
critical slowing-down is greatly reduced compared to local algorithms, but not
completely eliminated.Comment: self-unpacking archive including .tex, .sty and .ps files; 126 pages
including all figure
Gravity, Lorentz Violation, and the Standard Model
The role of the gravitational sector in the Lorentz- and CPT-violating
Standard-Model Extension (SME) is studied. A framework is developed for
addressing this topic in the context of Riemann-Cartan spacetimes, which
include as limiting cases the usual Riemann and Minkowski geometries. The
methodology is first illustrated in the context of the QED extension in a
Riemann-Cartan background. The full SME in this background is then considered,
and the leading-order terms in the SME action involving operators of mass
dimension three and four are constructed. The incorporation of arbitrary
Lorentz and CPT violation into general relativity and other theories of gravity
based on Riemann-Cartan geometries is discussed. The dominant terms in the
effective low-energy action for the gravitational sector are provided, thereby
completing the formulation of the leading-order terms in the SME with gravity.
Explicit Lorentz symmetry breaking is found to be incompatible with generic
Riemann-Cartan geometries, but spontaneous Lorentz breaking evades this
difficulty.Comment: 21 pages REVTeX, references added, accepted in Physical Review
Low-dose rectal inoculation of rhesus macaques by SIVsmE660 or SIVmac251 recapitulates human mucosal infection by HIV-1
We recently developed a novel strategy to identify transmitted HIV-1 genomes in acutely infected humans using single-genome amplification and a model of random virus evolution. Here, we used this approach to determine the molecular features of simian immunodeficiency virus (SIV) transmission in 18 experimentally infected Indian rhesus macaques. Animals were inoculated intrarectally (i.r.) or intravenously (i.v.) with stocks of SIVmac251 or SIVsmE660 that exhibited sequence diversity typical of early-chronic HIV-1 infection. 987 full-length SIV env sequences (median of 48 per animal) were determined from plasma virion RNA 1–5 wk after infection. i.r. inoculation was followed by productive infection by one or a few viruses (median 1; range 1–5) that diversified randomly with near starlike phylogeny and a Poisson distribution of mutations. Consensus viral sequences from ramp-up and peak viremia were identical to viruses found in the inocula or differed from them by only one or a few nucleotides, providing direct evidence that early plasma viral sequences coalesce to transmitted/founder viruses. i.v. infection was >2,000-fold more efficient than i.r. infection, and viruses transmitted by either route represented the full genetic spectra of the inocula. These findings identify key similarities in mucosal transmission and early diversification between SIV and HIV-1, and thus validate the SIV–macaque mucosal infection model for HIV-1 vaccine and microbicide research
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
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 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
Using Non-Homogeneous Models of Nucleotide Substitution to Identify Host Shift Events: Application to the Origin of the 1918 ‘Spanish’ Influenza Pandemic Virus
Nonhomogeneous Markov models of nucleotide substitution have received scant attention. Here we explore the possibility of using nonhomogeneous models to identify host shift nodes along phylogenetic trees of pathogens evolving in different hosts. It has been noticed that influenza viruses show marked differences in nucleotide composition in human and avian hosts. We take advantage of this fact to identify the host shift event that led to the 1918 ‘Spanish’ influenza. This disease killed over 50 million people worldwide, ranking it as the deadliest pandemic in recorded history. Our model suggests that the eight RNA segments which eventually became the 1918 viral genome were introduced into a mammalian host around 1882–1913. The viruses later diverged into the classical swine and human H1N1 influenza lineages around 1913–1915. The last common ancestor of human strains dates from February 1917 to April 1918. Because pigs are more readily infected with avian influenza viruses than humans, it would seem that they were the original recipient of the virus. This would suggest that the virus was introduced into humans sometime between 1913 and 1918
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