842 research outputs found
p21-Activated Kinase 3 (PAK3) Is an AP-1 Regulated Gene Contributing to Actin Organisation and Migration of Transformed Fibroblasts
Activating Protein 1 (AP-1) plays a vital role in cell proliferation, differentiation and apoptosis. While de-regulation of AP-1 has been linked to many cancers, little is known regarding its downstream transcriptional targets that associate with cellular transformation. Previous studies identified PAK3, a serine/threonine kinase, as a potential AP-1 target gene. PAK3 has been implicated in a variety of pathological disorders and over-expression of other PAK-family members has been linked to cancer. In this study, we investigate AP-1 regulation of PAK3 expression and the role of PAK3 in cJun/AP-1-associated cellular transformation. Our results showed elevated PAK3 expression at both the mRNA and protein level in cJun-over-expressing Rat1a fibroblasts, as well as in transformed human fibroblasts. Elevated PAK3 expression in cJun/AP-1 over-expressing cells associated with a significant increase in PAK3 promoter activation. This increased promoter activity was lost when a single putative Jun binding site, which can bind AP-1 directly both in vitro and in vivo, was mutated. Further, inhibition of PAK3 using siRNA showed a regression in the cell morphology, migratory potential and actin organisation associated with AP-1 transformed cells. Our study is a first to describe a role for AP-1 in regulating PAK3 expression and suggest that PAK3 is an AP-1 target required for actin organization and migration observed in transformed cells
Developing a Qualia-Based Multi-Agent Architecture for Use in Malware Detection
Detecting network intruders and malicious software is a significant problem for network administrators and security experts. New threats are emerging at an increasing rate, and current signature and statistics-based techniques are not keeping pace. Intelligent systems that can adapt to new threats are needed to mitigate these new strains of malware as they are released. This research detects malware based on its qualia, or essence rather than its low-level implementation details. By looking for the underlying concepts that make a piece of software malicious, this research avoids the pitfalls of static solutions that focus on predefined bit sequence signatures or anomaly thresholds. This research develops a novel, hierarchical modeling method to represent a computing system and demonstrates the representation’s effectiveness by modeling the Blaster worm. Using Latent Dirichlet Allocation and Support Vector Machines abstract concepts are automatically generated that can be used in the hierarchical model for malware detection. Finally, the research outlines a novel system that uses multiple levels of individual software agents that sharing contextual relationships and information across different levels of abstraction to make decisions. This qualia-based system provides a framework for developing intelligent classification and decision-making systems for a number of application areas
H0LiCOW XII. Lens mass model of WFI2033-4723 and blind measurement of its time-delay distance and
We present the lens mass model of the quadruply-imaged gravitationally lensed
quasar WFI2033-4723, and perform a blind cosmographical analysis based on this
system. Our analysis combines (1) time-delay measurements from 14 years of data
obtained by the COSmological MOnitoring of GRAvItational Lenses (COSMOGRAIL)
collaboration, (2) high-resolution imaging,
(3) a measurement of the velocity dispersion of the lens galaxy based on
ESO-MUSE data, and (4) multi-band, wide-field imaging and spectroscopy
characterizing the lens environment. We account for all known sources of
systematics, including the influence of nearby perturbers and complex
line-of-sight structure, as well as the parametrization of the light and mass
profiles of the lensing galaxy. After unblinding, we determine the effective
time-delay distance to be , an average
precision of . This translates to a Hubble constant , assuming a flat CDM
cosmology with a uniform prior on in the range [0.05, 0.5].
This work is part of the Lenses in COSMOGRAIL's Wellspring (H0LiCOW)
collaboration, and the full time-delay cosmography results from a total of six
strongly lensed systems are presented in a companion paper (H0LiCOW XIII).Comment: Version accepted by MNRAS. 29 pages including appendix, 17 figures, 6
tables. arXiv admin note: text overlap with arXiv:1607.0140
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H0LiCOW X: Spectroscopic/imaging survey and galaxy-group identification around the strong gravitational lens system WFI2033-4723
Galaxies and galaxy groups located along the line of sight towards
gravitationally lensed quasars produce high-order perturbations of the
gravitational potential at the lens position. When these perturbation are too
large, they can induce a systematic error on of a few-percent if the lens
system is used for cosmological inference and the perturbers are not explicitly
accounted for in the lens model. In this work, we present a detailed
characterization of the environment of the lens system WFI2033-4723 (, = 0.6575), one of the core targets of the H0LICOW
project for which we present cosmological inferences in a companion paper (Rusu
et al. 2019). We use the Gemini and ESO-Very Large telescopes to measure the
spectroscopic redshifts of the brightest galaxies towards the lens, and use the
ESO-MUSE integral field spectrograph to measure the velocity-dispersion of the
lens ( km/s) and of several nearby
galaxies. In addition, we measure photometric redshifts and stellar masses of
all galaxies down to mag, mainly based on Dark Energy Survey imaging
(DR1). Our new catalog, complemented with literature data, more than doubles
the number of known galaxy spectroscopic redshifts in the direct vicinity of
the lens, expanding to 116 (64) the number of spectroscopic redshifts for
galaxies separated by less than 3 arcmin (2 arcmin) from the lens. Using the
flexion-shift as a measure of the amplitude of the gravitational perturbation,
we identify 2 galaxy groups and 3 galaxies that require specific attention in
the lens models. The ESO MUSE data enable us to measure the
velocity-dispersions of three of these galaxies. These results are essential
for the cosmological inference analysis presented in Rusu et al. (2019).Comment: Matches the version accepted for publication by MNRAS. Note that this
paper previously appeared as H0LICOW X
Gas Accretion and Galactic Chemical Evolution: Theory and Observations
This chapter reviews how galactic inflows influence galaxy metallicity. The
goal is to discuss predictions from theoretical models, but particular emphasis
is placed on the insights that result from using models to interpret
observations. Even as the classical G-dwarf problem endures in the latest round
of observational confirmation, a rich and tantalizing new phenomenology of
relationships between , , SFR, and gas fraction is emerging both in
observations and in theoretical models. A consensus interpretation is emerging
in which star-forming galaxies do most of their growing in a quiescent way that
balances gas inflows and gas processing, and metal dilution with enrichment.
Models that explicitly invoke this idea via equilibrium conditions can be used
to infer inflow rates from observations, while models that do not assume
equilibrium growth tend to recover it self-consistently. Mergers are an overall
subdominant mechanism for delivering fresh gas to galaxies, but they trigger
radial flows of previously-accreted gas that flatten radial gas-phase
metallicity gradients and temporarily suppress central metallicities. Radial
gradients are generically expected to be steep at early times and then
flattened by mergers and enriched inflows of recycled gas at late times.
However, further theoretical work is required in order to understand how to
interpret observations. Likewise, more observational work is needed in order to
understand how metallicity gradients evolve to high redshifts.Comment: Invited review to appear in Gas Accretion onto Galaxies, Astrophysics
and Space Science Library, eds. A. J. Fox & R. Dav\'e, to be published by
Springer. 29 pages, 2 figure
curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome
This article introduces a manually curated data collection for gene expression meta-analysis of patients with ovarian cancer and software for reproducible preparation of similar databases. This resource provides uniformly prepared microarray data for 2970 patients from 23 studies with curated and documented clinical metadata. It allows users to efficiently identify studies and patient subgroups of interest for analysis and to perform meta-analysis immediately without the challenges posed by harmonizing heterogeneous microarray technologies, study designs, expression data processing methods and clinical data formats. We confirm that the recently proposed biomarker CXCL12 is associated with patient survival, independently of stage and optimal surgical debulking, which was possible only through meta-analysis owing to insufficient sample sizes of the individual studies. The database is implemented as the curatedOvarianData Bioconductor package for the R statistical computing language, providing a comprehensive and flexible resource for clinically oriented investigation of the ovarian cancer transcriptome. The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ovariancancer. Database URL: http://bcb.dfci.harvard.edu/ovariancance
Cosmological distance indicators
We review three distance measurement techniques beyond the local universe:
(1) gravitational lens time delays, (2) baryon acoustic oscillation (BAO), and
(3) HI intensity mapping. We describe the principles and theory behind each
method, the ingredients needed for measuring such distances, the current
observational results, and future prospects. Time delays from strongly lensed
quasars currently provide constraints on with < 4% uncertainty, and with
1% within reach from ongoing surveys and efforts. Recent exciting discoveries
of strongly lensed supernovae hold great promise for time-delay cosmography.
BAO features have been detected in redshift surveys up to z <~ 0.8 with
galaxies and z ~ 2 with Ly- forest, providing precise distance
measurements and with < 2% uncertainty in flat CDM. Future BAO
surveys will probe the distance scale with percent-level precision. HI
intensity mapping has great potential to map BAO distances at z ~ 0.8 and
beyond with precisions of a few percent. The next years ahead will be exciting
as various cosmological probes reach 1% uncertainty in determining , to
assess the current tension in measurements that could indicate new
physics.Comment: Review article accepted for publication in Space Science Reviews
(Springer), 45 pages, 10 figures. Chapter of a special collection resulting
from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in
the Space Ag
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
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
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