Forming double-barred galaxies from dynamically cool inner disks

About one-third of early-type barred galaxies host small-scale secondary bars. The formation and evolution of such double-barred (S2B) galaxies remain far from being well understood. In order to understand the formation of such systems, we explore a large parameter space of isolated pure-disk simulations. We show that a dynamically cool inner disk embedded in a hotter outer disk can naturally generate a steady secondary bar while the outer disk forms a large-scale primary bar. The independent bar instabilities of inner and outer disks result in long-lived double-barred structures whose dynamical properties are comparable to those in observations. This formation scenario indicates that the secondary bar might form from the general bar instability, the same as the primary bar. Under some circumstances, the interaction of the bars and the disk leads to the two bars aligning or single, nuclear, bars only. Simulations that are cool enough of the center to experience clump instabilities may also generate steady S2B galaxies. In this case, the secondary bars are “fast,” i.e., the bar length is close to the co-rotation radius. This is the first time that S2B galaxies containing a fast secondary bar are reported. Previous orbit-based studies had suggested that fast secondary bars were not dynamically possibl

The Trail, 1965-02-26

https://soundideas.pugetsound.edu/thetrail_all/1903/thumbnail.jp

Black Hole Growth in Disk Galaxies Mediated by the Secular Evolution of Short Bars

The growth of black holes (BHs) in disk galaxies lacking classical bulges, which implies an absence of significant mergers, appears to be driven by secular processes. Short bars of sub-kiloparsec radius have been hypothesized to be an important mechanism for driving gas inflows to small scale, feeding central BHs. In order to quantify the maximum BH mass allowed by this mechanism, we examine the robustness of short bars to the dynamical influence of BHs. Large-scale bars are expected to be robust, long-lived structures; extremely massive BHs, which are rare, are needed to completely destroy such bars. However, we find that short bars, which are generally embedded in largescale outer bars, can be destroyed quickly when BHs of mass Mbh ∼ 0.05% 0.2% of the total stellar mass (M∗) are present. In agreement with this prediction, all galaxies observed to host short bars have BHs with a mass fraction less than 0.2% M∗. Thus, the dissolution of short inner bars is possible, perhaps even frequent, in the universe. An important implication of this result is that inner-bar-driven gas inflows may be terminated when BHs grow to ∼0.1% M∗. We predict that 0.2% M∗ is the maximum mass of BHs allowed if they are fed predominately via inner bars. This value matches well the maximum ratio of BH-to-host-galaxy stellar mass observed in galaxies with pseudo-bulges and most nearby active galactic nucleus host galaxies. This hypothesis provides a novel explanation for the lower M Mbh in galaxies that have avoided significant mergers compared with galaxies with classical bulges

Genoviz Software Development Kit: Java tool kit for building genomics visualization applications

<p>Abstract</p> <p>Background</p> <p>Visualization software can expose previously undiscovered patterns in genomic data and advance biological science.</p> <p>Results</p> <p>The Genoviz Software Development Kit (SDK) is an open source, Java-based framework designed for rapid assembly of visualization software applications for genomics. The Genoviz SDK framework provides a mechanism for incorporating adaptive, dynamic zooming into applications, a desirable feature of genome viewers. Visualization capabilities of the Genoviz SDK include automated layout of features along genetic or genomic axes; support for user interactions with graphical elements (Glyphs) in a map; a variety of Glyph sub-classes that promote experimentation with new ways of representing data in graphical formats; and support for adaptive, semantic zooming, whereby objects change their appearance depending on zoom level and zooming rate adapts to the current scale. Freely available demonstration and production quality applications, including the Integrated Genome Browser, illustrate Genoviz SDK capabilities.</p> <p>Conclusion</p> <p>Separation between graphics components and genomic data models makes it easy for developers to add visualization capability to pre-existing applications or build new applications using third-party data models. Source code, documentation, sample applications, and tutorials are available at <url>http://genoviz.sourceforge.net/</url>.</p

Role of nitrogen lewis basicity in boronate affinity chromatography of nucleosides. Anal

Urinary modified nucleosides have a potential role as cancer biomarkers, and most of the methods used in their study have utilized low-pressure phenylboronate affinity chromatography materials for the purification of the cisdiol-containing nucleosides. In this study, a boronate HPLC column was surprisingly shown not to trap the nucleosides as would be expected from experience with the classic Affigel 601 resin but showed only partial selectivity toward cis-diol groups while other groups exhibited better retention. In aprotic conditions, trapping of nucleosides was possible; however, the selectivity toward cis-diol-containing compounds was lost with the Lewis basicity of available nitrogens being the main determinant of retention. The experimental findings are compared to and confirmed by DFT calculations. Modified nucleosides are naturally occurring modifications of the &quot;normal&quot; nucleosides. They have various roles within many nucleic acids but are mainly found in transfer RNA. They are excreted from the body via the urine as they cannot be salvaged; moreover, some are toxic when allowed to accumulate. Many past reports have investigated the modified nucleosides as potential cancer biomarkers and indicate considerable promise. [1][2][3][4][5] The methodologies used in these studies are wide ranging; however, since the introduction of boronate affinity chromatography as a ribonucleoside-selective cleanup step, on Affi-Gel 601 (Bio-Rad), utilized by Gehrke et al., 1,2 most research employed this off-line cleanup step process in the analysis. The subsequent identification/quantification of the ribonucleosides was almost exclusively carried out via RPLC-UV methods. More recently, some CE-UV methods have also been developed. [6][7][8][9] The further potential/ demand to obtain unambiguous identification via mass spectrometric detection led to the development of some off-line boronate chromatography GC/MS procedures. 3,5,10 However, the most natural choice for the analysis of the prepurified urinary nucleosides analysis is found in LC-MS. 11 Yet, the development of LC-MS procedures for urinary nucleosides only advanced 12 when electrospray mass spectrometry (ESI-MS) became available. Past studies by our group have considered the cleanup samples prior to ESI-MS analysis, 13 the optimization of the detection conditions, 14 comparison of various mass spectrometric methods, 15 and identification of the excreted nucleosides. 16,17 Other groups have taken advantage of mass spectrometry in the study of these compounds

Identifying Kinematic Structures in Simulated Galaxies Using Unsupervised Machine Learning

Galaxies host a wide array of internal stellar components, which need to be decomposed accurately in order to understand their formation and evolution. While significant progress has been made with recent integral-field spectroscopic surveys of nearby galaxies, much can be learned from analyzing the large sets of realistic galaxies now available through state-of-the-art hydrodynamical cosmological simulations. We present an unsupervised machine-learning algorithm, named auto-GMM, based on Gaussian mixture models, to isolate intrinsic structures in simulated galaxies based on their kinematic phase space. For each galaxy, the number of Gaussian components allowed by the data is determined through a modified Bayesian information criterion. We test our method by applying it to prototype galaxies selected from the cosmological simulation IllustrisTNG. Our method can effectively decompose most galactic structures. The intrinsic structures of simulated galaxies can be inferred statistically by non-human supervised identification of galaxy structures. We successfully identify four kinds of intrinsic structures: cold disks, warm disks, bulges, and halos. Our method fails for barred galaxies because of the complex kinematics of particles moving on bar orbits

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