Heterogeneous mantle source and magma differentiation of quaternary arc-like volcanic rocks from Tengchong, SE margin of the Tibetan Plateau

The Tengchong volcanic field north of the Burma arc comprises numerous Quaternary volcanoes in the southeastern margin of the Tibetan Plateau. The volcanic rocks are grouped into four units (1-4) from the oldest to youngest. Units 1, 3 and 4 are composed of olivine trachybasalt, basaltic trachyandesite and trachyandesite, and Unit 2 consists of hornblende dacite. The rocks of Units 1, 3, and 4 form a generally alkaline suite in which the rocks plot along generally linear trends on Harker diagrams with only slight offset from unit to unit. They contain olivine phenocrysts with Fo values ranging from 65 to 85 mol% and have Cr-spinel with Cr# ranging from 23 to 35. All the rocks have chondrite-normalized REE patterns enriched in LREE and primitive mantle-normalized trace element patterns depleted in Ti, Nb and Ta, but they are rich in Th, Ti and P relative to typical arc volcanics. Despite minor crustal contamination, 87Sr/ 86Sr ratios (0.706-0.709), εNd values (-3.2 to -8.7), and εHf values (+4.8 to -6.4) indicate a highly heterogeneous mantle source. The Pb isotopic ratios of the lavas ( 206Pb/ 204Pb = 18.02-18.30) clearly show an EMI-type mantle source. The underlying mantle source was previously modified by subduction of the Neo-Tethyan oceanic and Indian continental lithosphere. The present heterogeneous mantle source is interpreted to have formed by variable additions of fluids and sediments derived from the subducted Indian Oceanic lithosphere, probably the Ninety East Ridge. Magma generation and emplacement was facilitated by transtensional NS-trending strike-slip faulting. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 28 May 201

Quantum dissipation and broadening mechanisms due to electron-phonon interactions in self-formed InGaN quantum dots

Quantum dissipation and broadening mechanisms in Si-doped InGaN quantum dots are studied via the photoluminescence technique. It is found that the dissipative thermal bath that embeds the quantum dots plays an important role in the photon emission processes. Observed spontaneous emission spectra are modeled with the multimode Brownian oscillator model achieving an excellent agreement between experiment and theory for a wide temperature range. The dimensionless Huang-Rhys factor characterizing the strength of electron-LO-phonon coupling and damping constant accounting for the LO-phonon-bath interaction strength are found to be ∼0.2 and 200 cm-1, respectively, for the InGaN QDs. © 2006 American Institute of Physics.published_or_final_versio

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Effects of temperature on thick branes and the fermion (quasi-)localization

Following Campos's work [Phys. Rev. Lett. 88, 141602 (2002)], we investigate the effects of temperature on flat, de Sitter (dS), and anti-de Following Campos's work [Phys. Rev. Lett. \textbf{88}, 141602 (2002)], we investigate the effects of temperature on flat, de Sitter (dS), and anti-de Sitter (AdS) thick branes in five-dimensional (5D) warped spacetime, and on the fermion (quasi-)localization. First, in the case of flat brane, when the critical temperature reaches, the solution of the background scalar field and the warp factor is not unique. So the thickness of the flat thick brane is uncertain at the critical value of the temperature parameter, which is found to be lower than the one in flat 5D spacetime. The mass spectra of the fermion Kaluza-Klein (KK) modes are continuous, and there is a series of fermion resonances. The number and lifetime of the resonances are finite and increase with the temperature parameter, but the mass of the resonances decreases with the temperature parameter. Second, in the case of dS brane, we do not find such a critical value of the temperature parameter. The mass spectra of the fermion KK modes are also continuous, and there is a series of fermion resonances. The effects of temperature on resonance number, lifetime, and mass are the same with the case of flat brane. Last, in the case of AdS brane, {the critical value of the temperature parameter can less or greater than the one in the flat 5D spacetime.} The spectra of fermion KK modes are discrete, and the mass of fermion KK modes does not decrease monotonically with increasing temperature parameter.Comment: 24 pages, 15 figures, published versio

A database of microRNA expression patterns in Xenopus laevis

MicroRNAs (miRNAs) are short, non-coding RNAs around 22 nucleotides long. They inhibit gene expression either by translational repression or by causing the degradation of the mRNAs they bind to. Many are highly conserved amongst diverse organisms and have restricted spatio-temporal expression patterns during embryonic development where they are thought to be involved in generating accuracy of developmental timing and in supporting cell fate decisions and tissue identity. We determined the expression patterns of 180 miRNAs in Xenopus laevis embryos using LNA oligonucleotides. In addition we carried out small RNA-seq on different stages of early Xenopus development, identified 44 miRNAs belonging to 29 new families and characterized the expression of 5 of these. Our analyses identified miRNA expression in many organs of the developing embryo. In particular a large number were expressed in neural tissue and in the somites. Surprisingly none of the miRNAs we have looked at show expression in the heart. Our results have been made freely available as a resource in both XenMARK and Xenbase

A novel class of microRNA-recognition elements that function only within open reading frames.

MicroRNAs (miRNAs) are well known to target 3' untranslated regions (3' UTRs) in mRNAs, thereby silencing gene expression at the post-transcriptional level. Multiple reports have also indicated the ability of miRNAs to target protein-coding sequences (CDS); however, miRNAs have been generally believed to function through similar mechanisms regardless of the locations of their sites of action. Here, we report a class of miRNA-recognition elements (MREs) that function exclusively in CDS regions. Through functional and mechanistic characterization of these 'unusual' MREs, we demonstrate that CDS-targeted miRNAs require extensive base-pairing at the 3' side rather than the 5' seed; cause gene silencing in an Argonaute-dependent but GW182-independent manner; and repress translation by inducing transient ribosome stalling instead of mRNA destabilization. These findings reveal distinct mechanisms and functional consequences of miRNAs that target CDS versus the 3' UTR and suggest that CDS-targeted miRNAs may use a translational quality-control-related mechanism to regulate translation in mammalian cells

SILAC-based phosphoproteomics reveals an inhibitory role of KSR1 in p53 transcriptional activity via modulation of DBC1

BACKGROUND We have previously identified kinase suppressor of ras-1 (KSR1) as a potential regulatory gene in breast cancer. KSR1, originally described as a novel protein kinase, has a role in activation of mitogen-activated protein kinases. Emerging evidence has shown that KSR1 may have dual functions as an active kinase as well as a scaffold facilitating multiprotein complex assembly. Although efforts have been made to study the role of KSR1 in certain tumour types, its involvement in breast cancer remains unknown. METHODS A quantitative mass spectrometry analysis using stable isotope labelling of amino acids in cell culture (SILAC) was implemented to identify KSR1-regulated phosphoproteins in breast cancer. In vitro luciferase assays, co-immunoprecipitation as well as western blotting experiments were performed to further study the function of KSR1 in breast cancer. RESULTS Of significance, proteomic analysis reveals that KSR1 overexpression decreases deleted in breast cancer-1 (DBC1) phosphorylation. Furthermore, we show that KSR1 decreases the transcriptional activity of p53 by reducing the phosphorylation of DBC1, which leads to a reduced interaction of DBC1 with sirtuin-1 (SIRT1); this in turn enables SIRT1 to deacetylate p53. CONCLUSION Our findings integrate KSR1 into a network involving DBC1 and SIRT1, which results in the regulation of p53 acetylation and its transcriptional activity

Nuclear receptors in vascular biology

Nuclear receptors sense a wide range of steroids and hormones (estrogens, progesterone, androgens, glucocorticoid, and mineralocorticoid), vitamins (A and D), lipid metabolites, carbohydrates, and xenobiotics. In response to these diverse but critically important mediators, nuclear receptors regulate the homeostatic control of lipids, carbohydrate, cholesterol, and xenobiotic drug metabolism, inflammation, cell differentiation and development, including vascular development. The nuclear receptor family is one of the most important groups of signaling molecules in the body and as such represent some of the most important established and emerging clinical and therapeutic targets. This review will highlight some of the recent trends in nuclear receptor biology related to vascular biology

Bench-to-bedside review : targeting antioxidants to mitochondria in sepsis

Peer reviewedPublisher PD

Differential cross sections and spin density matrix elements for the reaction gamma p -> p omega

High-statistics differential cross sections and spin density matrix elements for the reaction gamma p -> p omega have been measured using the CLAS at Jefferson Lab for center-of-mass (CM) energies from threshold up to 2.84 GeV. Results are reported in 112 10-MeV wide CM energy bins, each subdivided into cos(theta_CM) bins of width 0.1. These are the most precise and extensive omega photoproduction measurements to date. A number of prominent structures are clearly present in the data. Many of these have not previously been observed due to limited statistics in earlier measurements