Search for C-parity violation in J/ψ→γγJ/ \psi \to \gamma\gamma and γϕ \gamma \phi

Using $1.06\times10^8$ $\psi(3686)$ events recorded in $e^{+}e^{-}$ collisions at $\sqrt{s}=$ 3.686 GeV with the BESIII at the BEPCII collider, we present searches for C-parity violation in $J/\psi \to \gamma\gamma$ and $\gamma \phi$ decays via $\psi(3686) \to J/\psi \pi^+\pi^-$. No significant signals are observed in either channel. Upper limits on the branching fractions are set to be $\mathcal{B}(J/\psi \to \gamma\gamma) < 2.7 \times 10^{-7}$ and $\mathcal{B}(J/\psi \to \gamma\phi) < 1.4 \times 10^{-6}$ at the 90\% confidence level. The former is one order of magnitude more stringent than the previous upper limit, and the latter represents the first limit on this decay channel.Comment: 7 pages, 2 figure

Observation of e+e−→π0π0hce^+e^-\to \pi^0\pi^0 h_c and a neutral charmoniumlike structure Zc(4020)0Z_c(4020)^0

Using data collected with the BESIII detector operating at the Beijing Electron Positron Collider at center-of-mass energies of $\sqrt{s}=4.23$, 4.26, and 4.36~GeV, we observe \EE\to \pphc for the first time. The Born cross sections are measured and found to be about half of those of \EE\to \pi^+\pi^-h_c within less than 2$\sigma$. In the $\pi^0h_c$ mass spectrum, a structure at 4.02~GeV/$c^2$ is found. It is most likely to be the neutral isospin partner of the \zcp^{\pm} observed in the process of \EE\to \pi^+\pi^-h_c is found. A fit to the $\pi^0 h_c$ invariant mass spectrum, with the width of the \zcpn fixed to that of its charged isospin partner and possible interferences with non-\zcpn amplitudes neglected, gives a mass of ($4023.9\pm 2.2 \pm 3.8$)~MeV/$c^2$ for the \zcpn, where the first error is statistical and the second systematic.Comment: 7 pages, 2 figure

Pyrosequencing the Bemisia tabaci Transcriptome Reveals a Highly Diverse Bacterial Community and a Robust System for Insecticide Resistance

BACKGROUND: Bemisia tabaci (Gennadius) is a phloem-feeding insect poised to become one of the major insect pests in open field and greenhouse production systems throughout the world. The high level of resistance to insecticides is a main factor that hinders continued use of insecticides for suppression of B. tabaci. Despite its prevalence, little is known about B. tabaci at the genome level. To fill this gap, an invasive B. tabaci B biotype was subjected to pyrosequencing-based transcriptome analysis to identify genes and gene networks putatively involved in various physiological and toxicological processes. METHODOLOGY AND PRINCIPAL FINDINGS: Using Roche 454 pyrosequencing, 857,205 reads containing approximately 340 megabases were obtained from the B. tabaci transcriptome. De novo assembly generated 178,669 unigenes including 30,980 from insects, 17,881 from bacteria, and 129,808 from the nohit. A total of 50,835 (28.45%) unigenes showed similarity to the non-redundant database in GenBank with a cut-off E-value of 10-5. Among them, 40,611 unigenes were assigned to one or more GO terms and 6,917 unigenes were assigned to 288 known pathways. De novo metatranscriptome analysis revealed highly diverse bacterial symbionts in B. tabaci, and demonstrated the host-symbiont cooperation in amino acid production. In-depth transcriptome analysis indentified putative molecular markers, and genes potentially involved in insecticide resistance and nutrient digestion. The utility of this transcriptome was validated by a thiamethoxam resistance study, in which annotated cytochrome P450 genes were significantly overexpressed in the resistant B. tabaci in comparison to its susceptible counterparts. CONCLUSIONS: This transcriptome/metatranscriptome analysis sheds light on the molecular understanding of symbiosis and insecticide resistance in an agriculturally important phloem-feeding insect pest, and lays the foundation for future functional genomics research of the B. tabaci complex. Moreover, current pyrosequencing effort greatly enriched the existing whitefly EST database, and makes RNAseq a viable option for future genomic analysis

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given