Two novel transcriptional regulators are essential for infection-related morphogenesis and pathogenicity of the rice blast fungus Magnaporthe oryzae.

This is the final version of the article. Available from the publisher via the DOI in this record.The cyclic AMP-dependent protein kinase A signaling pathway plays a major role in regulating plant infection by the rice blast fungus Magnaporthe oryzae. Here, we report the identification of two novel genes, MoSOM1 and MoCDTF1, which were discovered in an insertional mutagenesis screen for non-pathogenic mutants of M. oryzae. MoSOM1 or MoCDTF1 are both necessary for development of spores and appressoria by M. oryzae and play roles in cell wall differentiation, regulating melanin pigmentation and cell surface hydrophobicity during spore formation. MoSom1 strongly interacts with MoStu1 (Mstu1), an APSES transcription factor protein, and with MoCdtf1, while also interacting more weakly with the catalytic subunit of protein kinase A (CpkA) in yeast two hybrid assays. Furthermore, the expression levels of MoSOM1 and MoCDTF1 were significantly reduced in both Δmac1 and ΔcpkA mutants, consistent with regulation by the cAMP/PKA signaling pathway. MoSom1-GFP and MoCdtf1-GFP fusion proteins localized to the nucleus of fungal cells. Site-directed mutagenesis confirmed that nuclear localization signal sequences in MoSom1 and MoCdtf1 are essential for their sub-cellular localization and biological functions. Transcriptional profiling revealed major changes in gene expression associated with loss of MoSOM1 during infection-related development. We conclude that MoSom1 and MoCdtf1 functions downstream of the cAMP/PKA signaling pathway and are novel transcriptional regulators associated with cellular differentiation during plant infection by the rice blast fungus.Funding: This work was supported by National Key Basic Research and Development Program of China (2012CB114002), by Program for Changjiang Scholars and Innovative Research Team in University (IRT0943), by the Natural Science Foundation of China (Grant Nos. 30970129 and 31071648) and the Doctoral Fund of Ministry of Education of China (20100101110097) to ZW

Measurements of the Cross Section for e+e- -> hadrons at Center-of-Mass Energies from 2 to 5 GeV

We report values of $R = \sigma(e^+e^-\to {hadrons})/\sigma(e^+e^-\to\mu^+\mu^-)$ for 85 center-of-mass energies between 2 and 5 GeV measured with the upgraded Beijing Spectrometer at the Beijing Electron-Positron Collider.Comment: 5 pages, 3 figure

First Measurement of the Branching Fraction of the Decay psi(2S) --> tau tau

The branching fraction of the psi(2S) decay into tau pair has been measured for the first time using the BES detector at the Beijing Electron-Positron Collider. The result is $B_{\tau\tau}=(2.71\pm 0.43 \pm 0.55) \times 10^{-3}$, where the first error is statistical and the second is systematic. This value, along with those for the branching fractions into e+e- and mu+mu of this resonance, satisfy well the relation predicted by the sequential lepton hypothesis. Combining all these values with the leptonic width of the resonance the total width of the psi(2S) is determined to be $(252 \pm 37)$ keV.Comment: 9 pages, 2 figure

Measurement of the Total Cross Section for Hadronic Production by e+e- Annihilation at Energies between 2.6-5 Gev

Using the upgraded Beijing Spectrometer (BESII), we have measured the total cross section for $e^+e^-$ annihilation into hadronic final states at center-of-mass energies of 2.6, 3.2, 3.4, 3.55, 4.6 and 5.0 GeV. Values of $R$, $\sigma(e^+e^-\to {hadrons})/\sigma(e^+e^-\to\mu^+\mu^-)$, are determined.Comment: Submitted to Phys. Rev. Let

Measurement of the Inclusive Charm Cross Section at 4.03 GeV and 4.14 GeV

The cross section for charmed meson production at $\sqrt{s} = 4.03$ and 4.14 GeV has been measured with the Beijing Spectrometer. The measurement was made using 22.3 $pb^{-1}$ of $e^+e^-$ data collected at 4.03 GeV and 1.5 $pb^{-1}$ of $e^+e^-$ data collected at 4.14 GeV. Inclusive observed cross sections for the production of charged and neutral D mesons and momentum spectra are presented. Observed cross sections were radiatively corrected to obtain tree level cross sections. Measurements of the total hadronic cross section are obtained from the charmed meson cross section and an extrapolation of results from below the charm threshold.Comment: 11 pages, 13 figures. The top level tex file is paper.tex. It builds the paper from other tex files in this .tar and the .eps file

Study of the P-wave charmonium state \chi_{cJ} in \psi(2S) decays

The processes $\psi(2S)\to \gamma \pi^+ \pi^-$, $\gamma K^+ K^-$ and $\gamma p \bar{p}$ have been studied using a sample of $3.7 \times 10^6$ produced $\psi(2S)$ decays. We determine the total width of the $\chi_{c0}$ to be $\Gamma^{tot}_{\chi_{c0}} = 14.3\pm 2.0\pm 3.0$ MeV. We present the first measurement of the branching fraction $B(\chi_{c0} \to p \bar{p}) = (16.3 \pm 4.4 \pm 5.4)\times 10^{-5}$, where the first error is statistical and the second one systematic. Branching fractions of $\chi_{c0,2} \to \pi^+ \pi^-$ and $K^+ K^-$ are also reported.Comment: 10 pages, revtex, 3 figures, 2 table

Protein trafficking through the endosomal system prepares intracellular parasites for a home invasion

Toxoplasma (toxoplasmosis) and Plasmodium (malaria) use unique secretory organelles for migration, cell invasion, manipulation of host cell functions, and cell egress. In particular, the apical secretory micronemes and rhoptries of apicomplexan parasites are essential for successful host infection. New findings reveal that the contents of these organelles, which are transported through the endoplasmic reticulum (ER) and Golgi, also require the parasite endosome-like system to access their respective organelles. In this review, we discuss recent findings that demonstrate that these parasites reduced their endosomal system and modified classical regulators of this pathway for the biogenesis of apical organelles

Measurement of ψ(2S)\psi(2S) decays to baryon pairs

A sample of 3.95M $\psi(2S)$ decays registered in the BES detector are used to study final states containing pairs of octet and decuplet baryons. We report branching fractions for $\psi(2S)\to p\bar{p}$, $\Lambda\bar{\Lambda}$, $\Sigma^0\bar{\Sigma}{}^0$, $\Xi^-\bar{\Xi}{}^+$, $\Delta^{++}\bar{\Delta}{}^{--}$, $\Sigma^+(1385)\bar{\Sigma}{}^-(1385)$, $\Xi^0(1530)\bar{\Xi}{}^0(1530)$, and $\Omega^-\bar{\Omega}{}^+$. These results are compared to expectations based on the SU(3)-flavor symmetry, factorization, and perturbative QCD.Comment: 22 pages, 21 figures, 4 table

High-performance acceleration of 2-D and 3D CNNs on FPGAs using static block floating point

Over the past few years, 2-D convolutional neural networks (CNNs) have demonstrated their great success in a wide range of 2-D computer vision applications, such as image classification and object detection. At the same time, 3-D CNNs, as a variant of 2-D CNNs, have shown their excellent ability to analyze 3-D data, such as video and geometric data. However, the heavy algorithmic complexity of 2-D and 3-D CNNs imposes a substantial overhead over the speed of these networks, which limits their deployment in real-life applications. Although various domain-specific accelerators have been proposed to address this challenge, most of them only focus on accelerating 2-D CNNs, without considering their computational efficiency on 3-D CNNs. In this article, we propose a unified hardware architecture to accelerate both 2-D and 3-D CNNs with high hardware efficiency. Our experiments demonstrate that the proposed accelerator can achieve up to 92.4% and 85.2% multiply-accumulate efficiency on 2-D and 3-D CNNs, respectively. To improve the hardware performance, we propose a hardware-friendly quantization approach called static block floating point (BFP), which eliminates the frequent representation conversions required in traditional dynamic BFP arithmetic. Comparing with the integer linear quantization using zero-point, the static BFP quantization can decrease the logic resource consumption of the convolutional kernel design by nearly 50% on a field-programmable gate array (FPGA). Without time-consuming retraining, the proposed static BFP quantization is able to quantize the precision to 8-bit mantissa with negligible accuracy loss. As different CNNs on our reconfigurable system require different hardware and software parameters to achieve optimal hardware performance and accuracy, we also propose an automatic tool for parameter optimization. Based on our hardware design and optimization, we demonstrate that the proposed accelerator can achieve 3.8-5.6 times higher energy efficiency than graphics processing unit (GPU) implementation. Comparing with the state-of-the-art FPGA-based accelerators, our design achieves higher generality and up to 1.4-2.2 times higher resource efficiency on both 2-D and 3-D CNNs

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