A single-atom quantum memory

The faithful storage of a quantum bit (qubit) of light is essential for long-distance quantum communication, quantum networking and distributed quantum computing. The required optical quantum memory must be able to receive and recreate the photonic qubit; additionally, it must store an unknown quantum state of light better than any classical device. So far, these two requirements have been met only by ensembles of material particles that store the information in collective excitations. Recent developments, however, have paved the way for an approach in which the information exchange occurs between single quanta of light and matter. This single-particle approach allows the material qubit to be addressed, which has fundamental advantages for realistic implementations. First, it enables a heralding mechanism that signals the successful storage of a photon by means of state detection; this can be used to combat inevitable losses and finite efficiencies. Second, it allows for individual qubit manipulations, opening up avenues for in situ processing of the stored quantum information. Here we demonstrate the most fundamental implementation of such a quantum memory, by mapping arbitrary polarization states of light into and out of a single atom trapped inside an optical cavity. The memory performance is tested with weak coherent pulses and analysed using full quantum process tomography. The average fidelity is measured to be 93%, and low decoherence rates result in qubit coherence times exceeding 180 microseconds. This makes our system a versatile quantum node with excellent prospects for applications in optical quantum gates and quantum repeaters.     

Hydrogen is an energy source for hydrothermal vent symbioses

The discovery of deep-sea hydrothermal vents in 1977 revolutionized our understanding of the energy sources that fuel primary productivity on Earth. Hydrothermal vent ecosystems are dominated by animals that live in symbiosis with chemosynthetic bacteria. So far, only two energy sources have been shown to power chemosynthetic symbioses: reduced sulphur compounds and methane. Using metagenome sequencing, single-gene fluorescence in situ hybridization, immunohistochemistry, shipboard incubations and in situ mass spectrometry, we show here that the symbionts of the hydrothermal vent mussel Bathymodiolus from the Mid-Atlantic Ridge use hydrogen to power primary production. In addition, we show that the symbionts of Bathymodiolus mussels from Pacific vents have hupL, the key gene for hydrogen oxidation. Furthermore, the symbionts of other vent animals such as the tubeworm Riftia pachyptila and the shrimp Rimicaris exoculata also have hupL. We propose that the ability to use hydrogen as an energy source is widespread in hydrothermal vent symbioses, particularly at sites where hydrogen is abundant.     

Earth's Trojan asteroid

It was realized in 1772 that small bodies can stably share the same orbit as a planet if they remain near 'triangular points' 60° ahead of or behind it in the orbit. Such 'Trojan asteroids' have been found co-orbiting with Jupiter, Mars and Neptune. They have not hitherto been found associated with Earth, where the viewing geometry poses difficulties for their detection, although other kinds of co-orbital asteroid (horseshoe orbiters and quasi-satellites) have been observed. Here we report an archival search of infrared data for possible Earth Trojans, producing the candidate 2010 TK(7). We subsequently made optical observations which established that 2010 TK(7) is a Trojan companion of Earth, librating around the leading Lagrange triangular point, L(4). Its orbit is stable over at least ten thousand years.     

New gene functions in megakaryopoiesis and platelet formation

Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function.     

An open-system quantum simulator with trapped ions

The control of quantum systems is of fundamental scientific interest and promises powerful applications and technologies. Impressive progress has been achieved in isolating quantum systems from the environment and coherently controlling their dynamics, as demonstrated by the creation and manipulation of entanglement in various physical systems. However, for open quantum systems, engineering the dynamics of many particles by a controlled coupling to an environment remains largely unexplored. Here we realize an experimental toolbox for simulating an open quantum system with up to five quantum bits (qubits). Using a quantum computing architecture with trapped ions, we combine multi-qubit gates with optical pumping to implement coherent operations and dissipative processes. We illustrate our ability to engineer the open-system dynamics through the dissipative preparation of entangled states, the simulation of coherent many-body spin interactions, and the quantum non-demolition measurement of multi-qubit observables. By adding controlled dissipation to coherent operations, this work offers novel prospects for open-system quantum simulation and computation.     

Image-based genome-wide siRNA screen identifies selective autophagy factors

Selective autophagy involves the recognition and targeting of specific cargo, such as damaged organelles, misfolded proteins, or invading pathogens for lysosomal destruction. Yeast genetic screens have identified proteins required for different forms of selective autophagy, including cytoplasm-to-vacuole targeting, pexophagy and mitophagy, and mammalian genetic screens have identified proteins required for autophagy regulation. However, there have been no systematic approaches to identify molecular determinants of selective autophagy in mammalian cells. Here, to identify mammalian genes required for selective autophagy, we performed a high-content, image-based, genome-wide small interfering RNA screen to detect genes required for the colocalization of Sindbis virus capsid protein with autophagolysosomes. We identified 141 candidate genes required for viral autophagy, which were enriched for cellular pathways related to messenger RNA processing, interferon signalling, vesicle trafficking, cytoskeletal motor function and metabolism. Ninety-six of these genes were also required for Parkin-mediated mitophagy, indicating that common molecular determinants may be involved in autophagic targeting of viral nucleocapsids and autophagic targeting of damaged mitochondria. Murine embryonic fibroblasts lacking one of these gene products, the C2-domain containing protein, SMURF1, are deficient in the autophagosomal targeting of Sindbis and herpes simplex viruses and in the clearance of damaged mitochondria. Moreover, SMURF1-deficient mice accumulate damaged mitochondria in the heart, brain and liver. Thus, our study identifies candidate determinants of selective autophagy, and defines SMURF1 as a newly recognized mediator of both viral autophagy and mitophagy.     

Hyperforin is a novel type of 5-lipoxygenase inhibitor with high efficacy in vivo

We previously showed that, in vitro, hyperforin from St. John’s wort (Hypericum perforatum) inhibits 5-lipoxygenase (5-LO), the key enzyme in leukotriene biosynthesis. Here, we demonstrate that hyperforin possesses a novel and unique molecular pharmacological profile as a 5-LO inhibitor with remarkable efficacy in vivo. Hyperforin (4 mg/kg, i.p.) significantly suppressed leukotriene B₄ formation in pleural exudates of carrageenan-treated rats associated with potent anti-inflammatory effectiveness. Inhibition of 5-LO by hyperforin, but not by the iron-ligand type 5-LO inhibitor BWA4C or the nonredox-type inhibitor ZM230487, was abolished in the presence of phosphatidylcholine and strongly reduced by mutation (W13A-W75A-W102A) of the 5-LO C2-like domain. Moreover, hyperforin impaired the interaction of 5-LO with coactosin-like protein and abrogated 5-LO nuclear membrane translocation in ionomycin-stimulated neutrophils, processes that are typically mediated via the regulatory 5-LO C2-like domain. Together, hyperforin is a novel type of 5-LO inhibitor apparently acting by interference with the C2-like domain, with high effectiveness in vivo.     

Forecasting and trading currency volatility: an application of recurrent neural regression and model combination

In this paper, we examine the use of non‐parametric Neural Network Regression (NNR) and Recurrent Neural Network (RNN) regression models for forecasting and trading currency volatility, with an application to the GBP/USD and USD/JPY exchange rates. Both the results of the NNR and RNN models are benchmarked against the simpler GARCH alternative and implied volatility. Two simple model combinations are also analysed. The intuitively appealing idea of developing a nonlinear nonparametric approach to forecast FX volatility, identify mispriced options and subsequently develop a trading strategy based upon this process is implemented for the first time on a comprehensive basis. Using daily data from December 1993 through April 1999, we develop alternative FX volatility forecasting models. These models are then tested out‐of‐sample over the period April 1999–May 2000, not only in terms of forecasting accuracy, but also in terms of trading efficiency: in order to do so, we apply a realistic volatility trading strategy using FX option straddles once mispriced options have been identified. Allowing for transaction costs, most trading strategies retained produce positive returns. RNN models appear as the best single modelling approach yet, somewhat surprisingly, model combination which has the best overall performance in terms of forecasting accuracy, fails to improve the RNN‐based volatility trading results. Another conclusion from our results is that, for the period and currencies considered, the currency option market was inefficient and/or the pricing formulae applied by market participants were inadequate. Copyright © 2002 John Wiley & Sons, Ltd.