Solid state quantum memory using the 31P nuclear spin

The transfer of information between different physical forms is a central theme in communication and computation, for example between processing entities and memory. Nowhere is this more crucial than in quantum computation, where great effort must be taken to protect the integrity of a fragile quantum bit. Nuclear spins are known to benefit from long coherence times compared to electron spins, but are slow to manipulate and suffer from weak thermal polarisation. A powerful model for quantum computation is thus one in which electron spins are used for processing and readout while nuclear spins are used for storage. Here we demonstrate the coherent transfer of a superposition state in an electron spin 'processing' qubit to a nuclear spin 'memory' qubit, using a combination of microwave and radiofrequency pulses applied to 31P donors in an isotopically pure 28Si crystal. The electron spin state can be stored in the nuclear spin on a timescale that is long compared with the electron decoherence time and then coherently transferred back to the electron spin, thus demonstrating the 31P nuclear spin as a solid-state quantum memory. The overall store/readout fidelity is about 90%, attributed to systematic imperfections in radiofrequency pulses which can be improved through the use of composite pulses. We apply dynamic decoupling to protect the nuclear spin quantum memory element from sources of decoherence. The coherence lifetime of the quantum memory element is found to exceed one second at 5.5K.Comment: v2: Tomography added and storage of general initial state

Subcellular localization of MC4R with ADCY3 at neuronal primary cilia underlies a common pathway for genetic predisposition to obesity.

Most monogenic cases of obesity in humans have been linked to mutations in genes encoding members of the leptin-melanocortin pathway. Specifically, mutations in MC4R, the melanocortin-4 receptor gene, account for 3-5% of all severe obesity cases in humans1-3. Recently, ADCY3 (adenylyl cyclase 3) gene mutations have been implicated in obesity4,5. ADCY3 localizes to the primary cilia of neurons 6 , organelles that function as hubs for select signaling pathways. Mutations that disrupt the functions of primary cilia cause ciliopathies, rare recessive pleiotropic diseases in which obesity is a cardinal manifestation 7 . We demonstrate that MC4R colocalizes with ADCY3 at the primary cilia of a subset of hypothalamic neurons, that obesity-associated MC4R mutations impair ciliary localization and that inhibition of adenylyl cyclase signaling at the primary cilia of these neurons increases body weight. These data suggest that impaired signaling from the primary cilia of MC4R neurons is a common pathway underlying genetic causes of obesity in humans

The microwave background temperature at the redshift of 2.33771

The Cosmic Microwave Background radiation is a fundamental prediction of Hot Big Bang cosmology. The temperature of its black-body spectrum has been measured at the present time, $T_{\rm CMBR,0}$ = 2.726$\pm$ 0.010 K, and is predicted to have been higher in the past. At earlier time, the temperature can be measured, in principle, using the excitation of atomic fine structure levels by the radiation field. All previous measurements however give only upper limits as they assume that no other significant source of excitation is present. Here we report the detection of absorption from the first {\sl and} second fine-structure levels of neutral carbon atoms in an isolated remote cloud at a redshift of 2.33771. In addition, the unusual detection of molecular hydrogen in several rotational levels and the presence of ionized carbon in its excited fine structure level make the absorption system unique to constrain, directly from observation, the different excitation processes at play. It is shown for the first time that the cosmic radiation was warmer in the past. We find 6.0 < T_{\rm CMBR} < 14 K at z = 2.33771 when 9.1 K is expected in the Hot Big Bang cosmology.Comment: 20 pages, 5 figures, accepted for publication in Nature, Press embargo until 1900 hrs London time (GMT) on 20 Dec 200

Transit Photometry as an Exoplanet Discovery Method

Photometry with the transit method has arguably been the most successful exoplanet discovery method to date. A short overview about the rise of that method to its present status is given. The method's strength is the rich set of parameters that can be obtained from transiting planets, in particular in combination with radial velocity observations; the basic principles of these parameters are given. The method has however also drawbacks, which are the low probability that transits appear in randomly oriented planet systems, and the presence of astrophysical phenomena that may mimic transits and give rise to false detection positives. In the second part we outline the main factors that determine the design of transit surveys, such as the size of the survey sample, the temporal coverage, the detection precision, the sample brightness and the methods to extract transit events from observed light curves. Lastly, an overview over past, current and future transit surveys is given. For these surveys we indicate their basic instrument configuration and their planet catch, including the ranges of planet sizes and stellar magnitudes that were encountered. Current and future transit detection experiments concentrate primarily on bright or special targets, and we expect that the transit method remains a principal driver of exoplanet science, through new discoveries to be made and through the development of new generations of instruments.Comment: Review chapte

Planet Populations as a Function of Stellar Properties

Exoplanets around different types of stars provide a window into the diverse environments in which planets form. This chapter describes the observed relations between exoplanet populations and stellar properties and how they connect to planet formation in protoplanetary disks. Giant planets occur more frequently around more metal-rich and more massive stars. These findings support the core accretion theory of planet formation, in which the cores of giant planets form more rapidly in more metal-rich and more massive protoplanetary disks. Smaller planets, those with sizes roughly between Earth and Neptune, exhibit different scaling relations with stellar properties. These planets are found around stars with a wide range of metallicities and occur more frequently around lower mass stars. This indicates that planet formation takes place in a wide range of environments, yet it is not clear why planets form more efficiently around low mass stars. Going forward, exoplanet surveys targeting M dwarfs will characterize the exoplanet population around the lowest mass stars. In combination with ongoing stellar characterization, this will help us understand the formation of planets in a large range of environments.Comment: Accepted for Publication in the Handbook of Exoplanet

Predicting Protein Phenotypes Based on Protein-Protein Interaction Network

BACKGROUND: Identifying associated phenotypes of proteins is a challenge of the modern genetics since the multifactorial trait often results from contributions of many proteins. Besides the high-through phenotype assays, the computational methods are alternative ways to identify the phenotypes of proteins. METHODOLOGY/PRINCIPAL FINDINGS: Here, we proposed a new method for predicting protein phenotypes in yeast based on protein-protein interaction network. Instead of only the most likely phenotype, a series of possible phenotypes for the query protein were generated and ranked according to the tethering potential score. As a result, the first order prediction accuracy of our method achieved 65.4% evaluated by Jackknife test of 1,267 proteins in budding yeast, much higher than the success rate (15.4%) of a random guess. And the likelihood of the first 3 predicted phenotypes including all the real phenotypes of the proteins was 70.6%. CONCLUSIONS/SIGNIFICANCE: The candidate phenotypes predicted by our method provided useful clues for the further validation. In addition, the method can be easily applied to the prediction of protein associated phenotypes in other organisms

Sentinel node biopsy in early vulvar cancer

Lymph node pathologic status is the most important prognostic factor in vulvar cancer; however, complete inguinofemoral node dissection is associated with significant morbidity. Lymphoscintigraphy associated with gamma-probe guided surgery reliably detects sentinel nodes in melanoma and breast cancer patients. This study evaluates the feasibility of the surgical identification of sentinel groin nodes using lymphoscintigraphy and a gamma-detecting probe in patients with early vulvar cancer. Technetium-99m-labelled colloid human albumin was administered perilesionally in 37 patients with invasive epidermoid vulvar cancer (T1–T2) and lymphoscintigraphy performed the day before surgery. An intraoperative gamma-detecting probe was used to identify sentinel nodes during surgery. A complete inguinofemoral node dissection was then performed. Sentinel nodes were submitted separately to pathologic evaluation. A total of 55 groins were dissected in 37 patients. Localization of the SN was successful in all cases. Eight cases had positive nodes: in all the sentinel node as positive; the sentinel node was the only positive node in five cases. Twenty-nine patients showed negative sentinel nodes: all of them were negative for lymph node metastases. Lymphoscintigraphy and sentinel-node biopsy under gamma-detecting probe guidance proved to be an easy and reliable method for the detection of sentinel node in early vulvar cancer. This technique may represent a true advance in the direction of less aggressive treatments in patients with vulvar cancer. © 2000 Cancer Research Campaig

Dependence of Bacterial Chemotaxis on Gradient Shape and Adaptation Rate

Simulation of cellular behavior on multiple scales requires models that are sufficiently detailed to capture central intracellular processes but at the same time enable the simulation of entire cell populations in a computationally cheap way. In this paper we present RapidCell, a hybrid model of chemotactic Escherichia coli that combines the Monod-Wyman-Changeux signal processing by mixed chemoreceptor clusters, the adaptation dynamics described by ordinary differential equations, and a detailed model of cell tumbling. Our model dramatically reduces computational costs and allows the highly efficient simulation of E. coli chemotaxis. We use the model to investigate chemotaxis in different gradients, and suggest a new, constant-activity type of gradient to systematically study chemotactic behavior of virtual bacteria. Using the unique properties of this gradient, we show that optimal chemotaxis is observed in a narrow range of CheA kinase activity, where concentration of the response regulator CheY-P falls into the operating range of flagellar motors. Our simulations also confirm that the CheB phosphorylation feedback improves chemotactic efficiency by shifting the average CheY-P concentration to fit the motor operating range. Our results suggest that in liquid media the variability in adaptation times among cells may be evolutionary favorable to ensure coexistence of subpopulations that will be optimally tactic in different gradients. However, in a porous medium (agar) such variability appears to be less important, because agar structure poses mainly negative selection against subpopulations with low levels of adaptation enzymes. RapidCell is available from the authors upon request

Development of an Orthotopic Human Pancreatic Cancer Xenograft Model Using Ultrasound Guided Injection of Cells

Mice have been employed as models of cancer for over a century, providing significant advances in our understanding of this multifaceted family of diseases. In particular, orthotopic tumor xenograft mouse models are emerging as the preference for cancer research due to increased clinical relevance over subcutaneous mouse models. In the current study, we developed orthotopic pancreatic cancer xenograft models in mice by a minimally invasive method, ultrasound guided injection (USGI) comparable to highly invasive surgical orthotopic injection (SOI) methods. This optimized method prevented injection complications such as recoil of cells through the injection canal or leakage of cells out of the pancreas into the peritoneal cavity. Tumor growth was monitored in vivo and quantified by ultrasound imaging weekly, tumors were also detected by in vivo fluorescence imaging using a tumor targeted molecular probe. The mean tumor volumes for the USGI and SOI models after 2 weeks of tumor growth were 205 mm3 and 178 mm3 respectively. By USGI of human pancreatic cancer cell lines, human orthotopic pancreatic cancer xenografts were established. Based on ultrasound imaging, the orthotopic human pancreatic cancer xenograft take rate was 100% for both human pancreatic cancer cell lines used, MiaPaCa-2 and Su86.86, with mean tumor volumes of 28 mm3and 30 mm3. We demonstrated that this USGI method is feasible, reproducible, facile, minimally invasive and improved compared to the highly-invasive SOI method for establishing orthotopic pancreatic tumor xenograft models suitable for molecular imaging

Bioactive compounds of plum mango (Bouea macrophylla Griffith)

The fruit of Bouea macrophylla referred as Plum mango or Gandaria is a popular seasonal fruit, which is widely consumed in the Malay subcontinent. There is ample of traditional knowledge available among the locals on the use of leaves, bark, fruits and seeds of this plant. However, very limited research information and scientific report is available on their composition, phytochemicals or on the bioactive compounds. In the present chapter, we have aimed towards comprehensively providing information on nutritional value, functional qualities, health promoting bioactive compounds and volatile constituents of this underutilized fruit