Superconductivity in Ropes of Single-Walled Carbon Nanotubes

We report measurements on ropes of Single Walled Carbon Nanotubes (SWNT) in low-resistance contact to non-superconducting (normal) metallic pads, at low voltage and at temperatures down to 70 mK. In one sample, we find a two order of magnitude resistance drop below 0.55 K, which is destroyed by a magnetic field of the order of 1T, or by a d.c. current greater than 2.5 microA. These features strongly suggest the existence of superconductivity in ropes of SWNT.Comment: Accepted for publication in Phys. Rev. Let

Modeling the evolution of a classic genetic switch

Abstract Background The regulatory network underlying the yeast galactose-use pathway has emerged as a model system for the study of regulatory network evolution. Evidence has recently been provided for adaptive evolution in this network following a whole genome duplication event. An ancestral gene encoding a bi-functional galactokinase and co-inducer protein molecule has become subfunctionalized as paralogous genes (GAL1 and GAL3) in Saccharomyces cerevisiae, with most fitness gains being attributable to changes in cis- regulatory elements. However, the quantitative functional implications of the evolutionary changes in this regulatory network remain unexplored. Results We develop a modeling framework to examine the evolution of the GAL regulatory network. This enables us to translate molecular changes in the regulatory network to changes in quantitative network function. We computationally reconstruct an inferred ancestral version of the network and trace the evolutionary paths in the lineage leading to S. cerevisiae. We explore the evolutionary landscape of possible regulatory networks and find that the operation of intermediate networks leading to S. cerevisiae differs substantially depending on the order in which evolutionary changes accumulate; in particular, we systematically explore evolutionary paths and find that some network features cannot be optimized simultaneously. Conclusions We find that a computational modeling approach can be used to analyze the evolution of a well-studied regulatory network. Our results are consistent with several experimental studies of the evolutionary of the GAL regulatory network, including increased fitness in Saccharomyces due to duplication and adaptive regulatory divergence. The conceptual and computational tools that we have developed may be applicable in further studies of regulatory network evolution

Transgenerational Effects of Stress Exposure on Offspring Phenotypes in Apomictic Dandelion

Heritable epigenetic modulation of gene expression is a candidate mechanism to explain parental environmental effects on offspring phenotypes, but current evidence for environment-induced epigenetic changes that persist in offspring generations is scarce. In apomictic dandelions, exposure to various stresses was previously shown to heritably alter DNA methylation patterns. In this study we explore whether these induced changes are accompanied by heritable effects on offspring phenotypes. We observed effects of parental jasmonic acid treatment on offspring specific leaf area and on offspring interaction with a generalist herbivore; and of parental nutrient stress on offspring root-shoot biomass ratio, tissue P-content and leaf morphology. Some of the effects appeared to enhance offspring ability to cope with the same stresses that their parents experienced. Effects differed between apomictic genotypes and were not always consistently observed between different experiments, especially in the case of parental nutrient stress. While this context-dependency of the effects remains to be further clarified, the total set of results provides evidence for the existence of transgenerational effects in apomictic dandelions. Zebularine treatment affected the within-generation response to nutrient stress, pointing at a role of DNA methylation in phenotypic plasticity to nutrient environments. This study shows that stress exposure in apomictic dandelions can cause transgenerational phenotypic effects, in addition to previously demonstrated transgenerational DNA methylation effects

Cryptococcus gattii Virulence Composite: Candidate Genes Revealed by Microarray Analysis of High and Less Virulent Vancouver Island Outbreak Strains

Human and animal cryptococcosis due to an unusual molecular type of Cryptococcus gattii (VGII) emerged recently on Vancouver Island, Canada. Unlike C. neoformans, C. gattii causes disease mainly in immunocompetent hosts, despite producing a similar suite of virulence determinants. To investigate a potential relationship between the regulation of expression of a virulence gene composite and virulence, we took advantage of two subtypes of VGII (a and b), one highly virulent (R265) and one less virulent (R272), that were identified from the Vancouver outbreak. By expression microarray analysis, 202 genes showed at least a 2-fold difference in expression with 108 being up- and 94 being down-regulated in strain R265 compared with strain R272. Specifically, expression levels of genes encoding putative virulence factors (e.g. LAC1, LAC2, CAS3 and MPK1) and genes encoding proteins involved in cell wall assembly, carbohydrate and lipid metabolism were increased in strain R265, whereas genes involved in the regulation of mitosis and ergosterol biosynthesis were suppressed. In vitro phenotypic studies and transcription analysis confirmed the microarray results. Gene disruption of LAC1 and MPK1 revealed defects in melanin synthesis and cell wall integrity, respectively, where CAS3 was not essential for capsule production. Moreover, MPK1 also controls melanin and capsule production and causes a severe attenuation of the virulence in a murine inhalational model. Overall, this study provides the basis for further genetic studies to characterize the differences in the virulence composite of strains with minor evolutionary divergences in gene expression in the primary pathogen C. gattii, that have led to a major invasive fungal infection outbreak

Association Study of Common Genetic Variants and HIV- 1 Acquisition in 6,300 Infected Cases and 7,200 Controls

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6×10−11). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception ofCCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size

Vascular β-amyloid and early astrocyte alterations impair cerebrovascular function and cerebral metabolism in transgenic arcAβ mice

Cerebrovascular lesions related to congophilic amyloid angiopathy (CAA) often accompany deposition of β-amyloid (Aβ) in Alzheimer’s disease (AD), leading to disturbed cerebral blood flow and cognitive dysfunction, posing the question how cerebrovascular pathology contributes to the pathology of AD. To address this question, we characterised the morphology, biochemistry and functionality of brain blood vessels in transgenic arctic β-amyloid (arcAβ) mice expressing human amyloid precursor protein (APP) with both the familial AD-causing Swedish and Arctic mutations; these mice are characterised by strong CAA pathology. Mice were analysed at early, mid and late-stage pathology. Expression of the glucose transporter GLUT1 at the blood–brain barrier (BBB) was significantly decreased and paralleled by impaired in vivo blood-to-brain glucose transport and reduced cerebral lactate release during neuronal activation from mid-stage pathology onwards. Reductions in astrocytic GLUT1 and lactate transporters, as well as retraction of astrocyte endfeet and swelling consistent with neurovascular uncoupling, preceded wide-spread β-amyloid plaque pathology. We show that CAA at later disease stages is accompanied by severe morphological alterations of brain blood vessels including stenoses, BBB leakages and the loss of vascular smooth muscle cells (SMCs). Together, our data establish that cerebrovascular and astrocytic pathology are paralleled by impaired cerebral metabolism in arcAβ mice, and that astrocyte alterations occur already at premature stages of pathology, suggesting that astrocyte dysfunction can contribute to early behavioural and cognitive impairments seen in these mice

Robotic neurorehabilitation: a computational motor learning perspective

Conventional neurorehabilitation appears to have little impact on impairment over and above that of spontaneous biological recovery. Robotic neurorehabilitation has the potential for a greater impact on impairment due to easy deployment, its applicability across of a wide range of motor impairment, its high measurement reliability, and the capacity to deliver high dosage and high intensity training protocols

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

SPACE: the spectroscopic all-sky cosmic explorer

We describe the scientific motivations, the mission concept and the instrumentation of SPACE, a class-M mission proposed for concept study at the first call of the ESA Cosmic-Vision 2015–2025 planning cycle. SPACE aims to produce the largest three-dimensional evolutionary map of the Universe over the past 10 billion years by taking near-IR spectra and measuring redshifts for more than half a billion galaxies at 0 < z < 2 down to AB ∼ 23 over 3π sr of the sky. In addition, SPACE will also target a smaller sky field, performing a deep spectroscopic survey of millions of galaxies to AB ∼ 26 and at 2 < z < 10+. These goals are unreachable with ground-based observations due to the ≈500 times higher sky background (see e.g. Aldering, LBNL report number LBNL-51157, 2001). To achieve the main science objectives, SPACE will use a 1.5 m diameter Ritchey- Chretien telescope equipped with a set of arrays of Digital Micro-mirror Devices covering a total field of view of 0.4 deg2, and will perform large-multiplexing multi-object spectroscopy (e.g. ≈6000 targets per pointing) at a spectral resolution of R∼400 as well as diffraction-limited imaging with continuous coverage from 0.8 to 1.8 μm. Owing to the depth, redshift range, volume coverage and quality of its spectra, SPACE will reveal with unique sensitivity most of the fundamental cosmological signatures, including the power spectrum of density fluctuations and its turnover. SPACE will also place high accuracy constraints on the dark energy equation of state parameter and its evolution by measuring the baryonic acoustic oscillations imprinted when matter and radiation decoupled, the distanceluminosity relation of cosmological supernovae, the evolution of the cosmic expansion rate, the growth rate of cosmic large-scale structure, and high-z galaxy clusters. The datasets from the SPACE mission will represent a long lasting legacy for the whole astronomical community whose data will be mined for many years to come

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible