Common climatic signal from glaciers in the European Alps over the last 50 years

Conventional glacier-wide mass balances are commonly used to study the effect of climate forcing on glacier melt. Unfortunately, the glacier-wide mass balances are also influenced by the glacier's dynamic response. Investigations on the effects of climate forcing on glaciers can be largely improved by analyzing point mass balances. Using a statistical model, we have found that 52% of the year-to-year deviations in the point mass balances of six glaciers distributed across the entire European Alps can be attributed to a common variability. Point mass balance changes reveal remarkable regional consistencies reaching 80% for glaciers less than 10 km apart. Compared to the steady state conditions of the 1962–1982 period, the surface mass balance changes are −0.85 m water equivalent (w.e.) a⁻¹ for 1983–2002 and −1.63 m w.e. a⁻¹ for 2003–2013. This indicates a clear and regionally consistent acceleration of mass loss over recent decades over the entire European Alps

The SWAP EUV Imaging Telescope Part I: Instrument Overview and Pre-Flight Testing

The Sun Watcher with Active Pixels and Image Processing (SWAP) is an EUV solar telescope on board ESA's Project for Onboard Autonomy 2 (PROBA2) mission launched on 2 November 2009. SWAP has a spectral bandpass centered on 17.4 nm and provides images of the low solar corona over a 54x54 arcmin field-of-view with 3.2 arcsec pixels and an imaging cadence of about two minutes. SWAP is designed to monitor all space-weather-relevant events and features in the low solar corona. Given the limited resources of the PROBA2 microsatellite, the SWAP telescope is designed with various innovative technologies, including an off-axis optical design and a CMOS-APS detector. This article provides reference documentation for users of the SWAP image data.Comment: 26 pages, 9 figures, 1 movi

Erratum to: Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis

After publication of our article [1], we became aware that there were two minor data loading and analysis scripting errors in the human EEG data processing pipeline. These errors affected the channel loading/grouping and sleep/ wake coding of EEG data. We have re-analysed all the data affected by these errors. The errors do not affect any interpretations or conclusions, thus no changes to the text are required apart from correcting p values and raw values affected by the errors. There are no changes to statistical significance or lack-thereof. The errors affect data presented in Fig. 3, Fig. 4, Fig. 5, and Additional file 3: Figure S3 and thus we have re-plotted these figures (see below)

Interactive comment on “Monitoring water accumulation in a glacier using magnetic resonance imaging” by A. Legchenko et al.

Tête Rousse is a small polythermal glacier located in the Mont Blanc area (French Alps) at an altitude of 3100 to 3300 m. In 1892, an outburst flood from this glacier released about 200 000 m3 of water mixed with ice, causing much damage. A new accumulation of melt water in the glacier was not excluded. The uncertainty related to such glacier conditions initiated an extensive geophysical study for evaluating the hazard. Using three-dimensional surface nuclear magnetic resonance imaging (3-D-SNMR), we showed that the temperate part of the Tête Rousse glacier contains two separate water-filled caverns (central and upper caverns). In 2009, the central cavern contained about 55 000 m3 of water. Since 2010, the cavern is drained every year. We monitored the changes caused by this pumping in the water distribution within the glacier body. Twice a year, we carried out magnetic resonance imaging of the entire glacier and estimated the volume of water accumulated in the central cavern. Our results show changes in cavern geometry and recharge rate: in two years, the central cavern lost about 73% of its initial volume, but 65% was lost in one year after the first pumping. We also observed that, after being drained, the cavern was recharged at an average rate of 20 to 25 m3 d−1 during the winter months and 120 to 180 m3 d−1 in summer. These observations illustrate how ice, water and air may refill englacial volume being emptied by artificial draining. Comparison of the 3-D-SNMR results with those obtained by drilling and pumping showed a very good correspondence, confirming the high reliability of 3-D-SNMR imaging

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

How accurate and statistically robust are catalytic site predictions based on closeness centrality?

<p>Abstract</p> <p>Background</p> <p>We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex <it>i </it>and all other vertices.</p> <p>Results</p> <p>We benchmark the approach against 283 structurally unique proteins within the Catalytic Site Atlas. Our results, which are inline with previous investigations of smaller datasets, indicate closeness centrality predictions are statistically significant. However, unlike previous approaches, we specifically focus on residues with the very best scores. Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the first time) that filtering the predictions by residue identity improves the results even more than accessibility filtering. Here, we simply eliminate residues with physiochemical properties unlikely to be compatible with catalytic requirements from consideration. Residue identity filtering improves the average true to false positive rate ratio to 26.3 to 1. Combining the two filters together has little affect on the results. Calculated p-values for the three prediction schemes range from 2.7E-9 to less than 8.8E-134. Finally, the sensitivity of the predictions to structure choice and slight perturbations is examined.</p> <p>Conclusion</p> <p>Our results resolutely confirm that closeness centrality is a viable prediction scheme whose predictions are statistically significant. Simple filtering schemes substantially improve the method's predicted power. Moreover, no clear effect on performance is observed when comparing ligated and unligated structures. Similarly, the CC prediction results are robust to slight structural perturbations from molecular dynamics simulation.</p

NOMAD spectrometer on the ExoMars trace gas orbiter mission: part 2—design, manufacturing, and testing of the ultraviolet and visible channel

NOMAD is a spectrometer suite on board the ESA/Roscosmos ExoMars Trace Gas Orbiter, which launched in March 2016. NOMAD consists of two infrared channels and one ultraviolet and visible channel, allowing the instrument to perform observations quasi-constantly, by taking nadir measurements at the day- and night-side, and during solar occultations. Here, in part 2 of a linked study, we describe the design, manufacturing, and testing of the ultraviolet and visible spectrometer channel called UVIS. We focus upon the optical design and working principle where two telescopes are coupled to a single grating spectrometer using a selector mechanism

Surface-Enhanced Nitrate Photolysis on Ice

Heterogeneous nitrates photolysis is the trigger for many chemical processes occurring in the polar boundary layer and is widely believed to occur in a quasi-liquid layer (QLL) at the surface of ice. The dipole forbidden character of the electronic transition relevant to boundary layer atmospheric chemistry and the small photolysis/photoproducts quantum yields in ice (and in water) may confer a significant enhancement and interfacial specificity to this important photochemical reaction at the surface of ice. Using amorphous solid water films at cryogenic temperatures as models for the disordered interstitial air/ice interface within the snowpack suppresses the diffusive uptake kinetics thereby prolonging the residence time of nitrate anions at the surface of ice. This approach allows their slow heterogeneous photolysis kinetics to be studied providing the first direct evidence that nitrates adsorbed onto the first molecular layer at the surface of ice are photolyzed more effectively than those dissolved within the bulk. Vibrational spectroscopy allows the ~3-fold enhancement in photolysis rates to be correlated with the nitrates’ distorted intramolecular geometry thereby hinting at the role played by the greater chemical heterogeneity in their solvation environment at the surface of ice than in the bulk. A simple 1D kinetic model suggests 1-that a 3(6)-fold enhancement in photolysis rate for nitrates adsorbed onto the ice surface could increase the photochemical NO[subscript 2] emissions from a 5(8) nm thick photochemically active interfacial layer by 30%(60)%, and 2-that 25%(40%) of the NO[subscript 2] photochemical emissions to the snowpack interstitial air are released from the top-most molecularly thin surface layer on ice. These findings may provide a new paradigm for heterogeneous (photo)chemistry at temperatures below those required for a QLL to form at the ice surface

Cerebrospinal fluid biomarker candidates associated with human WNV neuroinvasive disease

During the last decade, the epidemiology of WNV in humans has changed in the southern regions of Europe, with high incidence of West Nile fever (WNF) cases, but also of West Nile neuroinvasive disease (WNND). The lack of human vaccine or specific treatment against WNV infection imparts a pressing need to characterize indicators associated with neurological involvement. By its intimacy with central nervous system (CNS) structures, modifications in the cerebrospinal fluid (CSF) composition could accurately reflect CNS pathological process. Until now, few studies investigated the association between imbalance of CSF elements and severity of WNV infection. The aim of the present study was to apply the iTRAQ technology in order to identify the CSF proteins whose abundances are modified in patients with WNND. Forty-seven proteins were found modified in the CSF of WNND patients as compared to control groups, and most of them are reported for the first time in the context of WNND. On the basis of their known biological functions, several of these proteins were associated with inflammatory response. Among them, Defensin-1 alpha (DEFA1), a protein reported with anti-viral effects, presente