Tropospheric HONO distribution and chemistry in the southeastern US

Here we report the measurement results of nitrous acid (HONO) and a suite of relevant parameters on the NCAR C-130 research aircraft in the southeastern US during the NOMADSS 2013 summer field study. The daytime HONO concentration ranged from low parts per trillion by volume (pptv) in the free troposphere (FT) to mostly within 5-15 pptv in the background planetary boundary layer (PBL). There was no discernible vertical HONO gradient above the lower flight altitude of 300m in the PBL, and the transport of ground surface HONO was not found to be a significant contributor to the tropospheric HONO budget. The total in situ HONO source mean (+/- 1 SD) was calculated as 53 (+/- 21) pptv h(-1) during the day. The upper-limit contribution from NOx-related reactions was 10 (+/- 5) pptv h(-1), and the contribution from photolysis of particulate nitrate (pNO(3)) was 38 (+/- 23) pptv h(-1), based on the measured pNO(3) concentrations and the median pNO(3) photolysis rate constant of 2.0 x 10 4 s(-1) determined in the laboratory using ambient aerosol samples. The photolysis of HONO contributed to less than 10% of the primary OH source. However, a recycling NOx source via pNO(3) photolysis was equivalent to similar to 2.3 x 10(-6) molm(-2) h(-1) in the air column within the PBL, a considerable supplementary NOx source in the low-NOx background area. Up to several tens of parts per trillion by volume of HONO were observed in power plant and urban plumes during the day, mostly produced in situ from precursors including NOx and pNO(3). Finally, there was no observable accumulation of HONO in the nocturnal residual layer and the nocturnal FT in the background southeastern US, with an increase in the HONO / NOx ratio ofPeer reviewe

Visualization of mouse barrel cortex using ex-vivo track density imaging

We describe the visualization of the barrel cortex of the primary somatosensory area (S1) of ex vivo adult mouse brain with short-tracks track density imaging (stTDI). stTDI produced much higher definition of barrel structures than conventional fractional anisotropy (FA), directionally-encoded color FA maps, spin-echo and T2-weighted imaging and gradient echo Ti/T2*-weighted imaging. 3D high angular resolution diffusion imaging (HARDI) data were acquired at 48 micron isotropic resolution for a (3 mm)3 block of cortex containing the barrel field and reconstructed using stTDI at 10 micron isotropic resolution. HARDI data were also acquired at 100 micron isotropic resolution to image the whole brain and reconstructed using stTDI at 20 micron isotropic resolution. The 10 micron resolution stTDI maps showed exceptionally clear delineation of barrel structures. Individual barrels could also be distinguished in the 20 micron stTDI maps but the septa separating the individual barrels appeared thicker compared to the 10 micron maps, indicating that the ability of stTDI to produce high quality structural delineation is dependent upon acquisition resolution. Close homology was observed between the barrel structure delineated using stTDI and reconstructed histological data from the same samples. stTDI also detects barrel deletions in the posterior medial barrel sub-field in mice with infraorbital nerve cuts. The results demonstrate that stTDI is a novel imaging technique that enables three-dimensional characterization of complex structures such as the barrels in S1 and provides an important complementary non-invasive imaging tool for studying synaptic connectivity, development and plasticity of the sensory system. (C) 2013 Elsevier Inc. All rights reserved

Why do models overestimate surface ozone in the Southeast United States?

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx  ≡  NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°  ×  0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30–60 %, dependent on the assumption of the contribution by soil NOx emissions. Upper-tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 6 ± 14 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer

Proton-Binding Sites of Acid-Sensing Ion Channel 1

Acid-sensing ion channels (ASICs) are proton-gated cation channels that exist throughout the mammalian central and peripheral nervous systems. ASIC1 is the most abundant of all the ASICs and is likely to modulate synaptic transmission. Identifying the proton-binding sites of ASCI1 is required to elucidate its pH-sensing mechanism. By using the crystal structure of ASIC1, the protonation states of each titratable site of ASIC1 were calculated by solving the Poisson-Boltzmann equation under conditions wherein the protonation states of all these sites are simultaneously in equilibrium. Four acidic-acidic residue pairs—Asp238-Asp350, Glu220-Asp408, Glu239-Asp346, and Glu80-Glu417—were found to be highly protonated. In particular, the Glu80-Glu417 pair in the inner pore was completely protonated and possessed 2 H+, implying its possible importance as a proton-binding site. The pKa of Glu239, which forms a pair with a possible pH-sensing site Asp346, differs among each homo-trimer subunit due to the different H-bond pattern of Thr237 in the different protein conformations of the subunits. His74 possessed a pKa of ≈6–7. Conservation of His74 in the proton-sensitive ASIC3 that lacks a residue corresponding to Asp346 may suggest its possible pH-sensing role in proton-sensitive ASICs

An analysis of fast photochemistry over high northern latitudes during spring and summer using in-situ observations from ARCTAS and TOPSE

Observations of chemical constituents and meteorological quantities obtained during the two Arctic phases of the airborne campaign ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) are analyzed using an observationally constrained steady state box model. Measurements of OH and HO<sub>2</sub> from the Penn State ATHOS instrument are compared to model predictions. Forty percent of OH measurements below 2 km are at the limit of detection during the spring phase (ARCTAS-A). While the median observed-to-calculated ratio is near one, both the scatter of observations and the model uncertainty for OH are at the magnitude of ambient values. During the summer phase (ARCTAS-B), model predictions of OH are biased low relative to observations and demonstrate a high sensitivity to the level of uncertainty in NO observations. Predictions of HO<sub>2</sub> using observed CH<sub>2</sub>O and H<sub>2</sub>O<sub>2</sub> as model constraints are up to a factor of two larger than observed. A temperature-dependent terminal loss rate of HO<sub>2</sub> to aerosol recently proposed in the literature is shown to be insufficient to reconcile these differences. A comparison of ARCTAS-A to the high latitude springtime portion of the 2000 TOPSE campaign (Tropospheric Ozone Production about the Spring Equinox) shows similar meteorological and chemical environments with the exception of peroxides; observations of H<sub>2</sub>O<sub>2</sub> during ARCTAS-A were 2.5 to 3 times larger than those during TOPSE. The cause of this difference in peroxides remains unresolved and has important implications for the Arctic HO<sub>x</sub> budget. Unconstrained model predictions for both phases indicate photochemistry alone is unable to simultaneously sustain observed levels of CH<sub>2</sub>O and H<sub>2</sub>O<sub>2</sub>; however when the model is constrained with observed CH<sub>2</sub>O, H<sub>2</sub>O<sub>2</sub> predictions from a range of rainout parameterizations bracket its observations. A mechanism suitable to explain observed concentrations of CH<sub>2</sub>O is uncertain. Free tropospheric observations of acetaldehyde (CH<sub>3</sub>CHO) are 2–3 times larger than its predictions, though constraint of the model to those observations is sufficient to account for less than half of the deficit in predicted CH<sub>2</sub>O. The box model calculates gross O<sub>3</sub> formation during spring to maximize from 1–4 km at 0.8 ppbv d<sup>−1</sup>, in agreement with estimates from TOPSE, and a gross production of 2–4 ppbv d<sup>−1</sup> in the boundary layer and upper troposphere during summer. Use of the lower observed levels of HO<sub>2</sub> in place of model predictions decreases the gross production by 25–50%. Net O<sub>3</sub> production is near zero throughout the ARCTAS-A troposphere, and is 1–2 ppbv in the boundary layer and upper altitudes during ARCTAS-B

The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma

Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach

Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoner's dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well

Efficient Analysis of High Dimensional Data in Tensor Formats

In this article we introduce new methods for the analysis of high dimensional data in tensor formats, where the underling data come from the stochastic elliptic boundary value problem. After discretisation of the deterministic operator as well as the presented random fields via KLE and PCE, the obtained high dimensional operator can be approximated via sums of elementary tensors. This tensors representation can be effectively used for computing different values of interest, such as maximum norm, level sets and cumulative distribution function. The basic concept of the data analysis in high dimensions is discussed on tensors represented in the canonical format, however the approach can be easily used in other tensor formats. As an intermediate step we describe efficient iterative algorithms for computing the characteristic and sign functions as well as pointwise inverse in the canonical tensor format. Since during majority of algebraic operations as well as during iteration steps the representation rank grows up, we use lower-rank approximation and inexact recursive iteration schemes

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases