Spatio-Temporal Variations of Atmospheric NH3 over East Asia by Comparison of Chemical Transport Model Results, Satellite Retrievals and Surface Observations

Atmospheric ammonia (NH3) plays an important role in the formation of secondary inorganic aerosols, the neutralization of acid rain, and the deposition to ecosystems, but has not been well understood yet, especially over East Asia. Based on the GEOS-Chem model results, the IASI satellite retrievals, the in-site surface observations of a nationwide filter pack (FP) network over Japan and the long-term high resolution online NH3 measurements at Fukuoka of western Japan, the spatio-temporal distributions of atmospheric NH3 over East Asia was analyzed comprehensively. A significant seasonal variation with a summer peak was found in all datasets. Comparison between the satellite retrievals and model simulations indicated that the IASI NH3 vertical column density (VCD) showed good consistency with GEOS-Chem results over North and central China, but had large differences over South China due to the effect of clouds. Over the Japan area, GEOS-Chem simulated NH3 concentrations successfully reproduced the spatio-temporal variations compared with in-situ observations, while IASI NH3 VCD retrievals were below or near the detection limit and difficult to obtain a reasonable correlation for with model results. The comprehensive analysis indicated that there were still some differences among different datasets, and more in-situ observations, improved satellite retrievals, and high-resolution model simulations with more accurate emissions are necessary for better understanding the atmospheric NH3 over East Asia

Linked alterations in gray and white matter morphology in adults with high-functioning autism spectrum disorder: A multimodal brain imaging study

Growing evidence suggests that a broad range of behavioral anomalies in people with autism spectrum disorder (ASD) can be linked with morphological and functional alterations in the brain. However, the neuroanatomical underpinnings of ASD have been investigated using either structural magnetic resonance imaging (MRI) or diffusion tensor imaging (DTI), and the relationships between abnormalities revealed by these two modalities remain unclear. This study applied a multimodal data-fusion method, known as linked independent component analysis (ICA), to a set of structural MRI and DTI data acquired from 46 adult males with ASD and 46 matched controls in order to elucidate associations between different aspects of atypical neuroanatomy of ASD. Linked ICA identified two composite components that showed significant between-group differences, one of which was significantly correlated with age. In the other component, participants with ASD showed decreased gray matter (GM) volumes in multiple regions, including the bilateral fusiform gyri, bilateral orbitofrontal cortices, and bilateral pre- and post-central gyri. These GM changes were linked with a pattern of decreased fractional anisotropy (FA) in several white matter tracts, such as the bilateral inferior longitudinal fasciculi, bilateral inferior fronto-occipital fasciculi, and bilateral corticospinal tracts. Furthermore, unimodal analysis for DTI data revealed significant reductions of FA along with increased mean diffusivity in those tracts for ASD, providing further evidence of disrupted anatomical connectivity. Taken together, our findings suggest that, in ASD, alterations in different aspects of brain morphology may co-occur in specific brain networks, providing a comprehensive view for understanding the neuroanatomy of this disorder

Altered Network Topologies and Hub Organization in Adults with Autism: A Resting-State fMRI Study

<div><p>Recent functional magnetic resonance imaging (fMRI) studies on autism spectrum condition (ASC) have identified dysfunctions in specific brain networks involved in social and non-social cognition that persist into adulthood. Although increasing numbers of fMRI studies have revealed atypical functional connectivity in the adult ASC brain, such functional alterations at the network level have not yet been fully characterized within the recently developed graph-theoretical framework. Here, we applied a graph-theoretical analysis to resting-state fMRI data acquired from 46 adults with ASC and 46 age- and gender-matched controls, to investigate the topological properties and organization of autistic brain network. Analyses of global metrics revealed that, relative to the controls, participants with ASC exhibited significant decreases in clustering coefficient and characteristic path length, indicating a shift towards randomized organization. Furthermore, analyses of local metrics revealed a significantly altered organization of the hub nodes in ASC, as shown by analyses of hub disruption indices using multiple local metrics and by a loss of “hubness” in several nodes (e.g., the bilateral superior temporal sulcus, right dorsolateral prefrontal cortex, and precuneus) that are critical for social and non-social cognitive functions. In particular, local metrics of the anterior cingulate cortex consistently showed significant negative correlations with the Autism-Spectrum Quotient score. Our results demonstrate altered patterns of global and local topological properties that may underlie impaired social and non-social cognition in ASC.</p></div

Hub nodes identified using the bootstrap method.

<p>The first row shows five NC-specific hubs (A), the second row shows six ASC-specific hubs (B), and the last row shows four common hubs (C). Hub distribution was visualized with the BrainNet Viewer (<a href="http://www.nitrc.org/projects/bnv/" target="_blank">http://www.nitrc.org/projects/bnv/</a>). Correspondences between colors and networks are as follows: fronto-parietal = red; cingulo-opercular = green; default mode = blue; occipital = cyan; sensorimotor = magenta.</p

Between-group differences in the AUC values of assortativity, <i>r</i>; clustering coefficient, <i>C</i>; characteristic path length, <i>L</i>; and small-worldness scalar, σ.

<p>In the AUC analyses, participants in the ASC group (black) also showed significantly lower <i>r</i> (<i>p</i> = 0.013) (A), <i>C</i> (<i>p</i> = 0.014) (B), and <i>L</i> (<i>p</i> = 0.002) (C) than those in the NC group (white), whereas there were no significant differences in the small-worldness scalar σ (D) between the groups. The error bar indicates the standard error of the mean (SEM). Significance levels are represented by *<i>p</i><0.05 and **<i>p</i><0.01, respectively.</p

The number of affected nodes (NC>ASC or ASC>NC) and non-affected nodes.

†<p>The numbers in parentheses indicate the number of nodes in each sub-network.</p>††<p>The percentages in parentheses indicate the proportion of affected (or non-affected) nodes to the total number of nodes in each sub-network.</p><p>FP: fronto-parietal, CO: cingulo-opercular, DEF: default-mode, OC: occipital, SE: sensorimotor, CER: cerebellar.</p

Global metrics of the assortativity, <i>r</i>; clustering coefficient, <i>C</i>; characteristic path length, <i>L</i>; and small-worldness scalar, σ as functions of the sparsity threshold.

<p>The ASC group (red line) exhibited lower <i>C</i> (B) and <i>L</i> (C) than the NC group (blue) over the range of sparsity thresholds (<i>p</i><0.05, FDR corrected), while σ was comparable between groups (D). In addition, <i>r</i> was significantly lower in participants with ASC than in NCs over 33.9% of sparsity threshold values (A). The error bar indicates the standard error of the mean (SEM).</p

Demographics and rating scale of the participants.

<p>NC: normal control, ASC: autism spectrum condition, s.d.: standard deviation, <i>N</i>: the sample size for each of demographic information, AQ: Autism Spectrum Quotient.</p