Ozone and alkyl nitrate formation from the Deepwater Horizon oil spill atmospheric emissions

Ozone (O3), alkyl nitrates (RONO2), and other photochemical products were formed in the atmosphere downwind from the Deepwater Horizon (DWH) oil spill by photochemical reactions of evaporating hydrocarbons with NOx (=NO+NO2) emissions from spill response activities. Reactive nitrogen species and volatile organic compounds (VOCs) were measured from an instrumented aircraft during daytime flights in the marine boundary layer downwind from the area of surfacing oil. A unique VOC mixture, where alkanes dominated the hydroxyl radical (OH) loss rate, was emitted into a clean marine environment, enabling a focused examination of O3 and RONO 2 formation processes. In the atmospheric plume from DWH, the OH loss rate, an indicator of potential O3 formation, was large and dominated by alkanes with between 5 and 10 carbons per molecule (C 5-C10). Observations showed that NOx was oxidized very rapidly with a 0.8h lifetime, producing primarily C6-C10 RONO2 that accounted for 78% of the reactive nitrogen enhancements in the atmospheric plume 2.5h downwind from DWH. Both observations and calculations of RONO2 and O3 production rates show that alkane oxidation dominated O3 formation chemistry in the plume. Rapid and nearly complete oxidation of NOx to RONO2 effectively terminated O3 production, with O3 formation yields of 6.0±0.5 ppbv O3 per ppbv of NOx oxidized. VOC mixing ratios were in large excess of NOx, and additional NOx would have formed additional O3 in this plume. Analysis of measurements of VOCs, O3, and reactive nitrogen species and calculations of O3 and RONO2 production rates demonstrate that NOx-VOC chemistry in the DWH plume is explained by known mechanisms. Copyright 2012 by the American Geophysical Union

Sampling constrained probability distributions using Spherical Augmentation

Statistical models with constrained probability distributions are abundant in machine learning. Some examples include regression models with norm constraints (e.g., Lasso), probit, many copula models, and latent Dirichlet allocation (LDA). Bayesian inference involving probability distributions confined to constrained domains could be quite challenging for commonly used sampling algorithms. In this paper, we propose a novel augmentation technique that handles a wide range of constraints by mapping the constrained domain to a sphere in the augmented space. By moving freely on the surface of this sphere, sampling algorithms handle constraints implicitly and generate proposals that remain within boundaries when mapped back to the original space. Our proposed method, called {Spherical Augmentation}, provides a mathematically natural and computationally efficient framework for sampling from constrained probability distributions. We show the advantages of our method over state-of-the-art sampling algorithms, such as exact Hamiltonian Monte Carlo, using several examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian bridge regression, reconstruction of quantized stationary Gaussian process, and LDA for topic modeling.Comment: 41 pages, 13 figure

Intra-arterial nitroglycerin as directed acute treatment in experimental ischemic stroke

BACKGROUND: Nitroglycerin (also known as glyceryl trinitrate (GTN)), a vasodilator best known for treatment of ischemic heart disease, has also been investigated for its potential therapeutic benefit in ischemic stroke. The completed Efficacy of Nitric Oxide in Stroke trial suggested that GTN has therapeutic benefit with acute (within 6 hours) transdermal systemic sustained release therapy. OBJECTIVE: To examine an alternative use of GTN as an acute therapy for ischemic stroke following successful recanalization. METHODS: We administered GTN IA following transient middle cerebral artery occlusion in mice. Because no standard dose of GTN is available following emergent large vessel occlusion, we performed a dose-response (3.12, 6.25, 12.5, and 25 µg/µL) analysis. Next, we looked at blood perfusion (flow) through the middle cerebral artery using laser Doppler flowmetry. Functional outcomes, including forced motor movement rotor rod, were assessed in the 3.12, 6.25, and 12.5 µg/µL groups. Histological analysis was performed using cresyl violet for infarct volume, and glial fibrillary activating protein (GFAP) and NeuN immunohistochemistry for astrocyte activation and mature neuron survival, respectively. RESULTS: Overall, we found that acute post-stroke IA GTN had little effect on vessel dilatation after 15 min. Functional analysis showed a significant difference between GTN (3.12 and 6.25 µg/µL) and control at post-stroke day 1. Histological measures showed a significant reduction in infarct volume and GFAP immunoreactivity and a significant increase in NeuN. CONCLUSIONS: These results demonstrate that acute IA GTN is neuroprotective in experimental ischemic stroke and warrants further study as a potentially new stroke therapy

Safety and efficacy of fluticasone propionate in the topical treatment of skin diseases

Fluticasone propionate - the first carbothioate corticosteroid - has been classified as a potent anti-inflammatory drug for dermatological use. It is available as 0.05% cream and 0.005% ointment formulations for the acute and maintenance treatment of patients with dermatological disorders such as atopic dermatitis, psoriasis and vitiligo. This glucocorticoid is characterized by high lipophilicity, high glucocorticoid receptor binding and activation, and a rapid metabolic turnover in skin. Although skin blanching following fluticasone propionate exceeds that of corticosteroids of medium strength, several clinical trials demonstrate a low potential for cutaneous and systemic side-effects, even in difficult-to-treat areas like the face, the eyelids and intertriginous areas. Even among paediatric patients with atopic dermatitis, fluticasone propionate proved to be safe and effective. These pharmacological and clinical properties are reflected by the high therapeutic index of this glucocorticoid

SMART: Unique splitting-while-merging framework for gene clustering

Copyright @ 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named “splitting merging awareness tactics” (SMART), which does not require any a priori knowledge of either the number of clusters or even the possible range of this number. Unlike existing self-splitting algorithms, which over-cluster the dataset to a large number of clusters and then merge some similar clusters, our framework has the ability to split and merge clusters automatically during the process and produces the the most reliable clustering results, by intrinsically integrating many clustering techniques and tasks. The SMART framework is implemented with two distinct clustering paradigms in two algorithms: competitive learning and finite mixture model. Nevertheless, within the proposed SMART framework, many other algorithms can be derived for different clustering paradigms. The minimum message length algorithm is integrated into the framework as the clustering selection criterion. The usefulness of the SMART framework and its algorithms is tested in demonstration datasets and simulated gene expression datasets. Moreover, two real microarray gene expression datasets are studied using this approach. Based on the performance of many metrics, all numerical results show that SMART is superior to compared existing self-splitting algorithms and traditional algorithms. Three main properties of the proposed SMART framework are summarized as: (1) needing no parameters dependent on the respective dataset or a priori knowledge about the datasets, (2) extendible to many different applications, (3) offering superior performance compared with counterpart algorithms.National Institute for Health Researc

Subclinical thyroid dysfunction and cognitive decline in old age

<p>Background: Subclinical thyroid dysfunction has been implicated as a risk factor for cognitive decline in old age, but results are inconsistent. We investigated the association between subclinical thyroid dysfunction and cognitive decline in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER).</p> <p>Methods: Prospective longitudinal study of men and women aged 70–82 years with pre-existing vascular disease or more than one risk factor to develop this condition (N = 5,154). Participants taking antithyroid medications, thyroid hormone supplementation and/or amiodarone were excluded. Thyroid function was measured at baseline: subclinical hyper- and hypothyroidism were defined as thyroid stimulating hormones (TSH) <0.45 mU/L or >4.50 mU/L respectively, with normal levels of free thyroxine (FT4). Cognitive performance was tested at baseline and at four subsequent time points during a mean follow-up of 3 years, using five neuropsychological performance tests.</p> <p>Results: Subclinical hyperthyroidism and hypothyroidism were found in 65 and 161 participants, respectively. We found no consistent association of subclinical hyper- or hypothyroidism with altered cognitive performance compared to euthyroid participants on the individual cognitive tests. Similarly, there was no association with rate of cognitive decline during follow-up.</p> <p>Conclusion: We found no consistent evidence that subclinical hyper- or hypothyroidism contribute to cognitive impairment or decline in old age. Although our data are not in support of treatment of subclinical thyroid dysfunction to prevent cognitive dysfunction in later life, only large randomized controlled trials can provide definitive evidence.</p&gt

Atmospheric emissions from the deepwater Horizon spill constrain air-water partitioning, hydrocarbon fate, and leak rate

The fate of deepwater releases of gas and oil mixtures is initially determined by solubility and volatility of individual hydrocarbon species; these attributes determine partitioning between air and water. Quantifying this partitioning is necessary to constrain simulations of gas and oil transport, to predict marine bioavailability of different fractions of the gas-oil mixture, and to develop a comprehensive picture of the fate of leaked hydrocarbons in the marine environment. Analysis of airborne atmospheric data shows massive amounts (∼258,000 kg/day) of hydrocarbons evaporating promptly from the Deepwater Horizon spill; these data collected during two research flights constrain air-water partitioning, thus bioavailability and fate, of the leaked fluid. This analysis quantifies the fraction of surfacing hydrocarbons that dissolves in the water column (∼33% by mass), the fraction that does not dissolve, and the fraction that evaporates promptly after surfacing (∼14% by mass). We do not quantify the leaked fraction lacking a surface expression; therefore, calculation of atmospheric mass fluxes provides a lower limit to the total hydrocarbon leak rate of 32,600 to 47,700 barrels of fluid per day, depending on reservoir fluid composition information. This study demonstrates a new approach for rapid-response airborne assessment of future oil spills. Copyright 2011 by the American Geophysical Union

Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research

Despite the many positive outcomes, excessive mobile phone use is now often associated with potentially harmful and/or disturbing behaviors (e.g., symptoms of deregulated use, negative impact on various aspects of daily life such as relationship problems, and work intrusion). Problematic mobile phone use (PMPU) has generally been considered as a behavioral addiction that shares many features with more established drug addictions. In light of the most recent data, the current paper reviews the validity of the behavioral addiction model when applied to PMPU. On the whole, it is argued that the evidence supporting PMPU as an addictive behavior is scarce. In particular, it lacks studies that definitively show behavioral and neurobiological similarities between mobile phone addiction and other types of legitimate addictive behaviors. Given this context, an integrative pathway model is proposed that aims to provide a theoretical framework to guide future research in the field of PMPU. This model highlights that PMPU is a heterogeneous and multi-faceted condition

The prognosis of allocentric and egocentric neglect : evidence from clinical scans

We contrasted the neuroanatomical substrates of sub-acute and chronic visuospatial deficits associated with different aspects of unilateral neglect using computed tomography scans acquired as part of routine clinical diagnosis. Voxel-wise statistical analyses were conducted on a group of 160 stroke patients scanned at a sub-acute stage. Lesion-deficit relationships were assessed across the whole brain, separately for grey and white matter. We assessed lesions that were associated with behavioural performance (i) at a sub-acute stage (within 3 months of the stroke) and (ii) at a chronic stage (after 9 months post stroke). Allocentric and egocentric neglect symptoms at the sub-acute stage were associated with lesions to dissociated regions within the frontal lobe, amongst other regions. However the frontal lesions were not associated with neglect at the chronic stage. On the other hand, lesions in the angular gyrus were associated with persistent allocentric neglect. In contrast, lesions within the superior temporal gyrus extending into the supramarginal gyrus, as well as lesions within the basal ganglia and insula, were associated with persistent egocentric neglect. Damage within the temporo-parietal junction was associated with both types of neglect at the sub-acute stage and 9 months later. Furthermore, white matter disconnections resulting from damage along the superior longitudinal fasciculus were associated with both types of neglect and critically related to both sub-acute and chronic deficits. Finally, there was a significant difference in the lesion volume between patients who recovered from neglect and patients with chronic deficits. The findings presented provide evidence that (i) the lesion location and lesion size can be used to successfully predict the outcome of neglect based on clinical CT scans, (ii) lesion location alone can serve as a critical predictor for persistent neglect symptoms, (iii) wide spread lesions are associated with neglect symptoms at the sub-acute stage but only some of these are critical for predicting whether neglect will become a chronic disorder and (iv) the severity of behavioural symptoms can be a useful predictor of recovery in the absence of neuroimaging findings on clinical scans. We discuss the implications for understanding the symptoms of the neglect syndrome, the recovery of function and the use of clinical scans to predict outcome