192 research outputs found

    Characterisation of the photolytic HONO-source in the atmosphere simulation chamber SAPHIR

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    HONO formation has been proposed as an important OH radical source in simulation chambers for more than two decades. Besides the heterogeneous HONO formation by the dark reaction of NO<sub>2</sub> and adsorbed water, a photolytic source has been proposed to explain the elevated reactivity in simulation chamber experiments. However, the mechanism of the photolytic process is not well understood so far. As expected, production of HONO and NO<sub>x</sub> was also observed inside the new atmospheric simulation chamber SAPHIR under solar irradiation. This photolytic HONO and NO<sub>x</sub> formation was studied with a sensitive HONO instrument under reproducible controlled conditions at atmospheric concentrations of other trace gases. It is shown that the photolytic HONO source in the SAPHIR chamber is not caused by NO<sub>2</sub> reactions and that it is the only direct NO<sub>y</sub> source under illuminated conditions. In addition, the photolysis of nitrate which was recently postulated for the observed photolytic HONO formation on snow, ground, and glass surfaces, can be excluded in the chamber. A photolytic HONO source at the surface of the chamber is proposed which is strongly dependent on humidity, on light intensity, and on temperature. An empirical function describes these dependencies and reproduces the observed HONO formation rates to within 10%. It is shown that the photolysis of HONO represents the dominant radical source in the SAPHIR chamber for typical tropospheric O<sub>3</sub>/H<sub>2</sub>O concentrations. For these conditions, the HONO concentrations inside SAPHIR are similar to recent observations in ambient air

    Fast and Compact Distributed Verification and Self-Stabilization of a DFS Tree

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    We present algorithms for distributed verification and silent-stabilization of a DFS(Depth First Search) spanning tree of a connected network. Computing and maintaining such a DFS tree is an important task, e.g., for constructing efficient routing schemes. Our algorithm improves upon previous work in various ways. Comparable previous work has space and time complexities of O(nlogΔ)O(n\log \Delta) bits per node and O(nD)O(nD) respectively, where Δ\Delta is the highest degree of a node, nn is the number of nodes and DD is the diameter of the network. In contrast, our algorithm has a space complexity of O(logn)O(\log n) bits per node, which is optimal for silent-stabilizing spanning trees and runs in O(n)O(n) time. In addition, our solution is modular since it utilizes the distributed verification algorithm as an independent subtask of the overall solution. It is possible to use the verification algorithm as a stand alone task or as a subtask in another algorithm. To demonstrate the simplicity of constructing efficient DFS algorithms using the modular approach, We also present a (non-sielnt) self-stabilizing DFS token circulation algorithm for general networks based on our silent-stabilizing DFS tree. The complexities of this token circulation algorithm are comparable to the known ones

    Self-stabilizing algorithms for Connected Vertex Cover and Clique decomposition problems

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    In many wireless networks, there is no fixed physical backbone nor centralized network management. The nodes of such a network have to self-organize in order to maintain a virtual backbone used to route messages. Moreover, any node of the network can be a priori at the origin of a malicious attack. Thus, in one hand the backbone must be fault-tolerant and in other hand it can be useful to monitor all network communications to identify an attack as soon as possible. We are interested in the minimum \emph{Connected Vertex Cover} problem, a generalization of the classical minimum Vertex Cover problem, which allows to obtain a connected backbone. Recently, Delbot et al.~\cite{DelbotLP13} proposed a new centralized algorithm with a constant approximation ratio of 22 for this problem. In this paper, we propose a distributed and self-stabilizing version of their algorithm with the same approximation guarantee. To the best knowledge of the authors, it is the first distributed and fault-tolerant algorithm for this problem. The approach followed to solve the considered problem is based on the construction of a connected minimal clique partition. Therefore, we also design the first distributed self-stabilizing algorithm for this problem, which is of independent interest

    Empowering Reentrant Projections from V5 to V1 Boosts Sensitivity to Motion

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    Evidence from macaques [1] and humans [2, 3] has shown that back projections from extrastriate areas to the primary visual area (V1) determine whether visual awareness will arise. For example, reentrant projections from the visual motion area (V5) to V1 are considered to be critical for awareness of motion [2, 3]. If these projections are also instrumental to functional processing of moving stimuli [4–8], then increasing synaptic efficacy in V5-V1 connections should induce functionally relevant short-term plastic changes, resulting in enhanced perception of visual motion. Using transcranial magnetic stimulation (TMS), we applied a novel cortico-cortical paired associative stimulation (ccPAS) protocol to transiently enhance visual motion sensitivity and demonstrate both the functional relevance of V5-V1 reentrant projections to motion perception and their plasticity. Specifically, we found that ccPAS aimed at strengthening reentrant connectivity from V5 to V1 (but not in the opposite direction) enhanced the human ability to perceive coherent visual motion. This perceptual enhancement followed the temporal profile of Hebbian plasticity [9–18] and was observed only when an optimal timing of 20 ms between TMS pulses [2, 3, 5, 6] was used, not when TMS pulses were delivered synchronously. Thus, plastic change is critically dependent on both the direction and timing of connectivity; if either of these requirements was not met, perceptual enhancement did not take place. We therefore provide novel causal evidence that V5-V1 back projections, instrumental to motion perception, are functionally malleable. These findings have implications for theoretical models of visual awareness and for the rehabilitation of visual deficits

    Macrophage Inhibitory Cytokine 1 (MIC-1/GDF15) Decreases Food Intake, Body Weight and Improves Glucose Tolerance in Mice on Normal & Obesogenic Diets

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    Food intake and body weight are controlled by a variety of central and peripheral factors, but the exact mechanisms behind these processes are still not fully understood. Here we show that that macrophage inhibitory cytokine-1 (MIC-1/GDF15), known to have anorexigenic effects particularly in cancer, provides protection against the development of obesity. Both under a normal chow diet and an obesogenic diet, the transgenic overexpression of MIC-1/GDF15 in mice leads to decreased body weight and fat mass. This lean phenotype was associated with decreased spontaneous but not fasting-induced food intake, on a background of unaltered energy expenditure and reduced physical activity. Importantly, the overexpression of MIC-1/GDF15 improved glucose tolerance, both under normal and high fat-fed conditions. Altogether, this work shows that the molecule MIC-1/GDF15 might be beneficial for the treatment of obesity as well as perturbations in glucose homeostasis

    Development of an enzyme-linked immunosorbent assay for the detection of human calretinin in plasma and serum of mesothelioma patients

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    <p>Abstract</p> <p>Background</p> <p>Calretinin is one of the well-established immunohistochemical markers in the diagnostics of malignant mesothelioma (MM). Its utility as a diagnostic tool in human blood, however, is scarcely investigated. The aim of this study was to develop an enzyme-linked immunosorbent assay (ELISA) for human calretinin in blood and to assess its usefulness as a potential minimally invasive diagnostic marker for MM.</p> <p>Methods</p> <p>Initially, attempts were made to establish an assay using commercially available antibodies and to optimize it by including a biotin-streptavidin complex into the assay protocol. Subsequently, a novel ELISA based on polyclonal antibodies raised in rabbit immunized with human recombinant calretinin was developed. The assay performance in human serum and plasma (EDTA/heparin) and the influence of calcium concentrations on antibody recognition were studied. Stability of spiked-in calretinin in EDTA plasma under different storage conditions was also examined. In preliminary studies serum and plasma samples from 97 healthy volunteers, 35 asbestos-exposed workers, and 42 MM patients were analyzed.</p> <p>Results</p> <p>The mean detection range of the new ELISA was 0.12 to 8.97 ng/ml calretinin. The assay demonstrated markedly lower background and significantly higher sensitivity compared to the initially contrived assay that used commercial antibodies. Recovery rate experiments confirmed dependence of calretinin antibody recognition on calcium concentration. Calcium adjustment is necessary for calretinin measurement in EDTA plasma. Spiked-in calretinin revealed high stability in EDTA plasma when stored at room temperature, 4°C, or after repeated freeze/thaw cycles. Median calretinin values in healthy volunteers, asbestos workers, and MM patients were 0.20, 0.33, and 0.84 ng/ml, respectively (p < 0.0001 for healthy vs. MM, p = 0.0036 for healthy vs. asbestos-exposed, p < 0.0001 for asbestos-exposed vs. MM). Median values in patients with epithelioid and biphasic MM were similar. No influence of age, gender, smoking status, or type of medium (plasma/serum) on calretinin values was found.</p> <p>Conclusions</p> <p>The novel assay is highly sensitive and applicable to human serum and plasma. Calretinin appears to be a promising marker for the blood-based detection of MM and might complement other markers. However, further studies are required to prove its usefulness in the diagnosis of MM patients.</p

    Identification of miRNA-103 in the Cellular Fraction of Human Peripheral Blood as a Potential Biomarker for Malignant Mesothelioma – A Pilot Study

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    Background: To date, no biomarkers with reasonable sensitivity and specificity for the early detection of malignant mesothelioma have been described. The use of microRNAs (miRNAs) as minimally-invasive biomarkers has opened new opportunities for the diagnosis of cancer, primarily because they exhibit tumor-specific expression profiles and have been commonly observed in blood of both cancer patients and healthy controls. The aim of this pilot study was to identify miRNAs in the cellular fraction of human peripheral blood as potential novel biomarkers for the detection of malignant mesothelioma. Methodology/Principal Findings: Using oligonucleotide microarrays for biomarker identification the miRNA levels in the cellular fraction of human peripheral blood of mesothelioma patients and asbestos-exposed controls were analyzed. Using a threefold expression change in combination with a significance level of p,0.05, miR-103 was identified as a potential biomarker for malignant mesothelioma. Quantitative real-time PCR (qRT-PCR) was used for validation of miR-103 in 23 malignant mesothelioma patients, 17 asbestos-exposed controls, and 25 controls from the general population. For discrimination of mesothelioma patients from asbestos-exposed controls a sensitivity of 83 % and a specificity of 71 % were calculated, and for discrimination of mesothelioma patients from the general population a sensitivity of 78 % and a specificity of 76%

    Performance of Survivin mRNA as a Biomarker for Bladder Cancer in the Prospective Study UroScreen

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    BACKGROUND: Urinary biomarkers have the potential to improve the early detection of bladder cancer. Most of the various known markers, however, have only been evaluated in studies with cross-sectional design. For proper validation a longitudinal design would be preferable. We used the prospective study UroScreen to evaluate survivin, a potential biomarker that has multiple functions in carcinogenesis. METHODS/RESULTS: Survivin was analyzed in 5,716 urine samples from 1,540 chemical workers previously exposed to aromatic amines. The workers participated in a surveillance program with yearly examinations between 2003 and 2010. RNA was extracted from urinary cells and survivin was determined by Real-Time PCR. During the study, 19 bladder tumors were detected. Multivariate generalized estimation equation (GEE) models showed that β-actin, representing RNA yield and quality, had the strongest influence on survivin positivity. Inflammation, hematuria and smoking did not confound the results. Survivin had a sensitivity of 21.1% for all and 36.4% for high-grade tumors. Specificity was 97.5%, the positive predictive value (PPV) 9.5%, and the negative predictive value (NPV) 99.0%. CONCLUSIONS: In this prospective and so far largest study on survivin, the marker showed a good NPV and specificity but a low PPV and sensitivity. This was partly due to the low number of cases, which limits the validity of the results. Compliance, urine quality, problems with the assay, and mRNA stability influenced the performance of survivin. However, most issues could be addressed with a more reliable assay in the future. One important finding is that survivin was not influenced by confounders like inflammation and exhibited a relatively low number of false-positives. Therefore, despite the low sensitivity, survivin may still be considered as a component of a multimarker panel

    Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS)

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    BACKGROUND: Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis. METHODS: Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we investigated whether demographic, clinical and conventional MRI markers at baseline were predictive for CI and longitudinal cognitive changes. RESULTS: At baseline, 22% of patients had CI (impairment in ≥2 cognitive domains) with highest frequencies and severity in processing speed and executive functions. Demographics (fewer years of academic education, higher age, male sex), clinical (EDSS, depressive symptoms) but no conventional MRI characteristics were linked to baseline CI. At follow-up, only 14% of patients showed CI suggesting effects of retesting. Neither baseline characteristics nor initiation of treatment between baseline and follow-up was able to predict cognitive changes within the follow-up period of 1 year. CONCLUSIONS: Identification of risk factors for short-term cognitive change in newly diagnosed MS or CIS is insufficient using only demographic, clinical and conventional MRI data. Change-sensitive, re-test reliable cognitive tests and more sophisticated predictors need to be employed in future clinical trials and cohort studies of early-stage MS to improve prediction
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