Tobacco Xenobiotics Release Nitric Oxide

Many xenobiotic compounds exert their actions through the release of free radicals and related oxidants [1,2], bringing about unwanted biological effects [3]. Indeed, oxidative events may play a significant role in tobacco toxicity from cigarette smoke. Here, we demonstrate the direct in vitro release of the free radical nitric oxide (•NO) from extracts and components of smokeless tobacco, including nicotine, nitrosonornicotine (NNN) and 4-(methyl-N-nitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in phosphate buffered saline and human saliva using electron spin resonance and chemiluminescence detection. Our findings suggest that tobacco xenobiotics represent as yet unrecognized sources of •NO in the body

On the Application of a Monolithic Array for Detecting Intensity-Correlated Photons Emitted by Different Source Types

It is not widely appreciated that many subtleties are involved in the accurate measurement of intensity-correlated photons; even for the original experiments of Hanbury Brown and Twiss (HBT). Using a monolithic 4x4 array of single-photon avalanche diodes (SPADs), together with an off-chip algorithm for processing streaming data, we investigate the difficulties of measuring second-order photon correlations g2 in a wide variety of light fields that exhibit dramatically different correlation statistics: a multimode He-Ne laser, an incoherent intensity-modulated lamp-light source and a thermal light source. Our off-chip algorithm treats multiple photon-arrivals at pixel-array pairs, in any observation interval, with photon fluxes limited by detector saturation, in such a way that a correctly normalized g2 function is guaranteed. The impact of detector background correlations between SPAD pixels and afterpulsing effects on second-order coherence measurements is discussed. These results demonstrate that our monolithic SPAD array enables access to effects that are otherwise impossible to measure with stand-alone detectors.Comment: 17 pages, 6 figure

How contemporary bioclimatic and human controls change global fire regimes

Anthropogenically driven declines in tropical savannah burnt area have recently received attention due to their effect on trends in global burnt area. Large-scale trends in ecosystems where vegetation has adapted to infrequent fire, especially in cooler and wetter forested areas, are less well understood. Here, small changes in fire regimes can have a substantial impact on local biogeochemistry. To investigate trends in fire across a wide range of ecosystems, we used Bayesian inference to quantify four primary controls on burnt area: fuel continuity, fuel moisture, ignitions and anthropogenic suppression. We found that fuel continuity and moisture are the dominant limiting factors of burnt area globally. Suppression is most important in cropland areas, whereas savannahs and boreal forests are most sensitive to ignitions. We quantify fire regime shifts in areas with more than one, and often counteracting, trends in these controls. Forests are of particular concern, where we show average shifts in controls of 2.3–2.6% of their potential maximum per year, mainly driven by trends in fuel continuity and moisture. This study gives added importance to understanding long-term future changes in the controls on fire and the effect of fire trends on ecosystem function

Pigment Epithelium–Derived Factor Regulates Lipid Metabolism via Adipose Triglyceride Lipase

OBJECTIVE: Pigment epithelium-derived factor (PEDF) is an adipocyte-secreted factor involved in the development of insulin resistance in obesity. Previous studies have identified PEDF as a regulator of triacylglycerol metabolism in the liver that may act through adipose triglyceride lipase (ATGL). We used ATGL(-/-) mice to determine the role of PEDF in regulating lipid and glucose metabolism. RESEARCH DESIGN AND METHODS: Recombinant PEDF was administered to ATGL(-/-) and wild-type mice, and whole-body energy metabolism was studied by indirect calorimetry. Adipose tissue lipolysis and skeletal muscle fatty acid metabolism was determined in isolated tissue preparations. Muscle lipids were assessed by electrospray ionization-tandem mass spectrometry. Whole-body insulin sensitivity and skeletal muscle glucose uptake were assessed. RESULTS: PEDF impaired the capacity to adjust substrate selection, resulting in a delayed diurnal decline in the respiratory exchange ratio, and suppressed daily fatty acid oxidation. PEDF enhanced adipocyte lipolysis and triacylglycerol lipase activity in skeletal muscle. Muscle fatty acid uptake and storage were unaffected, whereas fatty acid oxidation was impaired. These changes in lipid metabolism were abrogated in ATGL(-/-) mice and were not attributable to hypothalamic actions. ATGL(-/-) mice were also refractory to PEDF-mediated insulin resistance, but this was not related to changes in lipid species in skeletal muscle. CONCLUSIONS: The results are the first direct demonstration that 1) PEDF influences systemic fatty acid metabolism by promoting lipolysis in an ATGL-dependent manner and reducing fatty acid oxidation and 2) ATGL is required for the negative effects of PEDF on insulin action

Gene set of nuclear-encoded mitochondrial regulators is enriched for common inherited variation in obesity

There are hints of an altered mitochondrial function in obesity. Nuclear-encoded genes are relevant for mitochondrial function (3 gene sets of known relevant pathways: (1) 16 nuclear regulators of mitochondrial genes, (2) 91 genes for oxidative phosphorylation and (3) 966 nuclear-encoded mitochondrial genes). Gene set enrichment analysis (GSEA) showed no association with type 2 diabetes mellitus in these gene sets. Here we performed a GSEA for the same gene sets for obesity. Genome wide association study (GWAS) data from a case-control approach on 453 extremely obese children and adolescents and 435 lean adult controls were used for GSEA. For independent confirmation, we analyzed 705 obesity GWAS trios (extremely obese child and both biological parents) and a population-based GWAS sample (KORA F4, n = 1,743). A meta-analysis was performed on all three samples. In each sample, the distribution of significance levels between the respective gene set and those of all genes was compared using the leading-edge-fraction-comparison test (cut-offs between the 50(th) and 95(th) percentile of the set of all gene-wise corrected p-values) as implemented in the MAGENTA software. In the case-control sample, significant enrichment of associations with obesity was observed above the 50(th) percentile for the set of the 16 nuclear regulators of mitochondrial genes (p(GSEA,50) = 0.0103). This finding was not confirmed in the trios (p(GSEA,50) = 0.5991), but in KORA (p(GSEA,50) = 0.0398). The meta-analysis again indicated a trend for enrichment (p(MAGENTA,50) = 0.1052, p(MAGENTA,75) = 0.0251). The GSEA revealed that weak association signals for obesity might be enriched in the gene set of 16 nuclear regulators of mitochondrial genes

Validation of the SenseWear armband in circuit resistance training with different loads

The use of the SenseWear™ armband (SWA), an objective monitor of physical activity, is a relatively new device used by researchers to measure energy expenditure. These monitors are practical, relatively inexpensive and easy-to-use. The aim of the present study was to assess the validity of SWAs for the measurement of energy expenditure (EE) in circuit resistance training (CRT) at three different intensities in moderately active, healthy subjects. The study subjects (17 females, 12 males) undertook CRT at 30, 50 and 70% of the 15 repetition maximum for each exercise component wearing an SWA as well as an Oxycon Mobile (OM) portable metabolic system (a gold standard method for measuring EE). The EE rose as exercise intensity increased, but was underestimated by the SWAs. For women, Bland-Altman plots showed a bias of 1.13 ± 1.48 METs and 32.1 ± 34.0 kcal in favour of the OM system, while for men values of 2.33 ± 1.82 METs and 75.8 ± 50.8 kcal were recorded

The status and challenge of global fire modelling

This is the final version of the article. Available from European Geosciences Union / Copernicus Publications via the DOI in this record.The discussion paper version of this article was published in Biogeosciences Discussions on 25 January 2016 and is in ORE at http://hdl.handle.net/10871/34451Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.Stijn Hantson and Almut Arneth acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking fund. The MC-FIRE model development was supported by the global change research programmes of the Biological Resources Division of the US Geological Survey (CA 12681901,112-), the US Department of Energy (LWT-6212306509), the US Forest Service (PNW96–5I0 9 -2-CA), and funds from the Joint Fire Science Program. I. Colin Prentice is supported by the AXA Research Fund under the Chair Programme in Biosphere and Climate Impacts, part of the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Fang Li was funded by the National Natural Science Foundation (grant agreement no. 41475099 and no. 2010CB951801). Jed O. Kaplan was supported by the European Research Council (COEVOLVE 313797). Sam S. Rabin was funded by the National Science Foundation Graduate Research Fellowship, as well as by the Carbon Mitigation Initiative. Allan Spessa acknowledges funding support provided by the Open University Research Investment Fellowship scheme. FireMIP is a non-funded community initiative and participation is open to all. For more information, contact Stijn Hantson ([email protected])

The status and challenge of global fire modelling

This is the discussion paper version of the article. The final published version was published in Biogeosciences Vol. 13 (1), pp. 3359-3375 and is in ORE at http://hdl.handle.net/10871/22886Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.Stijn Hantson and Almut Arneth acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking fund. The MC-FIRE model development was supported by the global change research programmes of the Biological Resources Division of the US Geological Survey (CA 12681901,112-), the US Department of Energy (LWT6212306509), the US Forest Service (PNW96–5I0 9 -2-CA), and funds from the Joint Fire Science Program. I. Colin Prentice is supported by the AXA Research Fund under the Chair Programme in Biosphere and Climate Impacts, part of the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Fang Li was funded by the National Natural Science Foundation (grant agreement no. 41475099 and no. 2010CB951801). Jed O. Kaplan was supported by the European Research Council (COEVOLVE 313797). Sam S. Rabin was funded by the National Science Foundation Graduate Research Fellowship, as well as by the Carbon Mitigation Initiative. Allan Spessa acknowledges funding support provided by the Open University Research Investment Fellowship scheme. FireMIP is a non-funded community initiative and participation is open to all

The role of mTOR and phospho-p70S6K in pathogenesis and progression of gastric carcinomas: an immunohistochemical study on tissue microarray

<p>Abstract</p> <p>Background</p> <p>mTOR signaling pathway and its downstream serine/threonine kinase p70S6k were frequently activated in human cancers. The dysregulation of the mTOR pathway has been found to be a contributing factor of a variety of different cancer. To investigate the role of mTOR signal pathway in the stepwise development of gastric carcinomas, we analyzed the correlations between the mTOR and P70S6K expression and clinic pathological factors and studied its prognostic role in gastric carcinomas.</p> <p>Methods</p> <p>mTOR and phospho-p70S6K proteins were examined by immunohistochemistry on tissue microarray containing gastric carcinomas (n = 412), adenomas (n = 47) and non-neoplastic mucosa (NNM, n = 197) with a comparison of their expression with clinicopathological parameters of carcinomas.</p> <p>Results</p> <p>There was no difference of mTOR expression between these three tissues (p > 0.05). Cytoplasmic phospho(p)-P706SK was highly expressed in adenoma, compared with ANNMs (p < 0.05), whereas its nuclear expression was lower in gastric carcinomas than gastric adenoma and ANNMs (p < 0.05). These three markers were preferably expressed in the older patients with gastric cancer and intestinal-type carcinoma (p < 0.05). mTOR expression was positively correlated with the cytoplasmic and nuclear expression of p-P70S6K(p < 0.05). Nuclear P70S6K was inversely linked to tumor size, depth of invasion, lymph node metastasis and UICC staging (p < 0.05). Univariate analysis indicated that expression of mTOR and nuclear p-P70S6K was closely linked to favorable prognosis of the carcinoma patients (p < 0.05). Multivariate analysis showed that age, depth of invasion, lymphatic invasion, lymph node metastasis, Lauren's classification and mTOR expression were independent prognostic factors for overall gastric carcinomas (p < 0.05).</p> <p>Conclusion</p> <p>Aberrant expression of p-P70S6K possibly contributes to pathogenesis, growth, invasion and metastasis of gastric carcinomas. It was considered as a promising marker to indicate the aggressive behaviors and prognosis of gastric carcinomas.</p

Clinical Predictors of Immune Reconstitution following Combination Antiretroviral Therapy in Patients from the Australian HIV Observational Database

A small but significant number of patients do not achieve CD4 T-cell counts >500 cells/µl despite years of suppressive cART. These patients remain at risk of AIDS and non-AIDS defining illnesses. The aim of this study was to identify clinical factors associated with CD4 T-cell recovery following long-term cART.Patients with the following inclusion criteria were selected from the Australian HIV Observational Database (AHOD): cART as their first regimen initiated at CD4 T-cell count <500 cells/µl, HIV RNA<500 copies/ml after 6 months of cART and sustained for at least 12 months. The Cox proportional hazards model was used to identify determinants associated with time to achieve CD4 T-cell counts >500 cells/µl and >200 cells/µl.501 patients were eligible for inclusion from AHOD (n = 2853). The median (IQR) age and baseline CD4 T-cell counts were 39 (32-47) years and 236 (130-350) cells/µl, respectively. A major strength of this study is the long follow-up duration, median (IQR) = 6.5(3-10) years. Most patients (80%) achieved CD4 T-cell counts >500 cells/µl, but in 8%, this took >5 years. Among the patients who failed to reach a CD4 T-cell count >500 cells/µl, 16% received cART for >10 years. In a multivariate analysis, faster time to achieve a CD4 T-cell count >500 cells/µl was associated with higher baseline CD4 T-cell counts (p<0.001), younger age (p = 0.019) and treatment initiation with a protease inhibitor (PI)-based regimen (vs. non-nucleoside reverse transcriptase inhibitor, NNRTI; p = 0.043). Factors associated with achieving CD4 T-cell counts >200 cells/µl included higher baseline CD4 T-cell count (p<0.001), not having a prior AIDS-defining illness (p = 0.018) and higher baseline HIV RNA (p<0.001).The time taken to achieve a CD4 T-cell count >500 cells/µl despite long-term cART is prolonged in a subset of patients in AHOD. Starting cART early with a PI-based regimen (vs. NNRTI-based regimen) is associated with more rapid recovery of a CD4 T-cell count >500 cells/µl