Higher macrophage superoxide anion production in coronary artery disease (CAD) patients with Type D personality

BACKGROUND Type D personality (Type D) is an independent psychosocial risk factor for poor cardiac prognosis and increased mortality in patients with cardiovascular disease (CVD), but the involved mechanisms are poorly understood. Macrophages play a pivotal role in atherosclerosis, the process underlying coronary artery disease (CAD). We investigated macrophage superoxide anion production in production in CAD patients with and without Type D. METHODS AND RESULTS We studied 20 male CAD patients with Type D (M:66.7±9.9years) and 20 age-matched male CAD patients without Type D (M:67.7±8.5years). Type D was measured using the DS14 questionnaire with the two subscales 'negative affectivity' and 'social inhibition'. We assessed macrophage superoxide anion production using the WST-1 assay. All analyses were controlled for potential confounders. CAD patients with Type D showed higher superoxide anion production compared to CAD patients without Type D (F(1,38)=15.57, p<0.001). Complementary analyses using the Type D subscales 'negative affectivity' and 'social inhibition', and their interaction as continuous measures, showed that both Type D subscales (negative affectivity: (ß=0.48, p=0.002, R(2)=0.227); social inhibition: (ß=0.46, p=0.003, R(2)=0.208)) and their interaction (ß=0.36, p=0.022, R(2)=0.130) were associated with higher WST-1 reduction scores. Results remained significant when controlling for classical CVD risk factors (i.e. body mass index, mean arterial blood pressure), atherosclerosis severity (i.e. intima media thickness, presence of carotid plaques), and psychological factors (depressive symptom severity, chronic stress). CONCLUSIONS Our results indicate higher macrophage superoxide anion production in CAD patients with Type D compared to those without Type D. This may suggest a mechanism contributing to increased morbidity and mortality in CAD patients with Type D.

Calibration of cosmogenic noble gas production based on ³⁶Cl-³⁶Ar ages. Part 2. The ⁸¹Kr-Kr dating technique

We calibrated the ⁸¹Kr-Kr dating system for ordinary chondrites of different sizes using independent shielding-corrected ³⁶Cl-³⁶Ar ages. Krypton concentrations and isotopic compositions were measured in bulk samples from 14 ordinary chondrites of high petrologic type and the cosmogenic Kr component was obtained by subtracting trapped Kr from phase Q. The thus-determined average cosmogenic ⁷⁸Kr/⁸³Kr, ⁸⁰Kr/⁸³Kr, ⁸²Kr/⁸³Kr, and ⁸4Kr/⁸³Kr ratiC(Lavielle and Marti 1988; Wieler 2002). The cosmogenic ⁷⁸Kr/⁸³Kr ratio is correlated with the cosmogenic 22Ne/21Ne ratio, confirming that ⁷⁸Kr/⁸³Kr is a reliable shielding indicator. Previously, ⁸¹Kr-Kr ages have been determined by assuming the cosmogenic production rate of ⁸¹Kr, P(⁸¹Kr)c, to be 0.95 times the average of the cosmogenic production rates of ⁸⁰Kr and ⁸²Kr; the factor Y = 0.95 therefore accounts for the unequal production of the various Kr isotopes (Marti 1967a). However, Y should be regarded as an empirical adjustment. For samples whose ⁸⁰Kr and ⁸²Kr concentrations may be affected by neutron-capture reactions, the shielding-dependent cosmogenic (⁷⁸Kr/⁸³Kr)c ratio has been used instead to calculate P(⁸¹Kr)/P(⁸³Kr), as for some lunar samples, this ratio has been shown to linearly increase with (⁷⁸Kr/⁸³Kr)c (Marti and Lugmair 1971). However, the ⁸¹Kr-Kr ages of our samples calculated with these methods are on average ~30% higher than their ³⁶Cl-³⁶Ar ages, indicating that most if not all the ⁸¹Kr-Kr ages determined so far are significantly too high. We therefore re-evaluated both methods to determine P(⁸¹Kr)c/P(⁸³Kr)c. Our new Y value of 0.70 ± 0.04 is more than 25% lower than the value of 0.95 used so far. Furthermore, together with literature data, our data indicate that for chondrites, P(⁸¹Kr)c/P(⁸³Kr)c is rather constant at 0.43 ± 0.02, at least for the shielding range covered by our samples ([⁷⁸Kr/⁸³Kr]c = 0.119–0.185; [22Ne/21Ne]c = 1.083–1.144), in contrast to the observations on lunar samples. As expected considering the method used, ⁸¹Kr-Kr ages calculated either directly with this new P(⁸¹Kr)c/P(⁸³Kr)c value or with our new Y value both agree with the corresponding ³⁶Cl-³⁶Ar ages. However, the average deviation of 2% indicates the accuracy of both new ⁸¹Kr-Kr dating methods and the precision of the new dating systems of ~10% is demonstrated by the low scatter in the data. Consequently, this study indicates that the ⁸¹Kr-Kr ages published so far are up to 30% too high.

Production of Ethanol from Hardwood

Diminishing crude oil and natural gas supplies, along with concern about greenhouse gas are major driving forces in the search for efficient renewable energy sources. The conversion of lignocellulosic biomass to energy and useful chemicals is a component of the solution. Ethanol is most commonly produced by enzymatic hydrolysis of complex carbohydrates to simple sugars followed by fermentation using yeast. C6Hl0O5 + H2O −Enxymes→ C6H12O6 −Yeast→ 2CH3CH2OH + 2C02 In the U.S. corn is the primary starting raw material for commercial ethanol production. However, there is insufficient corn available to meet the future demand for ethanol as a gasoline additive. Consequently a variety of processes are being developed for producing ethanol from biomass; among which is the NREL process for the production of ethanol from white hardwood. The objective of the thesis reported here was to perform a technical economic analysis of the hardwood to ethanol process. In this analysis a Greenfield plant was compared to co-locating the ethanol plant adjacent to a Kraft pulp mill. The advantage of the latter case is that facilities can be shared jointly for ethanol production and for the production of pulp. Preliminary process designs were performed for three cases; a base case size of 2205 dry tons/day of hardwood (52 million gallons of ethanol per year) as well as the two cases of half and double this size. The thermal efficiency of the NREL process was estimated to be approximately 36%; that is about 36% of the thermal energy in the wood is retained in the product ethanol and by-product electrical energy. The discounted cash flow rate of return on investment and the net present value methods of evaluating process alternatives were used to evaluate the economic feasibility of the NREL process. The minimum acceptable discounted cash flow rate of return after taxes was assumed to be 10%. In all of the process alternatives investigated, the dominant cost factors are the capital recovery charges and the cost of wood. The Greenfield NREL process is not economically viable with the cost of producing ethanol varying from $2.58 to $2.08/gallon for the half capacity and double capacity cases respectively. The co-location cases appear more promising due to reductions in capital costs. The most profitable co-location case resulted in a discounted cash flow rate of return improving from 8.5% for the half capacity case to 20.3% for the double capacity case. Due to economy of scale, the investments become more and more profitable as the size of the plant increases. This concept is limited by the amount of wood that can be delivered to the plant on a sustainable basis as well as the demand for ethanol within a reasonable distance of the plant.

InGen of creative production in the health sciences: A workbook companion to innovation generation

InGen of Creative Production in the Health Sciences is a compendium of innovative thinking exercises for individuals and groups, derived from an eclectic array of practical guides for professionals in a variety of fields. Segmented into five subcategories across twenty two chapters, the effort seeks to make techniques for increasing innovative problem solving more accessible to a diverse audience of problem solvers. The chapters of Roberta Ness. Innovation Generation (2012, Oxford University Press) provide the themes for each of the chapters in the workbook. It is intended that those who read Ness. Innovation Generation will benefit from practicing the constructs of innovative thinking exemplified in each exercise.^ The methods used to gather data, in this case mostly innovative thinking exercises, included literature reviews of existing innovative thinking tools, classroom materials, and theory-driven exploration of exercises to fill in gaps in extant materials. Specifically, Google.com and Amazon.com searches were conducted using the terms “innovation,” “innovative,” “innovator,” “creative,” “novelty,” “thinking,” together with some variance of “book,” “workbook,” and “exercise.” The results were sorted thematically to show correspondence with the themes in Ness (2012) and compared to suggested best practices of 50 years of scientific research on innovative thinking. Where themes were suggested by Ness (2012) and peer-reviewed research on innovation but unavailable in published innovation thinking workbooks, new exercises were developed. The five type subcategories into which these results were organized are: individual direct, individual indirect, group direct, group indirect and probing question. It is anticipated that the five type subcategories and spectrum of themes will equip problem solvers in a variety of capacities.^

Bacterial production in the eastern Mediteranean Sea in October 2008 during SES_GR2

The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Bacterial production was estimated by the 3H-leucine method (Kirchman et al. 1986, Kirchman 1993). At each depth, duplicate samples and a control were incubated with 20 nM L-[4,5 3H]-leucine. Samples were incubated in the dark, at in situ temperature.

Daily polynya area and ice production in the North Water polynya region

The North Water (NOW) Polynya is a regularly-forming area of open-water and thin-ice, located between northwestern Greenland and Ellesmere Island (Canada) at the northern tip of Baffin Bay. Due to its large spatial extent, it is of high importance for a variety of physical and biological processes, especially in wintertime. Here, we present a long-term remote sensing study for the winter seasons 1978/1979 to 2014/2015. Polynya characteristics are inferred from (1) sea ice concentrations and brightness temperatures from passive microwave satellite sensors (Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS)) and (2) thin-ice thickness distributions, which are calculated using MODIS ice-surface temperatures and European Center for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis data in a 1D thermodynamic energy-balance model. Daily ice production rates are retrieved for each winter season from 2002/2003 to 2014/2015, assuming that all heat loss at the ice surface is balanced by ice growth. Two different cloud-cover correction schemes are applied on daily polynya area and ice production values to account for cloud gaps in the MODIS composites. Our results indicate that the NOW polynya experienced significant seasonal changes over the last three decades considering the overall frequency of polynya occurrences, as well as their spatial extent. In the 1980s, there were prolonged periods of a more or less closed ice cover in northern Baffin Bay in winter. This changed towards an average opening on more than 85% of the days between November and March during the last decade. Noticeably, the sea ice cover in the NOW polynya region shows signs of a later-appearing fall freeze-up, starting in the late 1990s. Different methods to obtain daily polynya area using passive microwave AMSR-E/AMSR2 data and SSM/I-SSMIS data were applied. A comparison with MODIS data (thin-ice thickness < 20 cm) shows that the wintertime polynya area estimates derived by MODIS are about 30 to 40% higher than those derived using the polynya signature simulation method (PSSM) with AMSR-E data. In turn, the difference in polynya area between PSSM and a sea ice concentration (SIC) threshold of 70% is fairly low (approximately 10%) when applied to AMSR-E data. For the coarse-resolution SSM/I-SSMIS data, this difference is much larger, particularly in November and December. Instead of a sea ice concentration threshold, the PSSM method should be used for SSM/I-SSMIS data. Depending on the type of cloud-cover correction, the calculated ice production based on MODIS data reaches an average value of 264.4 ± 65.1 km**3 to 275.7 ± 67.4 km**3 (2002/2003 to 2014/2015) and shows a high interannual variability. Our achieved long-term results underline the major importance of the NOW polynya considering its influence on Arctic ice production and associated atmosphere/ocean processes.

Bacterial production in the eastern Mediterranean Sea in March and April 2008 during SES_GR1

The dataset is based on samples collected in the framework of the project SESAME, in the Ionian, Libyan and Aegean Sea during March- April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column. Bacterial production was estimated by the 3H-leucine method (Kirchman et al. 1986, Kirchman 1993). At each depth, duplicate samples and a control were incubated with 20 nM L-[4,5 3H]-leucine. Samples were incubated in the dark, at in situ temperature.