The effect of ozonization on furniture dust: Microbial content and immunotoxicity in vitro

Moisture and mold problems in buildings contaminate also the furniture and other movable property. If cleaning of the contaminated furniture is neglected, it may continue to cause problems to the occupants even after the moisture-damage repairs. The aim of this study was to determine the effectiveness of high-efficiency ozone treatment in cleaning of the furniture from moisture-damaged buildings. In addition, the effectiveness of two cleaning methods was compared. Samples were vacuumed from the padded areas before and after the treatment. The microbial flora and concentrations in the dust sample were determined by quantitative cultivation and QPCR-methods. The immunotoxic potential of the dust samples was analyzed by measuring effects on cell viability and production of inflammatory mediators in vitro. Concentrations of viable microbes decreased significantly in most of the samples after cleaning. Cleaning with combined steam wash and ozonisation was more effective method than ozonising alone, but the difference was not statistically significant. Detection of fungal species with PCR showed a slight but nonsignificant decrease in concentrations after the cleaning. The immunotoxic potential of the collected dust decreased significantly in most of the samples. However, in a small subgroup of samples, increased concentrations of microbes and immunotoxicological activity were detected. This study shows that a transportable cleaning unit with high-efficiency ozonising is in most cases effective in decreasing the concentrations of viable microbes and immunotoxicological activity of the furniture dust. However, the method does not destroy or remove all fungal material present in the dust, as detected with QPCR analysis, and in some cases the cleaning procedure may increase the microbial concentrations and immunotoxicity of the dust.     

Long Residence Times Revealed by Aurora A Kinase‐Targeting Fluorescent Probes Derived from Inhibitors MLN8237 and VX‐689

We report the development of three fluorescent probes for protein kinase Aurora A that are derived from the well‐known inhibitors MLN8237 and VX‐689 (MK‐5108). Two of these probes target the ATP site of Aurora A, and one targets simultaneously the ATP and substrate sites of the kinase. The probes were tested in an assay with fluorescence polarisation/anisotropy readout, and we demonstrated slow association kinetics and long residence time of the probes (k_on 10⁵–10⁷ M ^?1 s^?1, k_off 10^?3–10^?4 s^?1; residence time 500–3000 s). The presence of the Aurora A activator TPX2 caused a significant reduction in the on‐rate and increase in the off‐rate of fluorescent probes targeting ATP site. These observations were supported by Aurora A inhibition assays with MLN8237 and VX‐689. Overall, our results emphasise the importance of rational design of experiments with these compounds and correct interpretation of the obtained data.     

TOPS information processing on a single chip

One of the main objectives in CNN design is to have as small a cell size as possible and because there are normally 19 synapses implemented in each cell, we cannot select an architecture that is very area consuming. In our approach we simplify the multiplication procedure without losing the overall input-output mapping. In that way the synapses can be built from very few transistors and the cell layout can be made small. What has been noticed is that when the initial values of the network are bipolar and when the obtained network output is also bipolar, in almost every case we can use a high-gain output nonlinearity to replace the unity gain. Another required modification is to move the whole processing into a positive range     

A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km × 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr^− 1 for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.     

Contribution of nitrification and denitrification to N2O production in peat, clay and loamy sand soils under different soil moisture conditions

Agricultural soils are a significant source of nitrous oxide (N₂O). Since mitigation of greenhouse gas emissions is needed in all sectors of society, it is important to identify the processes producing N₂O and the factors affecting the production rates in agricultural soils. This study aimed to elucidate the N₂O production in peat, clay and loamy sand at four different soil moisture conditions (40, 60, 80 and 100% Water Filled Pore Space). The ace­tylene inhibition technique was used to evaluate the contribution of nitrification to N₂O production. Nitrous oxide production responded markedly to soil moisture in all three soils. The highest N₂O production, measured at the wettest soils (100% WFPS), was up to four orders of magnitude higher than that at the dry soils (40% WFPS). In dry conditions N₂O production decreased in the order of peat > clay > loamy sand, while in wet conditions the highest N₂O production was measured in loamy sand, then in peat, and the lowest in clay soils. Nitrification was the dominant N₂O producing process in all the soils at 60% WFPS. In the sandy soil 70% of the total N₂O production originated from nitrification, while in the peat soil most of the total N₂O production originated from denitrification. Data on processes producing N₂O in agricultural soils are needed to develop process-based models that could reduce the uncertainty of the emission estimates in greenhouse gas inventories.     

The factor structure and factorial invariance of the 12-item General Health Questionnaire (GHQ-12) across time: Evidence from two community-based samples.

This study provides new knowledge about the factor structure of the 12-item General Health Questionnaire (GHQ-12; D. Goldberg, 1972) through the application of confirmatory factor analysis to longitudinal data, thereby enabling investigation of the factor structure, its invariance across time, and the rank-order stability of the factors. Two community-based longitudinal adult samples with 1-year (n = 640) and 6-year (n = 330) follow-up times were studied. As a result, the correlated 3-factor model (i.e., Anxiety/Depression, Social Dysfunction, and Loss of Confidence) showed a better fit with both samples than the alternative models. The correlated 3-factor structure was also relatively invariant across time in both samples, indicating that the scale has good construct validity. The rank-order stabilities of the factors were low across time, which suggests that the GHQ-12 measures temporal mental state. (PsycINFO Database Record (c) 2010 APA, all rights reserved)