A Study of Curing Methods and Type II Cements on the Durability of Concrete, R-11-Z(1), 1969

A program of A (90 day moist room), B (14 day moist room) and C (7 day moist room and 7 day 50%_humidity) type curing for the R-11-Z program of durability of concrete using the automatic freeze and thaw machine (ASTM C-291) has been used in the Materials Department of the Iowa State Highway Commission since December 6, 1966. A summary of the results obtained from then until March 25, 1968, indicates that the B and C type curing are yielding very little valuable information. However, the A cure exhibits a wide range of durability factors and also groups the aggregates in an order which is related to the service record (there are definite exceptions. The biggest disadvantage to the A cure is the length of time that it takes to complete the test (90 day cure and 38 day test). The Kansas Highway Department has experimented with different cements and aggregates in order to determine which combination offers a concrete with the best durability factor possible. In an experimental test section of highway, concrete made with a Type II cement appeared to have better durability than others made with Type I cements. Because of this, a question has been raised at the Iowa State Highway Commission - Can concrete made with Type II cements, because of a lesser amount of tricalcium aluminate, yield better durability than concrete made with Type I cements?

In vitro activity of gallium maltolate against Staphylococci in logarithmic, stationary, and biofilm growth phases: comparison of conventional and calorimetric susceptibility testing methods.

Ga(3+) is a semimetal element that competes for the iron-binding sites of transporters and enzymes. We investigated the activity of gallium maltolate (GaM), an organic gallium salt with high solubility, against laboratory and clinical strains of methicillin-susceptible Staphylococcus aureus (MSSA), methicillin-resistant S. aureus (MRSA), methicillin-susceptible Staphylococcus epidermidis (MSSE), and methicillin-resistant S. epidermidis (MRSE) in logarithmic or stationary phase and in biofilms. The MICs of GaM were higher for S. aureus (375 to 2000 microg/ml) than S. epidermidis (94 to 200 microg/ml). Minimal biofilm inhibitory concentrations were 3,000 to >or=6,000 microg/ml (S. aureus) and 94 to 3,000 microg/ml (S. epidermidis). In time-kill studies, GaM exhibited a slow and dose-dependent killing, with maximal action at 24 h against S. aureus of 1.9 log(10) CFU/ml (MSSA) and 3.3 log(10) CFU/ml (MRSA) at 3x MIC and 2.9 log(10) CFU/ml (MSSE) and 4.0 log(10) CFU/ml (MRSE) against S. epidermidis at 10x MIC. In calorimetric studies, growth-related heat production was inhibited by GaM at subinhibitory concentrations; and the minimal heat inhibition concentrations were 188 to 4,500 microg/ml (MSSA), 94 to 1,500 microg/ml (MRSA), and 94 to 375 microg/ml (MSSE and MRSE), which correlated well with the MICs. Thus, calorimetry was a fast, accurate, and simple method useful for investigation of antimicrobial activity at subinhibitory concentrations. In conclusion, GaM exhibited activity against staphylococci in different growth phases, including in stationary phase and biofilms, but high concentrations were required. These data support the potential topical use of GaM, including its use for the treatment of wound infections, MRSA decolonization, and coating of implants.

Effect of dark chocolate on renal tissue oxygenation as measured by BOLD-MRI in healthy volunteers.

Background: Cocoa is rich in flavonoids, has anti-oxidative properties and increases the bioavailability of nitric oxide (NO). Adequate renal tissue oxygenation is crucial for the maintenance of renal function. The goal of this study was to investigate the effect of cocoa-rich dark chocolate (DC) on renal tissue oxygenation in humans, as compared to flavonoid-poor white chocolate (WC). Methods: Ten healthy volunteers with preserved kidney function (mean age ± SD 35 ± 12 years, 70% women, BMI 21 ± 3 kg/m2) underwent blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) before and 2 hours after the ingestion of 1 g/kg of DC (70% cocoa). Renal tissue oxygenation was determined by the measurement of R2* maps on 4 coronal slices covering both kidneys. The mean R2* (= 1/T2*) values in the medulla and cortex were calculated, a low R2* indicating high tissue oxygenation. Eight participants also underwent BOLD-MRI at least 1 week later, before and 2 hours after the intake of 1 g/kg WC. Results: The mean medullary R2* was lower after DC intake compared to baseline (28.2 ± 1.3 s-1 vs. 29.6 ± 1.3 s-1, p = 0.04), whereas cortical and medullary R2* values did not change after WC intake. The change in medullary R2* correlated with the level of circulating (epi)catechines, metabolites of flavonoids (r = 0.74, p = 0.037), and was independent of plasma renin activity. Conclusion: This study suggests for the first time an increase of renal medullary oxygenation after intake of dark chocolate. Whether this is linked to flavonoid-induced changes in renal perfusion or oxygen consumption, and whether cocoa has potentially renoprotective properties, merits further study.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.