Calories,fat and cancer

The experiments reported are part of our effort to dissociate the tumor-enhancing effects of dietary fat and high caloric intake. Rats either were fed ad libitum diets containing 4% corn oil or their calories were restricted by 40% and their diets contained 13.1% corn oil. Incidence of 7,12-dimethylbenz(a)anthracene (DMBA)-induced mammary tumors was 80% in rats fed ad libitum and 20% in those fed the calorie-restricted diets. Incidence of 1,2-dimethylhydrazine (DMH)-induced colon tumors was 100% in rats fed ad libitum and 53% in those whose caloric intake was restricted by 40%. The tumor yield (tumors per tumor-bearing rat) was significantly lower in rats on caloric restriction. In another series, rats were fed diets containing 5, 15 or 20% corn oil ad libitum or were fed calorie-restricted (by 25%) diets which provided 20 or 26.6% corn oil (therefore, the same absolute amount of fat was consumed in each of the pair-fed groups). Tumor incidence and tumor yield in the two calorie-restricted groups were similar to those seen in the rats fed 5% fat ad lititum; tumor burden (total g of tumor) was 45–65% lower in the calorie-restricted rats. The data suggest that caloric intake is a more stringent determinant of tumor growth than fat intake.     

Metabolism of sitosteryl β-D-glucoside and its nutritional effects in rats

[4-¹⁴C]Sitosteryl β-D-glucoside, intragastrically administered to rats, was not absorbed by the intestinal mucosa. At three hr after the application, radioactivity was concentrated almost exclusively in the digesta of stomach, small intestine as well as cecum and colon, whereas only low proportions of radioactively labeled compounds were found in the various tissues of the gastrointestinal tract. Minor proportions of labeled metabolites of [4-¹⁴C]sitosteryl β-D-glucoside, such as sitosterol and sitosteryl esters, were formed in the small intestine in vivo and in slices of small intestine in vitro. In the tissues of cecum and colon as well as the digesta derived from them, high proportions of labeled coprositostanol, i.e. 24α-ethyl-5β-cholestan-3β-ol, that obviously had been formed by bacterial degradation of the substrate were detected. The feeding of sitosteryl β-D-glucoside (0.5 g/kg body weight×day) over a period of four weeks did not alter significantly body weights or organ weights of rats. Analyses of steryl lipids of the various organs and tissues confirmed the findings obtained with the radioactive substrate: neither sitosteryl β-D-glucoside nor sitosterol or sitosteryl esters derived therefrom had been transported in appreciable amounts to organs and tissues outside the alimentary canal during the feeding period. Minor proportions of unmetabolized sitosteryl β-D-glucoside were detected in the tissues of stomach and intestine, whereas large proportions of the substrate were found in feces of rats that had received the sitosteryl β-D-glucoside-containing diet; coprositostanol was found in feces of these animals in high proportions as well. Thus, the use of sitosteryl β-D-glucoside as emulsifier or preservative in food and feed does not appear to involve any risk. The systematic nomenclature of the sterols referred to by trivial names is, cholest-5-en-3β-ol (cholesterol); 5α-cholestan-3β-ol (5α-cholestanol); 5β-cholestan-3β-ol (5β-cholestanol, coprostanol); 24α-methylcholest-5-en-3β-ol (campesterol); 24α-methyl-5α-cholestan-3β-ol (5α-campestanol); 24α-methyl-5β-cholestan-3β-ol (5β-campestanol, coprocampestanol); 24α-methyl-cholesta-5,22-dien-3β-ol (brassicasterol); 24α-ethylcholest-5-en-3β-ol (sitosterol, β-sitosterol); 24α-ethyl-5α-cholestan-3β-ol (5α-sitostanol); 24α-ethyl-5β-cholestan-3β-cholestan-3β-ol (5β-sitostanol, coprositostanol); 24α-ethylcholesta-5,22-dien-3β-ol (stigmasterol).     

A new approach for mapping of Biological Soil Crusts in semidesert areas with hyperspectral imagery

Biological Soil Crusts (BSCs), consisting of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, live within or immediately on top of the uppermost millimeters of soil, where they form a more or less firm aggregation of soil particles and organisms. They mainly occur in soils of arid and semi-arid regions, which cover more than 35% of the earth's land surface and are assumed to play a major role as primary producers, C- and N-sinks and soil stabilizers.

In order to establish a methodology for mapping of BSCs, their spectral characteristics with respect to different crust types were analyzed. The resulting reflectance spectra of different crust types had a shallow absorption feature centered around 680 nm in common, in which they differed from the spectra of bare soil.

In October 2004, hyperspectral CASI data with a spatial resolution of 1 m were recorded in conjunction with field spectroscopic measurements in the Succulent Karoo, South Africa. Available spectral indices for Biological Soil Crusts were tested on the image but did not produce satisfying classifications. Therefore, an alternative approach was established based on spectral field data, field observations and the hyperspectral dataset. The newly developed Continuum Removal Crust Identification Algorithm (CRCIA) is based on small and narrow spectral characteristics, that were extracted by continuum removal and subsequently expressed as a set of logical conditions. Using this method, 16.2% of the area which covers 12 km² of gently sloping hills with some granite outcrops were classified as BSCs. Validation of the classification resulted in a Kappa index of 0.831.

In a next step, the methodology will be tested with regard to scale-dependent effects and applied to images covering areas with additional types of BSCs and soil to develop a robust and generally applicable method.     

Extraction Of Feature Lines On Surface Meshes Based On Discrete Morse Theory

We present an approach for extracting extremal feature lines of scalar indicators on surface meshes, based on discrete Morse Theory. By computing initial Morse‐Smale complexes of the scalar indicators of the mesh, we obtain a candidate set of extremal feature lines of the surface. A hierarchy of Morse‐Smale complexes is computed by prioritizing feature lines according to a novel criterion and applying a cancellation procedure that allows us to select the most significant lines. Given the scalar indicators on the vertices of the mesh, the presented feature line extraction scheme is interpolation free and needs no derivative estimates. The technique is insensitive to noise and depends only on one parameter: the feature significance. We use the technique to extract surface features yielding impressive, non photorealistic images.     

A simple index for assessing fuel moisture content

Assessing fuel moisture content to within a reasonable degree of accuracy is an important part of wildland fire management. In this paper we introduce a fuel moisture index that provides a simple and intuitive method for assessing fuel moisture content. The method can be quickly and easily applied in a field setting to provide a dimensionless measure of fuel moisture content. We compare the index with predictions from several models for fuel moisture content and conclude that it provides an equivalent measure of fuel moisture content for a number of fuel types. We go on to briefly discuss how the index could be used to construct a simple and intuitive fire danger index.     

A simple index for assessing fire danger rating

Fire danger rating systems are used to assess the potential for bushfire occurrence, fire spread and difficulty of fire suppression. Typically, fire danger rating systems combine meteorological information with estimates of the moisture content of the fuel to produce a fire danger index. Fire danger indices are used to declare fire bans and to schedule prescribed burns, among other applications. In this paper a simple fire danger index F that is intuitive and easy to calculate is introduced and compared to a number of fire danger indices pertaining to different fuel types that are used in an operational setting in Australia and the United States. The comparisons suggest that F provides a plausible measure of fire danger rating and that it may be a useful pedagogical tool in the context of fire danger and fire weather.     

Designing an extensible architecture for Personalized Ambient Information

Ambient displays provide us with information in the background of our awareness. However, as each user has individual wishes and needs of how, which and when information is presented, the acceptance of ambient displays is low.In this paper we introduce an extensible architecture for personalized ambient information.We employ a notification system to extend the capability of a fixture to display more than one variable. Multiple variables can be updated by multiple information providers. Thereby, our architecture covers a broader spectrum of notifications from alarms to ambient information.We evaluate our concept within a dual-task experiment in comparison to preset notifications. The results show a level of self-interruption which is significantly lower than using preset notifications. Therefore our approach outperforms preset notifications and moves ambient displays closer to secondary displays in human–computer interaction.     

Regulation of proteins mediating neurodegeneration in experimental autoimmune encephalomyelitis and multiple sclerosis

Multiple sclerosis is characterized by inflammatory demyelination and axonal loss as pathophysiological correlates of relapsing activity and progressive development of clinical disability. The molecular processes involved in this pathogenesis are still unclear as they are quite complex and heterogeneous. In this article we present protein expression analysis of brain and spinal cord tissues from different models of murine experimental autoimmune encephalomyelitis (EAE), the most commonly used animal model for multiple sclerosis. We observed a number of EAE-specific protein expression and PTM differences. Proteome analysis was extended to multiple sclerosis specimens in order to validate the EAE findings. Our findings suggest the regulation of a number of proteins that shed light on the molecular mechanisms of the disease processes taking place in EAE and multiple sclerosis. We found consistent modulation of proteins including serum amyloid P component, sirtuin 2, dihydropyrimidinase-related protein family proteins, stathmin 1, creatine kinase B and chloride intracellular channel protein 1. Functional classification of the proteins by database and the literature mining reveals their association with neuronal development and myelinogenesis, suggesting possible disease processes that mediate neurodegeneration.     

Estimating the virial coefficients of small polar molecules

We adapt existing models for estimating the second and third virial coefficients of small molecules to the halogenated methanes and ethanes. We compare the results with the abundant new, high-qualityPVT data resulting from the search for alternative refrigerants. The present model provides an accurate method for calculating densities, and therefore it should provide reliable thermodynamic properties and fugacity coefficients. We give equations and parameters useful for estimating the properties of pure refrigerants and their mixtures when noPVT data are available.Nomenclature B Second virial coeficient - B ₁₂ Mixture cross second virial - B _h Second virial of a hard sphere fluid - _i (T) Temperature function, second virial, Eq. (7) - C Third virial coefficient - C ₁₁₂,C ₁₂₂ Mixture cross third virials - C _h Third virial of a hard sphere fluid - N Avogadro's number Virial Coefficients P _c Critical pressure - P _c12 Characteristic critical pressure of a binary mixture - T _c Critical temperature - T _c12 Characteristic critical temperature of a binary mixture - T _r Reduced temperature,T/T _c - Parameter measuring polar contribution toB, Eq. (3) - b Volume of a hard sphere molecule - f ^(f) Polynomials determining temperature dependence of the nonpolar part ofB - k ₁₂ Binary interaction parameter for mixtures, Eq. (9a) - _c Critical volume - _e Molecular polarizability - Dipole moment - _R Reduced dipole moment, Eq. (4) - _R12 Mixture reduced dipole moment, second virial - _R112, _R122 Mixture reduced dipole moment, third virial - Pitzer acentric factor - ₁₂ Mixture acentric factor - (r) Intermolecular potential - _c Critical density (1/_c)