Increased HDL Size and Enhanced Apo A-I Catabolic Rates Are Associated With Doxorubicin-Induced Proteinuria in New Zealand White Rabbits

The catabolism and structure of high‐density lipoproteins (HDL) may be the determining factor of their atheroprotective properties. To better understand the role of the kidney in HDL catabolism, here we characterized HDL subclasses and the catabolic rates of apo A‐I in a rabbit model of proteinuria. Proteinuria was induced by intravenous administration of doxorubicin in New Zealand white rabbits (n = 10). HDL size and HDL subclass lipids were assessed by electrophoresis of the isolated lipoproteins. The catabolic rate of HDL‐apo A‐I was evaluated by exogenous radiolabelling with iodine‐131. Doxorubicin induced significant proteinuria after 4 weeks (4.47 ± 0.55 vs. 0.30 ± 0.02 g/L of protein in urine, P < 0.001) associated with increased uremia, creatininemia, and cardiotoxicity. Large HDL2b augmented significantly during proteinuria, whereas small HDL3b and HDL3c decreased compared to basal conditions. HDL2b, HDL2a, and HDL3a subclasses were enriched with triacylglycerols in proteinuric animals as determined by the triacylglycerol‐to‐phospholipid ratio; the cholesterol content in HDL subclasses remained unchanged. The fractional catabolic rate (FCR) of [¹³¹I]‐apo A‐I in the proteinuric rabbits was faster (FCR = 0.036 h^?1) compared to control rabbits group (FCR = 0.026 h^?1, P < 0.05). Apo E increased and apo A‐I decreased in HDL, whereas PON‐1 activity increased in proteinuric rabbits. Proteinuria was associated with an increased number of large HDL2b particles and a decreased number of small HDL3b and 3c. Proteinuria was also connected to an alteration in HDL subclass lipids, apolipoprotein content of HDL, high paraoxonase‐1 activity, and a rise in the fractional catabolic rate of the [¹³¹I]‐apo A‐I.     

Squeezing spectra from s -ordered quasiprobability distributions: application to dispersive optical bistability

It is well known that the squeezing spectrum of the field exiting a nonlinear cavity can be directly obtained from the fluctuation spectrum of normally ordered products of creation and annihilation operators of the cavity mode. In this article we show that the output field squeezing spectrum can be derived also by combining the fluctuation spectra of any pair of s -ordered products of creation and annihilation operators. The interesting result is that the spectrum obtained in this way from the linearized Langevin equations is exact, and this occurs in spite of the fact that no s -ordered quasiprobability distribution verifies a true Fokker–Planck equation; that is, the Langevin equations used for deriving the squeezing spectrum are not exact. The (linearized) intracavity squeezing obtained from any s -ordered distribution is also exact. These results are exemplified in the problem of dispersive optical bistability.     

Magnitude and Significance in Landscape Change

Landscape is organised in mosaics: sets of patches with a defined pattern of boundaries through which patches interact. Changes in patches cause changes in mosaics. Landscape change has two components: a quantitative one, referring to the areas in which changes happen, and a qualitative one, referring to the degree of similarity among the mosaics substituting each other. The quantitative component informs on the magnitude of the change: the total area in which landscape mosaics have changed; the qualitative one informs on the significance thereof: the ecological differences between the mosaics substituting each other. This paper presents an index for quantifying landscape change and for discriminating between magnitude and significance therein. It was tested by study of changes in the landscape mosaics in Madrid, Spain. Results show that the index developed is useful for this purpose. This enables objective comparison of different landscape changes presenting different combinations of magnitude and significance.     

Knowledge representation of the software architecture design process based on situation calculus

Software architecture design is an interactive, complex, decision‐making process. Such a design process involves the exploration, evaluation, and composition of design alternatives. Increasingly, new computer‐aided tools are available to help designers in these complex activities. However, these tools do not know how design is actually done, in other words, by means of which design activities the final artefact was obtained. In fact, the architectural design knowledge exclusively rests in the mind of designers, and there is an urgent need to move it, as much as possible, to a computer‐supported environment that enables the capture of this type of knowledge. This contribution addresses this need by introducing a model for capturing how products under development are generated and transformed along the software architecture design process. The proposed model follows an operational perspective, where architectural design decisions are modelled by means of sequences of operations that are applied on the design products. Situation calculus is used to formally express the existence of an object in a given state of a design process. In addition, this formalism allows us expressing without ambiguities when an operation can be performed in a specific state of the design process.     

Forest biomass estimation through NDVI composites. The role of remotely sensed data to assess Spanish forests as carbon sinks

The present study is focused on the capabilities of remote sensing data and techniques to help in the monitoring of forest ecosystems as carbon sinks. It will attempt to find statistical relationships between satellite‐derived NDVI (Normalized Difference Vegetation Index) data from SPOT‐VEGETATION and NOAA‐AVHRR and field measurements from the Spanish National Forest Inventory on the geographical basis of provinces. Statistically significant relationships were obtained when correlating the aforementioned datasets. These relationships were then used to predict forest biomass at a national level, in order to obtain updated forest information between consecutive National Forest Inventories.     

MERIS‐FR potential for land use–land cover mapping in Spain

Abstract

Since 1984, national and international agencies have sought to improve their ability to forecast famine in sub-Saharan Africa. A number of early warning systems have been implemented for this purpose that monitor physical and social variables that may indicate the likelihood and magnitude of famine. Several famine early warning systems use satellite remote sensing data to supplement ground-based observations. These systems have demonstrated the advantages in timeliness and consistency of remote sensing data. Although user needs have not been clearly defined, experience gained in the operation of early warning systems and the results of related research suggest that: (a) at the continental scale AVHRR GAC data offer many advantages over traditional, ground data sources;

(b) quantitative crop yield estimates might be improved through consideration of both photosynthetic activity of the vegetation and length of growing season;

(c)qualitative comparisons of crop years have provided useful inputs to current early warning needs; and (d) stratification of the region into coherent geographical areas would improve all estimates:     

Subcutaneous versus intravenous low-dose IL-2 therapy after autologous transplantation: results of a prospective, non-randomized study

Medorinone 5-methyl-1,6-napthyridin-2(1H)-one and some of its analogs having varying degrees of cardiotonic potency have been studied by molecular orbital and electric field mapping methods. Ground state geometries of the molecules were optimized using the MNDO molecular orbital method. Hybridization displacement charges (HDC) combined with L?wdin charges as well as Mulliken charges were used for electric field mapping around the molecules. Electric fields near the O2 site of medorinone and its analogs correlate well with their observed cardiotonic potencies. This result is in agreement with certain pharmacological models for cardiotonics.     

Excision of products of oxidative DNA base damage by human NTH1 protein

A functional human homologue of Escherichia coli endonuclease III (Nth-Eco protein) has recently been cloned and characterized [Aspinwall, R., Rothwell, D. G., Roldan-Arjona, T., Anselmino, C., Ward, C. J., Cheadle, J. P., Sampson, J. R., Lindahl, T., Harris, P. C., and Hickson, I. D. (1997) Proc. Natl. Acad. Sci. U.S.A., 94, 109-114]. This enzyme, designated hNTH1 protein, shares an extensive sequence similarity with Nth-Eco protein and a related enzyme from Schizosaccharomyces pombe (Nth-Spo protein). We investigated the substrate specificity of this human enzyme for oxidative DNA base damage, using the technique of gas chromatography/isotope-dilution mass spectrometry. Four different DNA substrates damaged by various free radical-generating systems were used. 5-Hydroxycytosine, thymine glycol, 5-hydroxy-6-hydrothymine, 5,6-dihydroxycytosine, and 5-hydroxyuracil were substrates of hNTH1 protein among 17 lesions found in DNA substrates. The substrate specificity and excision kinetics of the human enzyme were found to be significantly different from those of Nth-Spo and Nth-Eco proteins.     

Demand Forecasting for Irrigation Water Distribution Systems

One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines methodologies for consumer demand modeling and prediction in a real-time environment for an on-demand irrigation water distribution system. Approaches based on linear multiple regression, univariate time series models (exponential smoothing and ARIMA models), and computational neural networks (CNNs) are developed to predict the total daily volume demand. A set of templates is then applied to the daily demand to produce the diurnal demand profile. The models are established using actual data from an irrigation water distribution system in southern Spain. The input variables used in various CNN and multiple regression models are (1) water demands from previous days; (2) climatic data from previous days (maximum temperature, minimum temperature, average temperature, precipitation, relative humidity, wind speed, and sunshine duration); (3) crop data (surfaces and crop coefficients); and (4) water demands and climatic and crop data. In CNN models, the training method used is a standard back-propagation variation known as extended-delta-bar-delta. Different neural architectures are compared whose learning is carried out by controlling several threshold determination coefficients. The nonlinear CNN model approach is shown to provide a better prediction of daily water demand than linear multiple regression and univariate time series analysis. The best results were obtained when water demand and maximum temperature variables from the two previous days were used as input data.     

Video microscopy as an alternative method for somatic cell count in milk

This paper presents an alternative method to estimate somatic cell count (SCC) in cows' milk. SCC is an important indicator in the detection of inflammatory reactions within the udder in cows and Direct Optical Microscopy (DOM) is the present reference method for SCC but, owing to its dependence on human operators, it is extremely costly, time-consuming and potentially subjective. The industrial method of choice is Epifluorescence (EF), which has the potential for impressive throughput and acceptable precision, but requires huge inversions and handling of highly toxic reactives and waste. In this paper, an advantageous method that involves application of a low-cost Video Microscopy (VM) system is analysed and discussed, including a comparison between DOM and VM, and an example of application of both methods to evaluate EF counts. We conclude that VM is sufficiently precise and very cheap to implement and operate.