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To study the influence of dietary fatty acid composition on energy metabolism, forty male rats were fed elemental diets containing 42% of energy as fish oil, safflower oil, olive oil or beef tallow for 12 wk. Food intakes and body weights were measured daily. Energy expenditure and body composition were determined using doubly labeled water on the final 2 d. Pooled fecal energy losses differed in response to dietary manipulation, with losses greatest in rats fed beef tallow and least in those fed olive oil. Higher lean body mass gains and lower fat mass gains were observed in rats fed diets containing fish oil, compared with rats fed olive oil or beef tallow. Total energy gains in rats fed olive oil (3632 + or - 145 kJ) and beef tallow (3850 + or - 136 kJ) were higher than those in rats fed fish oil (2905 + or - 196 kJ). Energy efficiency in both the olive oil and beef tallow groups was also higher than that in the fish oil group. There were no differences in energy expenditure measured by doubly labeled water technique among the four groups. The data suggest that dietary fatty acid composition alters the efficiency of energy substrate accretion in rats.

Su, Wanfang, Boris E. Shmukler, Marina N. Chernova, Alan K. Stuart-Tilley, Lucia De Franceschi, Carlo Brugnara, and Seth L. Alper. Mouse K-Cl cotransporter KCC1: cloning, mapping, pathological expression, and functional regulation. Am. J. Physiol. 277 (Cell Physiol. 46): C899-C912, 1999.--Although K-Cl cotransporter (KCC1) mRNA is expressed in many tissues, K-Cl cotransport activity has been measured in few cell types, and detection of endogenous KCC1 polypeptide has not yet been reported. We have cloned the mouse erythroid KCC1 (mKCC1) cDNA and its flanking genomic regions and mapped the mKCC1 gene to chromosome 8. Three anti-peptide antibodies raised against recombinant mKCC1 function as immunoblot and immunoprecipitation reagents. The tissue distributions of mKCC1 mRNA and protein are widespread, and mKCC1 RNA is constitutively expressed during erythroid differentiation of ES cells. KCC1 polypeptide or related antigen is present in erythrocytes of multiple species in which K-Cl cotransport activity has been documented. Erythroid KCC1 polypeptide abundance is elevated in proportion to reticulocyte counts in density-fractionated cells, in bleeding-induced reticulocytosis, in mouse models of sickle cell disease and thalassemia, and in the corresponding human disorders, mKCC1-mediated uptake of [86.sup]Rb into Xenopus oocytes requires extracellular [Cl.sup.-], is blocked by the diuretic R(+)-[2-n-butyl-6,7-dichloro2-cyclopentyl-2,3-dihydro-1-oxo-1H-indenyl -5-yl-)oxy] acetic acid, and exhibits an erythroid pattern of acute regulation, with activation by hypotonic swelling, N-ethylmaleimide, and staurosporine and inhibition by calyculin and okadaic acid. These reagents and findings will expedite studies of KCC1 structure-function relationships and of the pathobiology of KCC1-mediated K-Cl cotransport. red blood cells; sickle cell disease; thalassemia; SC disease; SAD1

Introducing the theory of fuzzy set, mathematical morphology and computerized mask fast scanning, we developed the TOOTH.SCA software and method to analyze the effect of fluoride (NaF) on ore content of human tooth enamel automatically and quantitatively. And we obtained some characteristic parameters, such as the depth, the type and the demineralized content of every scathing layer of dental caries. The smallest scale of mask scanning is 0.1 μm × 0.1 μm and the time required to analyze a sample is only 12 s. The applied software and method we built play an important role to the research on the mechanism of pathological changes of teeth and preventing dental caries. [ABSTRACT FROM AUTHOR]

Some computer applications for cell characterization in medicine and biology, such as analysis of surface structure of cell wall-deficient EVC (El Tor Vibrio of Cholera), operate with cell samples taken from very small areas of interest. In order to perform texture characterization in such an application, only a few texture operators can be employed: the operators should be insensitive to noise and image distortion and be reliable in order to estimate texture quality from images. Therefore, we introduce wavelet theory and mathematical morphology to analyse the cellular surface micro-area image obtained by SEM (Scanning Electron Microscope). In order to describe the quality of surface structure of cell wall-deficient EVC, we propose a fully automatic computerized method. The image analysis process is carried out in two steps. In the first, we decompose the given image by dyadic wavelet transform and form an image approximation with higher resolution, by doing so, we perform edge detection of given images efficiently. In the second, we introduce many operations of mathematical morphology to obtain morphological quantitative parameters of surface structure of cell wall-deficient EVC. The obtained results prove that the method can eliminate noise, detect the edge and extract the feature parameters validly. In this work, we have built automatic analytic software named “EVC.CELL”. [ABSTRACT FROM AUTHOR]

Assesses the energy requirements and the accuracy of estimates of usual energy intake derived from food records in normal weight, middle aged women participating in an ongoing dietary-intervention trial. Average energy requirement for Canadian women aged 25-49 as determined by diet surveys; Subject characteristics, reported fat and energy intakes, energy expenditure and weight data for the validation study.

In this paper the recognition of Small Cell Carcinoma (SCC) is studied. For each type we select 128 samples for training, and randomly measure 200 cells in each sample. We introduce multi-scale morphology based on centroid coordinates to extract the boundaries of nuclei and obtain feature images of nuclei. The features of lung cancer cells are described by morphological and colorimetrical parameters, which is valuable to recognize SCC. Then the architecture of self-organizing feature mapping (SOFM) neural network is studied for recognition of SCC. The weights of the network are adjusted by self-organizing competition, and finally inputted patterns are classified. This algorithm has the advantage of parallelism and fast-convergence, and may simplify the analysis of SCC. Clinical experiment results show that the correctness ratio of this system may reach 95.3% while recognizing lung cancer cell types. Our work is significant to the pathological researches of lung cancer, assistant clinic diagnosis, and assessment of therapeutic effects. Meanwhile a software system named as SCC. LUNG is established for automatic analysis., (Copryright 2004 IOS Press)