A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

Application of inter simple sequence repeat (ISSR) markers to plant genetics

Microsatellites or simple sequence repeats (SSRs) are ubiquitous in eukaryotic genomes. Single-locus SSR markers have been developed for a number of species, although there is a major bottleneck in developing SSR markers whereby flanking sequences must be known to design 5'-anchors for polymerase chain reaction (PCR) primers. Inter SSR (ISSR) fingerprinting was developed such that no sequence knowledge was required. Primers based on a repeat sequence, such as (CA)(n), can be made with a degenerate 3'-anchor, such as (CA)(8)RG or (AGC)(6)TY. The resultant PCR reaction amplifies the sequence between two SSRs, yielding a multilocus marker system useful for fingerprinting, diversity analysis and genome mapping. PCR products are radiolabelled with P-32 or P-33 via end-labelling or PCR incorporation, and separated on a polyacrylamide sequencing gel prior to autoradiographic visualisation. A typical reaction yields 20-100 bands per lane depending on the species and primer. We have used ISSR fingerprinting in a number of plant species, and report here some results on two important tropical species, sorghum and banana. Previous investigators have demonstrated that ISSR analysis usually detects a higher level of polymorphism than that detected with restriction fragment length polymorphism (RFLP) or random amplified polymorphic DNA (RAPD) analyses. Our data indicate that this is not a result of greater polymorphism genetically, but rather technical reasons related to the detection methodology used for ISSR analysis.

Generation and phenotypic characterization of new human ovarian cancer cell lines with the identification of antigens potentially recognizable by HLA-restricted cytotoxic T cells

This study describes a simple method for long-term establishment of human ovarian tumor lines and prediction of T-cell epitopes that could be potentially useful in the generation of tumor-specific cytotoxic T lymphocytes (CTLs), Nine ovarian tumor lines (INT.Ov) were generated from solid primary or metastatic tumors as well as from ascitic fluid, Notably all lines expressed HLA class I, intercellular adhesion molecule-1 (ICAM-1), polymorphic epithelial mucin (PEM) and cytokeratin (CK), but not HLA class II, B7.1 (CD80) or BAGE, While of the 9 lines tested 4 (INT.Ov1, 2, 5 and 6) expressed the folate receptor (FR-alpha) and 6 (INT.Ov1, 2, 5, 6, 7 and 9) expressed the epidermal growth factor receptor (EGFR); MAGE-1 and p185(HER-2/neu) were only found in 2 lines (INT.Ov1 and 2) and GAGE-1 expression in 1 line (INT.Ov2). The identification of class I MHC ligands and T-cell epitopes within protein antigens was achieved by applying several theoretical methods including: 1) similarity or homology searches to MHCPEP; 2) BIMAS and 3) artificial neural network-based predictions of proteins MACE, GAGE, EGFR, p185(HER-2/neu) and FR-alpha expressed in INT.Ov lines, Because of the high frequency of expression of some of these proteins in ovarian cancer and the ability to determine HLA binding peptides efficiently, it is expected that after appropriate screening, a large cohort of ovarian cancer patients may become candidates to receive peptide based vaccines. (C) 1997 Wiley-Liss, Inc.

Cell cycle model to describe animal cell size variation and lag between cell number and biomass dynamics

The use of cell numbers rather than mass to quantify the size of the biotic phase in animal cell cultures causes several problems. First, the cell size varies with growth conditions, thus yields expressed in terms of cell numbers cannot be used in the normal mass balance sense. Second, experience from microbial systems shows that cell number dynamics lag behind biomass dynamics. This work demonstrates that this lag phenomenon also occurs in animal cell culture. Both the lag phenomenon and the variation in cell size are explained using a simple model of the cell cycle. The basis for the model is that onset of DNA synthesis requires accumulation of G1 cyclins to a prescribed level. This requirement is translated into a requirement for a cell to reach a critical size before commencement of DNA synthesis. A slower gl-owing cell will spend more time in G1 before reaching the critical mass. In contrast, the period between onset of DNA synthesis and mitosis, tau(B), is fixed. The two parameters in the model, the critical size and tau(B), were determined from eight steady-state measurements of mean cell size in a continuous hybridoma culture. Using these parameters, it was possible to predict with reasonable accuracy the transient behavior in a separate shift-up culture, i.e., a culture where cells were transferred from a lean environment to a rich environment. The implications for analyzing experimental data for animal cell culture are discussed. (C) 1997 John Wiley & Sons, Inc.

The generation of H-1-NMR-detectable mobile lipid in stimulated lymphocytes: Relationship ts cellular activation, the cell cycle, and phosphatidylcholine-specific phospholipase C

Mobile Lipids detected using H-1-NMR in stimulated lymphocytes were correlated with cell cycle phase, expression of the interleukin-2 receptor alpha and proliferation to assess the activation status of the lymphocytes. Mobile lipid levels, IL-2R alpha expression and proliferation increased after treatment with PMA and ionomycin. PMA or ionomycin stimulation alone induced increased IL-2R alpha expressiom but not proliferation, PMA- but not ionomycin-stimulation generated mobile lipid, Treatment with anti-CD3 antibody did not increase IL-2R alpha expression or proliferation but did generate increased amounts of mobile lipid, The cell cycle status of thymocytes treated with anti-CD3, PMA or ionomycin alone indicated an. accumulation of the cells in the G(1) phase of the cell cycle, The generation of mobile lipid was abrogated in anti-CD3 antibody-stimulated thymic lymphocytes but not in splenic lymphocytes, using a phosphatidylcholine-specific phospholipase C (PC-PLC) inhibitor which blocked cells in the G(1)/S phase of the cell cycle, This suggests that the H-1-NMR-detectable mobile Lipid may be generated in anti-CD3 antibody-stimulated thymic lymphocytes by the action of PC-PLC activity via the catabolism of PC, in the absence of classical signs of activation. (C) 1997 Academic Press.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.