RNAi-mediated knockdown of pituitary tumor- transforming gene-1 (PTTG1) suppresses the proliferation and invasive potential of PC3 human prostate cancer cells

Pituitary tumor-transforming gene-1 (PTTG1) is a proto-oncogene that promotes tumorigenesis and metastasis in numerous cell types and is overexpressed in a variety of human tumors. We have demonstrated that PTTG1 expression was up-regulated in both human prostate cancer specimens and prostate cancer cell lines. For a more direct assessment of the function of PTTG1 in prostate tumorigenesis, RNAi-mediated knockdown was used to selectively decrease PTTG1 expression in PC3 human prostate tumor cells. After three weeks of selection, colonies stably transfected with PTTG1-targeted RNAi (the knockdown PC3 cell line) or empty vector (the control PC3 cell line) were selected and expanded to investigate the role of PTTG1 expression in PC3 cell growth and invasion. Cell proliferation rate was significantly slower (28%) in the PTTG1 knockdown line after 6 days of growth as indicated by an MTT cell viability assay (P < 0.05). Similarly, a soft agar colony formation assay revealed significantly fewer (66.7%) PTTG1 knockdown PC3 cell colonies than control colonies after three weeks of growth. In addition, PTTG1 knockdown resulted in cell cycle arrest at G1 as indicated by fluorescence-activated cell sorting. The PTTG1 knockdown PC3 cell line also exhibited significantly reduced migration through Matrigel in a transwell assay of invasive potential, and down-regulation of PTTG1 could lead to increased sensitivity of these prostate cancer cells to a commonly used anticancer drug, taxol. Thus, PTTG1 expression is crucial for PC3 cell proliferation and invasion, and could be a promising new target for prostate cancer therapy.

Development of a bovine adenovirus type 2-based gene delivery vector /

ABSTRACT Recombinant adenoviruses are currently under intense investigation as potential gene delivery and gene expression vectors with applications in human and veterinary medicine. As part of our efforts to develop a bovine adenovirus type 2 (BAV2) based vector system, the nucleotide sequence of BAV2 was determined. Sixty-six open reading frames (ORFs) were found with the potential to encode polypeptides that were at least 50 amino acid (aa) residue long. Thirty-one of the BAV2 polypeptide sequences were found to share homology to already identified adenovirus proteins. The arrangement of the genes revealed that the BAV2 genomic organization closely resembles that of well-characterized human adenoviruses. In the course of this study, continuous propagation of BAV2 over many generations in cell culture resulted in the isolation of a BAV2 spontaneous mutant in which the E3 region was deleted. Restriction enzyme, sequencing and PCR analyses produced concordant results that precisely located the deletion and revealed that its size was exactly 1299 bp. The E3-deleted virus was plaque-purified and further propagated in cell culture. It appeared that the replication of such a virus lacking a portion of the E3 region was not affected, at least in cell culture. Attempts to rescue a recombinant BAV2 virus with the bacterial kanamycin resistance gene in the E3 region yielded a candidate as verified with extensive Southern blotting and PCR analyses. Attempts to purify the recombinant virus were not successful, suggesting that such recombinant BAV2 was helper-dependent. Ten clones containing full-length BAV2 genomes in a pWE15 cosmid vector were constructed. The infectivity of these constructs was tested by using different transfection methods. The BAV2 genomic clones did appear to be infectious only after extended incubation period. This may be due to limitations of various transfection methods tested, or biological differences between virus- and E. co//-derived BAV2 DNA.

Vector-Based Integration of Local and Long-Range Information in Visual Cortex

Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex, we argue that neuronal integration is a systems--level process better studied in terms of local cortical circuitry than at the level of single neurons, and we present a method for constructing self-contained modules which capture (nonlinear) local circuit interactions. In this framework, receptive field elements naturally have dual (rather than the traditional unitary influence since they drive both excitatory and inhibitory cortical neurons. This vector-based analysis, in contrast to scalarsapproaches, greatly simplifies integration by permitting linear summation of inputs from both "classical" and "extraclassical" receptive field regions. We illustrate this by explaining two complex visual cortical phenomena, which are incompatible with scalar notions of neuronal integration.

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Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

A vector approach to the assessment of undergraduate engineering courses

In any undergraduate engineering programme there is a need to assess the balance and flavour of the various educational strands. In order for a quality assurance of these programmes to be met there is a need to evaluate the course load, academic content and the assessment marks of each course in the undergraduate programme. The existing ranges of QA methods for these programmes are focused on one or two of these issues and do not provide a comprehensive assessment procedure. Following a review of the existing QA methods, this paper will define a three-dimensional approach to the assessment of the educational aspects of an undergraduate course. Various features of this method will be described and potential benefits explained.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Properties of singular vectors using convective available potential energy as final time norm

We study the feasibility of using the singular vector technique to create initial condition perturbations for short-range ensemble prediction systems (SREPS) focussing on predictability of severe local storms and in particular deep convection. For this a new final time semi-norm based on the convective available potential energy (CAPE) is introduced. We compare singular vectors using the CAPE-norm with SVs using the more common total energy (TE) norm for a 2-week summer period in 2007, which includes a case of mesoscale extreme rainfall in the south west of Finland. The CAPE singular vectors perturb the CAPE field by increasing the specific humidity and temperature of the parcel and increase the lapse rate above the parcel in the lower troposphere consistent with physical considerations. The CAPE-SVs are situated in the lower troposphere. This in contrast to TE-SVs with short optimization times which predominantly remain in the high troposphere. By examining the time evolution of the CAPE singular values we observe that the convective event in the south west of Finland is clearly associated with high CAPE singular values.

Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers

Background: There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi) fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues. Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect measurements of soil or tissue samples. Results: We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes. Conclusions: This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop, improving the sustainability of agriculture.

Spatial expansion and population structure of the neotropical malaria vector, Anopheles darlingi (Diptera: Culicidae)

Extensive population structuring is known to occur in Anopheles darlingi, the primary malaria vector of the Neotropics. We analysed the phylogeographic structure of the species using the mitochondrial cytochrome oxidase I marker. Diversity is divided into six main population groups in South America: Colombia, central Amazonia, southern Brazil, south-eastern Brazil, and two groups in north-east Brazil. The ancestral distribution of the taxon is hypothesized to be central Amazonia, and there is evidence of expansion from this region during the late Pleistocene. The expansion was not a homogeneous front, however, with at least four subgroups being formed due to geographic barriers. As the species spread, populations became isolated from each other by the Amazon River and the coastal mountain ranges of south-eastern Brazil and the Andes. Analyses incorporating distances around these barriers suggest that the entire South American range of An. darlingi is at mutation-dispersal-drift equilibrium. Because the species is distributed throughout such a broad area, the limited dispersal across some landscape types promotes differentiation between otherwise proximate populations. Moreover, samples from the An. darlingi holotype location in Rio de Janeiro State are substantially derived from all other populations, implying that there may be additional genetic differences of epidemiological relevance. The results obtained contribute to our understanding of gene flow in this species and allow the formulation of human mosquito health protocols in light of the potential population differences in vector capacity or tolerance to control strategies. (C) 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 97, 854-866.

The Immunomodulatory Action of Sialostatin L on Dendritic Cells Reveals Its Potential to Interfere with Autoimmunity

Sialostatin L (SialoL) is a secreted cysteine protease inhibitor identified in the salivary glands of the Lyme disease vector Ixodes scapularis. In this study, we reveal the mechanisms of SialoL immunomodulatory actions on the vertebrate host. LPS-induced maturation of dendritic cells from C57BL/6 mice was significantly reduced in the presence of SialoL. Although OVA degradation was not affected by the presence of SialoL in dendritic cell cultures, cathepsin S activity was partially inhibited, leading to an accumulation of a 10-kDa invariant chain intermediate in these cells. As a consequence, in vitro Ag-specific CD4(+) T cell proliferation was inhibited in a time-dependent manner by SialoL, and further studies engaging cathepsin S(-/-) or cathepsin L(-/-) dendritic cells confirmed that the immunomodulatory actions of SialoL are mediated by inhibition of cathepsin S. Moreover, mice treated with SialoL displayed decreased early T cell expansion and recall response upon antigenic stimulation. Finally, SialoL administration during the immunization phase of experimental autoimmune encephalomyelitis in mice significantly prevented disease symptoms, which was associated with impaired IFN-gamma and IL-17 production and specific T cell proliferation. These results illuminate the dual mechanism by which a human disease vector protein modulates vertebrate host immunity and reveals its potential in prevention of an autoimmune disease. The Journal of Immunology, 2009, 182: 7422-7429.

Scalar form factors and nuclear interactions

The scalar-isoscalar term in the two-pion exchange NN potential is abnormally large and does not respect the hierarchy of effects predicted by chiral perturbation theory. We argue that this anomaly is associated with non-perturbative effects, which are also present in the pi N scalar form factor.

Hamiltonian constraint analysis of vector field theories with spontaneous Lorentz symmetry breaking

Recent investigations of various quantum-gravity theories have revealed a variety of possible mechanisms that lead to Lorentz violation. One of the more elegant of these mechanisms is known as Spontaneous Lorentz Symmetry Breaking (SLSB), where a vector or tensor field acquires a nonzero vacuum expectation value. As a consequence of this symmetry breaking, massless Nambu-Goldstone modes appear with properties similar to the photon in Electromagnetism. This thesis considers the most general class of vector field theories that exhibit spontaneous Lorentz violation-known as bumblebee models-and examines their candidacy as potential alternative explanations of E&M, offering the possibility that Einstein-Maxwell theory could emerge as a result of SLSB rather than of local U(1) gauge invariance. With this aim we employ Dirac's Hamiltonian Constraint Analysis procedure to examine the constraint structures and degrees of freedom inherent in three candidate bumblebee models, each with a different potential function, and compare these results to those of Electromagnetism. We find that none of these models share similar constraint structures to that of E&M, and that the number of degrees of freedom for each model exceeds that of Electromagnetism by at least two, pointing to the potential existence of massive modes or propagating ghost modes in the bumblebee theories.

Vector Theory of Spontaneous Lorentz Violation

Classical electromagnetism predicts two massless propagating modes, which are known as the two polarizations of the photon. On the other hand, if the Lorentz symmetry of classical electromagnetism is spontaneously broken, the new theory will still have two massless Nambu-Goldstone modes resembling the photon. If the Lorentz symmetry is broken by a bumblebee potential that allows for excitations out of the minimum, then massive modes arise. Furthermore, in curved spacetime, such massive modes will be created through a process other than the usual Higgs mechanism because of the dependence of the bumblebee potential on both the vector field and the metric tensor. Also, it is found that these massive modes do not propagate due to the extra constraints.