PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

Design of a wideband conformal array antenna system with beamforming and null steering, for application in a DVB-T based passive radar

The use of radars in detecting low flying, small targets is being explored for several decades now. However radar with counter-stealth abilities namely the passive, multistatic, low frequency radars are in the focus recently. Passive radar that uses Digital Video Broadcast Terrestrial (DVB-T) signals as illuminator of opportunity is a major contender in this area. A DVB-T based passive radar requires the development of an antenna array that performs satisfactorily over the entire DVB-T band. At Fraunhofer FHR, there is currently a need for an array antenna to be designed for operation over the 450-900 MHz range with wideband beamforming and null steering capabilities. This would add to the ability of the passive radar in detecting covert targets and would improve the performance of the system. The array should require no mechanical adjustments to inter-element spacing to correspond to the DVB-T carrier frequency used for any particular measurement. Such an array would have an increased flexibility of operation in different environment or locations.

The design of such an array antenna and the applied techniques for wideband beamforming and null steering are presented in the thesis. The interaction between the inter-element spacing, the grating lobes and the mutual couplings had to be carefully studied and an optimal solution was to be reached at that meets all the specifications of the antenna array for wideband applications. Directional beams, nulls along interference directions, low sidelobe levels, polarization aspects and operation along a wide bandwidth of 450-900 MHz were some of the key considerations.

Development of M13 bacteriophage-based SPR detection using Salmonella detection as a case study

Surface plasmon resonance (SPR)-based biosensor is a popular platform for real-time monitoring and sensitive detection for a myriad of targets. However, only a few studies have reported the use of bacteriophages as specific binders for SPR-based detection. This study aimed to demonstrate how filamentous M13 bacteriophages expressing 12-mer peptides can be employed in an SPR-based assay, using a Salmonella-specific bacteriophage as a model binder to detect the foodborne bacterium Salmonella. Several important factors (immobilization buffers and methods, and interaction buffers) for a successful bacteriophage-based SPR assay were optimized. As a result, a Salmonella-specific bacteriophage-based SPR assay was achieved, with very low cross reactivity with other non-target foodborne pathogens and detection limits of 8.0 × 10⁷ and 1.3 × 10⁷ CFU/mL for one-time and five-time immobilized sensors, respectively. This proof-of-concept study demonstrates the feasibility of using M13 bacteriophages expressing target-specific peptides as a binder in a rapid and label-free SPR assay for pathogen detection.

Attention-based modulation of tactile stimuli: A comparison between prefrontal lesion patients and healthy age-matched controls

Objectives: To investigate the role of the prefrontal cortex in attention-based modulation of cortical somatosensory processing.

Methods: Six prefrontal stroke patients were compared with eleven neurologically intact older adults during a vibrotactile discrimination task. All subjects attended to stimuli on one digit while ignoring distracter stimuli on a separate digit of the same hand. Subjects were required to report infrequent targets on the attended digit only. Throughout testing electroencephalography was used to measure event-related potentials for both task-relevant and irrelevant stimuli.

Results: Prefrontal patients demonstrated significant changes in cortical somatosensory processing based on attention compared to age-matched controls. This was evident both in early unimodal somatosensory processing (i.e. P100) and in later cortical processing stages (i.e. long-latency positivity). Moreover, there was a tendency towards a tonic loss of inhibition over early somatosensory cortical processing (i.e. P50).

Conclusions: The attention-based modulation noted for neurologically intact older adults was absent in prefrontal lesion patients.

Significance: The present study highlights the important role of prefrontal regions in sustaining inhibition over early sensory cortical processing stages and in modifying somatosensory transmission based on task-relevance. Notably these deficits extend beyond those previously shown to occur as a function of age.

Using entropy based mean shift filter and modified watershed transform for grain segmentation

Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper,we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice.However,due to the over-segmentation issue,this technique has experienced poor performance in various applications,such as inhomogeneous background and connected targets. To solve this problem,we present a combination of two classical techniques to handle this issue.In the first step,a mean shift filter is used to eliminate the inhomogeneous background, where entropy is used to be a converging criterion. Secondly,a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.

A table-top laser-based source of short, collimated, ultra-relativistic positron beams

An ultra-relativistic electron beam passing through a thick, high-Z solid target triggers an electromagnetic cascade, whereby a large number of high energy photons and electron-positron pairs are produced. By exploiting this physical process, we present here the first experimental evidence of the generation of ultra-short, highly collimated and ultra-relativistic positron beams following the interaction of a laser-wake field accelerated electron beam with high-Z solid targets. Clear evidence has also been obtained of the generation of GeV electron-positron jets with variable composition depending on the solid target material and thickness. The percentage of positrons in the overall leptonic beam has been observed to vary from a few per cent up to almost fifty per cent, implying a quasi-neutral electron-positron beam. We anticipate that these beams will be of direct relevance to the laboratory study of astrophysical leptonic jets and their interaction with the interstellar medium.

Revising Partial Pre-Orders with Partial Pre-Orders: A Unit-Based Revision Framework

Belief revision studies strategies about how agents revise their belief states when receiving new evidence. Both in classical belief revision and in epistemic revision, a new input is either in the form of a (weighted) propositional formula or a total
pre-order (where the total pre-order is considered as a whole).
However, in some real-world applications, a new input can be a partial pre-order where each unit that constitutes the partial pre-order is important and should be considered individually. To address this issue, in this paper, we study how a partial preorder representing the prior epistemic state can be revised by another partial pre-order (the new input) from a different perspective, where the revision is conducted recursively on the individual units of partial pre-orders. We propose different revision operators (rules), dubbed the extension, match, inner and outer revision operators, from different revision points of view. We also analyze several properties for these operators.

Functional genomics to identify therapeutic prophylactic targets

Infectious diseases are a leading cause of global human mortality. The use of antimicrobials remains the most common strategy for treatment. However, the isolation of pathogens resistant to virtually all antimicrobials makes it urgent to develop effective therapeutics based on new targets. Here we review a new drug discovery paradigm focusing on identifying and targeting host factors important for infection as well as pathogen determinants involved in disease progression. We summarize innovative strategies which by combining bioinformatics with transcriptomics and chemical genetics have already identified host factors essential for pathogen entry, survival and replication. We describe how the discovery of RNA interference which allows loss-of-function studies has facilitated functional genomic studies in human cells. It is expected that these studies will identify targets to be used as host-directed drug therapy which, together with antimicrobials targeting microbial virulence factors, will efficiently eliminate the invading pathogen.

RNA interference in adult Ascaris suum - an opportunity for the development of a functional genomics platform that supports organism-, tissue- and cell-based biology in a nematode parasite

The sustainable control of animal parasitic nematodes requires the development of efficient functional genomics platforms to facilitate target validation and enhance anthelmintic discovery. Unfortunately, the utility of RNA interference (RNAi) for the validation of novel drug targets in nematode parasites remains problematic. Ascaris suum is an important veterinary parasite and a zoonotic pathogen. Here we show that adult A. suum is RNAi competent, and highlight the induction, spread and consistency of RNAi across multiple tissue types. This platform provides a new opportunity to undertake whole organism-, tissue- and cell-level gene function studies to enhance target validation processes for nematode parasites of veterinary/medical significance.

Uncovering BRCA1-regulated signalling pathways by microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has dramatically changed the way in which we now address basic biomedical questions. Expression profiling using microarrays facilitates an experimental approach where alterations in the transcript level of entire transcriptomes can be simultaneously assayed in response to defined stimuli. We have used microarray analysis to identify downstream transcriptional targets of the BRCA1 (Breast Cancer 1) tumour-suppressor gene as a means of defining its function. BRCA1 has been implicated in the predisposition to early onset breast and ovarian cancer and while its exact function remains to be defined, roles in DNA repair, cell-cycle control and transcriptional regulation have been implied. In the current study we have generated cell lines with tetracycline-regulated, inducible expression of BRCA1 as a tool to identify genes, which might represent important effectors of BRCA1 function. Oligonucleotide array-based expression profiling identified a number of genes that were upregulated at various times following inducible expression of BRCA1 including the DNA damage-responsive gene GADD45 (Growth Arrest after DNA Damage). Identified targets were confirmed by Northern blot analysis and their functional significance as BRCA1 targets examined.

Uncovering functionally relevant signaling pathways using microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has fundamentally altered the way in which we now address basic biomedical questions. Microarrays technology facilitates a more complete and inclusive experimental approach where alterations in the transcript level of entire genomes can be simultaneously assayed in response to a variety of stimuli. Conceptually different approaches to the development of microarray technology have resulted in the generation of two different array formats: oligonucleotide arrays and cDNA arrays. The application of microarray and related technologies to identify specific targets of defined genes that have clearly been implicated in cancer progression requires a specific experimental approach. The objective of tiffs approach is to define changes in transcriptional profile that occur in response to modulating the expression level of the gene to be studied. The resulting altered expression profile can then be viewed as a blueprint by which that gene effects its cellular function. We have used oligonucleotide array-based expression profiling in collaboration with Affymetrix to identify downstream transcriptional targets of the BRCA1 tumor-suppressor gene as a means of defining its function. BRCA1 has been implicated in at least three functional pathways, namely, mediating the cellular response to DNA damage, as a cell cycle checkpoint protein and in the regulation of transcription. The physiological significance of these properties and their implications for the function of BRCA1 as a tumor-suppressor gene remain to be defined.

Deep Salience: Visual Salience Modeling via Deep Belief Propagation

Visual salience is an intriguing phenomenon observed in biological neural systems. Numerous attempts have been made to model visual salience mathematically using various feature contrasts, either locally or globally. However, these algorithmic models tend to ignore the problem’s biological solutions, in which visual salience appears to arise during the propagation of visual stimuli along the visual cortex. In this paper, inspired by the conjecture that salience arises from deep propagation along the visual cortex, we present a Deep Salience model where a multi-layer model based on successive Markov random fields (sMRF) is proposed to analyze the input image successively through its deep belief propagation. As a result, the foreground object can be automatically separated from the background in a fully unsupervised way. Experimental evaluation on the benchmark dataset validated that our Deep Salience model can consistently outperform eleven state-of-the-art salience models, yielding the higher rates in the precision-recall tests and attaining the best F-measure and mean-square error in the experiments.

In silico analysis and DHPLC screening strategy identifies novel apoptotic gene targets of aberrant promoter hypermethylation in prostate cancer

BACKGROUND: Aberrant DNA methylation has been implicated as a key survival mechanism in cancer, whereby promoter hypermethylation silences genes essential for many cellular processes including apoptosis. Limited data is available on the methylation profile of apoptotic genes in prostate cancer (CaP). The aim of this study was to profile methylation of apoptotic-related genes in CaP using denaturing high performance liquid chromatography (DHPLC).

METHODS: Based on an in silico selection process, 13 genes were screened for methylation in CaP cell lines using DHPLC. Quantitative methylation specific PCR was employed to determine methylation levels in prostate tissue specimens (n = 135), representing tumor, histologically benign prostate, high-grade prostatic intraepithelial neoplasia and benign prostatic hyperplasia. Gene expression was measured by QRT-PCR in cell lines and tissue specimens.

RESULTS: The promoters of BIK, BNIP3, cFLIP, TMS1, DCR1, DCR2, and CDKN2A appeared fully or partially methylated in a number of malignant cell lines. This is the first report of aberrant methylation of BIK, BNIP3, and cFLIP in CaP. Quantitative methylation analysis in prostate tissues identified 5 genes (BNIP3, CDKN2A, DCR1, DCR2 and TMS1) which were frequently methylated in tumors but were unmethylated in 100% of benign tissues. Furthermore, 69% of tumors were methylated in at least one of the five-gene panel. In the case of all genes, except BNIP3, promoter hypermethylation was associated with concurrent downregulation of gene expression.

CONCLUSION: Future examination of this "CaP apoptotic methylation signature" in a larger cohort of patients is justified to further evaluate its value as a diagnostic and prognostic marker.

Phenotype-Based Discovery of 2-[(E)-2-(Quinolin-2-yl)vinyl]phenol as a Novel Regulator of Ocular Angiogenesis

Retinal angiogenesis is tightly regulated to meet oxygenation and nutritional requirements. In diseases such as proliferative diabetic retinopathy and neovascular age-related macular degeneration, uncontrolled angiogenesis can lead to blindness. Our goal is to better understand the molecular processes controlling retinal angiogenesis and discover novel drugs that inhibit retinal neovascularization. Phenotype-based chemical screens were performed using the ChemBridge Diverset^TM library and inhibition of hyaloid vessel angiogenesis in Tg(fli1:EGFP) zebrafish. 2-[(E)-2-(Quinolin-2-yl)vinyl]phenol, (quininib) robustly inhibits developmental angiogenesis at 4–10 μM in zebrafish and significantly inhibits angiogenic tubule formation in HMEC-1 cells, angiogenic sprouting in aortic ring explants, and retinal revascularization in oxygen-induced retinopathy mice. Quininib is well tolerated in zebrafish, human cell lines, and murine eyes. Profiling screens of 153 angiogenic and inflammatory targets revealed that quininib does not directly target VEGF receptors but antagonizes cysteinyl leukotriene receptors 1 and 2 (CysLT_1–2) at micromolar IC₅₀ values. In summary, quininib is a novel anti-angiogenic small-molecule CysLT receptor antagonist. Quininib inhibits angiogenesis in a range of cell and tissue systems, revealing novel physiological roles for CysLT signaling. Quininib has potential as a novel therapeutic agent to treat ocular neovascular pathologies and may complement current anti-VEGF biological agents.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.