Novel Dynamic Structure Neural Network for Optical Character Recognition

[[abstract]]This paper presents a novel dynamic structure neural network (DSNN) and a learning algorithm for training DSNN. The performance of a neural network system depends on several factors. In that, the architecture of a neural network plays an important role. The objective of the developing DSNN is to avoid trial-and-error process for designing a neural network system. The architecture of DSNN consists of a three-dimensional set of neurons with input/output nodes and connection weights. Designers can define the maximum connection number of each neuron. Moreover, designers can manually deploy neurons in a virtual 3D space, or randomly generate the system structure by the proposed learning algorithm. This work also develops an automatic restructuring algorithm integrated in the proposed learning algorithm to improve the system performance. Due to the novel dynamic structure of DSNN and the restructuring algorithm, the design of DSNN is fast and convenient. Furthermore, DSNN is implemented in C++ with man-machine interactive procedures and tested on many cases with very promising results.[[conferencetype]]國際[[conferencedate]]20041218~20041221[[iscallforpapers]]Y[[conferencelocation]]Rome, Ital

WebPARE: web-computing for inferring genetic or transcriptional interactions

Summary: Inferring genetic or transcriptional interactions, when done successfully, may provide insights into biological processes or biochemical pathways of interest. Unfortunately, most computational algorithms require a certain level of programming expertise. To provide a simple web interface for users to infer interactions from time course gene expression data, we present WebPARE, which is based on the pattern recognition algorithm (PARE). For expression data, in which each type of interaction (e.g. activator target) and the corresponding paired gene expression pattern are significantly associated, PARE uses a non-linear score to classify gene pairs of interest into a few subclasses of various time lags. In each subclass, PARE learns the parameters in the decision score using known interactions from biological experiments or published literature. Subsequently, the trained algorithm predicts interactions of a similar nature. Previously, PARE was shown to infer two sets of interactions in yeast successfully. Moreover, several predicted genetic interactions coincided with existing pathways; this indicates the potential of PARE in predicting partial pathway components. Given a list of gene pairs or genes of interest and expression data, WebPARE invokes PARE and outputs predicted interactions and their networks in directed graphs

Inferring genetic interactions via a nonlinear model and an optimization algorithm

<p>Abstract</p> <p>Background</p> <p>Biochemical pathways are gradually becoming recognized as central to complex human diseases and recently genetic/transcriptional interactions have been shown to be able to predict partial pathways. With the abundant information made available by microarray gene expression data (MGED), nonlinear modeling of these interactions is now feasible. Two of the latest advances in nonlinear modeling used sigmoid models to depict transcriptional interaction of a transcription factor (TF) for a target gene, but do not model cooperative or competitive interactions of several TFs for a target.</p> <p>Results</p> <p>An S-shape model and an optimization algorithm (GASA) were developed to infer genetic interactions/transcriptional regulation of several genes simultaneously using MGED. GASA consists of a genetic algorithm (GA) and a simulated annealing (SA) algorithm, which is enhanced by a steepest gradient descent algorithm to avoid being trapped in local minimum. Using simulated data with various degrees of noise, we studied how GASA with two model selection criteria and two search spaces performed. Furthermore, GASA was shown to outperform network component analysis, the time series network inference algorithm (TSNI), GA with regular GA (GAGA) and GA with regular SA. Two applications are demonstrated. First, GASA is applied to infer a subnetwork of human T-cell apoptosis. Several of the predicted interactions are supported by the literature. Second, GASA was applied to infer the transcriptional factors of 34 cell cycle regulated targets in <it>S. cerevisiae</it>, and GASA performed better than one of the latest advances in nonlinear modeling, GAGA and TSNI. Moreover, GASA is able to predict multiple transcription factors for certain targets, and these results coincide with experiments confirmed data in YEASTRACT.</p> <p>Conclusions</p> <p>GASA is shown to infer both genetic interactions and transcriptional regulatory interactions well. In particular, GASA seems able to characterize the nonlinear mechanism of transcriptional regulatory interactions (TIs) in yeast, and may be applied to infer TIs in other organisms. The predicted genetic interactions of a subnetwork of human T-cell apoptosis coincide with existing partial pathways, suggesting the potential of GASA on inferring biochemical pathways.</p

Actinomycosis of the Gallbladder: A Case Report

Introduction: Actinomycosis of the gallbladder is extremely rare and may mimic a malignancy leading to delayed diagnosis and/or inappropriate treatment.Presentation of case: Here we report the case of an 82-year-old man who presented with right upper abdominal discomfort for one month. Radiographically, an ill-defined mass was found in the gallbladder fossa that invaded the adjacent abdominal wall and liver bed. In addition, a stone was found in the gallbladder lumen. The imaging features suggested a gallbladder carcinoma. An initial CT-guided needle biopsy showed an inflammatory process. The subsequent open cholecystectomy revealed a contracted, thick-walled gallbladder surrounded by a soft tissue mass near the fundus. Histologically, the gallbladder revealed acute and chronic cholecystitis and microabscesses containing sulfur granules in the soft tissue mass, which showed Gram-positive filamentous bacilli. Under the diagnosis of gallbladder actinomycosis, the patient received post-operative antibiotics for 7 weeks and was well 5 months after diagnosis.Conclusion: Our case demonstrated that a gallbladder actinomycosis should be considered in the differential diagnosis in patients with cholelithiasis and cholecystitis presenting an invasive mass in the gallbladder fossa

A QoS-Guaranteed Coverage Precedence Routing Algorithm for Wireless Sensor Networks

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively

Extracts from Cladiella australis, Clavularia viridis and Klyxum simplex (Soft Corals) are Capable of Inhibiting the Growth of Human Oral Squamous Cell Carcinoma Cells

Many biomedical products have already been obtained from marine organisms. In order to search more therapeutic drugs against cancer, this study demonstrates the cytotoxicity effects of Cladiella australis, Clavularia viridis and Klyxum simplex extracts on human oral squamous cell carcinoma (SCC4, SCC9 and SCC25) cells using cell adhesion and cell viability assay. The morphological alterations in SCCs cells after treatment with three extracts, such as typical nuclear condensation, nuclear fragmentation and apoptotic bodies of cells were demonstrated by Hoechst stain. Flow cytometry indicated that three extracts sensitized SCC25 cells in the G0/G1 and S-G2/M phases with a concomitant significantly increased sub-G1 fraction, indicating cell death by apoptosis. This apoptosis process was accompanied by activation of caspase-3 expression after SCC25 cells were treated with three extracts. Thereby, it is possible that extracts of C. australis, C. viridis and K. simplex cause apoptosis of SCCs and warrant further research investigating the possible anti-oral cancer compounds in these soft corals

Gene Transfer of Pro-opiomelanocortin Prohormone Suppressed the Growth and Metastasis of Melanoma: Involvement of ␣-Melanocyte-Stimulating Hormone-Mediated Inhibition of the Nuclear Factor B/Cyclooxygenase-2 Pathway

ABSTRACT Pro-opiomelanocortin (POMC) is a prohormone of various neuropeptides, including corticotropin, ␣-melanocyte-stimulating hormone (␣-MSH), and ␤-endorphin (␤-EP) . POMC neuropeptides are potent inflammation inhibitors and immunosuppressants and may exert opposite influences during tumorigenesis. However, the role of POMC expression in carcinogenesis remains elusive. We evaluated the antineoplastic potential of POMC gene delivery in a syngenic B16-F10 melanoma model. Adenovirus-mediated POMC gene delivery in B16-F10 cells increased the release of POMC neuropeptides in cultured media, which differentially regulated the secretion of pro-and anti-inflammatory cytokines in lymphocytes. POMC gene transfer significantly reduced the anchorage-independent growth of melanoma cells. Moreover, pre-or post-treatment with POMC gene delivery effectively retarded the melanoma growth in mice. Intravenous injection of POMC-transduced B16-F10 cells resulted in reduced foci formation in lung by 60 to 70% of control. The reduced metastasis of POMC-transduced B16-F10 cells could be attributed to their attenuated migratory and adhesive capabilities. POMC gene delivery reduced the cyclooxygenase-2 (COX-2) expression and prostaglandin (PG) E 2 synthesis in melanoma cells and tumor tissues. In addition, application of NS-398, a selective COX-2 inhibitor, mimicked the antineoplastic functions of POMC gene transfer in melanoma. The POMC-mediated COX-2 down-regulation was correlated with its inhibition of nuclear factor B (NFB) activities. Exogenous supply of ␣-MSH inhibited NFB activities, whereas application of the ␣-MSH antagonist growth hormone-releasing peptide-6 (GHRP-6) abolished the POMC-induced inhibition of NFB activities and melanoma growth in mice. In summary, POMC gene delivery suppresses melanoma via ␣-MSH-induced inhibition of NFB/COX-2 pathway, thereby constituting a novel therapy for melanoma. POMC is a multifunctional polycistronic gene located on human chromosome 2p23.3. POMC is a 31 kDa prohormone that is processed into various neuropeptides, including corticotropin, melanotropins (␣-, ␤-, and ␥-MSH), lipotropins, and ␤-endorphin (␤-EP

Collaborative Localization in Wireless Sensor Networks via Pattern Recognition in Radio Irregularity Using Omnidirectional Antennas

In recent years, various received signal strength (RSS)-based localization estimation approaches for wireless sensor networks (WSNs) have been proposed. RSS-based localization is regarded as a low-cost solution for many location-aware applications in WSNs. In previous studies, the radiation patterns of all sensor nodes are assumed to be spherical, which is an oversimplification of the radio propagation model in practical applications. In this study, we present an RSS-based cooperative localization method that estimates unknown coordinates of sensor nodes in a network. Arrangement of two external low-cost omnidirectional dipole antennas is developed by using the distance-power gradient model. A modified robust regression is also proposed to determine the relative azimuth and distance between a sensor node and a fixed reference node. In addition, a cooperative localization scheme that incorporates estimations from multiple fixed reference nodes is presented to improve the accuracy of the localization. The proposed method is tested via computer-based analysis and field test. Experimental results demonstrate that the proposed low-cost method is a useful solution for localizing sensor nodes in unknown or changing environments