Investigation of monoclonal antibodies raised to human ovarian carcinoma cell lines

Monoclonal antibodies (MAb) were generated to multidrug resistant (MDR) and sensitive variants of the ovarian carcinoma cell line OAW42 which over-express the M D R associated protem LRP/MVP MAb 3/B6 was raised to the intrinsically resistant variant OAW42-SR Immunofluorescence and immunocytochemical analysis indicated that the antigen detected by MAb 3/B6 was expressed primarily on the external surface of the plasma membrane but was also found to be expressed in the cytoplasm of a series of human M D R cell lmes 3/B6 over-expression was associated primarily with cell lines which expressed the LRP/MVP. 3/B6 expression was studied in paraffin-embedded normal and malignant adult and in foetal tumour tissue. There was heterogeneous expression of the 3/B6 antigen and the LRP/MVP in normal adult and foetal kidney Low-level LRP/MVP expression was observed in 1/10 untreated malignant ovarian tumours while 3/B6 was absent. In two paired pre- and post-chemotherapy breast tumours sections, 3/B6 expression was observed in the post-chemotherapy sections only LRP/MVP expression was also observed in these sections. A new commercially available immunoprécipitation protocol based on biotm labelling of cellular proteins was extensively modified and improved for this project. The MAb 3/B6 was found to immunoprecipitate a 115 kDa un-glycosylated protein Immunoprécipitation experiments with anti-rat vault polyclonal serum, N2 and purified rat vault protems mdicated that MAb 3/B6 and LRP-56 (the standard MAb used to detect LRP/MVP) did not cross-react Competitive immunocytochemical studies confirmed these results Incubation of OAW42-SR cells with MAb 3/B6 did not have any effect on adnamycm drug accumulation or cellular proliferation. The antt-OAW42-SR MAb 5/C4 was also characterised by immunofluorescence and immunocytochemistry Results from these studies revealed that this MAb recognised a cytoplasmic antigen which migrated as 2 protein bands at 110 and 85 kDa by Western Blotting Further Western Blotting analysis indicated that MAb 5/C4 did not cross react with purified rat vault particles. The anti-OAW42-S MAb 3/E3 was partially characterised by immunofluorescence and immunocytochemistry. There did not appear to be any significant difference in expression of this antigen m a panel of multidrug resistant cell lines. It was not possible to determine the molecular weigh of the antigen by Western Blotting or immunoprécipitation. This suggested that the epitope was destroyed during sample preparation

A Quantum Many-body Wave Function Inspired Language Modeling Approach

The recently proposed quantum language model (QLM) aimed at a principled approach to modeling term dependency by applying the quantum probability theory. The latest development for a more effective QLM has adopted word embeddings as a kind of global dependency information and integrated the quantum-inspired idea in a neural network architecture. While these quantum-inspired LMs are theoretically more general and also practically effective, they have two major limitations. First, they have not taken into account the interaction among words with multiple meanings, which is common and important in understanding natural language text. Second, the integration of the quantum-inspired LM with the neural network was mainly for effective training of parameters, yet lacking a theoretical foundation accounting for such integration. To address these two issues, in this paper, we propose a Quantum Many-body Wave Function (QMWF) inspired language modeling approach. The QMWF inspired LM can adopt the tensor product to model the aforesaid interaction among words. It also enables us to reveal the inherent necessity of using Convolutional Neural Network (CNN) in QMWF language modeling. Furthermore, our approach delivers a simple algorithm to represent and match text/sentence pairs. Systematic evaluation shows the effectiveness of the proposed QMWF-LM algorithm, in comparison with the state of the art quantum-inspired LMs and a couple of CNN-based methods, on three typical Question Answering (QA) datasets.Comment: 10 pages,4 figures,CIK

Argumentation over Ontology Correspondences in MAS

laera2007aInternational audienceIn order to support semantic interoperation in open environments, where agents can dynamically join or leave and no prior assumption can be made on the ontologies to align, the different agents involved need to agree on the semantics of the terms used during the interoperation. Reaching this agreement can only come through some sort of negotiation process. Indeed, agents will differ in the domain ontologies they commit to; and their perception of the world, and hence the choice of vocabulary used to represent concepts. We propose an approach for supporting the creation and exchange of different arguments, that support or reject possible correspondences. Each agent can decide, according to its preferences, whether to accept or refuse a candidate correspondence. The proposed framework considers arguments and propositions that are specific to the matching task and are based on the ontology semantics. This argumentation framework relies on a formal argument manipulation schema and on an encoding of the agents' preferences between particular kinds of arguments

SERSE- An agent-based system for scalable search on the semantic web

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

SERSE: Searching for Digital Content in Esperonto

This paper presents SERSE, a multi-agent system that combines different technologies such as peer to peer, ontologies, and multi-agent technology in order to deal with the complexity of searching for digital content on the Semantic Web (SW). In SERSE, agents communicate and share responsibilities on a peer-to-peer basis. Peers are organised according to a semantic overlay network, where the neighbourhood is determined by the semantic proximity of the ontological definitions that are known to the agents. The integration of these technologies poses some problems. On the one hand, the more ontological knowledge the agents have, the better we can expect the system to perform. On the other hand, global knowledge would constitute a point of centralisation which might potentially degrade the performance of a P2P system. The paper identifies five requirements for efficiently searching SW content, and illustrates how the SERSE design addresses these requirements. The SERSE architecture is then presented, together with some experimental results that evaluate the performance of SERSE in response to changes in the size of semantic neighbourhood, ranging from strictly local knowledge (each agent knows about just one concept), to global knowledge (each agent has complete knowledge of the ontological definitions) Authors: Valentina Tamma (contact author

Determination of Minimum Gap in Congested Traffic

Bridge & Concrete Research in Ireland, Dublin, Ireland, 6 -7 September, 2012Accurate evaluation of site-specific loading can lead to cost and material savings in rehabilitation and replacement of bridges. Currently, bridge traffic load assessment is carried out using long run traffic simulations based on weigh-in-motion (WIM) data obtained at the site. Congestion is the governing load condition for long-span bridges. To correctly model congestion, a minimum gap between vehicles is usually assumed. Where the gap is overestimated, the calculated characteristic load is smaller than the actual characteristic load leading to an unsafe assessment. If the gap is underestimated, the safety assessment is too conservative, which is both costly and wasteful of finite resources. This paper outlines the development of an optical method to measure parameters required to model driver behaviour in congestion. Images are obtained using a camera with a wide angle, aspherical lens. Edge detection and Hough transforms are used to location wheels and bumpers. The resulting data can increase the accuracy of traffic microsimulation and hence, the assessment of long span bridge traffic loading.Science Foundation Irelan

Serse: Searching for semantic web content

Abstract. Searching the Semantic Web (SW) for digital content is arguably more complex than searching the current web. In fact, a SW search system must deal with a large number of distributed, heterogeneous resources, that may reference many different ontologies. In order to manage this complexity we have integrated different technologies such as peer-to-peer, ontologies, and multi-agent technology in the design of SERSE, a multi-agent system for searching the SW. In SERSE, agents are organised in a P2P network according to a semantic overlay, where the neighbourhood is determined by the semantic proximity of the ontological definitions that are known to the agents. The integration of these technologies poses some problems. On the one hand, the more ontological knowledge the agents have, the better we can expect the system to perform. On the other hand, global knowledge would constitute a point of centralisation which might potentially degrade the performance of a P2P system. In addition, maintenance of such semantic overlay can also degrade the performance. The paper presents SERSE together with some experimental results that evaluate the performance in response to changes in the size of semantic neighbourhood and an analytical evaluation of the workload of the system due to maintenance activities.