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Overexpression of epidermal growth factor receptor (EGFR) is common in pancreatic cancer and associated with the poor prognosis of this malignancy. To develop anti-EGFR antibody–drug conjugates (ADCs) for use in a novel EGFR-targeting approach to treat pancreatic cancer. A humanized anti-EGFR monoclonal antibody (RC68) was generated by mouse immunization and complementary-determining region grafting technology. Two RC68-based ADCs, RC68-MC-VC-PAB-MMAE and RC68-PY-VC-PAB-MMAE, were synthesized by conjugating monomethyl auristatin E (MMAE), a small-molecule cytotoxin, to RC68 through two distinct linkers (MC and PY). Internalization of the RC68-based ADCs was examined by flow cytometry. The in vitro and in vivo antitumor activities of RC68-based ADCs were evaluated in human pancreatic cancer cells and in a BXPC-3 xenograft nude mouse model, respectively. The RC68-based ADCs bound to EGFR on the surface of tumor cells and were effectively internalized, resulting in the death of EGFR-positive cancer cell lines. The RC68-based ADCs (at 5 or 10 mg/kg) were more potent than gemcitabine hydrochloride (60 mg/kg) at inhibiting the growth of BXPC-3 xenografts. Moreover, RC68-PY-VC-PAB-MMAE was found to have superior stability in human plasma compared with RC68-MC-VC-PAB-MMAE. A novel EGFR-targeting ADC, RC68-PY-VC-PAB-MMAE, shows promise as an effective, selective, and safe therapeutic agent for EGFR-positive pancreatic cancer.

Epidermal growth factor receptor (EGFR) is highly expressed on non-small cell lung cancers (NSCLC) and a valuable therapeutic target. This study aimed at producing and characterizing monomethyl auristatin E (MMAE)-conjugated anti-EGFR antibody as a novel EGFR-targeting therapy for NSCLC. A humanized anti-EGFR monoclonal antibody (named RC68) was purified and conjugated with MMAE using a MC-VC-PAB or PY-VC-PAB linker. The in vitro and in vivo antitumor activity of RC68-MC-VC-PAB-MMAE and RC68-PY-VC-PAB-MMAE were characterized. The RC68 was generated from RC68-expressing cells and had a purity of > 99.0%. The RC68 recognized EGFR on tumor cells, particularly for higher EGFR expressing H125, A431, HCC827 and H1975 cells. The RC68 was conjugated with an average of 4 MMAE molecules to generate RC68-MC-VC-PAB-MMAE and RC68-PY-VC-PAB-MMAE, respectively. The RC68-MC-VC-PAB-MMAE, RC68-PY-VC-PAB-MMAE and RC68 displayed similar binding affinity to EGFR on tumor cells, and RC68-MC-VC-PAB-MMAE and RC68-PY-VC-PAB-MMAE were effectively internalized by H125 cells. The RC68-MC-VC-PAB-MMAE and RC68-PY-VC-PAB-MMAE inhibited the growth of H125 cells in vitro with an IC50 7.37–8.04 ng/mL and implanted H125 tumors in vivo, but did not affect body weights of mice. The antitumor effect of RC68-MC-VC-PAB-MMAE was stronger than RC68-PY-VC-PAB-MMAE, which was also stronger than docetaxel in vivo. These novel antibody–drug conjugates, particularly for RC68-MC-VC-PAB-MMAE, may be a potential candidate for treatment of EGFR + NSCLC.

Objective To construct the eukaryotic expression vector of CD20 and overexpress soluble CD20 proteins in HEK293T cells. Methods The total RNA from human peripheral blood mononuclear cells (PBMCs) was used to amplify the coding sequence of CD20 by reverse transcription PCR, and then the CD20 gene was cloned into the expression vector pCMV3-C-His. After PCR and sequencing validation, the recombinant CD20 protein was transiently expressed in HEK293T cells and detected by ELISA and Western blot analysis. Moreover, the expression conditions were optimized to improve the expression level of CD20. Results The coding sequence of CD20 was successfully cloned into eukaryotic expression vector pCMV3-C-His. After 72 hours of transfection, the expression of CD20 was detected both in intracellular and supernatant by Western blot analysis. The passage number of HEK293T cells was related to the expression level of CD20 in supernatant. Conclusion The coding sequence of CD20 was successfully cloned into the eukaryotic expression vector, and CD20 was over expressed in HEK293T cells.

Scientific evaluation of the main transformer equipment suppliers is the premise to ensure the cost control and safe operation of the power grid. Based on the analysis of various factors affecting the main transformer equipment supplier, the evaluation index of the main transformer equipment supplier is constructed. Considering the fuzziness of the evaluation index, the index weight is determined by AHP, and the evaluation model of main transformer equipment supplier based on fuzzy comprehensive evaluation is established. The example calculation shows that the fuzzy comprehensive evaluation method can fully reveal the evaluation index information and reflect the actual situation of main transformer equipment suppliers scientifically and reasonably.

As an important state-owned energy backbone enterprise related to national energy security and the lifeline of national economy, power grid enterprises are responsible for ensuring the quality and safety of equipment and promoting the development of equipment quality. Therefore, continuously improving the quality evaluation of main transformer equipment is very important to improve the quality of power grid main transformer equipment. This paper first constructs the main transformer equipment quality evaluation index system from equipment procurement, equipment installation, equipment use and equipment decommissioning and scrapping; on this basis, the scoring method of each evaluation index is given, and the final main transformer equipment quality evaluation score is calculated by combining subjective and objective weight determination method; Finally, according to the evaluation of 500kV main transformer equipment of provincial power grid company price score, to evaluate the performance of equipment quality provided by suppliers.

An efficient cleaning method is crucial for the power production and equipment reliability of a Photovoltaic (PV) system. This paper presents an alternative cleaning and dust detection method for PV modules. Instead of monitoring the difference between the real and theoretical power production of PV modules, this method analyzes the soiling loss by alternatively cleaning two panels at the beginning of the cleaning period. When the loss reaches the cleaning cost, a cleaning reminder is generated while considering the weather forecast. The efficacy of the proposed theoretical model is established based on 1-year data collected in the Shandong PV system. Annual production improvement of more than 1.33% is achieved with a net return of more than 0.78% on the deduction of cleaning cost, which is equal to $1363/GWh economic benefit per year.

B-cell lymphoma remains one of the most refractory tumors, and as such the development of novel treatment approaches, such as antibody-drug conjugates (ADCs), is required. To improve the stability and homogeneity of the ADCs, a humanized anti-CD19 monoclonal antibody (RC58) was developed in the present study. RC58 was based on the CD19 antigen as a potential molecular target of human B-cell lymphomas. RC58 has high CD19-binding affinity and can be internalized in CD19-positive cells through endocytosis. Furthermore, three types of RC58-based ADCs (ADC-1, ADC-2, and ADC-3) were generated using three kinds of Maleimide-PEG-based linkers with two different cytotoxins. The anti-tumor activities of the ADCs were confirmed by in vitro and in vivo experiments. The stability of the ADCs was also evaluated by incubation in human plasma for 10 days. In vitro experiments showed that the three ADCs had distinct inhibitory effects on several B-lymphoma cell lines. Meanwhile, a close correlation between efficacy and drug concentration was found in a nude mouse xenograft model of human B-cell lymphoma, after treatment with RC58-based ADCs. Our results suggest that ADC-1, with high efficiency, could be used as a potential therapeutic agent for human B-cell malignancies.

G-quadruplexes are four-stranded DNA structures formed from G-rich sequences that are built around tetrads of hydrogen-bonded guanine bases. Accumulating studies have revealed that G-quadruplex structures are formed in vivo and play important roles in biological processes such as DNA replication, transcription, recombination, epigenetic regulation, meiosis, antigenic variation, and maintenance of telomeres stability. Mounting evidence indicates that a variety of proteins are capable of binding selectively and tightly to G-quadruplex and play essential roles in G-quadruplex-mediated regulation processes. Some of these proteins promote the formation or/and stabilization of G-quadruplex, while some other proteins act to unwind G-quadruplex preferentially. From a drug discovery perspective, many of these G-quadruplex binding proteins and/or their complexes with G-quadruplexes are potential drug targets. Here, we present a general summary of reported G-quadruplex binding proteins and their biological functions, with focus on those of medicinal research significance. We elaborated the possibility for some of these G-quadruplex binding proteins and their complexes with G-quadruplexes as potential drug targets.

Background Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder that is characterized by dementia, cognitive impairment, and memory loss. Diverse factors are related to the development of AD, such as increased level of β-amyloid (Aβ), acetylcholine, metal ion deregulation, hyperphosphorylated tau protein, and oxidative stress. Methods The following methods were used: organic syntheses of 1H-phenanthro[9,10-d]imidazole derivatives, inhibition of self-mediated and metal-induced Aβ1–42 aggregation, inhibition studies for acetylcholinesterase and butyrylcholinesterase, anti-oxidation activity studies, CD, MTT assay, transmission electron microscopy, dot plot assay, gel electrophoresis, Western blot, and molecular docking studies. Results We synthesized and characterized a new type of 1H-phenanthro[9,10-d]imidazole derivatives as multifunctional agents for AD treatment. Our results showed that most of these derivatives exhibited strong Aβ aggregation inhibitory activity. Compound 9g had 74% Aβ1–42 aggregation inhibitory effect at 10 μM concentration with its IC50 value of 6.5 μM for self-induced Aβ1–42 aggregation. This compound also showed good inhibition of metal-mediated (Cu2 + and Fe2 +) and acetylcholinesterase-induced Aβ1–42 aggregation, as indicated by using thioflavin T assay, transmission electron microscopy, gel electrophoresis, and Western blot. Besides, compound 9g exhibited cholinesterase inhibitory activity, with its IC50 values of 0.86 μM and 0.51 μM for acetylcholinesterase and butyrylcholinesterase, respectively. In addition, compound 9g showed good anti-oxidation effect with oxygen radical absorbance capacity (ORAC) value of 2.29. Conclusions Compound 9g was found to be a potent multi-target-directed agent for Alzheimer's disease. General significance Compound 9g could become a lead compound for further development as a multi-target-directed agent for AD treatment.

A series of hesperidin derivatives were prepared and identified by IR, (1)H NMR, and MS spectra. These compounds were evaluated in vitro and in vivo based on α-glucosidase inhibition, glucose consumption of HepG2 cells, and blood glucose level in streptozotocin-induced diabetic mice. The results revealed that all the compounds exhibited anti-hyperglycemic activities. The inhibition at 10(-3) M of compounds 3 and 7a on α-glucosidase were 55.02% and 53.34%, respectively, as compared to 54.80% by acarbose. Treated by compound 3 and the reference drug metformin, glucose consumption of HepG2 cell were 1.78 and 2.11 mM, respectively. After the streptozotocin-induced diabetic mice were oral administrated with compound 3 at 100 mg kg(-1) d(-1) for 10 days, the blood glucose level of 3 treated mice (13.23 mM, P

In telecommunications network troubleshooting, analytical applications are widely used. Such applications typically use CEP (Complex Event Processing) and SQL queries for data processing and network analysis. Performance engineers need in-depth knowledge of both the telecommunications domain and telecommunications data structures in order to create the required queries. Moreover valuable information contained in free form text data fields such as “additional_info”, “user_text” or “problem_text” can also be ignored. This work proposes CADMANT: Context Anomaly Detection for MAintenance and Network Troubleshooting. Traditional approaches focus on a specific record type and create specific cause and effect rules. With the CADMANT approach all free form text fields of alarms, logs, etc. are treated as text documents similar to Twitter feeds. CADMANT uses distance based outlier detection within sliding windows to detect abnormal terms at configurable time intervals. The CADMANT approach provides automated analysis without the requirement for SQL/CEP queries and provides distinct network insights in comparison to traditional approaches.

The thermal effect in hydraulic circuits becomes a more significant concern, because of the energy demand and management of the new generation airplane. Although fluid transients in pipelines have been researched for decades, thermal effect is hardly considered. This paper models thermo-fluid characteristics in pipe net analytically as well as other hydraulic components, using the transfer matrix method (TMM).

Service-based business processes are often developed and deployed by single organizations. In distributed, shared resource environments like the cloud on the other hand, consumers share resources owned by cloud providers. %Higher levels of resource sharing gives more economy of scale for providers in the software-as-a-service (SaaS) or business process-as-a-service (BPaaS) space. This requires multi-tenancy capability for service processes that provides customized behaviour for on shared process implementations to meet the varying needs of different process consumers as tenants of the process resource. In this paper, we define a distributed multi-tenant architecture for BPEL processes provided as a service. A single-version BPEL process is deployed by a provider and offered for all process consumers, combined with a customization and management functionality to create a unique experience for different consumers (process tenants). We provide two core components: a policy model for consumers to express customization/business requirements of service processes and a coordination framework for policy enforcement between consumers and providers to achieve on-the-fly customization of service processes.

Browsing and searching network information for observation, analysis and troubleshooting is an inherent part of using the features and functions of any Network Management System. Enterprise search has capabilities for handling various data types and sources and big data scalability, and is becoming an emerging technology for such network management functions development. In this paper, we give an overview on work done in our research and prototype team regarding an advanced search project. We provide a brief report on search fundamental knowledge and study of Solr search platform stack. It answers common questions from management and development teams regarding adopting search technology for production development, and gives a Solr reference card for developers. We also introduce two advanced search features, user experience based search recommendation and anomaly detection enhanced search ranking from our research work. Two features are developed to make network searches more efficient as it can help user quickly locate the most valuable search results, but the concept can be adopted for search applications in other domains.

Network operators are increasingly using analytic applications to improve the performance of their networks. Telecommunications analytical applications typically use SQL and Complex Event Processing (CEP) for data processing, network analysis and troubleshooting. Such approaches are hindered as they require an in-depth knowledge of both the telecommunications domain and telecommunications data structures in order to create the required queries. Valuable information contained in free form text data fields such as “additional_info”, “user_text” or “problem_text” can also be ignored. This work proposes An Anomaly Detection Algorithm for MAintenance and Network Troubleshooting (ADAMANT), a text analytic based network anomaly detection approach. Once telecommunications data records have been indexed, ADAMANT uses distance based outlier detection within sliding windows to detect abnormal terms at configurable time intervals. Traditional approaches focus on a specific type of record and create specific cause and effect rules. With the ADAMANT approach all free form text fields of alarms, logs, etc. are treated as text documents similar to Twitter feeds. All documents within a window represent a snapshot of the network state that is processed by ADAMANT. The ADAMANT approach focuses on text analytics to provide automated analysis without the requirement for SQL/CEP queries. Such an approach provides distinct network insights in comparison to traditional approaches.

When searching for data in a telecommunications network management application, large search result sets are common. In order to refine the results to retrieve useful information existing systems normally require additional user intervention such as appending or removing a search keyword, adding a filter, grouping results, etc. This work proposes a Probabilistic Search Recommendation Algorithm to Improve Search Efficiency for Network Intelligence and Troubleshooting (PRISENIT). PRISENIT is a query-based recommendation algorithm intended to improve search efficiency and usability for telecommunication system management. PRISENIT is an extension of an item-based collaborative filtering algorithm. It uses correlation-based similarity and users' implicit feedback in order to improve search efficiency. It learns from previous experiences in order to optimize decision-making. Currently there exists no known query-based recommender adaptation mechanism for network management. Existing search engines use previous user searches to make a suggestion based on the keyword. PRISENIT not only considers search terms, it also considers the influence of filters and features in order to makes network searches more efficient as it removes the necessity for users to manually choose search features or search filters. Experimental results show that PRISENIT can improve user experience in a telecommunications management environment.

Services are offered in an execution context that is determined by how a provider provisions the service and how the user consumes it. The need for more flexibility requires the provisioning and consumption aspects to be addressed at run-time. We propose an ontology-based context model providing a framework for service provisioning and consumption aspects and techniques for managing context constraints for Web service processes where dynamic context concerns can be monitored and validated at service process run-time. We discuss the contextualisation of dynamically relevant aspects of Web service processes as our main goal, i.e. capture aspects in an extended context model. The technical contributions of this paper are a context model ontology for dynamic service context and an operator calculus for integrated and coherent context manipulation, composition and reasoning. The context model ontology formalises dynamic aspects of Web services and facilitates reasoning. We present the context ontology in terms of four core dimensions--functional, QoS, domain and platform--which are internally interconnected.

Service processes are often enacted across different boundaries such as organisations, countries or even languages. Specifically, looking at the quality and governance of data or content processed by services in this context is important to control different constraints in this cross-boundary processing. In order to provide a context-aware solution that takes into account data and data processing requirements, a rule-based constraints specification and adaptation of processes shall be proposed. A domain ontology shall capture the key data/content data types, activities and constraints, which forms the basis of a rule-based policy monitoring solution. A provenance model is at the core of this ontology solution. The key contribution is a domain-specific model and specification template for constraint policy definition, which can be applied to adapt service processes to domain-specific needs.

In many domains such as Telecom various scenarios necessitate the processing of large amounts of data using statistical and machine learning algorithms. A noticeable effort has been made to move the data management systems into MapReduce parallel processing environments such as Hadoop and Pig. Nevertheless these systems lack the features of advanced machine learning and statistical analysis. Frame-works such as Mahout on top of Hadoop support machine learning but their implementations are at the preliminary stage. For example Mahout does not provide Support Vector Machine (SVM) algorithms and it is difficult to use. On the other hand traditional statistical software tools such as R containing comprehensive statistical algorithms for advanced analysis are widely used. But such software can only run on a single computer and therefore it is not scalable. In this paper we propose an integrated solution RPig which takes the advantages of R (for machine learning and statistical analysis capabilities) and parallel data processing capabilities of Pig. The RPig framework offers a scalable advanced data analysis solution for machine learning and statistical analysis. Analysis jobs can be easily developed with RPig script in high level languages. We describe the design implementation and an eclipse-based RPigEditor for the RPig framework. Using application scenarios from the Telecom domain we show the usage of RPig and how the framework can significantly reduce the development effort. The results demonstrate the scalability of our framework and the simplicity of deployment for analysis jobs.

Cloud computing needs end-user customisation and personalisation of multi-tenant cloud service offerings. Particularly, QoS and governance policy management and monitoring is needed. We propose a user-customisable policy definition solution that can be enforced in multitenant cloud offerings through automated instrumentation and monitoring. Service processes run by cloud and SaaS providers can be made policy-aware in a transparent way.

With software services becoming a strategic capability for the software sector, service engineering needs to address integration problems based on support that helps services to collaborate and coordinate their activities. The increasing need to address dynamic and automated changes - caused by on-demand environments and changing requirements - shall be answered through a service coordination architecture based on event-based collaboration. The solution is based on a service coordination space architecture that acts as a passive infrastructure for event-based collaboration. We discuss the information architecture and the coordination principles of such a collaboration environment.

Service engineering needs to address integration problems allowing services to collaborate and coordinate. The need to address dynamic automated changes - caused by on-demand environments and changing requirements - can be addressed through service coordination based on ontology-based composition and matching techniques. Our solution to composition and matching utilises a service coordination space that acts as a passive infrastructure for collaboration. We discuss the information models and the coordination principles of such a collaboration environment in terms of an ontology and its underlying description logics. We provide ontology-based solutions for structural composition of descriptions and matching between requested and provided services.

peer-reviewed Service-oriented architecture is an architectural approach that can be applied for building autonomous service systems dynamically to satisfy on-demand business requests. During the execution of service compositions, architectural constraint violations relating to functional and non-fucntional system properties need to be handled intelligently and autonomously, possibly requiring architectural reconfigurations. We propose integrated architectural constraint violation handling to deal with architectural quality problems through dynamic reconfiguration. We concentrate on service replacement selection as a remedial strategy for a possible quality violation requiring architectural remedies.

With the emergence of Business Process Outsourcing and Cloud Computing, enterprises are looking for available business processes outside of their organizations to quickly adopt to new business requirements and also reduce process development and maintenance costs. The process execution needs to be governed as policy enforcement might differ between different clients. Since a process is deployed outside of the organizations and serves multiple process clients, distribution and multi-tenancy have become two requirements for runtime governance of service processes. We address this problem by introducing a policy-oriented aspectual business process framework. The runtime governance constraints from process clients are integrated as aspects through dynamic weaving into rpcess execution.

Service-Oriented Architecture (SOA) offers a technical foundation for Enterprise Application Integration and business collaboration through service-based business components. With increasing process outsourcing and cloud computing, enterprises need process-level integration and collaboration (process-oriented) to quickly launch new business processes for new customers and products. However, business processes that cross organisations’ compliance regulation boundaries are still unaddressed. We introduce a distributed aspect-oriented service composition approach, which enables multiple process clients hot-plugging their business compliance models (business rules, fault handling policy, and execution monitor) to BPEL business processes.

Dynamic service composition is suitable for on-demand business requests. For autonomic computing, service composition needs to deal with runtime environment faults, but also with business constraint violations which result from business requirements. We propose an approach for integrated handling of business constraint violations and runtime environment faults for dynamic service composition. We introduce a loosely coupled implementation architecture to maintain the platform-independent nature.

Autonomic, i.e. dynamic and fault-tolerant Web service composition is a requirement resulting from recent developments such as on-demand services. In the context of planning-based service composition, multi-agent planning and dynamic error handling are still unresolved problems. Recently, business rule and constraint management has been looked at for enterprise SOA to add business flexibility. This paper proposes a constraint integration and violation handling technique for dynamic service composition. Higher degrees of reliability and fault-tolerance, but also performance for autonomously composed WS-BPEL processes are the objectives.

Web service composition is a technology that has received considerable attention in the last number of years. Languages and tools to aid in the process of creating composite Web services have been received specific attention. Web service composition is the process of linking single Web services together in order to accomplish more complex tasks. One area of Web service composition that has not received as much attention is the area of dynamic error handling and re-planning, enabling autonomic composition. Given a repository of service descriptions and a task to complete, it is possible for AI planners to automatically create a plan that will achieve this goal. If however a service in the plan is unavailable or erroneous the plan will fail. Motivated by this problem, this paper suggests autonomous re-planning as a means to overcome dynamic problems. Our solution involves automatically recovering from faults and creating a context-dependent alternate plan. We present an architecture that serves as a basis for the central activities autonomous composition, monitoring and fault handling.

Resistance to RAF-MEK targeted therapy is a major clinical challenge. RAF-MEK inhibitors are initially but only transiently effective in some but not all BRAF mutant patients, and largely ineffective in RAS mutant patients because of resistance. Through a genetic screen in BRAF mutant tumor cells, we show that the Hippo pathway effector YAP acts as a parallel survival input to promote resistance to RAF-MEK inhibitor therapy. Combined YAP and RAF-MEK inhibition was synthetically lethal not only in several BRAF mutant tumor types but also in RAS mutant tumors. Increased YAP in BRAFV600E patient tumors was a biomarker of worse initial response to RAF inhibition in patients, establishing the clinical relevance of our findings. Our data uncover YAP as a novel mechanism of resistance to RAF-MEK targeted therapy. The findings unveil the synthetic lethality of YAP and RAF-MEK co-suppression as a promising strategy to enhance response and patient survival. Citation Format: Luping Lin, Amit Sabnis, Elton Chan, Victor Olivas, Lindsay Cade, Evangelos Pazarentzos, Saurabh Asthana, Dana Neel, Jenny Jiacheng Yan, Xinyuan Lu, Luu Pham, Mingxue Wang, Niki Karachaliou, Maria G. Cao, Jose L. Manzano, Jose L. Ramirez, Jose M. Torres, Fiamma Buttitta, Charles M. Rudin, Eric A. Collisson, Alain Algazi, Eric Robinson, Iman Osman, Eva Munoz-Couselo, Javier Cortes, Dennie T. Frederick, Zachary A. Cooper, Martin McMahon, Antonio Marchetti, Rafael Rosell, Keith T. Flaherty, Jennifer A. Wargo, Trever G. Bivona. The Hippo effector YAP promotes resistance to RAF and MEK targeted therapies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-239. doi:10.1158/1538-7445.AM2015-LB-239

The effect of stocking density on growth of juveniles Acipenser schrenckii was studied, and the results showed that juveniles Acipenser schrenckii reared for 28 days in a flowing water system under different stocking densities of 0.232, 0.665, 1.347, and 2.469 kg.m-2 grew in allometry. There were no significant differences between the final and initial SV under the four treatments. The growth efficiency, DWG, NY, and SGR of juveniles were decreased with the increase of stocking densities. However, the FCR and NY were increased with the increase of stocking densities. There were significant differences between these parameters under the low and high densities treatment after 28 days. Moreover, there was a significant negative linear correlation between stocking density (D) and special growth rate (SGR).

Recent cross-organisational software service offerings, such as cloud computing, create higher integration needs. In particular, services are combined through brokers and mediators, solutions to allow individual services to collaborate and their interaction to be coordinated are required. The need to address dynamic management - caused by cloud and on-demand environments - can be addressed through service coordination based on ontology-based composition and matching techniques. Our solution to composition and matching utilises a service coordination space that acts as a passive infrastructure for collaboration where users submit requests that are then selected and taken on by providers. We discuss the information models and the coordination principles of such a collaboration environment in terms of an ontology and its underlying description logics. We provide ontology-based solutions for structural composition of descriptions and matching between requested and provided services.