In order for automated agent-based e-Commerce transactions to blossom, well-defined, analyzable and easily customizable interaction protocols or choreographies of involved parties need to be developed. Although, several domain-depended protocols have already been developed, efficient methodologies and technologies for facilitating the definition, deployment, reuse and maintenance of interaction protocols should be developed. This paper proposes a rule-based, reusable, analyzable and easily comprehensible by the user choreography definition methodology, called K-SWAN. Ôhe proposed choreography scheme separates the definition of the agent shared interaction protocol from the private agent interaction strategy and enables agents to choose the appropriate protocol for the transaction, from a library of re-usable interaction protocols, and automatically combine it with their personal strategy, from a private library, by using SW technologies for both. Complying with K-SWAN methodology will let agents participate seamlessly in different interaction processes and/or modify their behavior with a minimal programming effort. Finally, this paper presents the integration of the K-SWAN methodology into EMERALD, a multi-agent knowledge-based framework based on SW standards, which maximizes reusability and interoperability of behavior between agents.

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Background/Aim: Early-stage gastric cancer has a high risk of recurrence, despite trimodality therapy with surgery, chemotherapy and radiation. To improve patient selection for adjuvant chemoradiotherapy, we evaluated the prognostic significance of immunohistochemical and genetic biomarkers in patients with resected gastric adenocarcinoma. Patients and Methods: Tumors from 119 patients were subjected to immunohistochemistry for 12 protein biomarkers, as well as next-generation sequencing. Clinical and biomarker data were available for 91 patients. Results: EBV-positive tumors and tumors with mutations had higher intratumoral CD8 tumor-infiltrating lymphocyte density (p=0.009 and p=0.017, respectively). PIK3CA mutations were correlated with VEGFA overexpression (p=0.042), while KRAS mutations and HER2 expression were mutually exclusive (p=0.036). PTEN expression univariately confirmed longer overall survival (HR=0.27; p=0.046), while there was a trend between the presence of KRAS mutations and inferior disease-free and overall survival. Conclusion: PTEN protein expression and KRAS mutations may predict disease outcome in early-stage gastric cancer. These results need to be further validated in larger cohorts. Gastric cancer is the fifth most common cancer and the third leading cause of cancer-related mortality worldwide (1). Patients with stage I disease treated with gastrectomy have a 5-year survival rate of approximately 65%, whereas patients with more advanced disease have poorer outcomes with a 5year survival rate of 30% (2, 3). Complete surgical resection is required to cure gastric cancer (4). However, given the high recurrence rate after surgery, additional therapeutic approaches have been explored. These therapeutic strategies include 277 This article is freely accessible online.