Data Mining by Soft Computing Methods for The Coronary Heart Disease Database

For improvement of data mining technology, the advantages and disadvantages on respective data mining methods should be discussed by comparison under the same condition. For this purpose, the Coronary Heart Disease database (CHD DB) was developed in 2004, and the data mining competition was held in the International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES). In the competition, two methods based on soft computing were presented. In this paper, we report the overview of the CHD DB and the soft computing methods, and discuss the features of respective methods by comparison of the experimental results

Rule Extraction by Genetic Programming with Clustered Terminal Symbols

When Genetic Programming (GP) is applied to rule extraction from databases, the attributes of the data are often used for the terminal symbols. However, in the case of the database with a large number of attributes, the search space becomes vast because the size of the terminal set increases. As a result, the search performance declines. For improving the search performance, we propose new methods for dealing with the large-scale terminal set. In the methods, the terminal symbols are clustered based on the similarities of the attributes. In the beginning of search, by reducing the number of terminal symbols, the rough and rapid search is performed. In the latter stage of search, by using the original attributes for terminal symbols, the local search is performed. By comparison with the conventional GP, the proposed methods showed the faster evolutional speed and extracted more accurate classification rules

Classification results of coronary heart disease database by using the clonal selection method with receptor editing

The clonal selection principle is used to explain the basic features of an adaptive immune response to a antigenic stimulus. It established the idea that only those cells that recognize the antigens are selected to proliferate and differentiate. This paper explains a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune response. The clonal selection algorithm by incorporating receptor editing method, RECSA, has been proposed by Gao. This paper tries to classify the medical database of Coronary Heart Disease databases and reports the computational results for 4 kinds of training datasets

Basal Cell Carcinoma of the Head and Neck

Basal cell carcinoma (BCC) is a malignant neoplasm derived from nonkeratinizing cells that originate from the basal layer of the epidermis and is the most frequent type of skin cancer in humans, with cumulative exposure to ultraviolet radiation as an important risk factor. BCC occurs most frequently at sun-exposed sites, with the head and neck being common areas. Tumors can be classified as nodular, superficial, morpheaform, infiltrating, metatypic, and fibroepithelioma of Pinkus. Several treatment options such as surgical excision and nonsurgical procedures are available. The choice of treatment should be determined based on the histological subtype of a lesion, cost, its size and location, patient age, medical condition of the patient, treatment availability, and the patient's wishes. The aim of any therapy selected for BCC treatment involving the head and neck is to ensure complete removal, the preservation of function, and a good cosmetic outcome

Early Detection of Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is a unique disease with a clinical presentation, epidemiology, and histopathology differing from other squamous cell carcinomas of the head and neck. NPC is an Epstein-Barr virus-associated malignancy with a marked racial and geographic distribution. Specifically, it is highly prevalent in southern China, Southeast Asia, and the Middle East. To date, most NPC patients have been diagnosed in the advanced stage, but the treatment results for advanced NPC are not satisfactory. This paper provides a brief overview regarding NPC, with the focus on the early detection of initial and recurrent NPC lesions

Targeted Molecular Therapy in Glioblastoma.

This special issue was aimed at updating researchers on current topics and progress made in basic, preclinical, and clinical glioblastoma research. It also provided a platform for pharmaceutical and translational scientists to submit original research articles, review articles, and clinical studies, focusing on the evaluation of new molecular pathways as pharmacological targets for treatment strategies which may improve the management of aggressive, drug-resistant GBM, in the hope that a deeper knowledge of GBM biology may eventually lead to effective targeted therapeutic approaches based on the inhibition of tumor-specific proteins or molecular pathways

CXCL14 Acts as a Specific Carrier of CpG DNA into Dendritic Cells and Activates Toll-like Receptor 9-mediated Adaptive Immunity

CXCL14 is a primordial chemokine that plays multiple roles in tumor suppression, autoimmune arthritis, and obesity-associated insulin resistance. However, the underlying molecular mechanisms are unclear. Here, we show that CXCL14 transports various types of CpG oligodeoxynucleotide (ODN) into the endosomes and lysosomes of bone marrow-derived dendritic cells (DCs), thereby activating Toll-like receptor 9 (TLR9). A combination of CpG ODN (ODN2395) plus CXCL14 induced robust production of IL-12 p40 by wild-type, but not Tlr9-knockout, DCs. Consistent with this, ODN2395-mediated activation of DCs was significantly attenuated in Cxcl14-knockout mice. CXCL14 bound CpG ODN with high affinity at pH 7.5, but not at pH 6.0, thereby enabling efficient delivery of CpG ODN to TLR9 in the endosome/lysosome. Furthermore, the CXCL14-CpG ODN complex specifically bound to high affinity CXCL14 receptors on DCs. Thus, CXCL14 serves as a specific carrier of CpG DNA to sensitize TLR9-mediated immunosurveillance