Evidence for three tumor suppressor loci on chromosome 9p involved in melanoma development

Cytogenetic and loss of heterozygosity (LOH) studies have long indicated the presence of a tumor suppressor gene (TSG) on 9p involved in the development of melanoma. Although LOH at 9p has been reported in approximately 60% of melanoma tumors, only 5-10% of these tumors have been shown to carry CDKN2A mutations, raising the possibility that another TSG involved in melanoma maps to chromosome 9p. To investigate this possibility, a panel of 37 melanomas derived from 35 individuals was analyzed for CDKN2A mutations by single-strand conformation polymorphism analysis and sequencing. The melanoma samples were then typed for 15 markers that map to 9p13-24 to investigate LOH trends in this region. In those tumors demonstrating retention of heterozygosity at markers flanking CDKN2A and LOH on one or both sides of the gene, multiplex microsatellite PCR was performed to rule out homozygous deletion of the region encompassing CDKN2A. CDKN2A mutations were found in tumors from 5 patients [5 (14%) of 35], 4 of which demonstrated LOH across the entire region examined. The remaining tumor with no observed LOH carried two point mutations, one on each allele. Although LOH was identified at one or more markers in 22 (59%) of 37 melanoma tumors corresponding to 20 (57%) of 35 individuals, only 11 tumors from 9 individuals [9 (26%) of 35] demonstrated LOH at D9S942 and D9S1748 the markers closest to CDKN2A. Of the remaining 11 tumors with LOH 9 demonstrated LOH at two or more contiguous markers either centromeric and/or telomeric to CDKN2A while retaining heterozygosity at several markers adjacent to CDKN2A. Multiplex PCR revealed one tumor carried a homozygous deletion extending from D9S1748 to the IFN-alpha locus. In the remaining eight tumors, multiplex PCR demonstrated that the observed heterozygosity was not attributable to homozygous deletion and stromal contamination at D9S1748, D9S942, or D9S974, as measured by comparative amplification strengths, which indicates that retention of heterozygosity with flanking LOH does not always indicate a homozygous deletion. This report supports the conclusions of previous studies that a least two TSGs involved in melanoma development in addition to CDKN2A may reside on chromosome 9p.

Deletion mapping suggests that the 1p22 melanoma susceptibility gene is a tumor suppressor localized to a 9-Mb interval

Loss of the short arm of chromosome 1 is frequently observed in many tumor types, including melanoma. We recently localized a third melanoma susceptibility locus to chromosome band 1p22. Critical recombinants in linked families localized the gene to a 15-Mb region between D1S430 and D1S2664. To map the locus more finely we have performed studies to assess allelic loss across the region in a panel of melanomas from 1p22-linked families, sporadic melanomas, and melanoma cell lines. Eighty percent of familial melanomas exhibited loss of heterozygosity (LOH) within the region, with a smallest region of overlapping deletions (SRO) of 9 Mb between D1S207 and D1S435. This high frequency of LOH makes it very likely that the susceptibility locus is a tumor suppressor. In sporadic tumors, four SROs were defined. SRO1 and SRO2 map within the critical recombinant and familial tumor region, indicating that one or the other is likely to harbor the susceptibility gene. However, SRO3 may also be significant because it overlaps with the markers with the highest 2-point LOD score (D1S2776), part of the linkage recombinant region, and the critical region defined in mesothelioma. The candidate genes PRKCL2 and GTF2B, within SRO2, and TGFBR3, CDC7, and EVI5, in a broad region encompassing SRO3, were screened in 1p22-linked melanoma kindreds, but no coding mutations were detected. Allelic loss in melanoma cell lines was significantly less frequent than in fresh tumors, indicating that this gene may not be involved late in progression, such as in overriding cellular senescence, necessary for the propagation of melanoma cells in culture.

On a Syntactic Characterization of Classification with a Mind Change Bound

Most learning paradigms impose a particular syntax on the class of concepts to be learned; the chosen syntax can dramatically affect whether the class is learnable or not. For classification paradigms, where the task is to determine whether the underlying world does or does not have a particular property, how that property is represented has no implication on the power of a classifier that just outputs 1’s or 0’s. But is it possible to give a canonical syntactic representation of the class of concepts that are classifiable according to the particular criteria of a given paradigm? We provide a positive answer to this question for classification in the limit paradigms in a logical setting, with ordinal mind change bounds as a measure of complexity. The syntactic characterization that emerges enables to derive that if a possibly noncomputable classifier can perform the task assigned to it by the paradigm, then a computable classifier can also perform the same task. The syntactic characterization is strongly related to the difference hierarchy over the class of open sets of some topological space; this space is naturally defined from the class of possible worlds and possible data of the learning paradigm.

Classification of packet contents for malware detection

Many existing schemes for malware detection are signature-based. Although they can effectively detect known malwares, they cannot detect variants of known malwares or new ones. Most network servers do not expect executable code in their in-bound network traffic, such as on-line shopping malls, Picasa, Youtube, Blogger, etc. Therefore, such network applications can be protected from malware infection by monitoring their ports to see if incoming packets contain any executable contents. This paper proposes a content-classification scheme that identifies executable content in incoming packets. The proposed scheme analyzes the packet payload in two steps. It first analyzes the packet payload to see if it contains multimedia-type data (such as . If not, then it classifies the payload either as text-type (such as or executable. Although in our experiments the proposed scheme shows a low rate of false negatives and positives (4.69% and 2.53%, respectively), the presence of inaccuracies still requires further inspection to efficiently detect the occurrence of malware. In this paper, we also propose simple statistical and combinatorial analysis to deal with false positives and negatives.

Simple classification of walking activities using commodity smart phones

People interact with mobile computing devices everywhere, while sitting, walking, running or even driving. Adapting the interface to suit these contexts is important, thus this paper proposes a simple human activity classification system. Our approach uses a vector magnitude recognition technique to detect and classify when a person is stationary (or not walking), casually walking, or jogging, without any prior training. The user study has confirmed the accuracy.

Rethinking regulatory design : The Australian National Classification Scheme review

This paper considers issues of methodological innovation in communication, media and cultural studies, that arise out of the extent to which we now live in a media environment characterised by an digital media abundance, the convergence of media platforms, content and services, and the globalisation of media content through ubiquitous computing and high-speed broadband networks. These developments have also entailed a shift in the producer-consumer relationships that characterised the 20th century mass communications paradigm, with the rapid proliferation of user-created content, accelerated innovation, the growing empowerment of media users themselves, and the blurring of distinctions between public and private, as well as age-based distinctions in terms of what media can be accessed by whom and for what purpose. It considers these issues through a case study of the Australian Law Reform Commission's National Classification Scheme Review.

Using Web Search Logs to Identify Query Classification Terms

Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interfaces

Operations research for mining : a classification and literature review

In this paper, we describe the main processes and operations in mining industries and present a comprehensive survey of operations research methodologies that have been applied over the last several decades. The literature review is classified into four main categories: mine design; mine production; mine transportation; and mine evaluation. Mining design models are further separated according to two main mining methods: open-pit and underground. Moreover, mine production models are subcategorised into two groups: ore mining and coal mining. Mine transportation models are further partitioned in accordance with fleet management, truck haulage and train scheduling. Mine evaluation models are further subdivided into four clusters in terms of mining method selection, quality control, financial risks and environmental protection. The main characteristics of four Australian commercial mining software are addressed and compared. This paper bridges the gaps in the literature and motivates researchers to develop more applicable, realistic and comprehensive operations research models and solution techniques that are directly linked with mining industries.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.