Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A \emph{shapelet} is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselve

Proteomic Changes Resulting from Gene Copy Number Variations in Cancer Cells

Along the transformation process, cells accumulate DNA aberrations, including mutations, translocations, amplifications, and deletions. Despite numerous studies, the overall effects of amplifications and deletions on the end point of gene expression—the level of proteins—is generally unknown. Here we use large-scale and high-resolution proteomics combined with gene copy number analysis to investigate in a global manner to what extent these genomic changes have a proteomic output and therefore the ability to affect cellular transformation. We accurately measure expression levels of 6,735 proteins and directly compare them to the gene copy number. We find that the average effect of these alterations on the protein expression is only a few percent. Nevertheless, by using a novel algorithm, we find the combined impact that many of these regional chromosomal aberrations have at the protein level. We show that proteins encoded by amplified oncogenes are often overexpressed, while adjacent amplified genes, which presumably do not promote growth and survival, are attenuated. Furthermore, regulation of biological processes and molecular complexes is independent of general copy number changes. By connecting the primary genome alteration to their proteomic consequences, this approach helps to interpret the data from large-scale cancer genomics efforts

Topical Polyethylene Glycol as a Novel Chemopreventive Agent for Oral Cancer via Targeting of Epidermal Growth Factor Response

Head and neck squamous cell carcinoma (HNSCC) is a major cause of morbidity and mortality underscoring the need for safe and effective chemopreventive strategies. Targeting epidermal growth factor receptor (EGFR) is attractive in that it is an early critical event in HNSCC pathogenesis. However, current agents lack efficacy or have unacceptable toxicity. Several groups have demonstrated that the over-the-counter medication, polyethylene glycol (PEG) has remarkable chemopreventive efficacy against colon carcinogenesis. Importantly, we reported that this effect is mediated through EGFR internalization/degradation. In the current study, we investigated the chemopreventive efficacy of this agent against HNSCC, using both the well validated animal model 4-NQO (4-nitroquinoline 1-oxide) rat model and cell culture with the human HNSCC cell line SCC-25. We demonstrated that daily topical application of 10% PEG-8000 in the oral cavity (tongue and cavity wall) post 4NQO initiation resulted in a significant reduction in tumor burden (both, tumor size and tumors/tumor bearing rat) without any evidence of toxicity. Immunohistochemical studies depicted decreased proliferation (number of Ki67-positive cells) and reduced expression of EGFR and its downstream effectors cyclin D1 in the tongue mucosa of 4NQO-rats treated with PEG. We showed that EGFR was also markedly downregulated in SCC-25 cells by PEG-8000 with a concomitant induction of G1-S phase cell-cycle arrest, which was potentially mediated through upregulated p21cip1/waf1. In conclusion, we demonstrate, for the first time, that PEG has promising efficacy and safety as a chemopreventive efficacy against oral carcinogenesis

The relationship between the cell length, adhesion to acrylic and relative cell surface hydrophobicity of Candida parapsilosis

Candida parapsilosis is an emerging opportunistic pathogen which causes systemic and superficial infections in immunocompromised hosts. Successful colonization and subsequent infection of the host by a microorganism depends upon its ability to adhere to host surfaces, and its relative cell surface hydrophobicity (CSH) is a contributory physical force involved in the process. During a comprehensive study of a battery of C. parapsilosis isolates, we noted wide variations in their cell size. Hence we examined the relationship between the cell length, in vitro adhesion to acrylic surfaces and relative CSH of 24 isolates of C. parapsilosis from superficial and systemic sources. A strong positive correlation was observed between the cell length and adhesion of Candida to acrylic surfaces (r = 0.56; P = 0.004) as well as the cell length and the relative CSH, as measured by a hydrocarbon assay method (r = 0.72, P = 0.0001). Further, the cell length of both the superficial and systemic isolates correlated well with their CSH (r = 0.63, P = 0.01; r = 0.63, P = 0.03 for superficial and systemic isolates, respectively). These data provide a tantalizing glimpse of the structural and functional dynamics of the candidal cell surface.link_to_subscribed_fulltex