Showing papers by "Stephen McLaughlin published in 2013"

Time-Frequency Reassignment and Synchrosqueezing: An Overview

Abstract: This article provides a general overview of time-frequency (T-F) reassignment and synchrosqueezing techniques applied to multicomponent signals, covering the theoretical background and applications. We explain how synchrosqueezing can be viewed as a special case of reassignment enabling mode reconstruction and place emphasis on the interest of using such T-F distributions throughout with illustrative examples.

Nonlinear unmixing of hyperspectral images: models and algorithms

Abstract: When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM). However, the LMM may be not valid and other nonlinear models need to be considered, for instance, when there are multi-scattering effects or intimate interactions. Consequently, over the last few years, several significant contributions have been proposed to overcome the limitations inherent in the LMM. In this paper, we present an overview of recent advances in nonlinear unmixing modeling.

SMAD2, SMAD3 and SMAD4 mutations in colorectal cancer

Abstract: Activation of the canonical TGF-β signaling pathway provides growth inhibitory signals in the normal intestinal epithelium. Colorectal cancers (CRCs) frequently harbor somatic mutations in the pathway members TGFBR2 and SMAD4, but to what extent mutations in SMAD2 or SMAD3 contribute to tumorigenesis is unclear. A cohort of 744 primary CRCs and 36 CRC cell lines were sequenced for SMAD4, SMAD2, and SMAD3 and analyzed for allelic loss by single-nucleotide polymorphism (SNP) microarray analysis. Mutation spectra were compared between the genes, the pathogenicity of mutations was assessed, and relationships with clinicopathologic features were examined. The prevalence of SMAD4, SMAD2, and SMAD3 mutations in sporadic CRCs was 8.6% (64 of 744), 3.4% (25 of 744), and 4.3% (32 of 744), respectively. A significant overrepresentation of two genetic hits was detected for SMAD4 and SMAD3, consistent with these genes acting as tumor suppressors. SMAD4 mutations were associated with mucinous histology. The mutation spectra of SMAD2 and SMAD3 were highly similar to that of SMAD4, both in mutation type and location within the encoded proteins. In silico analyses suggested the majority of the mutations were pathogenic, with most missense changes predicted to reduce protein stability or hinder SMAD complex formation. The latter altered interface residues or disrupted the phosphorylation-regulated Ser-Ser-X-Ser motifs within SMAD2 and SMAD3. Functional analyses of selected mutations showed reductions in SMAD3 transcriptional activity and SMAD2-SMAD4 complex formation. Joint biallelic hits in SMAD2 and SMAD3 were overrepresented and mutually exclusive to SMAD4 mutation, underlining the critical roles of these three proteins within the TGF-β signaling pathway.

Different APC genotypes in proximal and distal sporadic colorectal cancers suggest distinct WNT/β-catenin signalling thresholds for tumourigenesis.

Abstract: Biallelic protein-truncating mutations in the adenomatous polyposis coli (APC) gene are prevalent in sporadic colorectal cancer (CRC). Mutations may not be fully inactivating, instead producing WNT/β-catenin signalling levels ‘just-right' for tumourigenesis. However, the spectrum of optimal APC genotypes accounting for both hits, and the influence of clinicopathological features on genotype selection remain undefined. We analysed 630 sporadic CRCs for APC mutations and loss of heterozygosity (LOH) using sequencing and single-nucleotide polymorphism microarrays, respectively. Truncating APC mutations and/or LOH were detected in 75% of CRCs. Most truncating mutations occurred within a mutation cluster region (MCR; codons 1282–1581) leaving 1–3 intact 20 amino-acid repeats (20AARs) and abolishing all Ser-Ala-Met-Pro (SAMP) repeats. Cancers commonly had one MCR mutation plus either LOH or another mutation 5′ to the MCR. LOH was associated with mutations leaving 1 intact 20AAR. MCR mutations leaving 1 vs 2–3 intact 20AARs were associated with 5′ mutations disrupting or leaving intact the armadillo-repeat domain, respectively. Cancers with three hits had an over-representation of mutations upstream of codon 184, in the alternatively spliced region of exon 9, and 3′ to the MCR. Microsatellite unstable cancers showed hyper-mutation at MCR mono- and di-nucleotide repeats, leaving 2–3 intact 20AARs. Proximal and distal cancers exhibited different preferred APC genotypes, leaving a total of 2 or 3 and 0 to 2 intact 20AARs, respectively. In conclusion, APC genotypes in sporadic CRCs demonstrate ‘fine-tuned' interdependence of hits by type and location, consistent with selection for particular residual levels of WNT/β-catenin signalling, with different ‘optimal' thresholds for proximal and distal cancers.

PIK3CA and PTEN Gene and Exon Mutation-Specific Clinicopathologic and Molecular Associations in Colorectal Cancer

Abstract: Purpose: PIK3CA and PTEN mutations are prevalent in colorectal cancer and potential markers of response to mitogen-activated protein/extracellular signal–regulated kinase inhibitors and anti-EGF receptor antibody therapy. Relationships between phosphoinositide 3-kinase (PI3K) pathway mutation, clinicopathologic characteristics, molecular features, and prognosis remain controversial. Experimental Design: A total of 1,093 stage I–IV colorectal cancers were screened for PIK3CA (exons 9 and 20), KRAS (codons 12–13), BRAF (codon 600) mutations, and microsatellite instability (MSI). PTEN (exons 3–8) and CpG island methylator phenotype (CIMP) status were determined in 744 and 489 cases. PIK3CA data were integrated with 17 previous reports ( n = 5,594). Results: PIK3CA and PTEN mutations were identified in 11.9% and 5.8% of colorectal cancers. PTEN mutation was associated with proximal tumors, mucinous histology, MSI-high (MSI-H), CIMP-high (CIMP-H), and BRAF mutation ( P PIK3CA mutation was related to older age, proximal tumors, mucinous histology, and KRAS mutation ( P PIK3CA exon 9 and 20 mutations were overrepresented in proximal, CIMP-low (CIMP-L), and KRAS -mutated cancers ( P ≤ 0.011). Comparing PIK3CA exonic mutants, exon 20 mutation was associated with MSI-H, CIMP-H, and BRAF mutation, and exon 9 mutation was associated with KRAS mutation ( P ≤ 0.027). Disease-free survival for stage II/III colorectal cancers did not differ by PI3K pathway status. Conclusion: PI3K pathway mutation is prominent in proximal colon cancers, with PIK3CA exon 20 and PTEN mutations associated with features of the sessile-serrated pathway (MSI-H/CIMP-H/ BRAF mut ), and PIK3CA exon 9 (and to a lesser extent exon 20) mutation associated with features of the traditional serrated pathway (CIMP-L/ KRAS mut ) of tumorigenesis. Our data highlight the PI3K pathway as a therapeutic target in distinct colorectal cancer subtypes. Clin Cancer Res; 19(12); 3285–96. ©2013 AACR .

Time-Frequency Analysis and Applications [From the Guest Editors]

Abstract: The articles in this special section on time frequency analysis and applications for its use.

Generalized Thresholding and Online Sparsity-Aware Learning in a Union of Subspaces

Abstract: This paper considers a sparse signal recovery task in time-varying (time-adaptive) environments. The contribution of the paper to sparsity-aware online learning is threefold; first, a generalized thresholding (GT) operator, which relates to both convex and non-convex penalty functions, is introduced. This operator embodies, in a unified way, the majority of well-known thresholding rules which promote sparsity. Second, a non-convexly constrained, sparsity-promoting, online learning scheme, namely the adaptive projection-based generalized thresholding (APGT), is developed that incorporates the GT operator with a computational complexity that scales linearly to the number of unknowns. Third, the novel family of partially quasi-nonexpansive mappings is introduced as a functional analytic tool for treating the GT operator. By building upon the rich fixed point theory, the previous class of mappings establishes also a link between the GT operator and a union of linear subspaces; a non-convex object which lies at the heart of any sparsity promoting technique, batch or online. Based on this functional analytic framework, a convergence analysis of the APGT is provided. Extensive experiments suggest that the APGT exhibits competitive performance when compared to computationally more demanding alternatives, such as the sparsity-promoting affine projection algorithm (APA)- and recursive least-squares (RLS)-based techniques.

A novel time-frequency technique for multicomponent signal denoising

Abstract: Multicomponent signals, i.e. superpositions of modulated waves, arise in many physical or biological systems. Exploiting the particular structure of these signals, denoising methods based on time-frequency distributions often outperform standard techniques such as those based on diagonal estimation or sparsity approaches. Recently, a simple denoising technique based on local integration in scale of the wavelet transform was proposed. In spite of its behaviour being better compared to classical techniques for medium noise levels, it does not perform so well in other cases. We propose here a method to improve denoising behaviour based on a more accurate mode reconstruction technique. The method is detailed for time-frequency representation given by short-time Fourier and continuous wavelet transforms, with the emphasis placed on their differences.

Voltage control of UK residential customers for power reduction

Abstract: Reducing peak system demand is generally regarded as a crucial step in deferring investment in electricity networks and improving overall performance. Several utilities have explored the used of voltage control for peak reduction but the results are inconclusive. This paper presents results of an ongoing study of the potential of voltage control for demand reduction within the UK distribution network. A stochastic simulation approach using detailed low-voltage residential load models and network models is implemented to quantify the scale of demand reduction for step change in voltage magnitude.

Thresholding-based online algorithms of complexity comparable to sparse LMS methods

Abstract: This paper deals with a novel class of set-theoretic adaptive sparsity promoting algorithms of linear computational complexity. Sparsity is induced via generalized thresholding operators, which correspond to nonconvex penalties such as those used in a number of sparse LMS based schemes. The results demonstrate the significant performance gain of our approach, at comparable computational cost.

Second primary colorectal cancer in the era of prevalent screening and imaging

Abstract: Background Oncology literature is increasingly recognizing prevalence of second primary cancers including several longitudinal studies showing an increased risk of colorectal cancer following a prostate cancer diagnosis. A retrospective study was conducted to examine the relationship between prior prostate cancer diagnoses and subsequent colorectal cancer diagnoses. Methods A multi-centre prospective colorectal cancer registry was queried for patients with a prior history of prostate, breast or lung cancer. Characteristics of these patients were compared to patients with colorectal cancer and no prior cancer history. Results Of 4660 cases of colorectal cancer diagnosed between 1998 and 2011, 2665 (57.2%) were male, median age was 68 years. For patients with a history of prostate cancer (n = 111), breast cancer (n = 61) and lung cancer (n = 23), the great majority of subsequent colorectal cancer diagnoses occurred in the initial 2 to 4 years after the first cancer diagnosis. This was accompanied by an increased rate of asymptomatic colorectal cancer at presentation, due to both screen detected and incidental cancer diagnoses. There was no clear relationship between any prostate cancer treatment and subsequent colorectal cancer risk, location or timing. Discussion In the modern era, there is an increased rate of colorectal cancer diagnosis in years shortly following another common cancer history. This is consistently seen across different primary tumour streams including prostate, breast and lung cancers and in part contributed by screen detected and incidental colorectal cancer diagnoses. Future studies should consider this potential confounding factor when asserting an increased rate of colorectal cancer as a second primary cancer.

Analysis of strongly modulated multicomponent signals with the short-time Fourier transform

Abstract: This paper addresses the issue of the retrieval of the components of a multicomponent signal from its short-time Fourier transform. It recalls two popular reconstruction methods, and extends each of them for the case of strong frequency modulation, by taking into account the second derivative of the phase. Numerical experiments illustrate the improvement and compare the methods.

Super-resolution Sparse Projected Capacitive Multitouch Sensing

Abstract: The resolution of capacitive touch sensors is not sufficient for some sensing applications. The coarse resolution of a sensor with a regular grid is limited by the half distance between two adjacent layer-crossovers. Increasing the density of such layer-crossovers, improves the resolution of touch signals. While this technique needs some modification in the hardware, it does not necessarily guarantee that the corresponding estimated touch locations are more accurate. We explore the problem of resolution enhancement for the multitouch sensors here, using the sparsity pattern of the touch signals. This is called the super-resolution as the goal is to enhance the sensor resolution, while not changing the sensing hardware, and only incorporates some prior information about the input. The super-resolution problem can be computationally very costly. The aim is to present a rather simple algorithm to run in the real-time. This has been achieved by exploiting a structured sparse representation, which allows a computationally simple superresolution algorithm.

Nonlinear hyperspectral unmixing using Gaussian processes

Abstract: This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components. We assume that the spectral signatures of the pure components and the nonlinear function are unknown. The first step of the proposed method estimates the abundance vectors for all the image pixels using a Gaussian process latent variable model. The endmembers are subsequently estimated using Gaussian process regression. The performance of the unmixing strategy is compared with state-of-the-art unmixing strategies on synthetic data. An interesting property is its robustness to the absence of pure pixels in the image.