Broadband metamaterial for nonresonant matching of acoustic waves

Unity transmittance at an interface between bulk media is quite common for polarized electromagnetic waves incident at the Brewster angle, but it is rarely observed for sound waves at any angle of incidence. In the following, we theoretically and experimentally demonstrate an acoustic metamaterial possessing a Brewster-like angle that is completely transparent to sound waves over an ultra-broadband frequency range with >100% bandwidth. The metamaterial, consisting of a hard metal with subwavelength apertures, provides a surface impedance matching mechanism that can be arbitrarily tailored to specific media. The nonresonant nature of the impedance matching effectively decouples the front and back surfaces of the metamaterial allowing one to independently tailor the acoustic impedance at each interface. On the contrary, traditional methods for acoustic impedance matching, for example in medical imaging, rely on resonant tunneling through a thin antireflection layer, which is inherently narrowband and angle specific

Incorporating rich background knowledge for gene named entity classification and recognition

<p>Abstract</p> <p>Background</p> <p>Gene named entity classification and recognition are crucial preliminary steps of text mining in biomedical literature. Machine learning based methods have been used in this area with great success. In most state-of-the-art systems, elaborately designed lexical features, such as words, n-grams, and morphology patterns, have played a central part. However, this type of feature tends to cause extreme sparseness in feature space. As a result, out-of-vocabulary (OOV) terms in the training data are not modeled well due to lack of information.</p> <p>Results</p> <p>We propose a general framework for gene named entity representation, called feature coupling generalization (FCG). The basic idea is to generate higher level features using term frequency and co-occurrence information of highly indicative features in huge amount of unlabeled data. We examine its performance in a named entity classification task, which is designed to remove non-gene entries in a large dictionary derived from online resources. The results show that new features generated by FCG outperform lexical features by 5.97 F-score and 10.85 for OOV terms. Also in this framework each extension yields significant improvements and the sparse lexical features can be transformed into both a lower dimensional and more informative representation. A forward maximum match method based on the refined dictionary produces an F-score of 86.2 on BioCreative 2 GM test set. Then we combined the dictionary with a conditional random field (CRF) based gene mention tagger, achieving an F-score of 89.05, which improves the performance of the CRF-based tagger by 4.46 with little impact on the efficiency of the recognition system. A demo of the NER system is available at <url>http://202.118.75.18:8080/bioner</url>.</p

Recent trends in breast cancer incidence in US white women by county-level urban/rural and poverty status

<p>Abstract</p> <p>Background</p> <p>Unprecedented declines in invasive breast cancer rates occurred in the United States between 2001 and 2004, particularly for estrogen receptor-positive tumors among non-Hispanic white women over 50 years. To understand the broader public health import of these reductions among previously unstudied populations, we utilized the largest available US cancer registry resource to describe age-adjusted invasive and <it>in situ </it>breast cancer incidence trends for non-Hispanic white women aged 50 to 74 years overall and by county-level rural/urban and poverty status.</p> <p>Methods</p> <p>We obtained invasive and <it>in situ </it>breast cancer incidence data for the years 1997 to 2004 from 29 population-based cancer registries participating in the North American Association of Central Cancer Registries resource. Annual age-adjusted rates were examined overall and by rural/urban and poverty of patients' counties of residence at diagnosis. Joinpoint regression was used to assess trends by annual quarter of diagnosis.</p> <p>Results</p> <p>Between 2001 and 2004, overall invasive breast cancer incidence fell 13.2%, with greater reductions among women living in urban (-13.8%) versus rural (-7.5%) and low- (-13.0%) or middle- (-13.8%) versus high- (-9.6%) poverty counties. Most incidence rates peaked around 1999 then declined after second quarter 2002, although in rural counties, rates decreased monotonically after 1999. Similar but more attenuated patterns were seen for <it>in situ </it>cancers.</p> <p>Conclusion</p> <p>Breast cancer rates fell more substantially in urban and low-poverty, affluent counties than in rural or high-poverty counties. These patterns likely reflect a major influence of reductions in hormone therapy use after July 2002 but cannot exclude possible effects due to screening patterns, particularly among rural populations where hormone therapy use was probably less prevalent.</p

Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus

Recent breast cancer trends among Asian/Pacific Islander, Hispanic, and African-American women in the US: changes by tumor subtype

Abstract available at publisher's website

Recent breast cancer incidence trends according to hormone therapy use: the California Teachers Study cohort

Abstract Introduction Recent, international declines in breast cancer incidence are unprecedented, and the causes remain controversial. Few data sources can address breast cancer incidence trends according to pertinent characteristics like hormone therapy use history. Methods We used the prospective California Teachers Study to evaluate changes in self-reported use of menopausal hormone therapy (HT) between 1995 to 1996 and 2005 to 2006 and age-adjusted breast cancer incidence among 74,647 participants aged 50 years or older. Breast cancer occurrence was determined by linkage with the California Cancer Registry. Results During 517,286 woman years of follow up, 565 in situ and 2,668 invasive breast cancers were diagnosed. In situ breast cancer incidence rates in this population did not change significantly from 2000 to 2002 to 2003 to 2005, whereas rates of invasive breast cancer declined significantly by 26.0% from 528.0 (95% confidence intervals (CI) = 491.1, 564.9) per 100,000 women in 2000 to 2002 to 390.6 (95% CI = 355.6, 425.7) in 2003 to 2005. The decline in invasive breast cancer incidence rates was restricted to estrogen receptor-positive tumors. In 1996 to 1999 and 2000 to 2002 invasive breast cancer incidence was higher for women who reported current HT use especially estrogen-progestin (EP) use at baseline than for never or past users; but by 2003 to 2005 rates were comparable between these groups. For women who were taking EP in 2001 to 2002,75% of whom had stopped use by 2005 to 2006, incidence had declined 30.6% by 2003 to 2005 (P = 0.001); whereas incidence did not change significantly for those who never took HT (P = 0.33). Conclusions Few data resources can examine prospectively individual HT use and breast cancer diagnosis. Stable in situ breast cancer rates imply consistent levels of screening and suggest recent declines in invasive breast cancer to be explained predominantly by changes in HT use

Upregulation of pirin expression by chronic cigarette smoking is associated with bronchial epithelial cell apoptosis

BACKGROUND: Cigarette smoke disrupts the protective barrier established by the airway epithelium through direct damage to the epithelial cells, leading to cell death. Since the morphology of the airway epithelium of smokers does not typically demonstrate necrosis, the most likely mechanism for epithelial cell death in response to cigarette smoke is apoptosis. We hypothesized that cigarette smoke directly up-regulates expression of apoptotic genes, which could play a role in airway epithelial apoptosis. METHODS: Microarray analysis of airway epithelium obtained by bronchoscopy on matched cohorts of 13 phenotypically normal smokers and 9 non-smokers was used to identify specific genes modulated by smoking that were associated with apoptosis. Among the up-regulated apoptotic genes was pirin (3.1-fold, p < 0.002), an iron-binding nuclear protein and transcription cofactor. In vitro studies using human bronchial cells exposed to cigarette smoke extract (CSE) and an adenovirus vector encoding the pirin cDNA (AdPirin) were performed to test the direct effect of cigarette smoke on pirin expression and the effect of pirin expression on apoptosis. RESULTS: Quantitative TaqMan RT-PCR confirmed a 2-fold increase in pirin expression in the airway epithelium of smokers compared to non-smokers (p < 0.02). CSE applied to primary human bronchial epithelial cell cultures demonstrated that pirin mRNA levels increase in a time-and concentration-dependent manner (p < 0.03, all conditions compared to controls). Overexpression of pirin, using the vector AdPirin, in human bronchial epithelial cells was associated with an increase in the number of apoptotic cells assessed by both TUNEL assay (5-fold, p < 0.01) and ELISA for cytoplasmic nucleosomes (19.3-fold, p < 0.01) compared to control adenovirus vector. CONCLUSION: These observations suggest that up-regulation of pirin may represent one mechanism by which cigarette smoke induces apoptosis in the airway epithelium, an observation that has implications for the pathogenesis of cigarette smoke-induced diseases

Promotional Tone in Reviews of Menopausal Hormone Therapy After the Women's Health Initiative: An Analysis of Published Articles

Adriane Fugh-Berman and colleagues analyzed a selection of published opinion pieces on hormone therapy and show that there may be a connection between receiving industry funding for speaking, consulting, or research and the tone of such opinion pieces

Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

<p>Abstract</p> <p>Background</p> <p>Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.</p> <p>Methods</p> <p>In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS) SNPs ranked by Random Forests (RF) importance score for the CAMP (Childhood Asthma Management Program) population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group.</p> <p>Results</p> <p>Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC) = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors.</p> <p>Conclusions</p> <p>Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.</p