DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

Photocatalytic activity of nitrogen-doped TiO2-based nanowires: a photo-assisted Kelvin probe force microscopy study

The emerging industrial business partnerships, which feature cross-functional and cross-company development efforts, raise the barrier for the establishment of effective knowledge sharing practices in the larger organization. This chapter aims to highlight the role of knowledge as a key enabler for effective engineering activities in the light of such emerging enterprise collaboration models. Knowledge Enabled Engineering (KEE) is presented as an approach to enhance the extended organization’s capability to establish effective collaboration among its parts, in spite of different organizational structures, technologies or processes. KEE is analysed in its constituent parts, highlighting areas, methods and tools that are particularly interesting for leveraging companies’ knowledge sharing capabilities

Using Magnetically Responsive Tea Waste to Remove Lead in Waters under Environmentally Relevant Conditions

We report the use of a simple yet highly effective magnetite-waste tea composite to remove lead(II) (Pb[superscript 2+]) ions from water. Magnetite-waste tea composites were dispersed in four different types of water–deionized (DI), artificial rainwater, artificial groundwater and artificial freshwater–that mimic actual environmental conditions. The water samples had varying initial concentrations (0.16–5.55 ppm) of Pb[superscript 2+] ions and were mixed with the magnetite-waste tea composite for at least 24 hours to allow adsorption of the Pb[superscript 2+] ions to reach equilibrium. The magnetite-waste tea composites were stable in all the water samples for at least 3 months and could be easily removed from the aqueous media via the use of permanent magnets. We detected no significant leaching of iron (Fe) ions into the water from the magnetite-waste tea composites. The percentage of Pb adsorbed onto the magnetite-waste tea composite ranged from ~70% to 100%; the composites were as effective as activated carbon (AC) in removing the Pb[superscript 2+] ions from water, depending on the initial Pb concentration. Our prepared magnetite-waste tea composites show promise as a green, inexpensive and highly effective sorbent for removal of Pb in water under environmentally realistic conditions.SUTD-MIT International Design Center (Research Grant IDG11200105/IDD11200109)Singapore-MIT Allianc

Environmental and Parental Influences on Offspring Health and Growth in Great Tits (Parus major)

PMCID: PMC3728352This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis

Health, Health-Related Quality of Life, and Quality of Life: What is the Difference?

The terms health, health-related quality of life (HRQoL), and quality of life (QoL) are used interchangeably. Given that these are three key terms in the literature, their appropriate and clear use is important. This paper reviews the history and definitions of the terms and considers how they have been used. It is argued that the definitions of HRQoL in the literature are problematic because some definitions fail to distinguish between HRQoL and health or between HRQoL and QoL. Many so-called HRQoL questionnaires actually measure self-perceived health status and the use of the phrase QoL is unjustified. It is concluded that the concept of HRQoL as used now is confusing. A potential solution is to define HRQoL as the way health is empirically estimated to affect QoL or use the term to only signify the utility associated with a health state

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Ideological Labels in America

This paper extends Ellis and Stimson’s (Ideology in America. New York: Cambridge UniversityPress, 2012) study of the operational-symbolic paradox using issue-level measures of ideological incongruence based on respondent positions and symbolic labels for these positions across 14 issues. Like Ellis and Stimson, we find that substantial numbers—over 30 %—of Americans experience conflicted conservatism. Our issue-level data reveal, furthermore, that conflicted conservatism is most common on the issues of education and welfare spending. In addition, we also find that 20 % of Americans exhibit conflicted liberalism. We then replicate Ellis and Stimson’s finding that conflicted conservatism is associated with low sophistication and religiosity, but also find that it is associated with being socialized in a post-1960s generation and using Fox News as a main news source. Finally, we show the important role played by identities, with both conflicted conservatism and conflicted liberalism linked with partisan and ideological identities, and conflicted liberalism additionally associated with ethnic identities

Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012