Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to cancer with a measure of probability. Of the triad of cancer-causing factors (inherited genomic susceptibility, environmental factors, and lifestyle factors), the inherited genomic component may be derivable from the recent public availability of a large body of whole-genome variation data. However, genome-wide association studies have so far showed limited success in predicting the inherited susceptibility to common cancers. We present here a multiple classification approach for predicting individuals' inherited genomic susceptibility to acquire the most likely phenotype among a panel of 20 major common cancer types plus 1 "healthy" type by application of a supervised machine-learning method under competing conditions among the cohorts of the 21 types. This approach suggests that, depending on the phenotypes of 5,919 individuals of "white" ethnic population in this study, (i) the portion of the cohort of a cancer type who acquired the observed type due to mostly inherited genomic susceptibility factors ranges from about 33 to 88% (or its corollary: the portion due to mostly environmental and lifestyle factors ranges from 12 to 67%), and (ii) on an individual level, the method also predicts individuals' inherited genomic susceptibility to acquire the other types ranked with associated probabilities. These probabilities may provide practical information for individuals, heath professionals, and health policymakers related to prevention and/or early intervention of cancer

Optimization of Force Sensitivity in Q-Controlled Amplitude-Modulation Atomic Force Microscopy

We present control of force sensitivity in Q-controlled amplitude-modulation atomic force microscopy (AM-AFM) that is based on the high-Q quartz tuning-fork. It is found that the phase noise is identical to the amplitude noise divided by oscillation amplitude in AM-AFM. In particular, we observe that while Q-control does not compromise the signal-to-noise ratio, it enhances the detection sensitivity because the minimum detectable force gradient is inversely proportional to the effective quality factor for large bandwidths, which is due to reduction of frequency noise. This work demonstrates Q-control in AM-AFM is a useful technique for enhancement of the force sensitivity with increased Q or improvement of the scanning speed with decreased Q

The Devil in the Details: Simple and Effective Optical Flow Synthetic Data Generation

Recent work on dense optical flow has shown significant progress, primarily in a supervised learning manner requiring a large amount of labeled data. Due to the expensiveness of obtaining large scale real-world data, computer graphics are typically leveraged for constructing datasets. However, there is a common belief that synthetic-to-real domain gaps limit generalization to real scenes. In this paper, we show that the required characteristics in an optical flow dataset are rather simple and present a simpler synthetic data generation method that achieves a certain level of realism with compositions of elementary operations. With 2D motion-based datasets, we systematically analyze the simplest yet critical factors for generating synthetic datasets. Furthermore, we propose a novel method of utilizing occlusion masks in a supervised method and observe that suppressing gradients on occluded regions serves as a powerful initial state in the curriculum learning sense. The RAFT network initially trained on our dataset outperforms the original RAFT on the two most challenging online benchmarks, MPI Sintel and KITTI 2015

Temperature-dependent evolutions of excitonic superfluid plasma frequency in a srong excitonic insulator candidate, Ta2_2NiSe5_5

We investigate an interesting anisotropic van der Waals material, Ta$_{2}$NiSe$_{5}$, using optical spectroscopy. Ta$_{2}$NiSe$_{5}$ has been known as one of the few excitonic insulators proposed over 50 years ago. Ta$_{2}$NiSe$_{5}$ has quasi-one dimensional chains along the $a$-axis. We have obtained anisotropic optical properties of a single crystal Ta$_{2}$NiSe$_{5}$ along the $a$- and $c$-axes. The measured $a$- and $c$-axis optical conductivities exhibit large anisotropic electronic and phononic properties. With regard to the $a$-axis optical conductivity, a sharp peak near 3050 cm$^{-1}$ at 9 K, with a well-defined optical gap ($\Delta^{EI} \simeq$ 1800 cm$^{-1}$) and a strong temperature-dependence, is observed. With an increase in temperature, this peak broadens and the optical energy gap closes around $\sim$325 K($T_c^{EI}$). The spectral weight redistribution with respect to the frequency and temperature indicates that the normalized optical energy gap ($\Delta^{EI}(T)/\Delta^{EI}(0)$) is $1-(T/T_c^{EI})^2$. The temperature-dependent superfluid plasma frequency of the excitonic condensation in Ta$_{2}$NiSe$_{5}$ has been determined from measured optical data. Our findings may be useful for future research on excitonic insulators.Comment: 17 pages, 5 figure

Crude Extracts of Caenorhabditis elegans Suppress Airway Inflammation in a Murine Model of Allergic Asthma

Epidemiological studies suggest an inverse relationship between helminth infections and allergic disease, and several helminth-derived products have been shown to suppress allergic responses in animals. This study was undertaken to evaluate the effect of a crude extract of Caenorhabditis elegans on allergic airway inflammation in a murine model of asthma. Allergic airway inflammation was induced in BALB/c mice by sensitization with ovalbumin. The effect of the C. elegans crude extract on the development of asthma and on established asthma was evaluated by analyzing airway hyperresponsiveness, serum antibody titers, lung histology and cell counts and cytokine levels in the bronchoalveolar lavage fluid. The role of IFN-γ in the suppression of asthma by the C. elegans crude extract was investigated in IFN-γ knockout and wild-type mice. When mice were sensitized with ovalbumin together with the crude extract of C. elegans, cellular infiltration into the lung was dramatically reduced in comparison with the ovalbumin-treated group. Treatment of mice with the C. elegans crude extract significantly decreased methacholine-induced airway hyperresponsiveness and the total cell counts and levels of IL-4, IL-5 and IL-13 in the bronchoalveolar lavage fluid but increased the levels of IFN-γ and IL-12. Sensitization with the C. elegans crude extract significantly diminished the IgE and IgG1 responses but provoked elevated IgG2a levels. However, the suppressive effect of the C. elegans crude extract was abolished in IFN-γ knockout mice, and the Th2 responses in these mice were as strong as those in wild-type mice sensitized with ovalbumin. The crude extract of C. elegans also suppressed the airway inflammation associated with established asthma. This study provides new insights into immune modulation by the C. elegans crude extract, which suppressed airway inflammation in mice not only during the development of asthma but also after its establishment by skewing allergen-induced Th2 responses to Th1 responses

Higher-dimensional black-hole solution with dilaton field

Using dimensional reduction by isometry from a higher-dimensional Einstein theory, the higher-dimensional black-hole solutions are considered. We obtain the spherically symmetric black-hole solutions in (4+n)-dimensional spacetime with the dilaton field. It is shown that the contribution of the dilaton field affects the gravitational coupling

Could Fractional Exhaled Nitric Oxide Test be Useful in Predicting Inhaled Corticosteroid Responsiveness in Chronic Cough? A Systematic Review

© 2016 Background Fractional exhaled nitric oxide (FENO) is a safe and convenient test for assessing T H 2 airway inflammation, which is potentially useful in the management of patients with chronic cough. Objective To summarize the current evidence on the diagnostic usefulness of FENO for predicting inhaled corticosteroid (ICS) responsiveness in patients with chronic cough. Methods A systematic literature review was conducted to identify articles published in peer-reviewed journals up to February 2015, without language restriction. We included studies that reported the usefulness of FENO (index test) for predicting ICS responsiveness (reference standard) in patients with chronic cough (target condition). The data were extracted to construct a 2 × 2 accuracy table. Study quality was assessed with Quality Assessment of Diagnostic Accuracy Studies 2. Results We identified 5 original studies (2 prospective and 3 retrospective studies). We identified considerable heterogeneities in study design and outcome definitions, and thus were unable to perform a meta-analysis. The proportion of ICS responders ranged from 44% to 59%. Sensitivity and specificity ranged from 53% to 90%, and from 63% to 97%, respectively. The reported area under the curve ranged from abou t 0.60 to 0.87; however, studies with a prospective design and a lower prevalence of asthma had lower area under the curve values. None measured placebo effects or objective cough frequency. Conclusions We did not find strong evidence to support the use of FENO tests for predicting ICS responsiveness in chronic cough. Further studies need to have a randomized, placebo-controlled design, and should use validated measurement tools for cough. Standardization would facilitate the development of clinical evidence