Harnessing the power of artificial intelligence to transform hearing healthcare and research

The advances in artificial intelligence that are transforming many fields have yet to make an impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model that fails to provide access to the majority of those in need, while hearing research suffers from a lack of computational tools with the capacity to match the complexities of auditory processing. This Perspective is a call for the artificial intelligence and hearing communities to come together to bring about a technological revolution in hearing. We describe opportunities for rapid clinical impact through the application of existing technologies and propose directions for the development of new technologies to create true artificial auditory systems. There is an urgent need to push hearing towards a future in which artificial intelligence provides critical support for the testing of hypotheses, the development of therapies and the effective delivery of care worldwide

The Search for Higher TcT_c in Houston

It is a great pleasure to be invited to join the chorus on this auspicious occasion to celebrate Professor K. Alex Mueller's 90th birthday by Professors Annette Bussman-Holder, Hugo Keller, and Antonio Bianconi. As a student in high temperature superconductivity, I am forever grateful to Professor Alex Mueller and Dr. Georg Bednorz "for their important breakthrough in the discovery of superconductivity in the ceramic materials" in 1986 as described in the citation of their 1987 Nobel Prize in Physics. It is this breakthrough discovery that has ushered in the explosion of research activities in high temperature superconductivity (HTS) and has provided immense excitement in HTS science and technology in the ensuing decades till now. Alex has not been resting on his laurels and has continued to search for the origin of the unusual high temperature superconductivity in cuprates.Comment: Dedicated to Alex Mueller, whose "important breakthrough in the discovery of superconductivity in ceramic materials" in 1986 has changed the world of superconductivit

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

Distribution-based bisimulation for labelled Markov processes

In this paper we propose a (sub)distribution-based bisimulation for labelled Markov processes and compare it with earlier definitions of state and event bisimulation, which both only compare states. In contrast to those state-based bisimulations, our distribution bisimulation is weaker, but corresponds more closely to linear properties. We construct a logic and a metric to describe our distribution bisimulation and discuss linearity, continuity and compositional properties.Comment: Accepted by FORMATS 201

Nucleosomes Correlate with In Vivo Progression Pattern of De Novo Methylation of p16 CpG Islands in Human Gastric Carcinogenesis

BACKGROUND: The exact relationship between nucleosome positioning and methylation of CpG islands in human pathogenesis is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we characterized the nucleosome position within the p16 CpG island and established a seeding methylation-specific PCR (sMSP) assay based on bisulfite modification to enrich the p16 alleles containing methylated-CpG at the methylation "seeding" sites within its intron-1 in gastric carcinogenesis. The sMSP-positive rate in primary gastric carcinoma (GC) samples (36/40) was significantly higher than that observed in gastritis (19/45) or normal samples (7/13) (P<0.01). Extensive clone sequencing of these sMSP products showed that the density of methylated-CpGs in p16 CpG islands increased gradually along with the severity of pathological changes in gastric tissues. In gastritis lesions the methylation was frequently observed in the region corresponding to the exon-1 coding-nucleosome and the 5'UTR-nucleosome; the methylation was further extended to the region corresponding to the promoter-nucleosome in GC samples. Only few methylated-CpG sites were randomly detected within p16 CpG islands in normal tissues. The significantly inversed relationship between the p16 exon-1 methylation and its transcription was observed in GC samples. An exact p16 promoter-specific 83 bp-MSP assay confirms the result of sMSP (33/55 vs. 1/6, P<0.01). In addition, p16 methylation in chronic gastritis lesions significantly correlated with H. pylori infection; however, such correlation was not observed in GC specimens. CONCLUSIONS/SIGNIFICANCE: It was determined that de novo methylation was initiated in the coding region of p16 exon-1 in gastritis, then progressed to its 5'UTR, and ultimately to the proximal promoter in GCs. Nucleosomes may function as the basic extension/progression unit of de novo methylation of p16 CpG islands in vivo

Temperature determines the diversity and structure of N2O-reducing microbial assemblages

Micro-organisms harbouring the nosZ gene convert N O to N and play a critical role in reducing global N O emissions. As higher denitrifier diversity can result in higher denitrification rates, here we aimed to understand the diversity, composition and spatial structure of N O-reducing microbial assemblages in forest soils across a large latitudinal and temperature gradient. We sequenced nosZ gene amplicons of 126 soil samples from six forests with mean annual soil temperatures (MAST) ranging from 3.7 to 25.3°C and tested predictions of the metabolic theory of ecology (MTE) and metabolic-niche theory (MNT). As predicted, α-diversity of nosZ communities increased with increasing MAST, within-site β-diversity decreased and two (pH and soil moisture) of the three niche widths examined were larger with increasing MAST. We calculated β-nearest taxon distance and Raup–Crick metric to quantify the relative influence of the assembly processes determining nosZ assemblage structure. Environmental selection was the primary process driving assemblage structure in all six forests. Homogenizing dispersal was also important at one site, which could be explained by the site's much lower variability in soil chemistry. We used canonical correspondence analysis and multiple regression on matrices to examine relationships between nosZ communities and environmental factors, and found that temperature and spatial distance were significant predictors of nosZ assemblage structure. Overall our results support both theories (MTE and MNT) tested, showing that higher temperatures are correlated with higher local diversity, wider niche breadths and lower within-site turnover rates. A plain language summary is available for this article. 2 2 2

Characterization of High-Fat, Diet-Induced, Non-alcoholic Steatohepatitis with Fibrosis in Rats

An ideal animal model is necessary for a clear understanding of the etiology, pathogenesis, and mechanisms of human non-alcoholic steatohepatitis (NASH) and for facilitating the design of effective therapy for this condition. We aimed to establish a rat model of NASH with fibrosis by using a high-fat diet (HFD). Male Sprague–Dawley (SD) rats were fed a HFD consisting of 88 g normal diet, 10 g lard oil, and 2 g cholesterol. Control rats were fed normal diet. Rats were killed at 4, 8, 12, 16, 24, 36, and 48 weeks after HFD exposure. Body weight, liver weight, and epididymal fat weight were measured. Serum levels of fasting glucose, triglyceride, cholesterol, alanine aminotransferase (ALT), free fatty acids (FFA), insulin, and tumor necrosis factor-alpha (TNF-α) were determined. Hepatic histology was examined by H&E stain. Hepatic fibrosis was assessed by VG stain and immunohistochemical staining for transforming growth factor beta 1 (TGF-β1), and alpha-smooth-muscle actin (α-SMA). The liver weight and liver index increased from week 4, when hepatic steatosis was also observed. By week 8, the body weight and epididymal fat weight started increasing, which was associated with increased serum levels of FFA, cholesterol, and TNF-α, as well as development of simple fatty liver. The serum ALT level increased from week 12. Steatohepatitis occurred from weeks 12 through 48. Apparent hepatic perisinosodial fibrosis did not occur until week 24, and progressed from week 36 to 48 with insulin resistance. Therefore, this novel model may be potentially useful in NASH study

Towards outperforming conventional sensor arrays with fabricated individual photonic vapour sensors inspired by Morpho butterflies.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.Combining vapour sensors into arrays is an accepted compromise to mitigate poor selectivity of conventional sensors. Here we show individual nanofabricated sensors that not only selectively detect separate vapours in pristine conditions but also quantify these vapours in mixtures, and when blended with a variable moisture background. Our sensor design is inspired by the iridescent nanostructure and gradient surface chemistry of Morpho butterflies and involves physical and chemical design criteria. The physical design involves optical interference and diffraction on the fabricated periodic nanostructures and uses optical loss in the nanostructure to enhance the spectral diversity of reflectance. The chemical design uses spatially controlled nanostructure functionalization. Thus, while quantitation of analytes in the presence of variable backgrounds is challenging for most sensor arrays, we achieve this goal using individual multivariable sensors. These colorimetric sensors can be tuned for numerous vapour sensing scenarios in confined areas or as individual nodes for distributed monitoring.We would like to acknowledge H. Ghiradella (University at Albany), M. Blohm and S. Duclos (GE) and V. Greanya, J. Abo-Shaeer, C. Nehl and M. Sandrock (DARPA) for fruitful discussions. This work has been supported in part from DARPA contract W911NF-10-C-0069 ‘Bio Inspired Photonics’ and from General Electric’s Advanced Technology research funds. The content of the information does not necessarily reflect the position or the policy of the US Government

The NLO QCD Corrections to BcB_c Meson Production in Z0Z^0 Decays

The decay width of $Z^0$ to $B_c$ meson is evaluated at the next-to-leading order(NLO) accuracy in strong interaction. Numerical calculation shows that the NLO correction to this process is remarkable. The quantum chromodynamics(QCD)renormalization scale dependence of the results is obviously depressed, and hence the uncertainties lying in the leading order calculation are reduced.Comment: 14 pages, 7 figures; references added; expressions and typos ammende

A 115-bp MethyLight assay for detection of p16 (CDKN2A) methylation as a diagnostic biomarker in human tissues

<p>Abstract</p> <p>Background</p> <p><it>p16 </it>Methylation is a potential biomarker for prediction of malignant transformation of epithelial dysplasia. A probe-based, quantitative, methylation-specific PCR (MSP) called MethyLight may become an eligible method for detecting this marker clinically. We studied oral mucosa biopsies with epithelial dysplasia from 78 patients enrolled in a published 4-years' followup cohort, in which cancer risk for patients with <it>p16 </it>methylation-positive dysplasia was significantly higher than those without <it>p16 </it>methylation (by 150-bp MSP and bisulfite sequencing; +133 ~ +283, transcription starting site, +1). The <it>p16 </it>methylation status in samples (<it>N </it>= 102) containing sufficient DNA was analyzed by the 70-bp classic (+238 ~ +307) and 115-bp novel (+157 ~ +272) MethyLight assays, respectively.</p> <p>Results</p> <p><it>p16 </it>Methylation was detectable in 75 samples using the classic MethyLight assay. The methylated-<it>p16 </it>positive rate and proportion of methylated-<it>p16 </it>by the MethyLight in MSP-positive samples were higher than those in MSP-negative samples (positive rate: 37/44 vs. 38/58, <it>P</it>=0.035, two-sided; proportion [median]: 0.78 vs. 0.02, <it>P <</it>0.007). Using the published results of MSP as a golden standard, we found sensitivity, specificity, and accuracy for this MethyLight assay to be 70.5%, 84.5%, and 55.0%, respectively. Because amplicon of the classic MethyLight procedure only partially overlapped with the MSP amplicon, we further designed a 115-bp novel MethyLight assay in which the amplicon on the sense-strand fully overlapped with the MSP amplicon on the antisense-strand. Using the 115-bp MethyLight assay, we observed methylated-<it>p16 </it>in 26 of 44 MSP-positive samples and 2 of 58 MSP-negative ones (<it>P </it>= 0.000). These results were confirmed with clone sequencing. Sensitivity, specificity, and accuracy using the 115-bp MethyLight assay were 59.1%, 98.3%, and 57.4%, respectively. Significant differences in the oral cancer rate were observed during the followup between patients (≥60 years) with and without methylated-<it>p16 </it>as detected by the 115-bp MethyLight assay (6/8 vs. 6/22, P = 0.034, two-sided).</p> <p>Conclusions</p> <p>The 115-bp MethyLight assay is a useful and practical assay with very high specificity for the detection of <it>p16 </it>methylation clinically.</p