Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection

Background: Voice disorders affect patients profoundly, and acoustic tools can potentially measure voice function objectively. Disordered sustained vowels exhibit wide-ranging phenomena, from nearly periodic to highly complex, aperiodic vibrations, and increased "breathiness". Modelling and surrogate data studies have shown significant nonlinear and non-Gaussian random properties in these sounds. Nonetheless, existing tools are limited to analysing voices displaying near periodicity, and do not account for this inherent biophysical nonlinearity and non-Gaussian randomness, often using linear signal processing methods insensitive to these properties. They do not directly measure the two main biophysical symptoms of disorder: complex nonlinear aperiodicity, and turbulent, aeroacoustic, non-Gaussian randomness. Often these tools cannot be applied to more severe disordered voices, limiting their clinical usefulness.

Methods: This paper introduces two new tools to speech analysis: recurrence and fractal scaling, which overcome the range limitations of existing tools by addressing directly these two symptoms of disorder, together reproducing a "hoarseness" diagram. A simple bootstrapped classifier then uses these two features to distinguish normal from disordered voices.

Results: On a large database of subjects with a wide variety of voice disorders, these new techniques can distinguish normal from disordered cases, using quadratic discriminant analysis, to overall correct classification performance of 91.8% plus or minus 2.0%. The true positive classification performance is 95.4% plus or minus 3.2%, and the true negative performance is 91.5% plus or minus 2.3% (95% confidence). This is shown to outperform all combinations of the most popular classical tools.

Conclusions: Given the very large number of arbitrary parameters and computational complexity of existing techniques, these new techniques are far simpler and yet achieve clinically useful classification performance using only a basic classification technique. They do so by exploiting the inherent nonlinearity and turbulent randomness in disordered voice signals. They are widely applicable to the whole range of disordered voice phenomena by design. These new measures could therefore be used for a variety of practical clinical purposes.
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Regurgitation Hemodynamics Alone Cause Mitral Valve Remodeling Characteristic of Clinical Disease States In Vitro

Mitral valve regurgitation is a challenging clinical condition that is frequent, highly varied, and poorly understood. While the causes of mitral regurgitation are multifactorial, how the hemodynamics of regurgitation impact valve tissue remodeling is an understudied phenomenon. We employed a pseudo-physiological flow loop capable of long-term organ culture to investigate the early progression of remodeling in living mitral valves placed in conditions resembling mitral valve prolapse (MVP) and functional mitral regurgitation (FMR). Valve geometry was altered to mimic the hemodynamics of controls (no changes from native geometry), MVP (5ﾠmm displacement of papillary muscles towards the annulus), and FMR (5ﾠmm apical, 5ﾠmm lateral papillary muscle displacement, 65% larger annular area). Flow measurements ensured moderate regurgitant fraction for regurgitation groups. After 1-week culture, valve tissues underwent mechanical and compositional analysis. MVP conditioned tissues were less stiff, weaker, and had elevated collagen III and glycosaminoglycans. FMR conditioned tissues were stiffer, more brittle, less extensible, and had more collagen synthesis, remodeling, and crosslinking related enzymes and proteoglycans, including decorin, matrix metalloproteinase-1, and lysyl oxidase. These models replicate clinical findings of MVP (myxomatous remodeling) and FMR (fibrotic remodeling), indicating that valve cells remodel extracellular matrix in response to altered mechanical homeostasis resulting from disease hemodynamics

Flows and cohesion: balancing capabilities across an expanded union

The dynamics of physical relocation of intellectual capital is seen in the flow of skilled workers across international boundaries and the internal movements within the increasingly integrated economy of the European Union. This article describes a research framework developed within the context of a globalised economy and its potential application to issues within the boundaries of the European Unio

Redox-neutral organocatalytic Mitsunobu reactions

Nucleophilic substitution reactions of alcohols are amongst the most fundamental and strategically important transformations in organic chemistry. For over half a century these reactions have been achieved using stoichiometric, and often hazardous, reagents to activate the otherwise unreactive alcohols. Here we demonstrate that a specially designed phosphine oxide promotes nucleophilic substitution reactions of primary and secondary alcohols within a redoxneutral catalysis manifold that produces water as the sole by-product. The scope of the catalytic coupling process encompasses a range of acidic pronucleophiles that allow stereospecific construction of carbon-oxygen and carbon-nitrogen bonds

Identification of BPIFA1/SPLUNC1 as an epithelium-derived smooth muscle relaxing factor

Asthma is a chronic airway disease characterized by inflammation, mucus hypersecretion and abnormal airway smooth muscle (ASM) contraction. Bacterial permeability family member A1, BPIFA1, is a secreted innate defence protein. Here we show that BPIFA1 levels are reduced in sputum samples from asthmatic patients and that BPIFA1 is secreted basolaterally from healthy, but not asthmatic human bronchial epithelial cultures (HBECs), where it suppresses ASM contractility by binding to and inhibiting the Ca2+ influx channel Orai1. We have localized this effect to a specific, C-terminal α-helical region of BPIFA1. Furthermore, tracheas from Bpifa1−/− mice are hypercontractile, and this phenotype is reversed by the addition of recombinant BPIFA1. Our data suggest that BPIFA1 deficiency in asthmatic airways promotes Orai1 hyperactivity, increased ASM contraction and airway hyperresponsiveness. Strategies that target Orai1 or the BPIFA1 deficiency in asthma may lead to novel therapies to treat this disease

A face for all seasons:searching for context-specific leadership traits and discovering a general preference for perceived health

Previous research indicates that followers tend to contingently match particular leader qualities to evolutionarily consistent situations requiring collective action (i.e., context-specific cognitive leadership prototypes) and information processing undergoes categorization which ranks certain qualities as first-order context-general and others as second-order context-specific. To further investigate this contingent categorization phenomenon we examined the “attractiveness halo”—a first-order facial cue which significantly biases leadership preferences. While controlling for facial attractiveness, we independently manipulated the underlying facial cues of health and intelligence and then primed participants with four distinct organizational dynamics requiring leadership (i.e., competition vs. cooperation between groups and exploratory change vs. stable exploitation). It was expected that the differing requirements of the four dynamics would contingently select for relatively healthier- or intelligent-looking leaders. We found perceived facial intelligence to be a second-order context-specific trait—for instance, in times requiring a leader to address between-group cooperation—whereas perceived health is significantly preferred across all contexts (i.e., a first-order trait). The results also indicate that facial health positively affects perceived masculinity while facial intelligence negatively affects perceived masculinity, which may partially explain leader choice in some of the environmental contexts. The limitations and a number of implications regarding leadership biases are discussed

Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis : A Tutorial

Cost-effectiveness analyses (CEA) of randomised controlled trials are a key source of information for health care decision makers. Missing data are, however, a common issue that can seriously undermine their validity. A major concern is that the chance of data being missing may be directly linked to the unobserved value itself [missing not at random (MNAR)]. For example, patients with poorer health may be less likely to complete quality-of-life questionnaires. However, the extent to which this occurs cannot be ascertained from the data at hand. Guidelines recommend conducting sensitivity analyses to assess the robustness of conclusions to plausible MNAR assumptions, but this is rarely done in practice, possibly because of a lack of practical guidance. This tutorial aims to address this by presenting an accessible framework and practical guidance for conducting sensitivity analysis for MNAR data in trial-based CEA. We review some of the methods for conducting sensitivity analysis, but focus on one particularly accessible approach, where the data are multiply-imputed and then modified to reflect plausible MNAR scenarios. We illustrate the implementation of this approach on a weight-loss trial, providing the software code. We then explore further issues around its use in practice

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

Variable geometries of connection: Urban digital divides and the uses of Information Technology

This paper proposes a new way of conceptualising urban ‘digital divides’. It focuses on the ways in which Information and Communication Technologies (ICTs) unevenly affect the pace of life within the urban environment. Based on a detailed case study of how ICT s are being used in an affluent and a marginalised neighbourhood in Newcastle-upon-Tyne, the paper suggests that urban digital divides need to be understood as more than uneven patterns of access. They emerge in this work as more than the presence or absence of specific technological artefacts. Rather, it is argued that different styles and speeds of technologically mediated life now work to define urban socio-spatial inequalities. The paper distinguishes between two such key styles and speeds. First, the paper argues that affluent and professional groups now use new media technologies pervasively and continuously as the ‘background’ infrastructure to sustain privileged and intensely distanciated, but time-stressed, lifestyles. Second, more marginalised neighbourhoods tend to be characterised by instrumental and episodic ICT usage patterns which are often collectively organised through strong neighbourhood ties. For the former, mediated networks help orchestrate neighbourhood ties; for the latter it is those neighbourhood ties that enable online access