Automatic Detection of ECG Abnormalities by using an Ensemble of Deep Residual Networks with Attention

Heart disease is one of the most common diseases causing morbidity and mortality. Electrocardiogram (ECG) has been widely used for diagnosing heart diseases for its simplicity and non-invasive property. Automatic ECG analyzing technologies are expected to reduce human working load and increase diagnostic efficacy. However, there are still some challenges to be addressed for achieving this goal. In this study, we develop an algorithm to identify multiple abnormalities from 12-lead ECG recordings. In the algorithm pipeline, several preprocessing methods are firstly applied on the ECG data for denoising, augmentation and balancing recording numbers of variant classes. In consideration of efficiency and consistency of data length, the recordings are padded or truncated into a medium length, where the padding/truncating time windows are selected randomly to sup-press overfitting. Then, the ECGs are used to train deep neural network (DNN) models with a novel structure that combines a deep residual network with an attention mechanism. Finally, an ensemble model is built based on these trained models to make predictions on the test data set. Our method is evaluated based on the test set of the First China ECG Intelligent Competition dataset by using the F1 metric that is regarded as the harmonic mean between the precision and recall. The resultant overall F1 score of the algorithm is 0.875, showing a promising performance and potential for practical use.Comment: 8 pages, 2 figures, conferenc

Differential regulation of immune responses and macrophage/neuron interactions in the dorsal root ganglion in young and adult rats following nerve injury

Background: Neuropathic pain is an apparently spontaneous experience triggered by abnormal physiology of the peripheral or central nervous system, which evolves with time. Neuropathic pain arising from peripheral nerve injury is characterized by a combination of spontaneous pain, hyperalgesia and allodynia. There is no evidence of this type of pain in human infants or rat pups; brachial plexus avulsion, which causes intense neuropathic pain in adults, is not painful when the injury is sustained at birth. Since infants are capable of nociception from before birth and display both acute and chronic inflammatory pain behaviour from an early neonatal age, it appears that the mechanisms underlying neuropathic pain are differentially regulated over a prolonged postnatal period.Results: We have performed a microarray analysis of the rat L4/L5 dorsal root ganglia (DRG), 7 days post spared nerve injury, a model of neuropathic pain. Genes that are regulated in adult rats displaying neuropathic behaviour were compared to those regulated in young rats (10 days old) that did not show the same neuropathic behaviour. The results show a set of genes, differentially regulated in the adult DRG, that are principally involved in immune system modulation. A functional consequence of this different immune response to injury is that resident macrophages cluster around the large A sensory neuron bodies in the adult DRG seven days post injury, whereas the macrophages in young DRG remain scattered evenly throughout the ganglion, as in controls.Conclusions: The results show, for the first time, a major difference in the neuroimmune response to nerve injury in the dorsal root ganglion of young and adult rats. Differential analysis reveals a new set of immune related genes in the ganglia, that are differentially regulated in adult neuropathic pain, and that are consistent with the selective activation of macrophages around adult, but not young large A sensory neurons post injury. These differences may contribute to the reduced incidence of neuropathic pain in infants

Optimization of a yeast estrogen screen and its applicability to study the release of estrogenic isoflavones from a soygerm powder.

Here we describe a redesigned protocol of the yeast estrogen screen developed by Routledge and Sumpter. The redesigned test comprises two steps. First, a large amount of yeast with estrogenic compounds is incubated for 24 hr. Subsequently, a mixture of cycloheximide and the chromogenic substrate chlorophenol red-beta-d-galactopyranoside (CPRG) is added. The cycloheximide stops protein synthesis and allows for an end-point measurement of beta-galactosidase activity generated during the first 24 hr. CPRG is converted to chlorophenol red and reflects beta-galactosidase activity, which is indicative of the estrogenic activity. The modifications shorten the duration of the assay at least 1 day and avoid interference of the estrogenic CPRG or chlorophenol red. The redesigned and the original protocol were used to study the estrogenic activity of bisphenol A, methoxychlor, p,p'-DDT, and isoflavones (genistein, daidzein, and glycitein). Bisphenol A, methoxychlor, and genistein triggered higher levels of beta-galactosidase activity in the redesigned protocol. Estrogenic activity of p,p'-DDT could only be demonstrated with the redesigned protocol. Glycitein and daidzein failed to give a response with both protocols. We also studied deconjugation of beta-glycosidic isoflavones present in soygerm powder. Treatment of the soygerm powder with beta-glycosidase released isoflavones. The estrogenic response of the samples was confirmed with the redesigned protocol and correlated with the amount of genistein present. The release of isoflavones under conditions prevailing in the intestines was studied. Bacterial beta-glycosidase present in the large intestine released isoflavones, and moderate estrogenic activity could be demonstrated

A False Start in the Race Against Doping in Sport: Concerns With Cycling’s Biological Passport

Professional cycling has suffered from a number of doping scandals. The sport’s governing bodies have responded by implementing an aggressive new antidoping program known as the biological passport. Cycling’s biological passport marks a departure from traditional antidoping efforts, which have focused on directly detecting prohibited substances in a cyclist’s system. Instead, the biological passport tracks biological variables in a cyclist’s blood and urine over time, monitoring for fluctuations that are thought to indirectly reveal the effects of doping. Although this method of indirect detection is promising, it also raises serious legal and scientific concerns. Since its introduction, the cycling community has debated the reliability of indirect biological-passport evidence and the clarity, consistency, and transparency of its use in proving doping violations. Such uncertainty undermines the legitimacy of finding cyclists guilty of doping based on this indirect evidence alone. Antidoping authorities should address these important concerns before continuing to pursue doping sanctions against cyclists solely on the basis of their biological passports

Phenotypic covariance of longevity, immunity and stress resistance in the Caenorhabditis nematodes

Background \ud Ageing, immunity and stresstolerance are inherent characteristics of all organisms. In animals, these traits are regulated, at least in part, by forkhead transcription factors in response to upstream signals from the Insulin/Insulin– like growth factor signalling (IIS) pathway. In the nematode Caenorhabditis elegans, these phenotypes are molecularly linked such that activation of the forkhead transcription factor DAF-16 both extends lifespan and simultaneously increases immunity and stress resistance. It is known that lifespan varies significantly among the Caenorhabditis species but, although DAF-16 signalling is highly conserved, it is unclear whether this phenotypic linkage occurs in other species. Here we investigate this phenotypic covariance by comparing longevity, stress resistance and immunity in four \ud Caenorhabditis species. \ud \ud Methodology/Principal Findings \ud We show using phenotypic analysis of DAF-16 influenced phenotypes that among four closely related Caenorhabditis nematodes, the gonochoristic species (Caenorhabditis remanei and Caenorhabditis brenneri) have diverged \ud significantly with a longer lifespan, improved stress resistance and higher immunity than the hermaphroditic species (C. elegans and Caenorhabditis briggsae). Interestingly, we also observe significant differences in expression levels between the daf-16 homologues in these species using Real-Time PCR, which positively correlate with the observed phenotypes. Finally, we provide additional evidence in support of a role for DAF-16 in regulating phenotypic coupling by using a combination of wildtype isolates, constitutively active daf-16 mutants and bioinformatic analysis. \ud \ud Conclusions \ud The gonochoristic species display a significantly longer lifespan (p < 0.0001)and more robust immune and stress response (p<0.0001, thermal stress; p<0.01, heavy metal stress; p<0.0001, pathogenic stress) than the hermaphroditic species. Our data suggests that divergence in DAF-16 mediated phenotypes may underlie many of the differences observed between these four species of Caenorhabditis nematodes. These findings are further supported by the correlative higher daf-16 expression levels among the gonochoristic species and significantly higher lifespan, immunity and stress tolerance in the constitutively active daf-16 hermaphroditic mutants

Phenotypic covariance of Longevity, Immunity and Stress Resistance in the Caenorhabditis Nematodes

Background: Ageing, immunity and stresstolerance are inherent characteristics of all organisms. In animals, these traits are regulated, at least in part, by forkhead transcription factors in response to upstream signals from the Insulin/Insulin–like growth factor signalling (IIS) pathway. In the nematode Caenorhabditis elegans, these phenotypes are molecularly linked such that activation of the forkhead transcription factor DAF-16 both extends lifespan and simultaneously increases immunity and stress resistance. It is known that lifespan varies significantly among the Caenorhabditis species but, although DAF-16 signalling is highly conserved, it is unclear whether this phenotypic linkage occurs in other species. Here we investigate this phenotypic covariance by comparing longevity, stress resistance and immunity in four Caenorhabditis species. \ud \ud Methodology/Principal Findings: We show using phenotypic analysis of DAF-16 influenced phenotypes that among four closely related Caenorhabditis nematodes, the gonochoristic species (Caenorhabditis remanei and Caenorhabditis brenneri) have diverged significantly with a longer lifespan, improved stress resistance and higher immunity than the hermaphroditic species (C. elegans and Caenorhabditis briggsae). Interestingly, we also observe significant differences in expression levels between the daf-16 homologues in these species using Real-Time PCR, which positively correlate with the observed phenotypes. Finally, we provide additional evidence in support of a role for DAF-16 in regulating phenotypic coupling by using a combination of wildtype isolates, constitutively active daf-16 mutants and bioinformatic analysis. \ud \ud Conclusions: The gonochoristic species display a significantly longer lifespan (p<0.0001) and more robust immune and stress response (p<0.0001, thermal stress; p<0.01, heavy metal stress; p<0.0001, pathogenic stress) than the hermaphroditic species. Our data suggests that divergence in DAF-16 mediated phenotypes may underlie many of the differences observed between these four species of Caenorhabditis nematodes. These findings are further supported by the correlative higher daf-16 expression levels among the gonochoristic species and significantly higher lifespan, immunity and stress tolerance in the constitutively active daf-16 hermaphroditic mutants

Slepian functions and their use in signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and on the surface of a sphere.Comment: Submitted to the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verla

Chern-Simons black holes: scalar perturbations, mass and area spectrum and greybody factors

We study the Chern-Simons black holes in d-dimensions and we calculate analytically the quasi-normal modes of the scalar perturbations and we show that they depend on the highest power of curvature present in the Chern-Simons theory. We obtain the mass and area spectrum of these black holes and we show that they have a strong dependence on the topology of the transverse space and they are not evenly spaced. We also calculate analytically the reflection and transmission coefficients and the absorption cross section and we show that at low frequency limit there is a range of modes which contributes to the absorption cross section.Comment: 19 pages, 18 figures, the title has been changed to reflect the addition of an another section on the reflection, transmission coefficients and absorption cross sections of the Chern-Simons black holes. Version to be published in JHE

Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi