Loss of PTB or Negative Regulation of Notch mRNA Reveals Distinct Zones of Notch and Actin Protein Accumulation in Drosophila Embryo

Polypyrimidine Tract Binding (PTB) protein is a regulator of mRNA processing and translation. Genetic screens and studies of wing and bristle development during the post-embryonic stages of Drosophila suggest that it is a negative regulator of the Notch pathway. How PTB regulates the Notch pathway is unknown. Our studies of Drosophila embryogenesis indicate that (1) the Notch mRNA is a potential target of PTB, (2) PTB and Notch functions in the dorso-lateral regions of the Drosophila embryo are linked to actin regulation but not their functions in the ventral region, and (3) the actin-related Notch activity in the dorso-lateral regions might require a Notch activity at or near the cell surface that is different from the nuclear Notch activity involved in cell fate specification in the ventral region. These data raise the possibility that the Drosophila embryo is divided into zones of different PTB and Notch activities based on whether or not they are linked to actin regulation. They also provide clues to the almost forgotten role of Notch in cell adhesion and reveal a role for the Notch pathway in cell fusions

Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

BACKGROUND: The Millennium Declaration in 2000 brought special global attention to HIV, tuberculosis, and malaria through the formulation of Millennium Development Goal (MDG) 6. The Global Burden of Disease 2013 study provides a consistent and comprehensive approach to disease estimation for between 1990 and 2013, and an opportunity to assess whether accelerated progress has occured since the Millennium Declaration. METHODS: To estimate incidence and mortality for HIV, we used the UNAIDS Spectrum model appropriately modified based on a systematic review of available studies of mortality with and without antiretroviral therapy (ART). For concentrated epidemics, we calibrated Spectrum models to fit vital registration data corrected for misclassification of HIV deaths. In generalised epidemics, we minimised a loss function to select epidemic curves most consistent with prevalence data and demographic data for all-cause mortality. We analysed counterfactual scenarios for HIV to assess years of life saved through prevention of mother-to-child transmission (PMTCT) and ART. For tuberculosis, we analysed vital registration and verbal autopsy data to estimate mortality using cause of death ensemble modelling. We analysed data for corrected case-notifications, expert opinions on the case-detection rate, prevalence surveys, and estimated cause-specific mortality using Bayesian meta-regression to generate consistent trends in all parameters. We analysed malaria mortality and incidence using an updated cause of death database, a systematic analysis of verbal autopsy validation studies for malaria, and recent studies (2010-13) of incidence, drug resistance, and coverage of insecticide-treated bednets. FINDINGS: Globally in 2013, there were 1·8 million new HIV infections (95% uncertainty interval 1·7 million to 2·1 million), 29·2 million prevalent HIV cases (28·1 to 31·7), and 1·3 million HIV deaths (1·3 to 1·5). At the peak of the epidemic in 2005, HIV caused 1·7 million deaths (1·6 million to 1·9 million). Concentrated epidemics in Latin America and eastern Europe are substantially smaller than previously estimated. Through interventions including PMTCT and ART, 19·1 million life-years (16·6 million to 21·5 million) have been saved, 70·3% (65·4 to 76·1) in developing countries. From 2000 to 2011, the ratio of development assistance for health for HIV to years of life saved through intervention was US$4498 in developing countries. Including in HIV-positive individuals, all-form tuberculosis incidence was 7·5 million (7·4 million to 7·7 million), prevalence was 11·9 million (11·6 million to 12·2 million), and number of deaths was 1·4 million (1·3 million to 1·5 million) in 2013. In the same year and in only individuals who were HIV-negative, all-form tuberculosis incidence was 7·1 million (6·9 million to 7·3 million), prevalence was 11·2 million (10·8 million to 11·6 million), and number of deaths was 1·3 million (1·2 million to 1·4 million). Annualised rates of change (ARC) for incidence, prevalence, and death became negative after 2000. Tuberculosis in HIV-negative individuals disproportionately occurs in men and boys (versus women and girls); 64·0% of cases (63·6 to 64·3) and 64·7% of deaths (60·8 to 70·3). Globally, malaria cases and deaths grew rapidly from 1990 reaching a peak of 232 million cases (143 million to 387 million) in 2003 and 1·2 million deaths (1·1 million to 1·4 million) in 2004. Since 2004, child deaths from malaria in sub-Saharan Africa have decreased by 31·5% (15·7 to 44·1). Outside of Africa, malaria mortality has been steadily decreasing since 1990. INTERPRETATION: Our estimates of the number of people living with HIV are 18·7% smaller than UNAIDS's estimates in 2012. The number of people living with malaria is larger than estimated by WHO. The number of people living with HIV, tuberculosis, or malaria have all decreased since 2000. At the global level, upward trends for malaria and HIV deaths have been reversed and declines in tuberculosis deaths have accelerated. 101 countries (74 of which are developing) still have increasing HIV incidence. Substantial progress since the Millennium Declaration is an encouraging sign of the effect of global action. FUNDING: Bill & Melinda Gates Foundation

Co-channel audiovisual speech separation using spectral matching constraints

In this paper the problem of co-channel speech separation for convolutive mixtures is considered where visual cues from one of the speakers is available as side information. The visual cues from the one speaker in the two speaker speech separation are used to estimate the spectral content of the speech and this spectral estimate is in turn used to constrain the solution of the coupling reconstruction filters in the convolutive mixture. The preliminary experimental results show that good performance in speech separation is obtained for our limited case study of visual cues obtained from the spoken numbers of "one" thru "four"

Performance of phase-space voicing-state classification for Co-channel speech

This paper discusses the performance of a classification algorithm that is capable of determining the voicing-state of co-channel speech. The algorithm uses some features of the reconstructed phase-space of the speech data as a measure to identify the three voicing-states of co-channel speech; Unvoiced/Unvoiced (U/U), Voiced/Unvoiced (V/U), and Voiced/Voiced (V/V). The proposed method requires neither a priori information nor speech training data. Nonetheless, simulation results show enhanced performance in identifying the three voicing-states compared to other existing techniques. The algorithm also shows a reliable, performance for different SIR values as well as different levels of background noise

Single channel speech separation using maximum a posteriori estimation

We present a new approach for separating two speech signals when only a single recording of their additive mixture is available. In this approach, log spectra of the sources are estimated using maximum a posteriori estimation given the mixture's log spectrum and the probability density functions of the sources. It is shown that the estimation leads to a two-state, non-linear filter whose states are controlled by the means of the sources. The first state of the filter is expressed using a combination of two Wiener filters whose parameters are controlled by the means and variances of the sources and noise variance and the second state is expressed by the means of the sources. Through the experiments, conducted on a wide variety of mixtures, we show that the MAP based estimator outperforms the methods which use binary mask filtering or Wiener filtering for the separation task

Long-term gain estimation in model-based single channel speech separation

Model-based single channel speech separation techniques commonly use trained patterns of the individual speakers to separate the speech signals. In most recent proposed techniques, it is assumed that data used in the train and test phase have the same level of energy, a prerequisite which is hardly met in the real situations. Considering this limitation, we propose a technique which estimates the gain associated with the individual speakers from the mixture and thus obviate the need for this assumption. The basic idea is to express the probability density function (PDF) of the mixture in terms of the individual speakers' PDFs and corresponding gains. Then, those patterns and gains which maximize the mixture's PDF are selected and used to recover the speech signals. Experimental results conducted on a wide variety of mixtures with signal-to-signal ratios ranging from 0 to 18 dB show that the proposed technique estimates the speakers' gain with 95% accuracy within the range of the actual gain ± %20. Comparing the separated speech signals with the original ones in terms of SNR criterion with/without including the gain estimation stage, we observe a significant SNR improvement (on average 5.73 dB) for the gain included scenario

Single channel speech separation using minimum mean square error estimation of sources' log spectra

We present an approach for separating two speech signals when only one single recording of their linear mixture is available. The log spectra of the sources are estimated from the mixture's log spectrum using minimum mean square error (MMSE) approach. The estimation is obtained from the assumption that the sources are modelled using a set of Gaussian subsources which are related to the mixture using MIXMAX approximation. The resulting estimator has a closed form and is expressed using the mean and variance of Gaussian subsources. In order to obtain the two most likely subsources which generate the mixture, we use the estimation-detection technique. We also show that the binary mask filtering which has been empirically - and with no mathematical justification - used in speech separation techniques is, in fact, a simplified form of the MMSE estimator. The proposed technique is compared with the binary mask when the input consists of male-male, female-female, and female-male mixtures. The experimental results in terms of segmental SNR show that the MMSE estimator outperforms binary mask filtering

Cramér-Rao Lower Bound Derivation and Performance Analysis for Space-Based SAR GMTI

This paper derives the Cramér-Rao lower bound (CRLB) for a general multichannel spaceborne synthetic aperture radar system for ground moving-target indication and provides a theoretical analysis of across-track velocity estimation for RADARSAT-2 and a fictitious satellite. The signal model assumes a deterministic target signal in Gaussian clutter and noise. In estimation theory, the CRLB provides a lower bound on the achievable variance of any unbiased estimator. An estimator that achieves this bound is called efficient; however, there is no guarantee that an efficient estimator can be found. Nonetheless, the theoretical variance of the efficient estimator provides a good measure of the capability of the system and serves as a valuable system performance validation tool. Even if an efficient estimator cannot be found, for radar systems, the CRLB provides a necessary, but not sufficient design baseline for measurement parameters, such as the number of subapertures for transmit and receive, power levels, pulse-repetition frequency, and so on. CRLBs for a limited number of system configurations for RADARSAT-2 and TerraSAR-X are presented by Cerutti-Maori et al. and Ender et al.; however, the complete analytical form of CRLB for a general system, which can be readily applied to an arbitrary antenna switching configuration, has not been previously derived

Multi-modal fetal ECG extraction using multi-kernel Gaussian processes

This study deals with fetal ECG extraction by multi-modal non-parametric modeling. In a recently proposed non-parametric approach, the fetal and maternal ECG are modeled from their respective references using Gaussian processes. The reference signals for maternal ECG and fetal ECG are the thoracic ECG and abdominal PCG, respectively. In this paper, multiple kernels are used instead of a single kernel for the covariance function of the Gaussian process. The proposed methodology improves the results of fetal ECG extraction as confirmed by experimental results