2,344 research outputs found

    QTL analysis of production traits on SSC3 in a Large White×Meishan pig resource family

    Get PDF
    In order to locate the genetic regions that are responsible for economically important traits, a resource population was established by crossing Large White boars and Meishan sows. Phenotypic data of a total of 287 F2 offspring were collected from 1998 to 2000 and QTL analysis conducted using nine microsatellites on Sus scrofa chromosome 3 (SSC3). Least square regression interval mapping revealed two significant QTL effects on dressing percentage and moisture in m. longissimus dorsi, respectively. They were located at 136 cM and 22 cM in the genetic linkage map, near the marker Sw349 and Swr1637, respectively. QTL for dressing percentage had an additive effect of -1.035 ± 0.296% and a dominance effect of 1.056 ± 0.481%, and the explained phenotypic variance was 15.9%. The additive and dominance effects of QTL for moisture in m. longissimus dorsi were -0.025 ± 0.076% and 0.365 ± 0.101%, respectively, indicating that this QTL seemed to be significantly dominant in action. The present study confirms previously identified QTL and provides an important step in the search for the actual major genes involved in the traits of economic interest. South African Journal of Animal Science Vol. 36(2) 2006: 122-12

    Human Bocavirus NS1 and NS1-70 Proteins Inhibit TNF-α-Mediated Activation of NF-κB by targeting p65.

    Get PDF
    Human bocavirus (HBoV), a parvovirus, is a single-stranded DNA etiologic agent causing lower respiratory tract infections in young children worldwide. Nuclear factor kappa B (NF-κB) transcription factors play crucial roles in clearance of invading viruses through activation of many physiological processes. Previous investigation showed that HBoV infection could significantly upregulate the level of TNF-α which is a strong NF-κB stimulator. Here we investigated whether HBoV proteins modulate TNF-α-mediated activation of the NF-κB signaling pathway. We showed that HBoV NS1 and NS1-70 proteins blocked NF-κB activation in response to TNF-α. Overexpression of TNF receptor-associated factor 2 (TRAF2)-, IκB kinase alpha (IKKα)-, IκB kinase beta (IKKβ)-, constitutively active mutant of IKKβ (IKKβ SS/EE)-, or p65-induced NF-κB activation was inhibited by NS1 and NS1-70. Furthermore, NS1 and NS1-70 didn't interfere with TNF-α-mediated IκBα phosphorylation and degradation, nor p65 nuclear translocation. Coimmunoprecipitation assays confirmed the interaction of both NS1 and NS1-70 with p65. Of note, NS1 but not NS1-70 inhibited TNF-α-mediated p65 phosphorylation at ser536. Our findings together indicate that HBoV NS1 and NS1-70 inhibit NF-κB activation. This is the first time that HBoV has been shown to inhibit NF-κB activation, revealing a potential immune-evasion mechanism that is likely important for HBoV pathogenesis

    Polypyrrole-Fe2O3 nanohybrid materials for electrochemical storage

    Get PDF
    We report on the synthesis and electrochemical characterization of nanohybrid polypyrrole (PPy) (PPy/Fe2O3) materials for electrochemical storage applications. We have shown that the incorporation of nanoparticles inside the PPy notably increases the charge storage capability in comparison to the “pure” conducting polymer. Incorporation of large anions, i.e., paratoluenesulfonate, allows a further improvement in the capacity. These charge storage modifications have been attributed to the morphology of the composite in which the particle sizes and the specific surface area are modified with the incorporation of nanoparticles. High capacity and stability have been obtained in PC/NEt4BF4 (at 20 mV/s), i.e., 47 mAh/g, with only a 3% charge loss after one thousand cyles. The kinetics of charge–discharge is also improved by the hybrid nanocomposite morphology modifications, which increase the rate of insertion–expulsion of counter anions in the bulk of the film. A room temperature ionic liquid such as imidazolium trifluoromethanesulfonimide seems to be a promising electrolyte because it further increases the capacity up to 53 mAh/g with a high stability during charge–discharge processes

    Singular values of the Dirac operator in dense QCD-like theories

    Full text link
    We study the singular values of the Dirac operator in dense QCD-like theories at zero temperature. The Dirac singular values are real and nonnegative at any nonzero quark density. The scale of their spectrum is set by the diquark condensate, in contrast to the complex Dirac eigenvalues whose scale is set by the chiral condensate at low density and by the BCS gap at high density. We identify three different low-energy effective theories with diquark sources applicable at low, intermediate, and high density, together with their overlapping domains of validity. We derive a number of exact formulas for the Dirac singular values, including Banks-Casher-type relations for the diquark condensate, Smilga-Stern-type relations for the slope of the singular value density, and Leutwyler-Smilga-type sum rules for the inverse singular values. We construct random matrix theories and determine the form of the microscopic spectral correlation functions of the singular values for all nonzero quark densities. We also derive a rigorous index theorem for non-Hermitian Dirac operators. Our results can in principle be tested in lattice simulations.Comment: 3 references added, version published in JHE

    An experiment of the combined treatment of traditional Lei-huo-jiu therapy with Chinese medicine for the lacrimal gland of Sjögren’s syndrome

    Get PDF
    This experiment chooses nonobese diabetic (NOD) mouse as the animal model of Sjögren’s syndrome and investigates the morphologic changes, the expression of inflammatory factors and growth factors of this mouse’s lacrimal gland in response to a combined treatment of traditional Lei-huo-jiu therapy alone and in combination with Chinese medicine. The methods were to (1) use a morphological approach to directly observe pathological changes of the lacrimal gland in response to combined treatment and (2) to detect the level of tumor necrosis factor (TNF)-α, interleukin (IL)-1, and nuclear factor kappa B (NF-κB) in lacrimal gland tissue caused by the combined treatments using a immunohistochemical approach. There is a reduction of the mast cell’s degranulation and modulation of the level of cytokines in TNF-α, IL-1, and NF-κB in the combined therapy group. The combined treatment of traditional Lei-huo-jiu therapy with Chinese medicine can improve the pathological changes of the lacrimal gland tissue of the NOD mouse through modulating the level of TNF-α, IL-1, and NF-κB which results in improved tear secretion and function of the lacrimal gland

    Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

    Get PDF
    Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

    Chiral perturbation theory in a magnetic background - finite-temperature effects

    Full text link
    We consider chiral perturbation theory for SU(2) at finite temperature TT in a constant magnetic background BB. We compute the thermal mass of the pions and the pion decay constant to leading order in chiral perturbation theory in the presence of the magnetic field. The magnetic field gives rise to a splitting between Mπ0M_{\pi^0} and Mπ±M_{\pi^{\pm}} as well as between Fπ0F_{\pi^0} and Fπ±F_{\pi^{\pm}}. We also calculate the free energy and the quark condensate to next-to-leading order in chiral perturbation theory. Both the pion decay constants and the quark condensate are decreasing slower as a function of temperature as compared to the case with vanishing magnetic field. The latter result suggests that the critical temperature TcT_c for the chiral transition is larger in the presence of a constant magnetic field. The increase of TcT_c as a function of BB is in agreement with most model calculations but in disagreement with recent lattice calculations.Comment: 24 pages and 9 fig

    Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

    Get PDF
    Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

    SdrF, a Staphylococcus epidermidis Surface Protein, Contributes to the Initiation of Ventricular Assist Device Driveline–Related Infections

    Get PDF
    Staphylococcus epidermidis remains the predominant pathogen in prosthetic-device infections. Ventricular assist devices, a recently developed form of therapy for end-stage congestive heart failure, have had considerable success. However, infections, most often caused by Staphylococcus epidermidis, have limited their long-term use. The transcutaneous driveline entry site acts as a potential portal of entry for bacteria, allowing development of either localized or systemic infections. A novel in vitro binding assay using explanted drivelines obtained from patients undergoing transplantation and a heterologous lactococcal system of surface protein expression were used to identify S. epidermidis surface components involved in the pathogenesis of driveline infections. Of the four components tested, SdrF, SdrG, PIA, and GehD, SdrF was identified as the primary ligand. SdrF adherence was mediated via its B domain attaching to host collagen deposited on the surface of the driveline. Antibodies directed against SdrF reduced adherence of S. epidermidis to the drivelines. SdrF was also found to adhere with high affinity to Dacron, the hydrophobic polymeric outer surface of drivelines. Solid phase binding assays showed that SdrF was also able to adhere to other hydrophobic artificial materials such as polystyrene. A murine model of infection was developed and used to test the role of SdrF during in vivo driveline infection. SdrF alone was able to mediate bacterial adherence to implanted drivelines. Anti-SdrF antibodies reduced S. epidermidis colonization of implanted drivelines. SdrF appears to play a key role in the initiation of ventricular assist device driveline infections caused by S. epidermidis. This pluripotential adherence capacity provides a potential pathway to infection with SdrF-positive commensal staphylococci first adhering to the external Dacron-coated driveline at the transcutaneous entry site, then spreading along the collagen-coated internal portion of the driveline to establish a localized infection. This capacity may also have relevance for other prosthetic device–related infections

    Online Continual Learning on Sequences

    Full text link
    Online continual learning (OCL) refers to the ability of a system to learn over time from a continuous stream of data without having to revisit previously encountered training samples. Learning continually in a single data pass is crucial for agents and robots operating in changing environments and required to acquire, fine-tune, and transfer increasingly complex representations from non-i.i.d. input distributions. Machine learning models that address OCL must alleviate \textit{catastrophic forgetting} in which hidden representations are disrupted or completely overwritten when learning from streams of novel input. In this chapter, we summarize and discuss recent deep learning models that address OCL on sequential input through the use (and combination) of synaptic regularization, structural plasticity, and experience replay. Different implementations of replay have been proposed that alleviate catastrophic forgetting in connectionists architectures via the re-occurrence of (latent representations of) input sequences and that functionally resemble mechanisms of hippocampal replay in the mammalian brain. Empirical evidence shows that architectures endowed with experience replay typically outperform architectures without in (online) incremental learning tasks.Comment: L. Oneto et al. (eds.), Recent Trends in Learning From Data, Studies in Computational Intelligence 89
    corecore