A Framework for Evaluating Approximation Methods for Gaussian Process Regression

Gaussian process (GP) predictors are an important component of many Bayesian approaches to machine learning. However, even a straightforward implementation of Gaussian process regression (GPR) requires O(n^2) space and O(n^3) time for a data set of n examples. Several approximation methods have been proposed, but there is a lack of understanding of the relative merits of the different approximations, and in what situations they are most useful. We recommend assessing the quality of the predictions obtained as a function of the compute time taken, and comparing to standard baselines (e.g., Subset of Data and FITC). We empirically investigate four different approximation algorithms on four different prediction problems, and make our code available to encourage future comparisons

Antimicrobial Activity of Human Prion Protein Is Mediated by Its N-Terminal Region

BACKGROUND: Cellular prion-related protein (PrP(c)) is a cell-surface protein that is ubiquitously expressed in the human body. The multifunctionality of PrP(c), and presence of an exposed cationic and heparin-binding N-terminus, a feature characterizing many antimicrobial peptides, made us hypothesize that PrP(c) could exert antimicrobial activity. METHODOLOGY AND PRINCIPAL FINDINGS: Intact recombinant PrP exerted antibacterial and antifungal effects at normal and low pH. Studies employing recombinant PrP and N- and C-terminally truncated variants, as well as overlapping peptide 20mers, demonstrated that the antimicrobial activity is mediated by the unstructured N-terminal part of the protein. Synthetic peptides of the N-terminus of PrP killed the Gram-negative bacteria Escherichia coli and Pseudomonas aeruginosa, and the Gram-positive Bacillus subtilis and Staphylococcus aureus, as well as the fungus Candida parapsilosis. Fluorescence studies of peptide-treated bacteria, paired with analysis of peptide effects on liposomes, showed that the peptides exerted membrane-breaking effects similar to those seen after treatment with the "classical" human antimicrobial peptide LL-37. In contrast to LL-37, however, no marked helix induction was detected for the PrP-derived peptides in presence of negatively charged (bacteria-mimicking) liposomes. PrP furthermore showed an inducible expression during wounding of human skin ex vivo and in vivo, as well as stimulation of keratinocytes with TGF-alpha in vitro. CONCLUSIONS: The demonstration of an antimicrobial activity of PrP, localisation of its activity to the N-terminal and heparin-binding region, combined with results showing an increased expression of PrP during wounding, indicate that PrPs could have a previously undisclosed role in host defense

Spin Effects in Two Quark System and Mixed States

Based on the numeric solution of a system of coupled channels for vector mesons ($S$- and $D$-waves mixing) and for tensor mesons ($P$- and $F$-waves mixing) mass spectrum and wave functions of a family of vector mesons $q\bar{q}$ in triplet states are obtained. The calculations are performed using a well known Cornell potential with a mixed Lorentz-structure of the confinement term. The spin-dependent part of the potential is taken from the Breit-Fermi approach. The effect of singular terms of potential is considered in the framework of the perturbation theory and by a configuration interaction approach (CIA), modified for a system of coupled equations. It is shown that even a small contribution of the $D$-wave to be very important at the calculation of certain characteristics of the meson states.Comment: 12 pages, LaTe

In ovo injection of prebiotics and synbiotics affects the digestive potency of the pancreas in growing chickens

Abstract The purpose of the study was to examine the effect of 2 prebiotics and 2 synbiotics on the digestive potency of pancreas in 1-, 3-, 7-, 14-, 21-, and 34-day-old cockerels. Prebiotics (inulin and Bi2 tos) and synbiotics (inulin + Lactococcus lactis subsp. lactis and Bi2 tos + Lactococcus lactis subsp. cremoris) were injected in ovo into the air cell on the 12th d embryonic development. Their application increased the activity of amylase, lipase, and trypsin in the pancreas. The most pronounced changes were observed at the end of the investigated rearing period (d 34). The strongest stimulative effects on amylase were shown by both synbiotics, on lipase synbiotic Bi2 tos + Lactococcus lactis subsp. cremoris, and on trypsin all the used prebiotics and synbiotics. Simultaneously, neither the absolute nor the relative mass of the pancreas in comparison to control group were changed. Also, the injected in ovo compounds did not cause a deterioration in the posthatching condition of the chicken liver, as determined by measurement of the activity of marker enzymes in the blood (alanine aminotransferase and aspartate aminotransferase). Treatment with the prebiotics and synbiotics did not change the feed conversion ratio but Bi2 tos (galacto-oligosaccharide) and inulin (fructan) + Lactococcus lactis subsp. lactis significantly increased final BW

Proteolysis of Human Thrombin Generates Novel Host Defense Peptides

The coagulation system is characterized by the sequential and highly localized activation of a series of serine proteases, culminating in the conversion of fibrinogen into fibrin, and formation of a fibrin clot. Here we show that C-terminal peptides of thrombin, a key enzyme in the coagulation cascade, constitute a novel class of host defense peptides, released upon proteolysis of thrombin in vitro, and detected in human wounds in vivo. Under physiological conditions, these peptides exert antimicrobial effects against Gram-positive and Gram-negative bacteria, mediated by membrane lysis, as well as immunomodulatory functions, by inhibiting macrophage responses to bacterial lipopolysaccharide. In mice, they are protective against P. aeruginosa sepsis, as well as lipopolysaccharide-induced shock. Moreover, the thrombin-derived peptides exhibit helical structures upon binding to lipopolysaccharide and can also permeabilize liposomes, features typical of “classical” helical antimicrobial peptides. These findings provide a novel link between the coagulation system and host-defense peptides, two fundamental biological systems activated in response to injury and microbial invasion

Histidine-Rich Glycoprotein Protects from Systemic Candida Infection

Fungi, such as Candida spp., are commonly found on the skin and at mucosal surfaces. Yet, they rarely cause invasive infections in immunocompetent individuals, an observation reflecting the ability of our innate immune system to control potentially invasive microbes found at biological boundaries. Antimicrobial proteins and peptides are becoming increasingly recognized as important effectors of innate immunity. This is illustrated further by the present investigation, demonstrating a novel antifungal role of histidine-rich glycoprotein (HRG), an abundant and multimodular plasma protein. HRG bound to Candida cells, and induced breaks in the cell walls of the organisms. Correspondingly, HRG preferentially lysed ergosterol-containing liposomes but not cholesterol-containing ones, indicating a specificity for fungal versus other types of eukaryotic membranes. Both antifungal and membrane-rupturing activities of HRG were enhanced at low pH, and mapped to the histidine-rich region of the protein. Ex vivo, HRG-containing plasma as well as fibrin clots exerted antifungal effects. In vivo, Hrg−/− mice were susceptible to infection by C. albicans, in contrast to wild-type mice, which were highly resistant to infection. The results demonstrate a key and previously unknown antifungal role of HRG in innate immunity

A Survey of Bayesian Statistical Approaches for Big Data

The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those that were available prior to the advent of Big Data. We present a review of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data