The Relativistic Hopfield network: rigorous results

The relativistic Hopfield model constitutes a generalization of the standard Hopfield model that is derived by the formal analogy between the statistical-mechanic framework embedding neural networks and the Lagrangian mechanics describing a fictitious single-particle motion in the space of the tuneable parameters of the network itself. In this analogy the cost-function of the Hopfield model plays as the standard kinetic-energy term and its related Mattis overlap (naturally bounded by one) plays as the velocity. The Hamiltonian of the relativisitc model, once Taylor-expanded, results in a P-spin series with alternate signs: the attractive contributions enhance the information-storage capabilities of the network, while the repulsive contributions allow for an easier unlearning of spurious states, conferring overall more robustness to the system as a whole. Here we do not deepen the information processing skills of this generalized Hopfield network, rather we focus on its statistical mechanical foundation. In particular, relying on Guerra's interpolation techniques, we prove the existence of the infinite volume limit for the model free-energy and we give its explicit expression in terms of the Mattis overlaps. By extremizing the free energy over the latter we get the generalized self-consistent equations for these overlaps, as well as a picture of criticality that is further corroborated by a fluctuation analysis. These findings are in full agreement with the available previous results.Comment: 11 pages, 1 figur

Murine norovirus virulence factor 1 (VF1) protein contributes to viral fitness during persistent infection

Murine norovirus (MNV) is widely used as a model for studying norovirus biology. While MNV isolates vary in their pathogenesis, infection of immunocompetent mice mostly results in persistent infection. The ability of a virus to establish a persistent infection is dependent on its ability to subvert or avoid the host immune response. Previously, we described the identification and characterization of virulence factor 1 (VF1) in MNV, and demonstrated its role as an innate immune antagonist. Here, we explore the role of VF1 during persistent MNV infection in an immunocompetent host. Using reverse genetics, we generated MNV-3 viruses carrying a single or a triple termination codon inserted in the VF1 ORF. VF1-deleted MNV-3 replicated to comparable levels to the wildtype virus in tissue culture. Comparative studies between MNV-3 and an acute MNV-1 strain show that MNV-3 VF1 exerts the same functions as MNV-1 VF1, but with reduced potency. C57BL/6 mice infected with VF1-deleted MNV-3 showed significantly reduced replication kinetics during the acute phase of the infection, but viral loads rapidly reached the levels seen in mice infected with wildtype virus after phenotypic restoration of VF1 expression. Infection with an MNV-3 mutant that had three termination codons inserted into VF1, in which reversion was suppressed, resulted in consistently lower replication throughout a 3 month persistent infection in mice, suggesting a role for VF1 in viral fitness in vivo. Our results indicate that VF1 expressed by a persistent strain of MNV also functions to antagonize the innate response to infection. We found that VF1 is not essential for viral persistence, but instead contributes to viral fitness in mice. These data fit with the hypothesis that noroviruses utilize multiple mechanisms to avoid and/or control the host response to infection and that VF1 is just one component of this

Pharmacogenetics and the print media:what is the public told?

Background: Pharmacogenetics is a rapidly growing field that aims to identify the genes that influence drug response. This science can be used as a powerful tool to tailor drug treatment to the genetic makeup of individuals. The present study explores the coverage of the topic of pharmacogenetics and its potential benefit in personalised medicine by the UK newsprint media. Methods: The LexisNexis database was used to identify and retrieve full text articles from the 10 highest circulation national daily newspapers and their Sunday equivalents in the UK. Content analysis of newspaper articles which referenced pharmacogenetic testing was carried out. A second researcher coded a random sample (21%) of newspaper articles to establish the inter-rater reliability of coding. Results: Of the 256 articles captured by the search terms, 96 articles (with pharmacogenetics as a major component) met the study inclusion criteria. The majority of articles over-stated the benefits of pharmacogenetic testing while paying less attention to the associated risks. Overall beneficial effects were mentioned 5.3 times more frequently than risks (p < 0.001). The most common illnesses for which pharmacogenetically based personalised medicine was discussed were cancer, cardiovascular disease and CNS diseases. Only 13% of newspaper articles that cited a specific scientific study mentioned this link in the article. There was a positive correlation between the size of the article and both the number of benefits and risks stated (P < 0.01). Conclusion: More comprehensive coverage of the area of personalised medicine within the print media is needed to inform public debate on the inclusion of pharmacogentic testing in routine practice

Reconstruction of Hydraulic Data by Machine Learning

Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (characterized by soil nature, infiltration capacity and moisture), current water height in the river, topography, nature and geometry of the river bed, etc. This data is tainted with uncertainties related to an imperfect knowledge of the field, measurement errors on the physical parameters calibrating the equations of physics, an approximation of the latter, etc. These uncertainties can lead the model to overestimate or underestimate the flow and height of the river. Moreover, complex assimilation models often require numerous evaluations of physical solvers to evaluate these uncertainties, limiting their use for some real-time operational applications. In this study, we explore the possibility of building a predictor for river height at an observation point based on drainage basin time series data. An array of data-driven techniques is assessed for this task, including statistical models, machine learning techniques and deep neural network approaches. These are assessed on several metrics, offering an overview of the possibilities related to hydraulic time-series. An important finding is that for the same hydraulic quantity, the best predictors vary depending on whether the data is produced using a physical model or real observations.Comment: Submitted to SimHydro 201

Robustness Verification of Support Vector Machines

We study the problem of formally verifying the robustness to adversarial examples of support vector machines (SVMs), a major machine learning model for classification and regression tasks. Following a recent stream of works on formal robustness verification of (deep) neural networks, our approach relies on a sound abstract version of a given SVM classifier to be used for checking its robustness. This methodology is parametric on a given numerical abstraction of real values and, analogously to the case of neural networks, needs neither abstract least upper bounds nor widening operators on this abstraction. The standard interval domain provides a simple instantiation of our abstraction technique, which is enhanced with the domain of reduced affine forms, which is an efficient abstraction of the zonotope abstract domain. This robustness verification technique has been fully implemented and experimentally evaluated on SVMs based on linear and nonlinear (polynomial and radial basis function) kernels, which have been trained on the popular MNIST dataset of images and on the recent and more challenging Fashion-MNIST dataset. The experimental results of our prototype SVM robustness verifier appear to be encouraging: this automated verification is fast, scalable and shows significantly high percentages of provable robustness on the test set of MNIST, in particular compared to the analogous provable robustness of neural networks

Identification of cell-surface mannans in a virulent Helicobacter pylori strain

With the intent of contributing to a carbohydrate-based vaccine against the gastroduodenal pathogen, Helicobacter pylori, we report here the structure of cell-surface mannans obtained from a virulent strain. Unlike other wild-type strains, this strain was found to express in good quantities this polysaccharide in vitro. Structural analysis revealed a branched mannan formed by a backbone of α-(1→6)-linked mannopyranosyl residues with approximately 80% branching at the O-2 position. The branches were composed of O-2-linked Man residues in both α- and β-configurations: (image) In addition, this strain also expressed cell-surface emblematic H. pylori lipopolysaccharides (LPS) containing partially fucosylated polyLacNAc O-chains. Affinity assays with polymyxin-B and concanavalin A revealed no association between the mannan and the LPS. The described mannans may be implicated in the mediation of host–microbial interactions and immunological modulation.This work was supported by Fundacao para a Ciencia e Tecnologia (FCT) through project Pylori E&LPS POCI/QUI/56393/2004, PhD grant SFRH/BD/19929/2004, by the Natural Sciences and Engineering Research Council of Canada (NSERC), and by the European Network of Research Infrastructures within the 6th Framework Programme of the EC (Contract # RII3-026145, EU-NMR). The authors further thank Dr. Adrien Favier (RALF-NMR facility, Grenoble - France) for conducting NMR experiments

Endo- and exometabolome crosstalk in mesenchymal stem cells undergoing osteogenic differentiation

This paper describes, for the first time to our knowledge, a lipidome and exometabolome characterization of osteogenic differentiation for human adipose tissue stem cells (hAMSCs) using nuclear magnetic resonance (NMR) spectroscopy. The holistic nature of NMR enabled the time-course evolution of cholesterol, mono- and polyunsaturated fatty acids (including ω-6 and ω-3 fatty acids), several phospholipids (phosphatidylcholine, phosphatidylethanolamine, sphingomyelins, and plasmalogens), and mono- and triglycerides to be followed. Lipid changes occurred almost exclusively between days 1 and 7, followed by a tendency for lipidome stabilization after day 7. On average, phospholipids and longer and more unsaturated fatty acids increased up to day 7, probably related to plasma membrane fluidity. Articulation of lipidome changes with previously reported polar endometabolome profiling and with exometabolome changes reported here in the same cells, enabled important correlations to be established during hAMSC osteogenic differentiation. Our results supported hypotheses related to the dynamics of membrane remodelling, anti-oxidative mechanisms, protein synthesis, and energy metabolism. Importantly, the observation of specific up-taken or excreted metabolites paves the way for the identification of potential osteoinductive metabolites useful for optimized osteogenic protocols.publishe

Screening for Multiple Endocrine Neoplasia Type 2A with DNA-Polymorphism Analysis

Nine chromosome 10 DNA markers (FNRB, D10S34, D10Z1, MEN203, D10S94, RBP3, D10S15, MBP [48.11], D10S22) were typed in two large Canadian pedigrees with multiple endocrine neoplasia type 2A (MEN 2A). These markers and the gene for MEN 2A (MEN2A) are believed to be in one linkage group spanning approximately 15 cM (male). MEN203 and D10S94 were informative and tightly linked to MEN2A with no recombinants observed in 26 meiotic events. D10S15 (MCK2), widely used in DNA genotyping predictions, demonstrated two recombinants in these two families. The use of multiple flanking markers increases both the likelihood of informativeness and the accuracy of risk assessments for predictive testing. We were able to assign a risk estimate for all 10 at-risk individuals

An NMR structural study of nickel-substituted rubredoxin

J Biol Inorg Chem (2010) 15:409–420 DOI 10.1007/s00775-009-0613-6The Ni(II) and Zn(II) derivatives of Desulfovibrio vulgaris rubredoxin (DvRd) have been studied by NMR spectroscopy to probe the structure at the metal centre. The βCH2 proton pairs from the cysteines that bind the Ni(II) atom have been identified using 1D nuclear Overhauser enhancement (NOE) difference spectra and sequence specifically assigned via NOE correlations to neighbouring protons and by comparison with the published X-ray crystal structure of a Ni(II) derivative of Clostridium pasteurianum rubredoxin. The solution structures of DvRd(Zn) and DvRd(Ni) have been determined and the paramagnetic form refined using pseudocontact shifts. The determination of the magnetic susceptibility anisotropy tensor allowed the contact and pseudocontact contributions to the observed chemical shifts to be obtained. Analysis of the pseudocontact and contact chemical shifts of the cysteine Hβ protons and backbone protons close to the metal centre allowed conclusions to be drawn as to the geometry and hydrogen-bonding pattern at the metal binding site. The importance of NH–S hydrogen bonds at the metal centre for the delocalization of electron spin density is confirmed for rubredoxins and can be extrapolated to metal centres in Cu proteins: amicyanin, plastocyanin, stellacyanin, azurin and pseudoazurin

Sex chromosome positions in human interphase nuclei as studied by in situ hybridization with chromosome specific DNA probes

Two cloned repetitive DNA probes, pXBR and CY1, which bind preferentially to specific regions of the human X and Y chromosome, respectively, were used to study the distribution of the sex chromosomes in human lymphocyte nuclei by in situ hybridization experiments. Our data indicate a large variability of the distances between the sex chromosomes in male and female interphase nuclei. However, the mean distance observed between the X and Y chromosome was significantly smaller than the mean distance observed between the two X-chromosomes. The distribution of distances determined experimentally is compared with three model distributions of distances, and the question of a non-random distribution of sex chromosomes is discussed. Mathematical details of these model distributions are provided in an Appendix to this paper. In the case of a human translocation chromosome (XqterXp22.2::Yq11Y qter) contained in the Chinese hamster x human hybrid cell line 445 x 393, the binding sites of pXBR and CY1 were found close to each other in most interphase nuclei. These data demonstrate the potential use of chromosome-specific repetitive DNA probes to study the problem of interphase chromosome topography