[Voyage en Italie : 1824-1830]. , [Façade à double rangée de loggia d'un palais] : [coupe sur la cour] : [dessin] / h. L. [Henri Labrouste]

Référence bibliographique : Weigert, 51b

A role for altered TLR gene expression in association with increased expression of CD200R in the induction of mucosal tissue CD4(+) Treg in aged mice following gavage with a liver extract along with intramuscular monophosphoryl lipid A (MPLA) injection.

Previous studies showed a fetal sheep liver extract (FSLE), in association with LPS, injected into aged (>20 months) mice reversed the altered polarization (increased IL-4 and IL-10 with decreased IL-2 and IFN-gamma) in cytokine production seen from ConA stimulated lymphoid cells of those mice. Aged mice show a >60% decline in numbers and suppressive function of both CD4(+)CD25(+)Foxp3(+)Treg and so-called Tr3 (CD4(+)TGFbeta(+)). Their number/function is restored to levels seen in control (8-week-old) mice by FSLE. We have reported at length on the ability of a novel pair of immunoregulatory molecules, members of the TREM family, namely CD200:CD200R, to control development of dendritic cells (DCs) which themselves regulate production of Foxp3(+) Treg. The latter express a distinct subset of TLRs which control their function. We report that a feature of the altered Treg expression following combined treatment with FSLE and monophosphoryl lipid A, MPLA (a bioactive component of lipid A of LPS) is the altered gene expression both of distinct subsets of TLRs and of CD200Rs. We speculate that this may represent one of the mechanisms by which FSLE and MPLA alter immunity in aged mice.

Induction of CTL in vivo by major histocompatibility complex class I-peptide complexes covalently associated on the cell surface.

The identification of endogenously produced antigenic peptides presented by MHC class I molecules has opened the way to peptide-based strategies for CTL induction in vivo. Here we demonstrate that the induction in vivo of CTL directed against naturally processed antigens can be triggered by injection of syngeneic cells expressing covalent major histocompatibility complex class I-peptide complexes. In the model system used, the induction of HLA-Cw3 specific cytotoxic T lymphocytes (CTL) in mice by cell surface-associated, covalent H-2Kd (Kd)-Cw3 peptide complexes was investigated. The Kd-restricted Cw3 peptide 170-179 (RYLKNGKETL), which mimics the major natural epitope recognized by Cw3-specific CTL in H-2d mice, was converted to a photoreactive derivative by replacing Arg-170 with N-beta-(4-azidosalicyloyl)-L-2,3-diaminopropionic acid. This peptide derivative was equivalent to the parental Cw3 peptide in terms of binding to Kd molecules and recognition by Cw3-specific CTL clones and could be cross-linked efficiently and selectively to Kd molecules on the surface of Con A-stimulated spleen cells from H-2d mice. Photocross-linking prevented the rapid dissociation of Kd-peptide derivative complexes that takes place under physiological conditions. Cultures of spleen cells or peritoneal exudate cells from mice inoculated i.p. with peptide-pulsed and photocross-linked cells developed a strong CTL response following antigenic stimulation in vitro. The cultured cells efficiently lysed not only target cells sensitized with the Cw3 170-179 peptide but also target cells transfected with the Cw3 gene. Moreover, their TCR preferentially expressed V beta 10 and J alpha pHDS58 segments as well as conserved junctional sequences, as has been observed previously in Cw3-specific CTL responses. In contrast, no Cw3-specific CTL response could be obtained in cultures derived from mice injected with Con A-stimulated spleen cells pulsed with the peptide derivative without photocross-linking.

Machine learning analysis and modeling of interest rate curves

The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.

Trace element supplementation modulates pulmonary infection rates after major burns: a double-blind, placebo-controlled trial.

Infections remain the leading cause of death after major burns. Trace elements are involved in immunity and burn patients suffer acute trace element depletion after injury. In a previous nonrandomized study, trace element supplementation was associated with increased leukocyte counts and shortened hospital stays. This randomized, placebo-controlled trial studied clinical and immune effects of trace element supplements. Twenty patients, aged 40 +/- 16 y (mean +/- SD), burned on 48 +/- 17% of their body surfaces, were studied for 30 d after injury. They consumed either standard trace element intakes plus supplements (40.4 micromol Cu, 2.9 micromol Se, and 406 micromol Zn; group TE) or standard trace element intakes plus placebo (20 micromol Cu, 0.4 micromol Se, and 100 micromol Zn; group C) for 8 d. Demographic data were similar for both groups. Mean plasma copper and zinc concentrations were below normal until days 20 and 15, respectively (NS). Plasma selenium remained normal for group TE but decreased for group C (P < 0.05 on days 1 and 5). Total leukocyte counts tended to be higher in group TE because of higher neutrophil counts. Proliferation to mitogens was depressed compared with healthy control subjects (NS). The number of infections per patient was significantly (P < 0.05) lower in group TE (1.9 +/- 0.9) than in group C (3.1 +/- 1.1) because of fewer pulmonary infections. Early trace element supplementation appears beneficial after major burns; it was associated with a significant decrease in the number of bronchopneumonia infections and with a shorter hospital stay when data were normalized for burn size.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Fast and simple epidemiological typing of Pseudomonas aeruginosa using the double-locus sequence typing (DLST) method.

Although the molecular typing of Pseudomonas aeruginosa is important to understand the local epidemiology of this opportunistic pathogen, it remains challenging. Our aim was to develop a simple typing method based on the sequencing of two highly variable loci. Single-strand sequencing of three highly variable loci (ms172, ms217, and oprD) was performed on a collection of 282 isolates recovered between 1994 and 2007 (from patients and the environment). As expected, the resolution of each locus alone [number of types (NT) = 35-64; index of discrimination (ID) = 0.816-0.964] was lower than the combination of two loci (NT = 78-97; ID = 0.966-0.971). As each pairwise combination of loci gave similar results, we selected the most robust combination with ms172 [reverse; R] and ms217 [R] to constitute the double-locus sequence typing (DLST) scheme for P. aeruginosa. This combination gave: (i) a complete genotype for 276/282 isolates (typability of 98%), (ii) 86 different types, and (iii) an ID of 0.968. Analysis of multiple isolates from the same patients or taps showed that DLST genotypes are generally stable over a period of several months. The high typability, discriminatory power, and ease of use of the proposed DLST scheme makes it a method of choice for local epidemiological analyses of P. aeruginosa. Moreover, the possibility to give unambiguous definition of types allowed to develop an Internet database ( http://www.dlst.org ) accessible by all.

[Archives de la Parole]. , Vackra sky [i.e. Vackra sky som tågar öfver det vida blå] / [Carl Alexander Brolèn, comp.] ; [Carl Snoilsky, aut.] ; Double quatuor M. M. [i.e. Muntra Musikanter]. Sjöfararen vid Milan / [Selim Palmgren, comp.] ; [Gustaf Fröding, aut.] ; Double quatuor M. M. [i.e. Muntra Musikanter]

Suédois de Finlande

Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Safety and efficacy of the peptide-based therapeutic vaccine for HIV-1, Vacc-4x: a phase 2 randomised, double-blind, placebo-controlled trial.

BACKGROUND: Present combination antiretroviral therapy (cART) alone does not cure HIV infection and requires lifelong drug treatment. The potential role of HIV therapeutic vaccines as part of an HIV cure is under consideration. Our aim was to assess the efficacy, safety, and immunogenicity of Vacc-4x, a peptide-based HIV-1 therapeutic vaccine targeting conserved domains on p24(Gag), in adults infected with HIV-1. METHODS: Between July, 2008, and June, 2010, we did a multinational double-blind, randomised, phase 2 study comparing Vacc-4x with placebo. Participants were adults infected with HIV-1 who were aged 18-55 years and virologically suppressed on cART (viral load <50 copies per mL) with CD4 cell counts of 400 × 10(6) cells per L or greater. The trial was done at 18 sites in Germany, Italy, Spain, the UK, and the USA. Participants were randomly assigned (2:1) to Vacc-4x or placebo. Group allocation was masked from participants and investigators. Four primary immunisations, weekly for 4 weeks, containing Vacc-4x (or placebo) were given intradermally after administration of adjuvant. Booster immunisations were given at weeks 16 and 18. At week 28, cART was interrupted for up to 24 weeks. The coprimary endpoints were cART resumption and changes in CD4 counts during treatment interruption. Analyses were by modified intention to treat: all participants who received one intervention. Furthermore, safety, viral load, and immunogenicity (as measured by ELISPOT and proliferation assays) were assessed. The 52 week follow-up period was completed in June, 2011. For the coprimary endpoints the proportion of participants who met the criteria for cART resumption was analysed with a logistic regression model with the treatment effect being assessed in a model including country as a covariate. This study is registered with ClinicalTrials.gov, number NCT00659789. FINDINGS: 174 individuals were screened; because of slow recruitment, enrolment stopped with 136 of a planned 345 participants and 93 were randomly assigned to receive Vacc-4x and 43 to receive placebo. There were no differences between the two groups for the primary efficacy endpoints in those participants who stopped cART at week 28. Of the participants who resumed cART, 30 (34%) were in the Vacc-4x group and 11 (29%) in the placebo group, and percentage changes in CD4 counts were not significant (mean treatment difference -5·71, 95% CI -13·01 to 1·59). However, a significant difference in viral load was noted for the Vacc-4x group both at week 48 (median 23 100 copies per mL Vacc-4x vs 71 800 copies per mL placebo; p=0·025) and week 52 (median 19 550 copies per mL vs 51 000 copies per mL; p=0·041). One serious adverse event, exacerbation of multiple sclerosis, was reported as possibly related to study treatment. Vacc-4x was immunogenic, inducing proliferative responses in both CD4 and CD8 T-cell populations. INTERPRETATION: The proportion of participants resuming cART before end of study and change in CD4 counts during the treatment interruption showed no benefit of vaccination. Vacc-4x was safe, well tolerated, immunogenic, seemed to contribute to a viral-load setpoint reduction after cART interruption, and might be worth consideration in future HIV-cure investigative strategies. FUNDING: Norwegian Research Council GLOBVAC Program and Bionor Pharma ASA.