Front Matter

The carbohydrate Galα1-3Galβ1-(3)4GlcNAc-R (α-Gal) is produced in all mammals except for humans, apes and old world monkeys that lost the ability to synthetize this carbohydrate. Therefore, humans can produce high antibody titers against α-Gal. Anti-α-Gal IgE antibodies have been associated with tick-induced allergy (i.e. α-Gal syndrome) and anti-α-Gal IgG/IgM antibodies may be involved in protection against malaria, leishmaniasis and Chagas disease. The α-Gal on tick salivary proteins plays an important role in the etiology of the α-Gal syndrome. However, whether ticks are able to produce endogenous α-Gal remains currently unknown. In this study, the Ixodes scapularis genome was searched for galactosyltransferases and three genes were identified as potentially involved in the synthesis of α-Gal. Heterologous gene expression in α-Gal-negative cells and gene knockdown in ticks confirmed that these genes were involved in α-Gal synthesis and are essential for tick feeding. Furthermore, these genes were shown to play an important role in tick-pathogen interactions. Results suggested that tick cells increased α-Gal levels in response to Anaplasma phagocytophilum infection to control bacterial infection. These results provided the molecular basis of endogenous α-Gal production in ticks and suggested that tick galactosyltransferases are involved in vector development, tick-pathogen interactions and possibly the etiology of α-Gal syndrome in humans.This research was supported by the Consejería de Educación, Cultura y Deportes, JCCM, Spain, project CCM17-PIC-036 (SBPLY/17/180501/000185). JJV was supported by Project FIT (Pharmacology, Immunotherapy, nanoToxicology), funded by the European Regional Development Fund.Peer Reviewe

Diet supplementation for 5 weeks with polyphenol-rich cereals improves several functions and the redox state of mouse leucocytes

BACKGROUND: Cereals naturally contain a great variety of polyphenols, which exert a wide range of physiological effects both in vitro and in vivo. Many of their protective effects, including an improvement of the function and redox state of immune cells in unhealthy or aged subjects come from their properties as powerful antioxidant compounds. However, whether cereal-based dietary supplementation positively affects the immune function and cellular redox state of healthy subjects remains unclear. AIM OF THE STUDY: To investigate the effects of supplementation (20% wt/wt) for 5 weeks with four different cereal fractions on healthy mice. METHODS: Several parameters of function and redox state of peritoneal leukocytes were measured. The cereals, named B (wheat germ), C (buckwheat flour), D (fine rice bran) and E (wheat middlings) contained different amounts of gallic acid, p-hydroxybenzoic acid, vanillic acid, sinapic acid, p-coumaric acid, ferulic acid, quercetin, catechin, rutin and oryzanol as major polyphenols. RESULTS: In general, all cereal fractions caused an improvement of the leukocyte parameters studied such as chemotaxis capacity, microbicidal activity, lymphoproliferative response to mitogens, interleukin-2 (IL-2) and tumor necrosis factor (TNFα) release, as well as oxidized glutathione (GSSG), GSSG/GSH ratio, catalase (CAT) activity and lipid oxidative damage. We observed similar effects among the cereal fractions. CONCLUSIONS: The results suggest that some of these effects may due, at least partially, to the antioxidant activity of the polyphenols naturally present in cereals. Since an appropriate function of the leukocytes has been proposed as marker of the health state, a short-term intake of cereals seems to be sufficient to exert a benefit in the health of the general population. However, further studies are needed to assess the optimal doses and to find out which active polyphenols are able to mediate the observed physiological effects before recommending their regular consumption

Power management and control strategies for off-grid hybrid power systems with renewable energies and storage

This document is the Accepted Manuscript of the following article: Belkacem Belabbas, Tayeb Allaoui, Mohamed Tadjine, and Mouloud Denai, 'Power management and control strategies for off-grid hybrid power systems with renewable energies and storage', Energy Systems, September 2017. Under embargo. Embargo end date: 19 September 2018. The final publication is available at Springer via https://doi.org/10.1007/s12667-017-0251-y.This paper presents a simulation study of standalone hybrid Distributed Generation Systems (DGS) with Battery Energy Storage System (BESS). The DGS consists of Photovoltaic (PV) panels as Renewable Power Source (RPS), a Diesel Generator (DG) for power buck-up and a BESS to accommodate the surplus of energy, which may be employed in times of poor PV generation. While off-grid DGS represent an efficient and cost-effective energy supply solution particularly to rural and remote areas, fluctuations in voltage and frequency due to load variations, weather conditions (temperature, irradiation) and transmission line short-circuits are major challenges. The paper suggests a hierarchical Power Management (PM) and controller structure to improve the reliability and efficiency of the hybrid DGS. The first layer of the overall control scheme includes a Fuzzy Logic Controller (FLC) to adjust the voltage and frequency at the Point of Common Coupling (PCC) and a Clamping Bridge Circuit (CBC) which regulates the DC bus voltage. A maximum power point tracking (MPPT) controller based on FLC is designed to extract the optimum power from the PV. The second control layer coordinates among PV, DG and BESS to ensure reliable and efficient power supply to the load. MATLAB Simulink is used to implement the overall model of the off-grid DGS and to test the performance of the proposed control scheme which is evaluated in a series of simulations scenarios. The results demonstrated the good performance of the proposed control scheme and effective coordination between the DGS for all the simulation scenarios considered.Peer reviewedFinal Accepted Versio

Inferring gene regression networks with model trees

<p>Abstract</p> <p>Background</p> <p>Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities.</p> <p>Results</p> <p>We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named R<smcaps>EG</smcaps>N<smcaps>ET</smcaps>, is experimentally tested on two well-known data sets: <it>Saccharomyces Cerevisiae </it>and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that R<smcaps>EG</smcaps>N<smcaps>ET</smcaps> performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods.</p> <p>Conclusions</p> <p>R<smcaps>EG</smcaps>N<smcaps>ET</smcaps> generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate areas of the search space favoring to infer localized similarities over a more global similarity. Furthermore, experimental results show the good performance of R<smcaps>EG</smcaps>N<smcaps>ET</smcaps>.</p

A Network Analysis of the Human T-Cell Activation Gene Network Identifies Jagged1 as a Therapeutic Target for Autoimmune Diseases

Understanding complex diseases will benefit the recognition of the properties of the gene networks that control biological functions. Here, we set out to model the gene network that controls T-cell activation in humans, which is critical for the development of autoimmune diseases such as Multiple Sclerosis (MS). The network was established on the basis of the quantitative expression from 104 individuals of 20 genes of the immune system, as well as on biological information from the Ingenuity database and Bayesian inference. Of the 31 links (gene interactions) identified in the network, 18 were identified in the Ingenuity database and 13 were new and we validated 7 of 8 interactions experimentally. In the MS patients network, we found an increase in the weight of gene interactions related to Th1 function and a decrease in those related to Treg and Th2 function. Indeed, we found that IFN-ß therapy induces changes in gene interactions related to T cell proliferation and adhesion, although these gene interactions were not restored to levels similar to controls. Finally, we identify JAG1 as a new therapeutic target whose differential behaviour in the MS network was not modified by immunomodulatory therapy. In vitro treatment with a Jagged1 agonist peptide modulated the T-cell activation network in PBMCs from patients with MS. Moreover, treatment of mice with experimental autoimmune encephalomyelitis with the Jagged1 agonist ameliorated the disease course, and modulated Th2, Th1 and Treg function. This study illustrates how network analysis can predict therapeutic targets for immune intervention and identified the immunomodulatory properties of Jagged1 making it a new therapeutic target for MS and other autoimmune diseases

Comparative maturation of cynomolgus monkey oocytes in vivo and in vitro

BACKGROUND: In vitro maturation (IVM) of oocytes followed by fertilization in vitro (IVF) and embryo transfer offers an alternative to conventional IVF treatment that minimises drug administration and avoids ovarian hyperstimulation. However, the technique is less efficient than maturation in vivo. In the present study, a non-human primate model was used to address the hypothesis that the number of oocytes is increased and their nuclear and cytoplasmic maturity after IVM are improved when maturation is initiated in vivo by priming with hCG. METHODS: Young, adult cynomolgus monkeys were given recombinant human (rh) gonadotropins to stimulate the development of multiple follicles, and oocytes were aspirated 0, 12, 24, or 36 h after injection of an ovulatory dose of rhCG. The nuclear status of oocytes was determined at the time of recovery and after culture for a total elapsed time of 40–44 hours after hCG. RESULTS: Priming with hCG significantly increased the number of oocytes harvested, especially after delaying aspiration for 24 h or longer. Nuclear maturation after the full period in culture was also enhanced by priming: 71.5, 83.6, and 94.6% of oocytes collected at 0, 12, and 24 h hCG had progressed to MII by the end of the culture period, compared to 87.8% of oocytes that were retrieved at 36 h. A large proportion of oocytes reaching the MII stage had either or both abnormal spindles (>40%) and misaligned chromosomes (>60%), judging by immunofluorescence microscopy, but these abnormalities were independent of culture time. The mitochondria were evenly distributed throughout the cytoplasm at all stages of maturation. Importantly, there was no microscopic evidence that the duration of culture had any injurious effects on the cells. CONCLUSION: In conclusion, the evidence supports this non-human primate as a model for human IVM and the practice of priming with hCG to promote developmental potential

Metagenomic Profile of the Bacterial Communities Associated with Ixodes ricinus Ticks

Assessment of the microbial diversity residing in arthropod vectors of medical importance is crucial for monitoring endemic infections, for surveillance of newly emerging zoonotic pathogens, and for unraveling the associated bacteria within its host. The tick Ixodes ricinus is recognized as the primary European vector of disease-causing bacteria in humans. Despite I. ricinus being of great public health relevance, its microbial communities remain largely unexplored to date. Here we evaluate the pathogen-load and the microbiome in single adult I. ricinus by using 454- and Illumina-based metagenomic approaches. Genomic DNA-derived sequences were taxonomically profiled using a computational approach based on the BWA algorithm, allowing for the identification of known tick-borne pathogens at the strain level and the putative tick core microbiome. Additionally, we assessed and compared the bacterial taxonomic profile in nymphal and adult I. ricinus pools collected from two distinct geographic regions in Northern Italy by means of V6-16S rRNA amplicon pyrosequencing and community based ecological analysis. A total of 108 genera belonging to representatives of all bacterial phyla were detected and a rapid qualitative assessment for pathogenic bacteria, such as Borrelia, Rickettsia and Candidatus Neoehrlichia, and for other bacteria with mutualistic relationship or undetermined function, such as Wolbachia and Rickettsiella, was possible. Interestingly, the ecological analysis revealed that the bacterial community structure differed between the examined geographic regions and tick life stages. This finding suggests that the environmental context (abiotic and biotic factors) and host-selection behaviors affect their microbiome