Novel combination of feed enzymes to improve the degradation of Chlorella vulgaris recalcitrant cell wall

Research Areas: Science & TechnologyABSTRACT - In this study, a rational combination of 200 pre-selected Carbohydrate-Active enzymes (CAZymes) and sulfatases were tested, individually or combined, according to their ability to degrade Chlorella vulgaris cell wall to access its valuable nutritional compounds. The disruption of microalgae cell walls by a four enzyme mixture (Mix) in comparison with the control, enabled to release up to 1.21g/L of reducing sugars (p<0.001), led to an eight-fold increase in oligosaccharides release (p<0.001), and reduced the fuorescence intensity by 47% after staining with Calcofuor White (p<0.001). The Mix treatment was successful in releasing proteins (p<0.001), some MUFA (p<0.05), and the benefcial 18:3n-3 fatty acid (p0.05), total carotenoids were increased in the supernatant (p<0.05) from the Mix treatment, relative to the control. Taken together, these results indicate that this four-enzyme Mix displays an efective capacity to degrade C. vulgaris cell wall. Thus, these enzymes may constitute a good approach to improve the bioavailability of C. vulgaris nutrients for monogastric diets, in particular, and to facilitate the cost-efective use of microalgae by the feed industry, in general.info:eu-repo/semantics/publishedVersio

Oral vaccination with heat inactivated Mycobacterium bovis activates the complement system to protect against tuberculosis

Tuberculosis (TB) remains a pandemic affecting billions of people worldwide, thus stressing the need for new vaccines. Defining the correlates of vaccine protection is essential to achieve this goal. In this study, we used the wild boar model for mycobacterial infection and TB to characterize the protective mechanisms elicited by a new heat inactivated Mycobacterium bovis vaccine (IV). Oral vaccination with the IV resulted in significantly lower culture and lesion scores, particularly in the thorax, suggesting that the IV might provide a novel vaccine for TB control with special impact on the prevention of pulmonary disease, which is one of the limitations of current vaccines. Oral vaccination with the IV induced an adaptive antibody response and activation of the innate immune response including the complement component C3 and inflammasome. Mycobacterial DNA/RNA was not involved in inflammasome activation but increased C3 production by a still unknown mechanism. The results also suggested a protective mechanism mediated by the activation of IFN-γ producing CD8+ T cells by MHC I antigen presenting dendritic cells (DCs) in response to vaccination with the IV, without a clear role for Th1 CD4+ T cells. These results support a role for DCs in triggering the immune response to the IV through a mechanism similar to the phagocyte response to PAMPs with a central role for C3 in protection against mycobacterial infection. Higher C3 levels may allow increased opsonophagocytosis and effective bacterial clearance, while interfering with CR3-mediated opsonic and nonopsonic phagocytosis of mycobacteria, a process that could be enhanced by specific antibodies against mycobacterial proteins induced by vaccination with the IV. These results suggest that the IV acts through novel mechanisms to protect against TB in wild boar

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background: Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. / Methods: We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. / Findings: Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). / Interpretation: These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. / Funding: The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Identification of sixteen novel candidate genes for late onset Parkinson’s disease

Background Parkinson’s disease (PD) is a neurodegenerative movement disorder affecting 1–5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. Methods The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). Results Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10− 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. Conclusions Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment

Observation of the diphoton decay of the Higgs boson and measurement of its properties

Peer reviewe

Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at root s=8 TeV

Peer reviewe

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Search for the X(5568) State Decaying into B-s(0)pi(+/-) in Proton-Proton Collisions at root s=8 TeV

A search for resonancelike structures in the B-s(0)pi(+/-) invariant mass spectrum is performed using proton-proton collision data collected by the CMS experiment at the LHC at root s = 8 TeV, corresponding to an integrated luminosity of 19.7 fb(-1). The B-s(0) mesons are reconstructed in the decay chain B-s(0) -> J/Psi phi, with J/Psi -> mu(+) mu(-) and phi -> K+K-. The B-s(0)pi(+/-) invariant mass distribution shows no statistically significant peaks for different selection requirements on the reconstructed B-s(0) and pi(+/-) candidates. Upper limits are set on the relative production rates of the X(5568) and B-s(0) states times the branching fraction of the decay X(5568)(+/-) -> B-s(0)pi(+/-). In addition, upper limits are obtained as a function of the mass and the natural width of possible exotic states decaying into B-s(0)pi(+/-).Peer reviewe

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯