Second order QCD corrections to gluonic jet production at hadron colliders

We report on the calculation of the next-to-next-to-leading order (NNLO) QCD corrections to the production of two gluonic jets at hadron colliders. In previous work, we discussed gluonic dijet production in the gluon-gluon channel. Here, for the first time, we update our numerical results to include the leading colour contribution to the production of two gluonic jets via quark-antiquark scattering.Comment: 8 pages, 4 figures, Proceedings of "Loops and Legs in Quantum Field Theory", Weimar April 201

DCcov: Repositioning of Drugs and Drug Combinations for SARS-CoV-2 Infected Lung through Constraint-Based Modelling

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no effective antiviral drug except treatments for symptomatic therapy. Flux balance analysis is an efficient method to analyze metabolic networks. It allows optimizing for a metabolic function and thus e.g., predicting the growth rate of a specific cell or the production rate of a metabolite of interest. Here flux balance analysis was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the replication of the SARS-CoV-2 virus within the host tissue. Making use of expression data sets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then host-specific essential genes and gene-pairs were determined through in-silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, as well as ferroptosis, sphingolipid metabolism, cysteine metabolism, and fat digestion. By in-silico screening of FDA approved drugs on the putative disease-specific essential genes and gene-pairs, 45 drugs and 99 drug combinations were predicted as promising candidates for COVID-19 focused drug repositioning (https://github.com/sysbiolux/DCcov). Among the 45 drug candidates, six antiviral drugs were found and seven drugs that are being tested in clinical trials against COVID-19. Other drugs like gemcitabine, rosuvastatin and acetylcysteine, and drug combinations like azathioprine-pemetrexed might offer new chances for treating COVID-19

Carbenoid-mediated nucleophilic "hydrolysis" of 2-(dichloromethylidene)-1, 1, 3, 3-tetramethylindane with DMSO participation, affording access to one-sidedly overcrowded ketone and bromoalkene descendants

2-(Dichloromethylidene)-1, 1, 3, 3-tetramethylindane was "hydrolyzed" by solid KOH in DMSO as the solvent at >= 100 degrees C through an initial chlorine particle transfer to give a Cl, K-carbenoid. This short-lived intermediate disclosed its occurrence through a reversible proton transfer which competed with an oxygen transfer from DMSO that created dimethyl sulfide. The presumably resultant transitory ketene incorporated KOH to afford the potassium salt of 1, 1, 3, 3-tetramethylindan-2-carboxylic acid (the product of a formal hydrolysis). The lithium salt of this key acid is able to acylate aryllithium compounds, furnishing one-sidedly overcrowded ketones along with the corresponding tertiary alcohols. The latter side-products (ca. 10%) were formed against a substantially increasing repulsive resistance, as testified through the diminished rotational mobility of their aryl groups. As a less troublesome further side-product, the dianion of the above key acid was recognized through carboxylation which afforded 1, 1, 3, 3-tetramethyl-indan-2, 2-dicarboxylic acid. Brominative deoxygenation of the ketones furnished two one-sidedly overcrowded bromoalkenes. Some presently relevant properties of the above Cl, K-carbenoid are provided in Supporting Information File 1

Training on citizen engagement in Policy-relevant Science, Technology and Innovation: Sarajevo 12 -13 October 2017. @ Rektorat, Univerzitet u Sarajevu, Obala Kulina Bana 7/II, 71000 Sarajevo, BiH

In the framework of its Enlargement and Integration Action, JRC is organizing in collaboration with the Ministry of Civil Affairs of Bosnia and Herzegovina this "Training on citizen engagement in Policy relevant Science, Technology and Innovation", in Sarajevo on 12th-13th October 2017. Creating the conditions for genuine engagement of citizens and other societal actors in matters of their concern where science and technology are relevant is an issue of increasing political attention; not least because the diffusion of “low cost” and “low tech” media through which citizens can, like never before, express opinions and concerns calls for institutional reflexivity. Public engagement is one of the pillars of the RRI lemma, together with Ethics. This training course responds to a concrete lack of genuine and legitimate places whereby institutions can explore insights, expectations and imaginaries of citizens in matters of concern to all. This training is concerned with the science for policy realm where engagement of citizens is needed and relevant to ensure quality of policy formulation processes in situations described in the framework of “post-normal science” where “facts uncertain, values in dispute, stakes high and decisions urgent". This training will look into participatory approaches to discuss science and technology developments as well as discuss what makes trustful relationships between the scientific community and the public trustworthyJRC.I.2-Foresight, Behavioural Insights and Design for Polic

A review of the distribution and ecology of the elusive Brown Hairstreak butterfly Thecla betulae (Lepidoptera, Lycaenidae) in the Iberian Peninsula

The Brown Hairstreak (Thecla betulae L.) is one of the least observed butterflies of the Palaearctic region, even though its distribution spans from Portugal in the west, to Russia and Korea in the far east. Adults are arboreal and seldom descend to ground level. As a result, this species is mostly monitored via the detection of eggs on the food plant during wintertime. In the Iberian Peninsula, this species was largely unknown until very recently, but a recent burst of regional studies in Spain has begun bridging this gap. However, their focused nature and a still incomplete knowledge on T. betulae in Portugal promoted the need for an integrative study at the Iberian scale. Here, we carried out a full literature review on the distribution, ecology and behaviour of T. betulae in Portugal and Spain. Complemented with field work in Portugal, we revealed an almost continuous distribution in the northern third of Iberia, whilst populations further south are mostly mountain-bound. In order to help with future discovery of new populations, we built a species-distribution model relating its occurrence with bioclimatic variables. This model accurately explains the current known occupation of the territory and highlights other areas where the species may potentially be found. Finally, we found evidence of a broadening of the species’ niche through the local use of an hitherto unknown food plant. This study sets a new knowledge baseline for future works and conservation of T. betulae through southern Europe.info:eu-repo/semantics/publishedVersio

Towards the routine use of in silico screenings for drug discovery using metabolic modelling

Currently, the development of new effective drugs for cancer therapy is not only hindered by development costs, drug efficacy, and drug safety but also by the rapid occurrence of drug resistance in cancer. Hence, new tools are needed to study the underlying mechanisms in cancer. Here, we discuss the current use of metabolic modelling approaches to identify cancer-specific metabolism and find possible new drug targets and drugs for repurposing. Furthermore, we list valuable resources that are needed for the reconstruction of cancer-specific models by integrating various available datasets with genome-scale metabolic reconstructions using model-building algorithms. We also discuss how new drug targets can be determined by using gene essentiality analysis, an in silico method to predict essential genes in a given condition such as cancer and how synthetic lethality studies could greatly benefit cancer patients by suggesting drug combinations with reduced side effects