One-dimensional steady-state thermal model for rotary kilns used in the manufacture of cement

Peer reviewedPostprin

Innate immune response to intramammary infection with Serratia marcescens and Streptococcus uberis

Streptococcus uberis and Serratia marcescens are Gram-positive and Gram-negative bacteria, respectively, that induce clinical mastitis. Once initial host barrier systems have been breached by these pathogens, the innate immune system provides the next level of defense against these infectious agents. The innate immune response is characterized by the induction of pro-inflammatory cytokines, as well as increases in other accessory proteins that facilitate host recognition and elimination of the pathogens. The objective of the current study was to characterize the innate immune response during clinical mastitis elicited by these two important, yet less well-studied, Gram-positive and Gram-negative organisms. The pro-inflammatory cytokine response and changes in the levels of the innate immune accessory recognition proteins, soluble CD14 (sCD14) and lipopolysaccharide (LPS)-binding protein (LBP), were studied. Decreased milk output, induction of a febrile response, and increased acute phase synthesis of LBP were all characteristic of the systemic response to intramammary infection with either organism. Infection with either bacteria similarly resulted in increased milk levels of IL-1$\beta$, IL-8, IL-10, IL-12, IFN-$\gamma$, TNF-$\alpha$, sCD14, LBP, and the complement component, C5a. However, the duration of and/or maximal changes in the increased levels of these inflammatory markers were significantly different for several of the inflammatory parameters assayed. In particular, S. uberis infection was characterized by the sustained elevation of higher milk levels of IL-1$\beta$, IL-10, IL-12, IFN-$\gamma$, and C5a, relative to S. marcescens infection. Together, these data demonstrate the variability of the innate immune response to two distinct mastitis pathogens

CONTRABASS: exploiting flux constraints in genome-scale models for the detection of vulnerabilities

Motivation: Despite the fact that antimicrobial resistance is an increasing health concern, the pace of production of new drugs is slow due to the high cost and uncertain success of the process. The development of high-throughput technologies has allowed the integration of biological data into detailed genome-scale models of multiple organisms. Such models can be exploited by means of computational methods to identify system vulnerabilities such as chokepoint reactions and essential reactions. These vulnerabilities are appealing drug targets that can lead to novel drug developments. However, the current approach to compute these vulnerabilities is only based on topological data and ignores the dynamic information of the model. This can lead to misidentified drug targets. Results: This work computes flux constraints that are consistent with a certain growth rate of the modelled organism, and integrates the computed flux constraints into the model to improve the detection of vulnerabilities. By exploiting these flux constraints, we are able to obtain a directionality of the reactions of metabolism consistent with a given growth rate of the model, and consequently, a more realistic detection of vulnerabilities can be performed. Several sets of reactions that are system vulnerabilities are defined and the relationships among them are studied. The approach for the detection of these vulnerabilities has been implemented in the Python tool CONTRABASS. Such tool, for which an online web server has also been implemented, computes flux constraints and generates a report with the detected vulnerabilities

Multispecies reconstructions uncover widespread conservation, and lineage-specific elaborations in eukaryotic mRNA metabolism.

The degree of conservation and evolution of cytoplasmic mRNA metabolism pathways across the eukaryotes remains incompletely resolved. In this study, we describe a comprehensive genome and transcriptome-wide analysis of proteins involved in mRNA maturation, translation, and mRNA decay across representative organisms from the six eukaryotic super-groups. We demonstrate that eukaryotes share common pathways for mRNA metabolism that were almost certainly present in the last eukaryotic common ancestor, and show for the first time a correlation between intron density and a selective absence of some Exon Junction Complex (EJC) components in eukaryotes. In addition, we identify pathways that have diversified in individual lineages, with a specific focus on the unique gene gains and losses in members of the Excavata and SAR groups that contribute to their unique gene expression pathways compared to other organisms

Production of belite calcium sulfoaluminate cement using sulfur as a fuel and as a source of clinker sulfur trioxide : pilot kiln trial

The authors gratefully acknowledge the financial support provided by the Gulf Organization for Research and Development (GORD), Qatar, through research grant number ENG016RGG11757. The authors would also like to acknowledge Thomas Matschei and Guanshu Li for the stimulating and fruitful discussions concerning the development of this work. The continuous support prior to, during and after the pilot kiln trial from Vadym Kuznietsov and the entire team at IBU-tec is also greatly appreciated.Peer reviewedPublisher PD

Movers and shakers: Granular damping in microgravity

The response of an oscillating granular damper to an initial perturbation is studied using experiments performed in microgravity and granular dynamics mulations. High-speed video and image processing techniques are used to extract experimental data. An inelastic hard sphere model is developed to perform simulations and the results are in excellent agreement with the experiments. The granular damper behaves like a frictional damper and a linear decay of the amplitude is bserved. This is true even for the simulation model, where friction forces are absent. A simple expression is developed which predicts the optimal damping conditions for a given amplitude and is independent of the oscillation frequency and particle inelasticities.Comment: 9 pages, 9 figure

Transport properties of highly asymmetric hard-sphere mixtures

The static and dynamic properties of binary mixtures of hard spheres with a diameter ratio of sigma(B)/sigma(A)= 0.1 and a mass ratio of m(B)/m(A)= 0.001 are investigated using event driven molecular dynamics. The contact values of the pair correlation functions are found to compare favorably with recently proposed theoretical expressions. The transport coefficients of the mixture, determined from simulation, are compared to the predictions of the revised Enskog theory using both a third-order Sonine expansion and direct simulation Monte Carlo. Overall, the Enskog theory provides a fairly good description of the simulation data, with the exception of systems at the smallest mole fraction of larger spheres (x(A)=0.01) examined. A "fines effect" was observed at higher packing fractions, where adding smaller spheres to a system of large spheres decreases the viscosity of the mixture; this effect is not captured by the Enskog theory

Integrated human/SARS-CoV-2 metabolic models present novel treatment strategies against COVID-19

The coronavirus disease 2019 (COVID-19) pandemic caused by the new coronavirus (SARS-CoV-2) is currently responsible for more than 3 million deaths in 219 countries across the world and with more than 140 million cases. The absence of FDA-approved drugs against SARS-CoV-2 has highlighted an urgent need to design new drugs. We developed an integrated model of the human cell and SARS-CoV-2 to provide insight into the virus'' pathogenic mechanism and support current therapeutic strategies. We show the biochemical reactions required for the growth and general maintenance of the human cell, first, in its healthy state. We then demonstrate how the entry of SARS-CoV-2 into the human cell causes biochemical and structural changes, leading to a change of cell functions or cell death. A new computational method that predicts 20 unique reactions as drug targets from our models and provides a platform for future studies on viral entry inhibition, immune regulation, and drug optimisation strategies. The model is available in BioModels (https://www.ebi.ac.uk/biomodels/MODEL2007210001) and the software tool, findCPcli, that implements the computational method is available at https://github.com/findCP/findCPcli. © 2021 Bannerman et al