Disease re-classi cation via integration of biological networks

Currently, human diseases are classi ed as they were in the late 19th century, by considering only symptoms of the a ected organ. With a growing body of transcriptomic, proteomic, metabolomic and genomics data sets describing diseases, we ask whether the old classi cation still holds in the light of modern biological data. These large-scale and complex biological data can be viewed as networks of inter-connected elements. We propose to rede ne human disease classi cation by considering diseases as systemslevel disorders of the entire cellular system. To do this, we will integrate di erent types of biological data mentioned above. A network-based mathematical model will be designed to represent these integrated data, and computational algorithms and tools will be developed and implemented for its analysis. In this report, a review of the research progress so far will be presented, including 1) a detailed statement of the research problem, 2) a literature survey on relative research topics, 3) reports of on-going work, and 4) future research plans.

ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behavior

<div><p>A calibrated computational model reflects behaviours that are expected or observed in a complex system, providing a baseline upon which sensitivity analysis techniques can be used to analyse pathways that may impact model responses. However, calibration of a model where a behaviour depends on an intervention introduced after a defined time point is difficult, as model responses may be dependent on the conditions at the time the intervention is applied. We present ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), a cross-platform, open-source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML). ASPASIA can generate and modify models using SBML solver output as an initial parameter set, allowing interventions to be applied once a steady state has been reached. Additionally, multiple SBML models can be generated where a subset of parameter values are perturbed using local and global sensitivity analysis techniques, revealing the model’s sensitivity to the intervention. To illustrate the capabilities of ASPASIA, we demonstrate how this tool has generated novel hypotheses regarding the mechanisms by which Th17-cell plasticity may be controlled <i>in vivo</i>. By using ASPASIA in conjunction with an SBML model of Th17-cell polarisation, we predict that promotion of the Th1-associated transcription factor T-bet, rather than inhibition of the Th17-associated transcription factor ROR<i>γ</i>t, is sufficient to drive switching of Th17 cells towards an IFN-<i>γ</i>-producing phenotype. Our approach can be applied to all SBML-encoded models to predict the effect that intervention strategies have on system behaviour. ASPASIA, released under the Artistic License (2.0), can be downloaded from <a href="http://www.york.ac.uk/ycil/software" target="_blank">http://www.york.ac.uk/ycil/software</a>.</p></div

Review of battery electric vehicle propulsion systems incorporating flywheel energy storage

The development of battery electric vehicles (BEV) must continue since this can lead us towards a zero emission transport system. There has been an advent of the production BEVs in recent years; however their low range and high cost still remain the two important drawbacks. The battery is the element which strongly affects the cost and range of the BEV. The batteries offer either high specific power or high specific energy but not both. To provide the BEVs with the characteristic to compete with conventional vehicles it is beneficial to hybridize the energy storage combining a high energy battery with a high power source. This shields the battery from peak currents and improves its capacity and life. There are various devices which could qualify as a secondary storage system for the BEV such as high power battery, supercapacitor and high speed flywheel (FW). This paper aims to review a specific type of hybridisation of energy storage which combines batteries and high speed flywheels. The flywheel has been used as a secondary energy system in BEVs from the early 1970s when the oil crises triggered an interest in BEVs. Since the last decade the interest in flywheels has strengthened and their application in the kinetic energy recovery system (KERS) in Formula 1 has further bolstered the case for flywheels. With a number of automotive manufacturers getting involved in developing flywheels for road applications, the authors believe commercial flywheel based powertrains are likely to be seen in the near future. It is hence timely to produce a review of research and development in the area of flywheel assisted BEVs

Loss of Regulator of G Protein Signaling 5 Exacerbates Obesity, Hepatic Steatosis, Inflammation and Insulin Resistance

BACKGROUND: The effect of regulator of G protein signaling 5 (RGS5) on cardiac hypertrophy, atherosclerosis and angiogenesis has been well demonstrated, but the role in the development of obesity and insulin resistance remains completely unknown. We determined the effect of RGS5 deficiency on obesity, hepatic steatosis, inflammation and insulin resistance in mice fed either a normal-chow diet (NC) or a high-fat diet (HF). METHODOLOGY/PRINCIPAL FINDINGS: Male, 8-week-old RGS5 knockout (KO) and littermate control mice were fed an NC or an HF for 24 weeks and were phenotyped accordingly. RGS5 KO mice exhibited increased obesity, fat mass and ectopic lipid deposition in the liver compared with littermate control mice, regardless of diet. When fed an HF, RGS5 KO mice had a markedly exacerbated metabolic dysfunction and inflammatory state in the blood serum. Meanwhile, macrophage recruitment and inflammation were increased and these increases were associated with the significant activation of JNK, IκBα and NF-κBp65 in the adipose tissue, liver and skeletal muscle of RGS5 KO mice fed an HF relative to control mice. These exacerbated metabolic dysfunction and inflammation are accompanied with decreased systemic insulin sensitivity in the adipose tissue, liver and skeletal muscle of RGS5 KO mice, reflected by weakened Akt/GSK3β phosphorylation. CONCLUSIONS/SIGNIFICANCE: Our data suggest that loss of RGS5 exacerbates HF-induced obesity, hepatic steatosis, inflammation and insulin resistance

Stratification of asthma phenotypes by airway proteomic signatures

© 2019 Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.</p

Degradation aspects of water formation and transport in Proton Exchange Membrane Fuel Cell: A review

This review paper summarises the key aspects of Proton Exchange Membrane Fuel Cell (PEMFC) degradation that are associated with water formation, retention, accumulation, and transport mechanisms within the cell. Issues related to loss of active surface area of the catalyst, ionomer dissolution, membrane swelling, ice formation, corrosion, and contamination are also addressed and discussed. The impact of each of these water mechanisms on cell performance and durability was found to be different and to vary according to the design of the cell and its operating conditions. For example, the presence of liquid water within Membrane Electrode Assembly (MEA), as a result of water accumulation, can be detrimental if the operating temperature of the cell drops to sub-freezing. The volume expansion of liquid water due to ice formation can damage the morphology of different parts of the cell and may shorten its life-time. This can be more serious, for example, during the water transport mechanism where migration of Pt particles from the catalyst may take place after detachment from the carbon support. Furthermore, the effect of transport mechanism could be augmented if humid reactant gases containing impurities poison the membrane, leading to the same outcome as water retention or accumulation. Overall, the impact of water mechanisms can be classified as aging or catastrophic. Aging has a long-term impact over the duration of the PEMFC life-time whereas in the catastrophic mechanism the impact is immediate. The conversion of cell residual water into ice at sub-freezing temperatures by the water retention/ accumulation mechanism and the access of poisoning contaminants through the water transport mechanism are considered to fall into the catastrophic category. The effect of water mechanisms on PEMFC degradation can be reduced or even eliminated by (a) using advanced materials for improving the electrical, chemical and mechanical stability of the cell components against deterioration, and (b) implementing effective strategies for water management in the cell