Genome-wide analysis of blood lipid metabolites in over 5000 South Asians reveals biological insights at cardiometabolic disease loci

Background Genetic, lifestyle, and environmental factors can lead to perturbations in circulating lipid levels and increase the risk of cardiovascular and metabolic diseases. However, how changes in individual lipid species contribute to disease risk is often unclear. Moreover, little is known about the role of lipids on cardiovascular disease in Pakistan, a population historically underrepresented in cardiovascular studies. Methods We characterised the genetic architecture of the human blood lipidome in 5662 hospital controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS) and 13,814 healthy British blood donors from the INTERVAL study. We applied a candidate causal gene prioritisation tool to link the genetic variants associated with each lipid to the most likely causal genes, and Gaussian Graphical Modelling network analysis to identify and illustrate relationships between lipids and genetic loci. Results We identified 253 genetic associations with 181 lipids measured using direct infusion high-resolution mass spectrometry in PROMIS, and 502 genetic associations with 244 lipids in INTERVAL. Our analyses revealed new biological insights at genetic loci associated with cardiometabolic diseases, including novel lipid associations at the LPL, MBOAT7, LIPC, APOE-C1-C2-C4, SGPP1, and SPTLC3 loci. Conclusions Our findings, generated using a distinctive lipidomics platform in an understudied South Asian population, strengthen and expand the knowledge base of the genetic determinants of lipids and their association with cardiometabolic disease-related loci.

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid the literature, making it difficult to formulate new hypotheses to be tested in clinical settings and ultimately improve this technology platform. Here, we propose a systems biology approach, based on the combination of literature mining and mechanistic graphical modeling, to consolidate existing knowledge around mRNA vaccines mode of action and enhance the translatability of preclinical hypotheses into clinical evidence. A Natural Language Processing (NLP) pipeline for automated knowledge extraction retrieved key biological evidences that were joined into an interactive mechanistic graphical model representing the chain of immune events induced by mRNA vaccines administration. The achieved mechanistic graphical model will help the design of future experiments, foster the generation of new hypotheses and set the basis for the development of mathematical models capable of simulating and predicting the immune response to mRNA vaccines.

Direct and indirect viral associations predict coexistence in wild plant virus communities

Integration of community ecology with disease biology is viewed as a promising avenue for uncovering determinants of pathogen diversity, and for predicting disease risks. Plant-infecting viruses represent a vastly underestimated component of biodiversity with potentially important ecological and evolutionary roles. We performed hierarchal spatial analysis of wild plant populations to characterise the diversity and coexistence structure of within-host virus communities, and their predictors. Our results show that these virus communities are characterised by single infections of few, dominating virus taxa as well as diverse, non-random coinfections. Using a novel graphical modelling framework we demonstrate that after accounting for environmental heterogeneity at the level of both individual host plants and populations, most virus co-occurrence patterns can be attributed to virus-virus associations. Moreover, we show that conditioning variables changed virus association networks especially through their indirect effects. This highlights a previously underestimated mechanism of how human-driven environmental change can influence disease risks.

Four waves of digitalisation of the economic system in the EU countries and Ukraine

The digitalisation of the economic system of the EU countries is taking place in stages corresponding to certain "waves". Each wave of digitalisation represents, on the one hand, the accumulation of technological changes (for example, the spread of electronic operations, automated product management systems and the creation of electronic enterprises). And on the other hand, the transformation of industrial and socio-economic relations in society (digital socialisation and institutionalisation, the establishment of the information society). The emergence of a separate wave of digitalisation of the economy begins only as a result of the implementation of the relevant prerequisites, but in the same two planes: technological and socio-economic. At the same time, each previous wave of digitalisation creates the necessary material and socio-economic foundation for the transition to a new level of digitalisation of the economic system. The purpose of this study is to identify the relevant stages of digitalisation of the economic system in the EU based on the generalisation and systematisation of technological changes. The basis of this study is a formational and technocratic approach, based on a systematic analysis of the national economy as a complex entity, the elements of which are subject to permanent and differentiated digitisation. The analysis is based on the principle of dialectical unity of transformation of system components. Disclosure of systems analysis is due to the use of auxiliary methods, namely: graphical modelling, dynamics method, equilibrium and boundary analysis, deduction and induction, analysis and synthesis. The scientific novelty of the study is conditioned by the fact that the authors proposed a graphical model of the impact of digitalisation on the production sphere, as well as the impact of digitalisation on the distributive services with the allocation of the point of social optimum. The preconditions and characteristic features of each stage of digitalisation of the economic system in the EU countries are determined. The need to create a single information space for the integration of automated management system (AMS) into enterprise (for example, CALS) has been proved. The findings of the study can be used by: public administration bodies to determine the social optimum level of digitalisation, as well as to develop a protection policy to promote digitalisation in the economic system of the country; enterprises to select CALS-compliant business automation systems.

Graphical Modelling of Hoop Force Distribution for Equilibrium Analysis of Masonry Domes

The behaviour of axisymmetric masonry shells can be simulated by a system of forces constituted by meridian forces acting in the vertical planes, and by hoop forces acting circumferentially. A crucial component for the assessment of these structures using the Modified Thrust Line Method (MTLM) is the determination of hoop forces, whose computation is strenuous, limiting the practical application of MTLM. Working around this limitation, the current research introduces a strategy to manipulate the hoop forces by graphically implementing a function describing their distribution. The adaptiveness of this distribution function not only allows the application of MTLM for the analysis of a range of geometries, but also enables the simulation of membrane behaviour, arch behaviour and their combination, for considering partially cracked structures. Taking this into account, the approach is applied in the case studies illustrated within the current research.

Computational Modelling and Prediction of Consequences in Case of Accidental Releases of Hazardous Substances in an Industrial Plant

Storing relatively large amounts of hazardous materials under certain conditions can lead to high-risk situations. In industrial units, the assessment of the amplitude and severity of the consequences of the identified major accidents is done in order to provide data on site intervention and emergency planning. This study aims to assess the consequences of untimely releases of hazardous explosive / toxic substances in an industrial unit by graphical modelling and analysis of such accident scenarios using specialized software tools. The main activity of the industrial unit under study consists in the manufacture, processing and marketing of essential oils and their derived products.