The adjoint mehod for automotive optimisation using a sphericity based morpher

A robust workflow for shape optimisation of internal and external flows with application to automotive design is demonstrated in this paper. A gradient based approach is presented, in which the surface sensitivity with respect to the flow variables is computed with the continuous adjoint method. For aerodynamic shape optimisation cases, mesh displacement algorithms are indispensable in order to avoid re-meshing the updated geometry in each optimisation step. Keeping the same mesh topology at every optimisation cycle secures gradient consistency and the possibility to use the previous solution as initial conditions in order to converge the CFD equations faster. Simple mesh displacement algorithms, such as the spring analogy, run into problems under complex surface deformations. Thus a mesh optimisation approach can be proved to be more robust as it copes better with complex elements optimising also the base mesh. In this paper the mesh displacement algorithm is based on sphericity, which quantifies the mesh quality. Solving an extra optimisation problem for the maximisation of the sphericity value, results in the new internal mesh nodes positions. The methodology is heuristic in nature in that it does not consider known numerical quality metrics explicitly. It has shown however to be exceptionally robust and effective allowing the maintenance of high cell quality even during extreme deformation events. The suggested method is applied to automotive test cases of internal and external aerodynamics. In such cases, the use of a robust morpher which preserves geometry features and delays mesh quality deterioration is found to be crucial

The Values of Tangible User Interfaces: How to discover, assess and evaluate them?

Since the introduction of Tangible User Interfaces, in the beginning of the 90s, a generation grew up interacting with computers. At the same time the context of computing changed dramatically: from a device used almost exclusively by specialists, it evolved to a general device that plays a dominant role in our societies. But where does this leave TUI? In many respects, the idea of tangibility plays a marginal role in Human Computer Interaction. It makes sense to re-evaluate the intrinsic values of TUI design. This paper proposes to research the appropriate metrics to do so

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1 + profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas. </p

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2(+)TMPRSS2(+) cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

BACKGROUND: The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS: In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS: Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS: Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity

Cannabinoid receptor 2 modulates neutrophil recruitment in a murine model of endotoxemia.

The endocannabinoid system consists of endogenous lipid mediators and cannabinoid receptors (CB) 1 and 2. It has previously been demonstrated that activation of the leukocyte-expressed CB2 has anti-inflammatory effects in vivo. Here, we report its role under baseline conditions and in a model of low-dose endotoxemia by comparing CB2 knockout to littermate control mice. CB2-deficient mice displayed significantly more neutrophils and fewer monocytes in the bone marrow under steady state. In initial validation experiments, administration of 1 mg/kg LPS to male C57BL/6J mice was shown to transiently upregulate systemic proinflammatory mediators (peaked at 2 hours) and mobilise bone marrow neutrophils and monocytes into circulation. In CB2 knockout mice, the level of the metalloproteinase MMP-9 was significantly elevated by 2 hours and we also observed augmented recruitment of neutrophils to the spleen in addition to increased levels of Ccl2, Ccl3, Cxcl10, and Il6. Collectively, our data show that the absence of CB2 receptor increases the levels of innate immune cell populations in the bone marrow under steady state. Furthermore, during an acute systemic inflammatory insult, we observe a highly reproducible and site-specific increase in neutrophil recruitment and proinflammatory chemokine expression in the spleen of CB2 knockout mice