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Additional file 1: Supplementary Figure 1. Gating strategies used to analyze leucocyte subsets in aorta and blood samples. (A-F) A representative analysis of total leucocytes, granulocytes, monocyte/macrophages, total T cells, CD4+ and CD8+ T cells in aorta is shown. Cells were first identified based on their size and granularity (A, FSC versus SSC) and then total leucocytes were identified on the expression of the pan-leucocyte marker, CD45 (B). Then, viable CD45+ cells were selected using the Fixable Viability Dye eFluor 780 (FvD) (C). In these viable CD45+ cells, monocytes/macrophages and neutrophils were distinguished based on the expression of CD11b/c and granulocytes (RP-1 antigen) (E). T cells were identified in viable CD45+ cells by the expression of CD3 (D). In these viable CD3+ T cells, CD4+ and CD8+ T cells were distinguished based on the expression of CD4 and CD8, respectively (F). (G-J) A representative analysis of IL-17-producing T cells in aorta is shown. Cells were first identified based on their size and granularity (FSC versus SSC), their viability (FvD low) and the expression of CD45. Then, Th17 cells were identified by the expression of CD3 and CD4 (G) and intracellular expression of IL-17A (H), while Tc17 were identified by the expression of CD3 and CD8 (I) and intracellular expression of IL-17A (J). (K-R) A representative analysis of circulating total leucocytes, myeloid cells, total T cells, CD4+ and CD8+ T cells is shown. Cells were first identified based on their size and granularity (K, FSC versus SSC). This gate allows us to identify microbeads that were quantified in L. Total leucocytes were identified on the expression of the pan-leucocyte marker, CD45 (M). In these CD45+ cells, myeloid cells (monocytes/macrophages and neutrophils) were distinguished based on the expression of CD11b/c expression (O). T cells were identified in CD45+ cells by the expression of CD3 (N). In these CD3+ T cells, CD4+ and CD8+ T cells were distinguished based on the expression of CD4 and CD8, respectively (P). (Q-R) A representative analysis of circulating IL-17-producing T cells is shown. Cells were first identified based on their size and granularity (FSC versus SSC), their viability (FvD low) and the expression of CD45. In these viable CD3+ T cells, CD4+ and CD8+ T cells were distinguished based on the expression of CD4 and CD8, respectively. Then, Tc17 were identified by the expression of CD8 and intracellular expression of IL-17A (Q), while Th17 cells were identified by the expression of CD4 and intracellular expression of IL-17A (R).

National audience; This paper presents a comparison in terms of accuracy and efficiency between two fully nonlinear potential flow solvers for the solution of gravity wave propagation. One model is based on the high-order spectral (HOS) method, whereas the second model is the high-order finite difference model OceanWave3D. Although both models solve the nonlinear potential flow problem, they make use of two different approaches. The HOS model uses a modal expansion in the vertical direction to collapse the numerical solution to the two-dimensional horizontal plane. On the other hand, the finite difference model simply directly solves the three-dimensional problem. Both models have been well validated on standard test cases and shown to exhibit attractive convergence properties and an optimal scaling of the computational effort with increasing problem size. These two models are compared for solution of a typical problem: propagation of highly nonlinear periodic waves on a finite constant-depth domain. The HOS model is found to be more efficient than OceanWave3D with a difference dependent on the level of accuracy needed as well as the wave steepness. Also, the higher the order of the finite difference schemes used in OceanWave3D, the closer the results come to the HOS model.

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