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Additional file 1: Genealogical trees of to the 6 consanguineous MMA probands.

Additional file 5: Quantitative PCR results comparing relative expression of NOS3 mRNA in cells transfected with the wild type and with the M035 mutated cDNA.

Additional file 2: 3D structural analysis of the functional consequences of the eNOS p.C648R variant and sGC alpha1 subunit p.R593H variant.

Additional file 3: Candidate homozygous variants identified in the 6 consanguineous probands.

Additional file 4: NOS3 homozygous splice variant in M084 and NOS3 homozygous missense variant in M035.

Additional file 5. Supplementary figure 5. (A) Representative macroscopic images (left panels) of a mouse dorsal chamber without (superior panel) and with ischemia (inferior panel) at day 5 and day 29 post-injection of hPSC-ECs. Right panels show the corresponding treated images used for quantification of the area occupied by blood vessels. (B) Representative confocal image at day 19 post-injection of a mouse dorsal skinfold chamber with ischemia, injected with mcherry-hPSC-ECs (red, white arrows). Vessel perfusion was observed thanks to the injection of dextran 70 kDa-FITC (green). Scale bar: 200 μm.

Additional file 13. Supplementary table 4. Oligonucleotides used in qPCR for the detection of human DNA.

Additional file 3. Supplementary figure 3. Arterial and vein differentiation of hPSC-ECs. (A) Differentiation scheme of hPSC-EB-CD144+ into hPSC-ECs in the presence or absence of DAPT and representative phase-contrast microscopy images after differentiation. Scale Bar 500 μm. Flow cytometry analysis of the endothelial phenotype of hPSC-ECs in the presence and absence of DAPT. (B) Confocal immunofluorescent image of Matrigel networks formed by hPSC-ECs. CD31 in green and DAPI in blue. Scale Bar: 100 μm.

Additional file 8. Supplementary figure 8. Counting of differential transcripts between undifferentiated hESCs, differentiated hESCs and EL cell populations. P

Additional file 4. Supplementary figure 4. (A) Representative histograms of the flow cytometry analysis of eNOS expression in hPSC-ECs and ECFC (B) Representative histograms of the flow cytometry analysis of the probe DAF-FM for NO detection in hPSC-EC and ECFC in the presence and absence of LPS and SNAP.

Additional file 6. Supplementary figure 6. Representative flow cytometry histograms and dot plots of hPSC-BCs from A29 (top), SA01 (center) and H1 (below) cell lines for the expression of hematoendothelial (CD309, CD143 and CD34), endothelial (CD144 and CD31) and hematopoietic markers (CD43, CD45 and CD41) as (A) simple and (B) double labeling.

Additional file 7. Supplementary figure 7. Relative mRNA expression of the hemoglobin subunit epsilon-1 (HBE1), gamma-1 (HBG1) and beta-1 (HBB1) in the BFU-E and CFU-GEMM derived from every hPSC-cell line compared to mRNAs from human embryonic liver.

Additional file 9. Supplementary figure 9. (A) Heatmap depicting mean level expression of POU5F1, NANOG, KDR, CDH5, CD34, SPN, ITGA2B and PTPRC genes in undifferentiated hPSC (H1 cell line), in hPSC-EB-CD144+, hPSC-BCs and hPSC-BC-CD144+CD45+ and hPSC-ECs derived populations obtained by gene microarray analysis (GeneChip® HumanGene 2.0 ST; Affymetrix). Mean level expression of selected genes are also visualizing in CD144+CD45-CD34+ EL-EC, CD144+CD45lowCD34+ EL-pre-HSC, CD144-CD45lowCD34+ EL-HSC/HP and CD144-CD45highCD34-EL-mature HC EL cell subpopulations for comparison. Heatmap revealed the loss of pluripotency during hPSC-EB-CD144+ formation and subsequent hPSC- BCs and hPSC-ECs derivation and distinct endothelial and hematopoietic signatures in hPSC-EB-CD144+, hPSCBCs, hPSC-BC-CD144+CD45+ and hPSC-ECs derived populations. (B) Heatmap depicting mean level expression of embryonic HBE1 (Hemoglobin ε), fetal HBG1 (Hemoglobin γ), and adult HBB (hemoglobin β) genes in undifferentiated hPSC (H1 cell line), in hPSC-EB-CD144+, hPSC-BCs and hPSC-BC-CD144+CD45+ and hPSC-ECs derived populations obtained by gene microarray analysis (GeneChip® HumanGene 2.0 ST; Affymetrix). Mean level expression of selected genes are also visualizing in CD144+CD45lowCD34+ EL-pre-HSC, CD144-CD45lowCD34+ EL-HSCs/HPs and CD144-CD45highCD34- EL-mature HCs EL cell subpopulations for comparison. Heatmap revealed that hPSC-BCs, hPSC-BC-CD144+CD45+ contained principally embryonic erythrocytes and to lesser extent definitive erythrocytes. Undifferentiated hESC (H1) , hESC-derived cell populations (n=3) and EL cell populations (n=4) After normalization, for each cell population, a Tukey's Biweight Robust Mean is calculated from log2 expression values. For each gene analyzed the most highly expressed transcript, is in red, the lowest level expressed transcript is in green. ID, Identifiant Affymetrix; Undiff, undifferentiated.

Additional file 2. Supplementary figure 2. (A) Representative phase-contrast images of hPSC-derived endothelial cells (hPSC-ECs) from passage (p) 1 to 5 derived from H1-CD144+-EBs. Scale bar 500 μm. (B) Representative flow cytometry histograms of hPSC-ECs from A29 (top), SA01 (center) and H1 (below) cell lines at p1 and p3 for the expression of hematoendothelial (CD309, CD143 and CD34), endothelial (CD144 and CD31) and hematopoietic markers (CD43, CD45 and CD41).

International audience; Due to the current lack of innovative and effective therapeutic approaches, tissue engineering (TE) has attracted much attention during the last decades providing new hopes for the treatment of several degenerative disorders. Tissue engineering is a complex procedure, which includes processes of decellularization and recellularization of biological tissues or functionalization of artificial scaffolds by active cells. In this review, we have first discussed those conventional steps, which have led to great advancements during the last several years. Moreover, we have paid special attention to the new methods of post-decellularization that can significantly ameliorate the efficiency of decellularized cartilage extracellular matrix (ECM) for the treatment of osteoarthritis (OA). We propose a series of post-decellularization procedures to overcome the current shortcomings such as low mechanical strength and poor bioactivity to improve decellularized ECM scaffold towards much more efficient and higher integration.

International audience; Graft versus host disease (GVHD) is one of the main causes of mortality and the reason for up to 50% of morbidity after hematopoietic stem cell transplantations (HSCT) which is the treatment of choice for many blood malignancies. Thanks to years of research and exploration, we have acquired a profound understanding of the pathophysiology and immunopathology of these disorders. This led to the proposition and development of many therapeutic approaches during the last decades, some of them with very promising results. In this review, we have focused on the recent GVHD treatments from classical chemical and pharmacological prophylaxis to more innovative treatments including gene therapy and cell therapy, most commonly based on the application of a variety of immunomodulatory cells. Furthermore, we have discussed the advantages and potentials of cell-free therapy as a newly emerging approach to treat GVHD. Among them, we have particularly focused on the implication of the TNFα-TNFR2 axis as a new immune checkpoint signaling pathway controlling different aspects of many immunoregulatory cells.