Mesenchymal stem cells induce a weak immune response in the rat striatum after allo or xenotransplantation.

Mesenchymal stem cells (MSCs) have attracted attention for their potential use in regenerative medicine such as brain transplantation. As MSCs are considered to be hypoimmunogenic, transplanted MSCs should not trigger a strong host inflammatory response. To verify this hypothesis, we studied the brain immune response after transplantation of human or rat MSCs into the rat striatum and MSC fate at days 5, 14, 21 and 63 after transplantation. Flow cytometry analysis indicated that both MSCs express CD90 and human leucocyte antigen (MHC) class I, but no MHC class II molecules. They do not express CD45 or CD34 antigens. However, MSC phenotype varies with passage number. Human MSCs have mRNAs for interleukin (IL)-6, IL-8, IL-12, tumour necrosis factor (TNF)-alpha and TGF-beta(1), whereas rat MSCs express IL-6-, IL-10-, IL-12- and TGF-beta(1)-mRNAs. The quantification shows higher levels of mRNAs for the anti-inflammatory molecules IL-6 and TGF-beta(1) than for pro-inflammatory cytokines IL-8 and IL-12; ELISA analysis showed no IL-12 whereas TGF-beta(1) and IL-6 were detected. Transplant size did not significantly vary between 14 and 63 days after transplantation, indicating an absence of immune rejection of the grafts. Very few mast cells and moderate macrophage and microglial infiltrations, observed at day 5 remained stable until day 63 after transplantation in both rat and human MSC grafts. The observations of very few dendritic cells, T alphabeta-cells, and no T gammadelta-lymphocytes, all three being associated with Tp rejection in the brain, support the contention that MSCs are hypoimmunogenic. Our results suggest that MSCs are of great interest in regenerative medicine in a (xeno)transplantation setting.

Richardson-Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution.

Confocal laser scanning microscopy is a powerful and popular technique for 3D imaging of biological specimens. Although confocal microscopy images are much sharper than standard epifluorescence ones, they are still degraded by residual out-of-focus light and by Poisson noise due to photon-limited detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy iterative algorithm, which computes maximum likelihood estimation adapted to Poisson statistics. As this algorithm tends to amplify noise, regularization constraints based on some prior knowledge on the data have to be applied to stabilize the solution. Here, we propose to combine the Richardson-Lucy algorithm with a regularization constraint based on Total Variation, which suppresses unstable oscillations while preserving object edges. We show on simulated and real images that this constraint improves the deconvolution results as compared with the unregularized Richardson-Lucy algorithm, both visually and quantitatively.