RESUMEN
Mesenchymal stem cell (MSC) therapy has become a promising treatment for liver fibrosis due to its predominant immunomodulatory performance in hepatic stellate cell inhibition and fibrosis resolution. However, the cellular and molecular mechanisms underlying these processes remain limited. In the present study, we provide insights into the functional role of bone marrow-derived MSCs (BM-MSCs) in alleviating liver fibrosis by targeting intrahepatic Ly6Chi and Ly6Clo macrophage subsets in a mouse model. Upon chronic injury, the Ly6Chi subset was significantly increased in the inflamed liver. Transplantation of BM-MSCs markedly promoted a phenotypic switch from pro-fibrotic Ly6Chi subset to restorative Ly6Clo subpopulation by secreting paracrine cytokines IL-4 and IL-10 from the BM-MSCs. The Ly6Chi/Ly6Clo subset switch significantly blocked the source of fibrogenic TGF-ß, PDGF, TNF-α, and IL-1ß cytokines from Ly6Chi macrophages. Unexpectedly, BM-MSCs experienced severe apoptosis and produced substantial apoptotic bodies in the fibrotic liver during the 72 h period of transplantation. Most apoptotic bodies were engulfed by Ly6Clo macrophages, and this engulfment robustly triggered MMP12 expression for fibrosis resolution through the PtdSer-MerTK-ERK signaling pathway. This paper is the first to show previously unrecognized dual regulatory functions of BM-MSCs in attenuating hepatic fibrosis by promoting Ly6Chi/Ly6Clo subset conversion and Ly6Clo macrophage restoration through secreting antifibrogenic-cytokines and activating the apoptotic pathway.
RESUMEN
Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. In this study, we integrate the data of HJ-1 CCD and Landsat-8 operational land imager (OLI) by using the ordinary least-squares (OLS), and construct higher temporal resolution vegetation indices (VIs) time-series data to extract the phenological parameters of single-cropped rice. Two widely used VIs, namely the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2), were adopted to minimize the influence of environmental factors and the intrinsic difference between the two sensors. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. The results showed that, compared with NDVI, EVI2 was more stable and comparable between the two sensors. Compared with the observed phenological data of the single-cropped rice, the integrated VI time-series had a relatively low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available.