[Transferability of Hyperspectral Model for Estimating Soil Organic Matter Concerned with Soil Moisture].

Hyperspectral remote sensing, known as the state-of-the-art technology in the field of remote sensing, can be used to retrieve physical and chemical properties of surface objects based on the interactions between electromagnetic waves and the objects. Soil organic matter (SOM) is one of the most important parameters used in the assessment of soil fertility. Quick estimation of SOM with hyperspectral remote sensing technique can provide essential soil data to support the development of precision agriculture. The presence of external parameters, however, may affect the modeling precision, and further handicap the transfer ability of existing model. With the aim to study the effects of soil moisture on the Vis/NIR estimation of soil organic matter, and the capacity of direct standardization(DS)algorithm in the calibration transfer, 95 soil samples collected in the Jianghan plain were rewetted and air-dried. Reflectance of these samples at 13 moisture levels was measured. Results show that the model calibrated using air-dried samples has the highest prediction accuracy. This model, however, was not suitable for SOM prediction of the rewetted samples. Prediction bias and RPD improved from -8.34-3.32 g x kg(-1) and 0.64-2.04 to 0 and 7.01, when DS algorithm was applied to the spectra of the rewetted samples. DS algorithm has been proven to be effective in removing the effects of soil moisture on the Vis/NIR estimation of SOM, ensuring a transferrable model for SOM prediction with soil samples at different moisture levels.

[Spatial interpolation model of soil organic carbon density considering land-use and spatial heterogeneity.] / 综合土地利用及空间异质性的土壤有机碳空间插值模型.

Soil organic carbon pool is an important component of terrestrial carbon pool. Soil organic carbon pool and its dynamic change have important influence on carbon cycle in terrestrial ecosystem. Soil organic carbon density (SOCD) is an important parameter of soil carbon storage, and it is also an important index to evaluate farmland soil quality. Accurate prediction of regional organic carbon density spatial distribution is of great significance to the development of precision agriculture. A total of 242 farmland soil samples collected from the Jianghan Plain were used to explore the effects of land use types on the spatial distribution of SOCD in plain areas. Moreover, in the presence of spatial heterogeneity and spatial outliers of SOCD, three Kriging approaches combining land use types were used for the spatial prediction of SOCD. They were dummy variable regression Kriging (DV_RK), mean centering ordinary Kriging (MC_OK1) and median centering ordinary Kriging (MC_OK2). Results showed that the difference of land use types between paddy field and irrigable land was one of the reasons for the spatial heterogeneity of SOCD in the study area, resulting in spatial non-stationary characteristics of SOCD and lowering the performance of OK. DV_RK, MC_OK1 and MC_OK2, however, eliminating the impacts of SOCD spatialheterogeneity caused by land use types while modeling, enhancing the model stability. Therefore, the prediction accuracy of these three models was higher than that of ordinary Kriging (OK). Moreover, MC_OK2 outperformed the others in terms of model reliability, prediction accuracy and the ability to explain the total variance of SOCD. In summary, as an easily accessed auxiliary variable, land use type could effectively decrease the effects of spatial heterogeneity and spatial outliers on SOCD spatial interpolation model, improving the prediction performance and reducing the model uncertainty. SOCD map with higher quality could also be achieved to help reveal the spatial characteristics of SOCD for guiding the agricultural production.

SCD1 negatively regulates autophagy-induced cell death in human hepatocellular carcinoma through inactivation of the AMPK signaling pathway.

Stearoyl-CoA desaturase 1 (SCD1) is a key regulator in the mechanisms of cell proliferation, survival and transformation to cancer, and autophagy also plays a critical role in hepatocellular carcinoma (HCC). However, whether SCD1 mediates autophagy in HCC remains unknown. In this study, we observed significantly elevated SCD1 expression levels and evident suppression of autophagy in HCC, and the positive SCD1 expression and autophagy defect were independently correlated with poor prognosis of HCC patients. We also found that the inhibition of SCD1 by a pharmacological inhibitor reduced cell viability and induced apoptosis and autophagy of human HCC cells in a dose- and time-dependent manner. Moreover, the pharmacological inhibition of AMPK supported the hypothesis that the induction of autophagy caused by SCD1 inhibition relied on AMPK stimulation. Furthermore, the human HCC cells death triggered by inhibition of SCD1 was partly involved in autophagy-induced apoptosis via AMPK signaling. Our findings reveal a novel role for SCD1 in the regulation of autophagy via AMPK signaling and provide mechanistic input for the clinical exploration that the combination of SCD1 inhibition with autophagy induction may be attractive for the management of HCC.