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Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha−1. Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

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Glioblastoma multiforme (GBM) presents one of the most lethal brain tumor with a dismal prognosis. And nanodrug delivery system (nano-DDS) have raised a lot of concern, while the conventional nanoformulations addressed many limitations, especially the low drug loading capacity and poor stability in vivo. Herein, we proposed PTX prodrug (PTX-SS-C) conjugate self-assembled nanoparticles (PSNPs) functionalized with Pep-1, glioma homing peptide, to overcome the blood brain tumor barrier (BBTB) via interleukin 13 receptor α2 (IL-13Rα2)-mediated endocytosis for targeting GMB. This nanocarrier was with ultrahigh drug loading capacity (56.03%) and redox-sensitivity to the up-expression of glutathione in glioma tumors. And compared with PEG-PSNPs, Pep-PSNPs could significantly enhance cellular uptake in U87MG cells via IL-13Rα2-mediated endocytosis. Enhanced cytotoxicity of Pep-PSNPs against U87MG cells and BCEC cells pretreated with glutathione monoester (GSH-OEt) confirmed that this nanosystem was sensitive to reduction environment, and there was significant difference between targeting and nontargeting groups in MTT assay. Real-time fluorescence image of intracranialU87MG glioma-bearing mice revealed that Pep-PSNPs could more efficiently accumulate at tumor site and improve the penetration. Furthermore, the ex vivo fluorescence imaging and corresponding semiquantitative results displayed that the glioma fluorescence intensity of Pep-PSNPs group was 1.74-fold higher than that of nontargeting group. Pep-PSNPs exhibited remarkable antiglioblastoma efficacy with an extended median survival time. In conclusion, Pep-PSNPs had a promising perspective as a targeting drug delivery system of PTX for glioma treatment.

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Background Cerebral infarction ranks as the second leading cause of disability and death globally, and inflammatory response of glial cells is the main cause of brain damage during cerebral infarction. Methods Studies have shown that mesenchymal stem cells (MSCs) can secrete exosomes and contribute to cerebral disease. Here, we would explore the function of MSC-derived exosome in cerebral infarction. Results Microarray indicated a decrease of miR-542-3p and an increase of Toll-Like Receptor 4 (TLR4) in middle cerebral artery occlusion (MCAO) mice comparing with sham mice. And luciferase and RIP analysis indicated a binding of miR-542-3p and TLR4. Then, we injected AAV9-miR-542-3p into paracele of sham or MCAO mice. Functional analysis showed that AAV9-miR-542-3p inhibited infarction area and the number of degenerating neurons and suppressed inflammatory factors’ expression and inflammatory cell infiltration. As well, transfection of miR-542-3p mimics into HA1800 cells underwent oxygen and glucose deprivation (OGD). Similarly, overexpression of miR-542-3p alleviated OGD induced cell apoptosis, ROS, and activation of inflammation response. Moreover, miR-542-3p could be packaged into MSCs and secreted into HA1800 cells. The extractive exosome-miR-21-3p treatment relieved MCAO- or OGD-induced cerebral injury and inflammation through targeting TLR4. Conclusion These results confirmed that MSC-derived exosome miR-542-3p prevented ischemia-induced glial cell inflammatory response via inhibiting TLR4. These results suggest possible therapeutic strategies for using exosome delivery of miR-542-3p to cure cerebral ischemic injury.