Digital mapping of soil salinization based on Sentinel-1 and Sentinel-2 data combined with machine learning algorithms

Soil salinization is one of the most important causes of land degradation and desertification,especially in arid and semi-arid areas.The dynamic monitoring of soil salinization is of great significance to land management,agricultural activities,water quality,and sustainable development.The remote sensing images taken by the synthetic aperture radar(SAR)Sentinel-1 and the multispectral satellite Sentinel-2 with high resolution and short revisit period have the potential to monitor the spatial distribution of soil attribute information on a large area;however,there are limited studies on the combination of Sentinel-1 and Sentinel-2 for digital mapping of soil salinization.Therefore,in this study,we used topography indices derived from digital elevation model(DEM),SAR indices generated by Sentinel-1,and vegetation indices generated by Sentinel-2 to map soil salinization in the Ogan-Kuqa River Oasis located in the central and northern Tarim Basin in Xinjiang of China,and evaluated the potential of multi-source sensors to predict soil salinity.Using the soil electrical conductivity(EC)values of 70 ground sampling sites as the target variable and the optimal environmental factors as the predictive variable,we constructed three soil salinity inversion models based on classification and regression tree(CART),random forest(RF),and extreme gradient boosting(XGBoost).Then,we evaluated the prediction ability of different models through the five-fold cross validation.The prediction accuracy of XGBoost model is better than those of CART and RF,and soil salinity predicted by the three models has similar spatial distribution characteristics.Compared with the combination of topography indices and vegetation indices,the addition of SAR indices effectively improves the prediction accuracy of the model.In general,the method of soil salinity prediction based on multi-source sensor combination is better than that based on a single sensor.In addition,SAR indices,vegetation indices,and topography indices are all effective variables for soil salinity prediction.Weighted Difference Vegetation Index(WDVI)is designated as the most important variable in these variables,followed by DEM.The results showed that the high-resolution radar Sentinel-1 and multispectral Sentinel-2 have the potential to develop soil salinity prediction model.

Hippocampal and thalamic neuronal metabolism in a putative rat model of schizophrenia°

The transcription factor early growth response protein 3 （EGR3） is involved in schizophrenia. We developed a putative rat model of schizophrenia by transfecting lentiviral particles carrying the Egr3 gene into bilateral hippocampal dentate gyrus. We assessed spatial working memory using the Morris water maze test, and neuronal metabolite levels in bilateral hippocampus and thalamus were determined by 3.0 T proton magnetic resonance spectroscopy. Choline content was significantly greater in the hippocampus after transfection, while N-acetylaspartate and the ratio of N-acetylaspartate to creatine/phosphocreatine in the thalamus were lower than in controls. This study is the first to report evaluation of brain metabolites using 3,0 T proton magnetic resonance spectroscopy in rats transfected with Egr3, and reveals metabolic abnormalities in the hippocampus and thalamus in this putative model of schizophrenia.

Engineering of electrospun nanofiber scaffolds for repairing brain injury

Patients with brain injury can suffer disability and accompanying complications.Current clinical treatments have significant limitations to successful repair due to the complexity of the pathological processes and the inhibitory microenvironment that follows brain injury.Here,we conclude recent research progresses in engineering strate-gies based on electrospun nanofibers for promoting neural repair and functional recovery after brain injury.Firstly,we introduce the main pathological mechanisms of current brain injuries,pointing out the prospect of the application of electrospun nanofiber scaffolds compared to current clinical treatment strategies.We then discuss the repair strategies combining the structure and the morphology of nanofiber scaffolds with load therapeutic factors such as cells,drugs and growth factors.All of these strategies show potential for improving the repair of brain injury.Finally,we point out the challenges facing the effective treatment of brain injury,aiming to provide insights into the development of repairing scaffolds for brain function recovery from the perspective of clinical treatment.

Let there be light： a bright future for Ca2＋ signaling

Calcium ion(Ca^(2+))is a ubiquitous second messenger in eukaryotic cells.In response to electrical,hormonal,or mechanical stimulation,cytosolic Ca^(2+)levels increase due to Ca^(2+) influxes through ion channels embedded in the plasma membrane or Ca^(2+) releases from intracellular Ca^(2+) stores,such as the endoplasmic

Gambogic acid-encapsulated polymeric micelles improved therapeutic effects on pancreatic cancer

Gambogic acid(GA) is a natural product with potent anticancer activity in vitro. However, poor water solubility and systematic toxicity limit the further clinical application of GA. Micellization of hydrophobic molecule could effectively ameliorate aqueous dispersity of GA and induce better blood retention and tumor accumulation, hence lead to improved stability and therapeutic effect of GA. In this study, monomethyl poly(ethylene glycol)-poly(ε-caprolactone)-poly(trimethylene carbonate)(MPEG-P(CL-ran-TMC)) was used to encapsulate GA by a single-step solid dispersion method to form a GA encapsulated MPEG-P(CLran-TMC) micelles(GA micelles). GA micelles were characterized with a small particle size(44 ±1 nm),high drug loading content(26.28% ± 0.12%) and high-efficiency encapsulation(87.59% ± 0.41 %). Compared with free GA, GA micelles showed better dispersion in water, prolonged release behavior in vitro, and enhanced tumor cellular uptake. GA micelles could also effectively induce apoptosis in AsPC-1 cells.Compared with free GA, GA micelles exhibited superior antitumor efficacy and better apoptosis induced effect in a subcutaneous xenograft mouse model of AsPC-1 cells. In conclusion, GA micelles which showed high-efficiency anti-tumor effect in vitro and in vivo may serve as a candidate for pancreatic cancer therapy.