Species-specific responses to drought, salinity and their interactions in Populus euphratica and P. pruinosa seedlings

Aims Drought and salinity are severe abiotic stress factors, which limit plant growth and productivity, particularly in desert regions. In this study, we employed two desert poplars, Populus euphratica Oliver and Populus pruinosa Schrenk seedlings, to compare their tolerance to drought, salinity and combined stress. Methods We investigated species-specific responses of P. euphratica and P. pruinosa in growth, photosynthetic capacity and pigment contents, nonstructural carbohydrate concentrations, Cl- allocation, osmotic regulation and the accumulation of reactive oxygen species (ROS) under drought, salinity and the combined stress. Important Findings Populus pruinosa exhibited greater growth inhibitory effects, photosynthesis decline, stomata! closure and ROS accumulation, and lower antioxidant enzyme activities and osmotic regulation compared with P. euphratica under drought, salinity and especially under their combined stress. On the other hand, salt-stressed P. euphratica plants restricted salt transportation from roots to leaves, and allocated more Cl- to coarse roots and less to leaves, whereas salt-stressed P. pruinosa allocated more Cl- to leaves. It was shown that there is species-specific variation in these two desert poplars, and P. pruinosa suffers greater negative effects compared with P. euphratica under drought, salinity and especially under the combined stress. Therefore, in ecological restoration and afforestation efforts, species-specific responses and tolerances of these two poplar species to drought and salinity should be considered under climate change with increasing drought and soil salinity developing.Peer reviewe

Improved SnO2 Electron Transport Layers Solution-Deposited at Near Room Temperature for Rigid or Flexible Perovskite Solar Cells with High Efficiencies

Electron transport layer (ETL) is a functional layer of great significance for boosting the power conversion efficiency (PCE) of perovskite solar cells (PSCs). To date, it is still a challenge to simultaneously reduce the surface defects and improve the crystallinity in ETLs during their low-temperature processing. Here, a novel strategy for the mediation of in situ regrowth of SnO2 nanocrystal ETLs is reported: introduction of controlled trace amounts of surface absorbed water on the fluorinated tin oxide (FTO) or indium-tin oxide (ITO) surfaces of the substrates using ultraviolet ozone (UVO) pretreatment. The optimum amount of adsorbed water plays a key role in balancing the hydrolysis-condensation reactions during the structural evolution of SnO2 thin films. This new approach results in a full-coverage SnO2 ETL with a desirable morphology and crystallinity for superior optical and electrical properties, as compared to the control SnO2 ETL without the UVO pretreatment. Finally, the rigid and flexible PSC devices based on the new SnO2 ETLs yield high PCEs of up to 20.5% and 17.5%, respectively

Urbanization and air quality as major drivers of altered spatiotemporal patterns of heavy rainfall in China

Context Land use/land cover change and other human activities contribute to the changing climate on regional and global scales, including the increasing occurrence of extreme precipitation events, but the relative importance of these anthropogenic factors, as compared to climatic factors, remains unclear. Objectives The main goal of this study was to determine the relative contributions of human-induced and climatic factors to the altered spatiotemporal patterns of heavy rainfall in China during the past several decades. Methods We used daily precipitation data from 659 meteorological stations in China from 1951 to 2010, climatic factors, and anthropogenic data to identify possible causes of the observed spatiotemporal patterns of heavy rainfall in China in the past several decades, and quantify the relative contributions between climatic and human-induced factors.This research was supported by the 973 Project ‘‘National Key Research and Development Program– Global Change and Mitigation Project: Global change risk of population and economic system: mechanisms and assessments’’ under Grant No. 201531480029, Ministry of Science and Technology of China, People’s Republic of China, the National Natural Science Foundation of Innovative Research Group Project ‘‘Earth Surface Process Model and Simulation’’ under Grant No. 41621061

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively