CRISPR knockout rat cytochrome P450 3A1/2 model for advancing drug metabolism and pharmacokinetics research

Cytochrome P450 (CYP) 3A accounts for nearly 30% of the total CYP enzymes in the human liver and participates in the metabolism of over 50% of clinical drugs. Moreover, CYP3A plays an important role in chemical metabolism, toxicity, and carcinogenicity. New animal models are needed to investigate CYP3A functions, especially for drug metabolism. In this report, Cyp3a1/2 double knockout (KO) rats were generated by CRISPR-Cas9 technology, and then were characterized for viability and physiological status. The Cyp3a1/2 double KO rats were viable and fertile, and had no obvious physiological abnormities. Compared with the wild-type (WT) rat, Cyp3a1/2 expression was completely absent in the liver of the KO rat. In vitro and in vivo metabolic studies of the CYP3A1/2 substrates indicated that CYP3A1/2 was functionally inactive in double KO rats. The Cyp3a1/2 double KO rat model was successfully generated and characterized. The Cyp3a1/2 KO rats are a novel rodent animal model that will be a powerful tool for the study of the physiological and pharmacological roles of CYP3A, especially in drug and chemical metabolism in vivo

Transonic flow calculation of Euler equations by implicit iterating scheme with flux splitting

Three-dimensional Euler equations are solved in the finite volume form with Van Leer's flux vector splitting scheme. The block matrix is inverted by Gauss-Seidel iteration in the two-dimensional plane while strongly implicit alternating sweeping is implemented in the direction of the third dimension. Very rapid convergence rate is obtained with a CFL number reaching the order of 100. The memory resources can be greatly saved too. (Author

Sensor Network Disposition Facing the Task of Multisensor Cross Cueing

In order to build the sensor network facing the task of multisensor crossing cueing, the requirements of initiating cueing and being cued are analyzed. Probability theory is used when building models, then probability of sensor cueing in the case of target moving is given, and, after that, the best distance between two sensors is calculated. The operational environment is described by normal distribution function. In the process of distributing sensor network, their elements, operational environment demand of cueing, and the probability of sensor network coverage are considered; then the optimization algorithm of sensor network based on hypothesis testing theory is made. The simulation result indicates that the algorithm can make sensor network which is required. On the basis of that, the two cases, including targets that make linear motion and orbit motion, are used to test the performance of the sensor network, which show that the sensor network can make uninterrupted detection on targets through multisensor cross cuing

Two-dimensional monitoring of soil water content in fields with plastic mulching using electrical resistivity tomography

Plastic mulching (PM) has become an important agricultural practice to improve crop yields worldwide, while there is still a lack of methods to quantify the complex spatial variations of soil water content (SWC) in the PM field. In this study, a methodology for using Electrical Resistivity Tomography (ERT) to get SWC information in the PM field was presented. Its performance in monitoring SWC was validated, and the spatial variation of SWC was analyzed using the ERT results. A simplified Waxman and Smits model was selected to calibrate the pedo-physical relationship, and it showed good performance (coefficient of determination > 0.92). With the calibrated model, the SWC obtained using ERT showed good agreement with soil moisture sensors in different soil layers (RMSE < 0.027 cm3 cm−3). The ERT results showed that rainfall and drying events have different effects on SWC at different growing stages. At the early stage, rainfall and drying events mainly influenced SWC on the bare strip, while at the later stage, rainfall and drying events had more obvious effects on the zone near the planting hole. On a seasonal scale, a higher SWC was not only found in the middle part of the mulched strip, but also in the bare strip, while a lower SWC was found in positions near the planting hole. At the same time, a high-resolution ERT measurement revealed that the SWC was also largely influenced by the soil heterogeneity. As such, SWC in the mulched strip was not necessarily higher than in the bare strip as we had supposed, but showed a high degree of irregularity in two dimensions. Considering the irregularity of SWC in two dimensions, our study calls for replacing point-scale measurement with two-dimensional monitoring methods when acquiring SWC information in a field with PM

Warmer and Wetter Soil Stimulates Assimilation More than Respiration in Rainfed Agricultural Ecosystem on the China Loess Plateau: The Role of Partial Plastic Film Mulching Tillage.

Effects of agricultural practices on ecosystem carbon storage have acquired widespread concern due to its alleviation of rising atmospheric CO2 concentrations. Recently, combining of furrow-ridge with plastic film mulching in spring maize ecosystem was widely applied to boost crop water productivity in the semiarid regions of China. However, there is still limited information about the potentials for increased ecosystem carbon storage of this tillage method. The objective of this study was to quantify and contrast net carbon dioxide exchange, biomass accumulation and carbon budgets of maize (Zea maize L.) fields under the traditional non-mulching with flat tillage (CK) and partial plastic film mulching with furrow-ridge tillage (MFR) on the China Loess Plateau. Half-hourly net ecosystem CO2 exchange (NEE) of both treatments were synchronously measured with two eddy covariance systems during the growing seasons of 2011 through 2013. At same time green leaf area index (GLAI) and biomass were also measured biweekly. Compared with CK, the warmer and wetter (+1.3°C and +4.3%) top soil at MFR accelerated the rates of biomass accumulation, promoted greater green leaf area and thus shortened the growing seasons by an average value of 10.4 days for three years. MFR stimulated assimilation more than respiration during whole growing season, resulting in a higher carbon sequestration in terms of NEE of -79 gC/m2 than CK. However, after considering carbon in harvested grain (or aboveground biomass), there is a slight higher carbon sink (or a stronger carbon source) in MFR due to its greater difference of aboveground biomass than that of grain between both treatments. These results demonstrate that partial plastic film mulched furrow-ridge tillage with aboveground biomass exclusive of grain returned to the soil is an effective way to enhance simultaneously carbon sequestration and grain yield of maize in the semiarid regions

Genetic Algorithm-Optimized Extreme Learning Machine Model for Estimating Daily Reference Evapotranspiration in Southwest China

Reference evapotranspiration (ET0) is an essential component in hydrological and ecological processes. The Penman–Monteith (PM) model of Food and Agriculture Organization of the United Nations (FAO) model requires a number of meteorological parameters; it is urgent to develop high-precision and computationally efficient ET0 models with fewer parameter inputs. This study proposed the genetic algorithm (GA) to optimize extreme learning machine (ELM), and evaluated the performances of ELM, GA-ELM, and empirical models for estimating daily ET0 in Southwest China. Daily meteorological data including maximum temperature (Tmax), minimum temperature (Tmin), wind speed (u2), relative humidity (RH), net radiation (Rn), and global solar radiation (Rs) during 1992–2016 from meteorological stations were used for model training and testing. The results from the FAO-56 Penman–Monteith formula were used as a control group. The results showed that GA-ELM models (with R2 ranging 0.71–0.99, RMSE ranging 0.036–0.77 mm·d−1) outperformed the standalone ELM models (with R2 ranging 0.716–0.99, RMSE ranging 0.08–0.77 mm·d−1) during training and testing, both of which were superior to empirical models (with R2 ranging 0.36–0.91, RMSE ranging 0.69–2.64 mm·d−1). ET0 prediction accuracy varies with different input combination models. The machine learning models using Tmax, Tmin, u2, RH, and Rn/Rs (GA-ELM5/GA-ELM4 and ELM5/ELM4) obtained the best ET0 estimates, with R2 ranging 0.98–0.99, RMSE ranging 0.03–0.21 mm·d−1, followed by models with Tmax, Tmin, and Rn/Rs (GA-ELM3/GA-ELM2 and ELM3/ELM2) as inputs. The machine learning models involved with Rn outperformed those with Rs when the quantity of input parameters was the same. Overall, GA-ELM5 (Tmax, Tmin, u2, RH and Rn as inputs) outperformed the other models during training and testing, and was thus recommended for daily ET0 estimation. With the estimation accuracy, computational costs, and availability of input parameters accounted, GA-ELM2 (Tmax, Tmin, and Rs as inputs) was determined to be the most effective model for estimating daily ET0 with limited meteorological data in Southwest China

Deficit drip irrigation improves kiwifruit quality and water productivity under rain-shelter cultivation in the humid area of South China

Comprehending crop responses to water deficit at different growth stages is crucial for developing effective irrigation strategies. Different water deficit treatments (WDTs) were applied to the kiwifruit vines to investigate the effect of water deficit during different growth stages on the fruit quality, yield, and water productivity (WP); subsequently, the technique for order preference by similarity to an ideal solution method (TOPSIS) was employed to determine optimal treatments for kiwifruit cultivation. A total of 17 irrigation treatments were applied, including one control treatment (CTL, full irrigation) and four WDTs (denoted as D15%, D25%, D35%, and D45% respectively) during the bud burst to leafing (I), flowering to fruit set (II), fruit expansion (III), and fruit maturation (IV) stages. Results showed that WDTs during I, II, III, and IV decreased evapotranspiration (ET) over the whole growth period of kiwifruit vines by 1.2–3.8, 1.5–4.4, 4.7–14.3, and 6.9–21.3% compared with CTL, respectively. WDTs during stages I and II increased fruit volume (Vf) and fruit weight (FW), while exhibiting no significant impact on yield, WP, and chemical quality of kiwifruit. WDTs during stage III improved fruit firmness (Fn), total soluble solids (TSS), and titratable acidity (TA); however, it also caused severe reduction in Vf, FW, yield, and WP. Appropriate WDTs during stage IV significantly improved Fn, TSS, TA, vitamin C (Vc), and WP without compromising Vf, FW, and yield of kiwifruit. The IV-D25% treatment was determined to be the optimal treatment for improving fruit quality and WP of kiwifruit while maintaining yield, which increased TSS, TA, Vc, and WP by 9.1, 6.1, 19.2, 4.6%, respectively; the combination of D25%, D25%, full irrigation, and D25% treatments during stages I, II, III, and IV should be a viable irrigation strategy to simultaneously achieve high yield, quality, and WP of kiwifruit

Genetic Algorithm-Optimized Extreme Learning Machine Model for Estimating Daily Reference Evapotranspiration in Southwest China

Reference evapotranspiration (ET0) is an essential component in hydrological and ecological processes. The Penman&ndash;Monteith (PM) model of Food and Agriculture Organization of the United Nations (FAO) model requires a number of meteorological parameters; it is urgent to develop high-precision and computationally efficient ET0 models with fewer parameter inputs. This study proposed the genetic algorithm (GA) to optimize extreme learning machine (ELM), and evaluated the performances of ELM, GA-ELM, and empirical models for estimating daily ET0 in Southwest China. Daily meteorological data including maximum temperature (Tmax), minimum temperature (Tmin), wind speed (u2), relative humidity (RH), net radiation (Rn), and global solar radiation (Rs) during 1992&ndash;2016 from meteorological stations were used for model training and testing. The results from the FAO-56 Penman&ndash;Monteith formula were used as a control group. The results showed that GA-ELM models (with R2 ranging 0.71&ndash;0.99, RMSE ranging 0.036&ndash;0.77 mm&middot;d&minus;1) outperformed the standalone ELM models (with R2 ranging 0.716&ndash;0.99, RMSE ranging 0.08&ndash;0.77 mm&middot;d&minus;1) during training and testing, both of which were superior to empirical models (with R2 ranging 0.36&ndash;0.91, RMSE ranging 0.69&ndash;2.64 mm&middot;d&minus;1). ET0 prediction accuracy varies with different input combination models. The machine learning models using Tmax, Tmin, u2, RH, and Rn/Rs (GA-ELM5/GA-ELM4 and ELM5/ELM4) obtained the best ET0 estimates, with R2 ranging 0.98&ndash;0.99, RMSE ranging 0.03&ndash;0.21 mm&middot;d&minus;1, followed by models with Tmax, Tmin, and Rn/Rs (GA-ELM3/GA-ELM2 and ELM3/ELM2) as inputs. The machine learning models involved with Rn outperformed those with Rs when the quantity of input parameters was the same. Overall, GA-ELM5 (Tmax, Tmin, u2, RH and Rn as inputs) outperformed the other models during training and testing, and was thus recommended for daily ET0 estimation. With the estimation accuracy, computational costs, and availability of input parameters accounted, GA-ELM2 (Tmax, Tmin, and Rs as inputs) was determined to be the most effective model for estimating daily ET0 with limited meteorological data in Southwest China

Net ecosystem exchange, harvested grain carbon and carbon balance at different climate zone and for different tillage and maize varieties.

<p>^a. mean value in growing season.</p><p>Net ecosystem exchange, harvested grain carbon and carbon balance at different climate zone and for different tillage and maize varieties.</p

Sustaining Yield of Winter Wheat under Alternate Irrigation Using Saline Water at Different Growth Stages: A Case Study in the North China Plain

Brackish water used for irrigation can restrict crop growth and lead to environmental problems. The alternate irrigation with saline water at different growth stages is still not well understood. Therefore, field trials were conducted during 2015&ndash;2018 in the NCP to investigate whether alternate irrigation is practicable for winter wheat production. The treatments comprised rain-fed cultivation (NI), fresh and saline water irrigation (FS), saline and fresh water irrigation (SF), saline water irrigation (SS) and fresh water irrigation (FF). The results showed that the grain yield was increased by 20% under SF and FS treatments compared to NI, while a minor decrease of 2% in grain yield was observed compared with FF treatment. The increased soil salinity and risk of long-term salt accumulation in the soil due to alternate irrigation during peak dry periods was insignificant due to leaching of salts from crop root zone during monsoon season. Although Na+ concentration in the leaves increased with saline irrigation, resulting in significantly lower K+:Na+ ratio in the leaves, the Na+ and K+ concentrations in the roots and grains were not affected. In conclusion, the alternate irrigation for winter wheat is a most promising option to harvest more yield and save fresh water resources