Search

This study aimed to develop and evaluate a population pharmacokinetic (PPK) combined machine learning approach to predict tacrolimus trough concentrations for Chinese adult liver transplant recipients in the early posttransplant period. Tacrolimus trough concentrations were retrospectively collected from routine monitoring records of liver transplant recipients and divided into the training data set (1287 concentrations in 145 recipients) and the test data set (296 concentrations in 36 recipients). A PPK model was first established using NONMEM. Then a machine learning model of Xgboost was adapted to fit the estimated individual pharmacokinetic parameters obtained from the PPK model with Bayesian forecasting. The performance of the final PPK model and Xgboost model was compared in the test data set. In the final PPK model, tacrolimus daily dose, postoperative days, hematocrit, aspartate aminotransferase, and concomitant voriconazole, were identified to significantly influence the clearance. The postoperative days along with hematocrit significantly influence the volume of distribution. In the Xgboost model, the first 5 predictors for predicting the clearance were concomitant with voriconazole, sex, single nucleotide polymorphisms of CYP3A4*1G and CYP3A5*3 in recipients, and tacrolimus daily dose, for the volume of distribution were postoperative days, age, weight, total bilirubin and graft : recipient weight ratio. In the test data set, the Xgboost model showed the minimum median prediction error of tacrolimus concentrations, less than the PPK model with or without Bayesian forecasting. In conclusion, a PPK combined machine learning approach could improve the prediction of tacrolimus concentrations for Chinese adult liver transplant recipients in the early posttransplant period. [ABSTRACT FROM AUTHOR]

Carbon supported metal catalysts have received considerable interest due to their widespread applications in heterogeneous catalysis. However, the controllable synthesis of carbon support with defined morphology and composition still represents great challenging. Herein, we reported the synthesis of a well-defined hierarchically nanosized H-ZrO2/NC (nitrogen-doped carbon) network via an inheritable carbonization strategy. When immobilizing the palladium clusters into the support, the N-doped sites and oxygen vacancy of the carbon composite can effectively stabilize and activate Pd through strong metal-support interaction which was also confirmed by density functional theory (DFT) calculations. Moreover, the hierarchically nanosized network can contribute to the exposure of active sites and facilitate the mass transfer during the catalytic process. As a result, benefiting from the hierarchical structure, composition and hydrolytic nature, Pd@H-ZrO2/NC exhibited excellent catalytic activity and stability towards the hydrogenation of furfural in mild reaction conditions, as well as good universality toward the hydrogenation of a series of unsaturated hydrocarbons. [ABSTRACT FROM AUTHOR]

To investigate the effects of gravel content on runoff and sediment yield on Lou soil accumulation slopes, we conducted indoor simulation rainfall experiments and examined the characteristics of runoff and sediment yield on accumulation slopes with five gravel contents (10%, 20%, 30%, 40%, 50%) under four rainfall intensities (1.0, 1.5, 2.0, 2.5 mm·min -1 ), with a no gravels slope as control. The average runoff rate under different test conditions ranged from 2.18 to 13.07 L·min -1 . The average runoff rate was the maximum under the gravel content of 10% (or 20%) and the minimum under the 50% gravel content. The average flow velocity ranged from 0.06 to 0.22 m·s -1 . The variation of flow velocity was complex. The smaller the gravel content, the larger the range of variation and the coefficient of variation. The average flow velocity reached the maximum when the gravel content was 10%. The presence of gravel effectively inhibited the sediment yield, and the sediment reduction benefit reached 84.2%. The rainfall intensity had more influence on the average sediment yield rate than gravel content. Results of partial correlation analysis showed that gravel content was significantly negatively correlated with the ave-rage runoff rate, the average flow velocity, and the average sediment yield rate. The relationships between the ave-rage sediment yield and the average runoff rate, the average flow velocity, and their interaction were all extremely significant linear functions, with the strongest relationship between the average sediment yield and the average runoff rate. This study could provide references for the control of soil erosion and the establishment of erosion models for engineering accumulations in Lou soil areas.

Reducing the application of chemical fertilizer and increasing fertilizer efficiency can contribute to the sustainable development of agriculture. To evaluate the impacts of N fertilizer reduction and biochar application on soil organic carbon active components and mineralization in yellow soil, an experiment was carried out with five different substitution rates of chemical N fertilizer by biochar under the same rate of N input, i.e ., 0, 10%, 20%, 30%, 40% (CK, T 1 -T 4 ). The results showed that chemical N fertilizer reduction combined with biochar application could significantly improve soil organic carbon (SOC), the magnitude of which was proportional to the amount of biochar application. Under the condition of 20% substitution rate (T 2 ), soil microbial biomass carbon (MBC) and readily oxidized carbon (ROC) were the highest with 293.68 mg·kg -1 and 250.00 mg·kg -1 , respectively, but the concentration of soil dissolved organic carbon (DOC) was the lowest. SOC mineralization rate reached the highest on the third day of incubation. Then, it decreased rapidly in the early period (day 3 of incubation to day 6), decreased slowly in the middle period (day 6 of incubation to day 18), and stabilized in the later period (day 18 of incubation to day 30). There was a logarithmic relationship between mineralization rate of soil organic carbon and incubation time. SOC cumulative mineralization amount and cumulative mineralization rate were the lowest in the T 2 treatment with 0.66-0.86 g·kg -1 and 2.9%-4.0%, respectively. As the substitution rate of chemical N fertilizer by biochar increased, rice yield increased firstly and then decreased. Rice yield in the T 2 treatment was the highest, which increased by 13.4% compared with the CK. The substitution of 20% chemical N fertilizer with biochar (5 t·hm -2 ) could effectively improve the contents of SOC, MBC, ROC, and rice yield, reduce the cumulative mineralization amount of organic carbon and cumulative mineralization rate, and enhance the capacity of soil carbon sequestration. Hence, it could be the most effective fertilizer practice for improving soil fertility and rice yield in paddy field of yellow soil in Guizhou Province.