Effects of straw returning combined with blended controlled-release urea fertilizer on crop yields, greenhouse gas emissions, and net ecosystem economic benefits: A nine-year field trial.

Although straw returning combined with blended controlled-release urea fertilizer (BUFS) has been shown to improve wheat-maize rotation system productivity, their effects on greenhouse gas (GHG) emissions, carbon footprints (CF), and net ecosystem economic benefits (NEEB) are still unknown. Life cycle assessment was used to investigate a long-term (2013-2022) wheat-maize rotation experiment that included straw combined with two N fertilizer types [BUFS and (conventional urea fertilizer) CUFS] and straw-free treatments (BUF and CUF). The results showed that BUFS and CUFS treatments increased the annual yield by 13.8% and 11.5%, respectively, compared to BUF and CUF treatments. The BUFS treatment increased the yearly yield by 13.8% compared to the CUFS treatment. Since BUFS and CUFS treatments increased soil organic carbon (SOC) sink sequestration by 25.0% and 27.0% compared to BUF and CUF treatments, they reduced annual GHG emissions by 7.1% and 4.7% and CF per unit of yield (CFY) by 13.7% and 9.6%, respectively. BUFS treatment also increased SOC sink sequestration by 20.3%, reduced GHG emissions by 10.7% and CFY by 23.0% compared to CUFS treatment. It is worth noting that the BUFS and CUFS treatments increased the annual ecological costs by 41.6%, 26.9%, and health costs by 70.1% and 46.7% compared to the BUF and CUF treatments, but also increased the net yield benefits by 9.8%, 6.8%, and the soil nutrient cycling values by 29.2%, 27.3%, and finally improved the NEEB by 10.1%, 7.3%, respectively. Similar results were obtained for the BUFS treatment compared to the CUFS treatment, ultimately improving the NEEB by 23.1%. Based on assessing yield, GHG emissions, CF, and NEEB indicators, the BUFS treatment is recommended as an ideal agricultural fertilization model to promote sustainable and clean production in the wheat-maize rotation system and to protect the agroecological environment.

In vitro assessment and phase I randomized clinical trial of anfibatide a snake venom derived anti-thrombotic agent targeting human platelet GPIbα.

The interaction of platelet GPIbα with von Willebrand factor (VWF) is essential to initiate platelet adhesion and thrombosis, particularly under high shear stress conditions. However, no drug targeting GPIbα has been developed for clinical practice. Here we characterized anfibatide, a GPIbα antagonist purified from snake (Deinagkistrodon acutus) venom, and evaluated its interaction with GPIbα by surface plasmon resonance and in silico modeling. We demonstrated that anfibatide interferds with both VWF and thrombin binding, inhibited ristocetin/botrocetin- and low-dose thrombin-induced human platelet aggregation, and decreased thrombus volume and stability in blood flowing over collagen. In a single-center, randomized, and open-label phase I clinical trial, anfibatide was administered intravenously to 94 healthy volunteers either as a single dose bolus, or a bolus followed by a constant rate infusion of anfibatide for 24 h. Anfibatide inhibited VWF-mediated platelet aggregation without significantly altering bleeding time or coagulation. The inhibitory effects disappeared within 8 h after drug withdrawal. No thrombocytopenia or anti-anfibatide antibodies were detected, and no serious adverse events or allergic reactions were observed during the studies. Therefore, anfibatide was well-tolerated among healthy subjects. Interestingly, anfibatide exhibited pharmacologic effects in vivo at concentrations thousand-fold lower than in vitro, a phenomenon which deserves further investigation.Trial registration: Clinicaltrials.gov NCT01588132.

Developing water and nitrogen budgets of a wheat-maize rotation system using auto-weighing lysimeters: Effects of blended application of controlled-release and un-coated urea.

Evaluation of the effectiveness of best management practices for reducing nitrate leaching in agricultural systems requires detailed water and nitrogen (N) budgets. A 3-year field experiment using 15 auto-weighing lysimeters was set up to quantify nitrate leaching, crop evapotranspiration (ET), and N and water use efficiencies within an intensive wheat-maize rotation system in the Northern China Plain. The lysimeter consists mainly of the following: (1) high-resolution weighing cells; (2) ceramic solution samplers for soil solutions collection; and (3) circular stainless steel leaching trays for collecting seepage water. Two N fertilizer types were applied at two rates (150 and 225 kg N hm-2 for each crop) with no-N applied as the control. The N fertilizer types were monotypic un-coated urea and a blend product with controlled-release urea (CRU) and un-coated urea. The results indicate that when compared with un-coated urea at the same application rate, the blend product greatly improved water and N use efficiencies with significant increase in yields and crop ET as well as reduction of nitrate accumulation and leaching in the soil profile (p < 0.05). This was mostly because the blend product consistently supplied N to meet crop demands over the entire growth season. The study implied that effective best management practices to control nitrate leaching should be based on technically sound fertilization and irrigation schemes in terms of timing, rate, and fertilizer type to suit site specific conditions.

A novel approach to determine two optimal cut-points of a continuous predictor with a U-shaped relationship to hazard ratio in survival data: simulation and application.

BACKGROUND: In clinical and epidemiological researches, continuous predictors are often discretized into categorical variables for classification of patients. When the relationship between a continuous predictor and log relative hazards is U-shaped in survival data, there is a lack of a satisfying solution to find optimal cut-points to discretize the continuous predictor. In this study, we propose a novel approach named optimal equal-HR method to discretize a continuous variable that has a U-shaped relationship with log relative hazards in survival data. METHODS: The main idea of the optimal equal-HR method is to find two optimal cut-points that have equal log relative hazard values and result in Cox models with minimum AIC value. An R package 'CutpointsOEHR' has been developed for easy implementation of the optimal equal-HR method. A Monte Carlo simulation study was carried out to investigate the performance of the optimal equal-HR method. In the simulation process, different censoring proportions, baseline hazard functions and asymmetry levels of U-shaped relationships were chosen. To compare the optimal equal-HR method with other common approaches, the predictive performance of Cox models with variables discretized by different cut-points was assessed. RESULTS: Simulation results showed that in asymmetric U-shape scenarios the optimal equal-HR method had better performance than the median split method, the upper and lower quantiles method, and the minimum p-value method regarding discrimination ability and overall performance of Cox models. The optimal equal-HR method was applied to a real dataset of small cell lung cancer. The real data example demonstrated that the optimal equal-HR method could provide clinical meaningful cut-points and had good predictive performance in Cox models. CONCLUSIONS: In general, the optimal equal-HR method is recommended to discretize a continuous predictor with right-censored outcomes if the predictor has an asymmetric U-shaped relationship with log relative hazards based on Cox regression models.