94 research outputs found

    Assessing biogeochemical effects and best management practice for a wheat–maize cropping system using the DNDC model

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    Contemporary agriculture is shifting from a single-goal to a multi-goal strategy, which in turn requires choosing best management practice (BMP) based on an assessment of the biogeochemical effects of management alternatives. The bottleneck is the capacity of predicting the simultaneous effects of different management practice scenarios on multiple goals and choosing BMP among scenarios. The denitrification–decomposition (DNDC) model may provide an opportunity to solve this problem. We validated the DNDC model (version 95) using the observations of soil moisture and temperature, crop yields, aboveground biomass and fluxes of net ecosystem exchange of carbon dioxide, methane, nitrous oxide (N2O), nitric oxide (NO) and ammonia (NH3) from a wheat–maize cropping site in northern China. The model performed well for these variables. Then we used this model to simulate the effects of management practices on the goal variables of crop yields, NO emission, nitrate leaching, NH3 volatilization and net emission of greenhouse gases in the ecosystem (NEGE). Results showed that no-till and straw-incorporated practices had beneficial effects on crop yields and NEGE. Use of nitrification inhibitors decreased nitrate leaching and N2O and NO emissions, but they significantly increased NH3 volatilization. Irrigation based on crop demand significantly increased crop yield and decreased nitrate leaching and NH3 volatilization. Crop yields were hardly decreased if nitrogen dose was reduced by 15% or irrigation water amount was reduced by 25%. Two methods were used to identify BMP and resulted in the same BMP, which adopted the current crop cultivar, field operation schedules and full straw incorporation and applied nitrogen and irrigation water at 15 and 25% lower rates, respectively, than the current use. Our study indicates that the DNDC model can be used as a tool to assess biogeochemical effects of management alternatives and identify BMP

    Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC

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    Degradation of water quality has been widely observed in China, and loadings of nitrogen (N) and other nutrients from agricultural systems play a key role in the water contamination. Process‐based biogeochemical models have been applied to quantify nutrient loading from nonpoint sources at the watershed scale. However, this effort is often hindered by the fact that few existing biogeochemical models of nutrient cycling are able to simulate the two‐dimensional soil hydrology. To overcome this challenge, we launched a new attempt to incorporate two fundamental hydrologic features, the Soil Conservation Service curve and the Modified Universal Soil Loss Equation functions, into a biogeochemistry model, Denitrification‐Decomposition (DNDC). These two features have been widely utilized to quantify surface runoff and soil erosion in a suite of hydrologic models. We incorporated these features in the DNDC model to allow the biogeochemical and hydrologic processes to exchange data at a daily time step. By including the new features, DNDC gained the additional ability to simulate both horizontal and vertical movements of water and nutrients. The revised DNDC was tested against data sets observed in a small watershed dominated by farmlands in a mountainous area of southwest China. The modeled surface runoff flow, subsurface drainage flow, sediment yield, and N loading were in agreement with observations. To further observe the behaviors of the new model, we conducted a sensitivity test with varied climate, soil, and management conditions. The results indicated that precipitation was the most sensitive factor determining the rate of N loading from the tested site. A Monte Carlo test was conducted to quantify the potential uncertainty derived by variations in four selected input parameters. This study demonstrates that it is feasible and effective to use enhanced biogeochemical models such as DNDC for quantifying N loadings by incorporating basic hydrological features into the model framework

    Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

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    The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

    UV-radiation Induced Disruption of Dry-Cavities in Human γD-crystallin Results in Decreased Stability and Faster Unfolding

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    Age-onset cataracts are believed to be expedited by the accumulation of UV-damaged human γD-crystallins in the eye lens. Here we show with molecular dynamics simulations that the stability of γD-crystallin is greatly reduced by the conversion of tryptophan to kynurenine due to UV-radiation, consistent with previous experimental evidences. Furthermore, our atomic-detailed results reveal that kynurenine attracts more waters and other polar sidechains due to its additional amino and carbonyl groups on the damaged tryptophan sidechain, thus breaching the integrity of nearby dry center regions formed by the two Greek key motifs in each domain. The damaged tryptophan residues cause large fluctuations in the Tyr-Trp-Tyr sandwich-like hydrophobic clusters, which in turn break crucial hydrogen-bonds bridging two β-strands in the Greek key motifs at the “tyrosine corner”. Our findings may provide new insights for understanding of the molecular mechanism of the initial stages of UV-induced cataractogenesis.International Business Machines Corporation (IBM Blue Gene Program

    Characteristics of multiple‐year nitrous oxide emissions from conventional vegetable fields in southeastern China

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    The annual and interannual characteristics of nitrous oxide (N2O) emissions from conventional vegetable fields are poorly understood. We carried out 4 year measurements of N2O fluxes from a conventional vegetable cultivation area in the Yangtze River delta. Under fertilized conditions subject to farming practices, approximately 86% of the annual total N2O release occurred following fertilization events. The direct emission factors (EFd) of the 12 individual vegetable seasons investigated ranged from 0.06 to 14.20%, with a mean of 3.09% and a coefficient of variation (CV) of 142%. The annual EFd varied from 0.59 to 4.98%, with a mean of 2.88% and an interannual CV of 74%. The mean value is much larger than the latest default value (1.00%) of the Intergovernmental Panel on Climate Change. Occasional application of lagoon‐stored manure slurry coupled with other nitrogen fertilizers, or basal nitrogen addition immediately followed by heavy rainfall, accounted for a substantial portion of the large EFds observed in warm seasons. The large CVs suggest that the emission factors obtained from short‐term observations that poorly represent seasonality and/or interannual variability will inevitably yield large uncertainties in inventory estimation. The results of this study indicate that conventional vegetable fields associated with intensive nitrogen addition, as well as occasional applications of manure slurry, may substantially account for regional N2O emissions. However, this conclusion needs to be further confirmed through studies at multiple field sites. Moreover, further experimental studies are needed to test the mitigation options suggested by this study for N2O emissions from open vegetable fields

    A coupled terrestrial and aquatic biogeophysical model of the Upper Merrimack River watershed, New Hampshire, to inform ecosystem services evaluation and management under climate and land-cover change

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    Accurate quantification of ecosystem services (ES) at regional scales is increasingly important for making informed decisions in the face of environmental change. We linked terrestrial and aquatic ecosystem process models to simulate the spatial and temporal distribution of hydrological and water quality characteristics related to ecosystem services. The linked model integrates two existing models (a forest ecosystem model and a river network model) to establish consistent responses to changing drivers across climate, terrestrial, and aquatic domains. The linked model is spatially distributed, accounts for terrestrial–aquatic and upstream–downstream linkages, and operates on a daily time-step, all characteristics needed to understand regional responses. The model was applied to the diverse landscapes of the Upper Merrimack River watershed, New Hampshire, USA. Potential changes in future environmental functions were evaluated using statistically downscaled global climate model simulations (both a high and low emission scenario) coupled with scenarios of changing land cover (centralized vs. dispersed land development) for the time period of 1980–2099. Projections of climate, land cover, and water quality were translated into a suite of environmental indicators that represent conditions relevant to important ecosystem services and were designed to be readily understood by the public. Model projections show that climate will have a greater influence on future aquatic ecosystem services (flooding, drinking water, fish habitat, and nitrogen export) than plausible changes in land cover. Minimal changes in aquatic environmental indicators are predicted through 2050, after which the high emissions scenarios show intensifying impacts. The spatially distributed modeling approach indicates that heavily populated portions of the watershed will show the strongest responses. Management of land cover could attenuate some of the changes associated with climate change and should be considered in future planning for the region

    Protective effect of the curcumin-baicalein combination against macrovascular changes in diabetic angiopathy

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    Endothelial dysfunction is an early pathological event in diabetic angiopathy which is the most common complication of diabetes. This study aims to investigate individual and combined actions of Curcumin (Cur) and Baicalein (Bai) in protecting vascular function. The cellular protective effects of Cur, Bai and Cur+Bai (1:1, w/w) were tested in H2O2 (2.5 mM) impaired EA. hy926 cells. Wistar rats were treated with vehicle control as the control group, Goto-Kakizaki rats (n=5 each group) were treated with vehicle control (model group), Cur (150 mg/kg), Bai (150 mg/kg), or Cur+Bai (75 mg/kg Cur + 75 mg/kg Bai, OG) for 4 weeks after a four-week high-fat diet to investigate the changes on blood vessel against diabetic angiopathy. Our results showed that Cur+Bai synergistically restored the endothelial cell survival and exhibited greater effects on lowering the fasting blood glucose and blood lipids in rats comparing to individual compounds. Cur+Bai repaired the blood vessel structure in the aortic arch and mid thoracic aorta. The network pharmacology analysis showed that Nrf2 and MAPK/JNK kinase were highly relevant to the multi-targeted action of Cur+Bai which has been confirmed in the in vitro and in vivo studies. In conclusion, Cur+Bai demonstrated an enhanced activity in attenuating endothelial dysfunction against oxidative damage and effectively protected vascular function in diabetic angiopathy rats

    Effect of Tanshinone IIA on gut microbiome in diabetes-induced cognitive impairment

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    Diabetes-induced cognitive impairment (DCI) presents a major public health risk among the aging population. Previous clinical attempts on known therapeutic targets for DCI, such as depleted insulin secretion, insulin resistance, and hyperglycaemia have delivered poor patient outcomes. However, recent evidence has demonstrated that the gut microbiome plays an important role in DCI by modulating cognitive function through the gut–brain crosstalk. The bioactive compound tanshinone IIA (TAN) has shown to improve cognitive and memory function in diabetes mellitus models, though the pharmacological actions are not fully understood. This study aims to investigate the effect and underlying mechanism of TAN in attenuating DCI in relation to regulating the gut microbiome. Metagenomic sequencing analyses were performed on a group of control rats, rats with diabetes induced by a high-fat/high-glucose diet (HFD) and streptozotocin (STZ) (model group) and TAN-treated diabetic rats (TAN group). Cognitive and memory function were assessed by the Morris water maze test, histopathological assessment of brain tissues, and immunoblotting of neurological biomarkers. The fasting blood glucose (FBG) level was monitored throughout the experiments. The levels of serum lipopolysaccharide (LPS) and tumor necrosis factor-α (TNF-α) were measured by enzyme-linked immunoassays to reflect the circulatory inflammation level. The morphology of the colon barrier was observed by histopathological staining. Our study confirmed that TAN reduced the FBG level and improved the cognitive and memory function against HFD- and STZ-induced diabetes. TAN protected the endothelial tight junction in the hippocampus and colon, regulated neuronal biomarkers, and lowered the serum levels of LPS and TNF-α. TAN corrected the reduced abundance of Bacteroidetes in diabetic rats. At the species level, TAN regulated the abundance of B. dorei, Lachnoclostridium sp. YL32 and Clostridiodes difficile. TAN modulated the lipid metabolism and biosynthesis of fatty acids in related pathways as the main functional components. TAN significantly restored the reduced levels of isobutyric acid and butyric acid. Our results supported the use of TAN as a promising therapeutic agent for DCI, in which the underlying mechanism may be associated with gut microbiome regulation

    Совершенствование маркетинговой деятельности промышленного предприятия (на примере РУП «Белоруснефть-Особино»)

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    We report a detailed computational and experimental study of the interaction of single-walled carbon nanotubes (SWCNTs) with the drug-metabolizing cytochrome P450 enzyme, CYP3A4. Dose-dependent inhibition of CYP3A4-mediated conversion of the model compound, testosterone, to its major metabolite, 6β-hydroxy testosterone was noted. Evidence for a direct interaction between SWCNTs and CYP3A4 was also provided. The inhibition of enzyme activity was alleviated when SWCNTs were pre-coated with bovine serum albumin. Furthermore, covalent functionalization of SWCNTs with polyethylene glycol (PEG) chains mitigated the inhibition of CYP3A4 enzymatic activity. Molecular dynamics simulations suggested that inhibition of the catalytic activity of CYP3A4 is mainly due to blocking of the exit channel for substrates/products through a complex binding mechanism. This work suggests that SWCNTs could interfere with metabolism of drugs and other xenobiotics and provides a molecular mechanism for this toxicity. Our study also suggests means to reduce this toxicity, eg., by surface modification
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