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The susceptibility of purple soil and intensive tillage render the land prone to erosion under heavy precipitations in a sloping cropland in southwestern China. This study aimed to improve the evaluation of the potential benefits of surface protection tillage and organic matter addition to decreasing nutrient losses. A field plot experiment under natural rainfall conditions was conducted, which employed four management practices: conventional downslope tillage system as control (CK), contour tillage (CT) with organic matter addition (CT + OM), CT with wheat straw mulching (CT + SM), and CT combining straw mulching and organic matter addition (CT + OM + SM). Runoff depth, nutrient loads, and soil erodibility were used to estimate the effects of straw mulching and organic matter addition. Results indicated that the runoff depth under CK was largest during the experimental period, with an average of 16.91 mm, and runoff coefficient average was 32%. Compared with CK, the runoff depth under CT + OM, CT + SM, and CT + OM + SM were reduced by 19%, 34%, and 50%, respectively. A significant difference in soil erodibility indicator among the four treatments was indicated (p < 0.05); CK achieved the highest value, whereas CT + OM + SM obtained the least value. In addition, the contour cultivation (i.e., CT approaches) were more sustainable than the downslope tillage system (i.e., CK). Soil erodibility under CK was 9.83 kg ha −1 mm −1 . Meanwhile, soil erodibility under CT + OM, CT + SM, and CT + OM + SM were 8.49, 6.99, and 6.87 kg ha −1 mm −1 , respectively. These values were 14%, 29%, and 30% lower than that of CK, respectively. CK was more susceptible to accelerated erosion compared with the plots with a surface cover or organic addition. This greater erodibility resulted in higher runoff, sediment yield, and associated nutrient loss for CK. The runoff-associated nitrogen losses were mainly controlled by the runoff rate and soil erodibility (p < 0.05). Variations in NO 3 − –N and NH 4 + –N concentration in runoff water were markedly affected by rainfall events and agricultural practice. A significant logarithmic correlation between NO 3 − –N load and runoff depth was identified. NO 3 − –N was proven to be the main form of inorganic nitrogen loss; therefore, fertilizer application of NO 3 − –N should be reduced in the purple soil region. Soil erodibility significantly influenced the available N losses (p < 0.01), which was best described by a positive logarithmic correlation. Soil nutrient concentration also played an important role in nitrogen loss. However, further research is needed to understand the dynamic interactions between soil erodibility as well as soil and nutrient losses. Results indicated that surface protection by CT + OM + SM is one of the good management practices to reduce soil loss by water erosion in regions with intense agricultural activity. [ABSTRACT FROM AUTHOR]

In this study, FeCrNiCoMo maraging stainless steel was fabricated by laser melting deposition. The initial nonequilibrium microstructure exhibited cellular segregation of Cr and Mo with a 10–20 μm cell size. We investigated the microstructural evolution, particularly during aging with different time(1 h, 3 h, 5 h), for three post heat treatments: direct aging (500 °C) and low-temperature solution treatment (750 °C) and aging without and with additional prior homogenization (1000 °C). Microsegregation profoundly affected the austenite reversion behavior. The segregation at the cell walls promoted the nucleation and growth of reverted austenite, which eventually linked to form a net-like structure after prolonged aging. The net-like austenite in the direct-aged samples exhibited low thermal stability and result in brittle fracture upon impact at the temperature of liquid nitrogen (−196 °C). Net-like austenite and abundant lath austenite in the cell interior were found in the low-temperature solution-treated samples, which exhibited well-matched strength, toughness, and annealing temperature. Prior homogenization eliminated the microsegregation-induced net-like austenite. The measured mechanical properties indicate that the segregation-induced net-like austenite failed to benefit both the strength and toughness of the studied steel. [ABSTRACT FROM AUTHOR]

Electrocardiogram (ECG) is an important tool for the detection of acute ST-segment elevation myocardial infarction (STEMI). However, machine learning (ML) for the diagnosis of STEMI complicated with arrhythmia and infarct-related arteries is still underdeveloped based on real-world data. Therefore, we aimed to develop an ML model using the Least Absolute Shrinkage and Selection Operator (LASSO) to automatically diagnose acute STEMI based on ECG features. A total of 318 patients with STEMI and 502 control subjects were enrolled from Jan 2017 to Jun 2019. Coronary angiography was performed. A total of 180 automatic ECG features of 12-lead ECG were input into the model. The LASSO regression model was trained and validated by the internal training dataset and tested by the internal and external testing datasets. A comparative test was performed between the LASSO regression model and different levels of doctors. To identify the STEMI and non-STEMI, the LASSO model retained 14 variables with AUCs of 0.94 and 0.93 in the internal and external testing datasets, respectively. The performance of LASSO regression was similar to that of experienced cardiologists (AUC: 0.92) but superior (p < 0.05) to internal medicine residents, medical interns, and emergency physicians. Furthermore, in terms of identifying left anterior descending (LAD) or non-LAD, LASSO regression achieved AUCs of 0.92 and 0.98 in the internal and external testing datasets, respectively. This LASSO regression model can achieve high accuracy in diagnosing STEMI and LAD vessel disease, thus providing an assisting diagnostic tool based on ECG, which may improve the early diagnosis of STEMI. [ABSTRACT FROM AUTHOR]

• Soil colloids and extracellular enzymes undergo co-transport during hydrological processes. • Extracellular enzyme of hydrological pathways have a powerful effect on nitrogen loss by controlled enzyme stoichiometric. • Soil colloids' and extracellular enzymes' synergistic transport have potential impact on nitrogen loss in hydrology path. The extracellular enzyme plays a crucial role in nitrogen (N) conversion. Soil colloid serves as an important transporter of N transport in hydrological processes. This study investigated soil colloid-mediated N loss co-transporting with soil extracellular enzymes. Five simulated rainfall experiments were conducted under four tillage treatments in a purple sloping farmland in Sichuan, China. The N concentrations, soil mineral colloids, and four carbon (C), N and phosphorus (P) acquisition extracellular enzymes (βG, AP, NAG, and LAP) in surface runoff and interflow were measured. The results showed that cross-slope tillage with straw returning practices significantly reduced the concentrations of TN, PN, NH 4 +, and DON in surface runoff. The activities of N and P acquisition enzymes in interflow were higher than in surface runoff, while C acquisition enzymes showed the opposite trend. The BG and AP enzymes dominated in surface runoff, while AP and NAG dominated in interflow. The concentrations of fine soil mineral colloids (SMC, φ<1 μm) and coarse mineral colloids (CMC, φ＞1 μm) in interflow were higher than that in surface runoff. The extracellular enzymes were found to co-transport with soil colloid migration during the hydrologic process. The involvement of colloid in extracellular enzyme migration in surface runoff was primarily due to SMC, while in interflow, it was the joint action of SMC and CMC. Surface runoff is always in N and P limits, while interflow is only in the P limits. With a SEM combined model quantitatively analysis, we found the synergistic transport of soil colloid and extracellular enzymes significantly impacted TN loss, explaining 95 % and 55 % of the differences between surface runoff and interflow N loss pathways. This emphasizes the importance of understanding the co-transport mechanism between soil colloid and extracellular enzymes in N loss processes. [ABSTRACT FROM AUTHOR]

Ginsenoside Rb1 (Rb1) exerts many beneficial effects and protects against cardiovascular disease. To investigate whether Rb1 could attenuate age-related vascular impairment and identify the mechanism. Female C57BL/6J mice aged 2 and 18 months, randomly assigned to Young, Young + 20 mg/kg Rb1, Old + vehicle, Old + 10 mg/kg Rb1 and Old + 20 mg/kg Rb1 groups, were daily intraperitoneal injected with vehicle or Rb1 for 3 months. The thoracic aorta segments were used to inspect the endothelium-dependent vasorelaxation. Left thoracic aorta tissues were collected for histological or molecular expression analyses, including ageing-related proteins, markers relevant to calcification and fibrosis, and expression of Gas6/Axl. We found that in Old + vehicle group, the expression of senescence proteins and cellular adhesion molecules were significantly increased, with worse endothelium-dependent thoracic aorta relaxation (58.35% ± 2.50%) than in Young group (88.84% ± 1.20%). However, Rb1 treatment significantly decreased the expression levels of these proteins and preserved endothelium-dependent relaxation in aged mice. Moreover, Rb1 treatment also reduced calcium deposition, collagen deposition, and the protein expression levels of collagen I and collagen III in aged mice. Furthermore, we found that the downregulation of Gas6 protein expression by 41.72% and mRNA expression by 52.73% in aged mice compared with young mice was abrogated by Rb1 treatment. But there was no significant difference on Axl expression among the groups. Our study confirms that Rb1 could ameliorate vascular injury, suggesting that Rb1 might be a potential anti-ageing related vascular impairment agent. [ABSTRACT FROM AUTHOR]

Endothelial dysfunction and senescence are closely associated with cardiovascular diseases including atherosclerosis and hypertension. Ginsenoside Rb1 (Rb1), the major active constituent of ginseng, has been investigated intensively because of its anti-obesity and anti-inflammatory effects. In a previous study, hydrogen peroxide (H2O2) was applied to induce human umbilical vein endothelial cell (HUVEC) aging. It was demonstrated that Sirtuin-1 (SIRT1) was activated by Rb1 to protect HUVECs from H2O2-induced senescence. However, the mechanisms are not fully understood. The present study examined the role of AMP-activated protein kinase (AMPK), an energy sensor of cellular metabolism, in the signaling pathway of SIRT1 during H2O2-stimulated HUVEC aging. It was identified that Rb1 restored the H2O2-induced reduction of SIRT1 expression, which was consistent with our previous study, together with the activation of AMPK phosphorylation. Using compound C, an AMPK inhibitor, the role of AMPK in the protective effect of Rb1 against H2O2-induced HUVEC senescence was examined. It was identified that the induction of phosphorylated AMPK by Rb1 markedly increased endothelial nitric oxide synthase expression and nitric oxide production, and suppressed PAI-1 expression, which were abrogated in HUVECs pretreated with compound C. Further experiments demonstrated that nicotinamide, a SIRT1 inhibitor, downregulated the phosphorylation of AMPK and reduced the protective effects of Rb1 against H2O2-induced endothelial aging. Taken together, these results provide new insights into the possible molecular mechanisms by which Rb1 protects against H2O2-induced HUVEC senescence via the SIRT1/AMPK pathway. [ABSTRACT FROM AUTHOR]

Waterlogging stress is a common limiting factor for winter rapeseed, which greatly affects the growth and potential production. The present study was conducted to investigate the effects of waterlogging with different durations (0day (D0), 6days (D6) and 9days (D9)) and supplemental nitrogen fertilization (N1, 0 kg ha−1; N2, 30 kg ha−1; N3, 60 kg ha−1 and N4, 90 kg ha−1) on the physiological characteristics, dry matter and nitrogen accumulation in winter rapeseed (Chuanyou36). The results showed that the supplementary application of nitrogen fertilizer could effectively improve the physiological indexes of winter rapeseed in both pot and field experiments. The supplemental nitrogen increased the chlorophyll content in leaves, enhanced the activities of SOD, CAT, and POD, and decreased the MDA content in leaves and roots of rapeseed. The chlorophyll contents, the antioxidant enzyme activity of leaves and roots significantly increased under D6N3 and D9N4 conditions in both (pot and field) experiments. However, MDA contents significantly decreased compared with waterlogging without nitrogen application. Moreover, the application of nitrogen fertilizer after waterlogging increased the accumulation of dry matter and nitrogen in rapeseed at different growth stages. Therefore, waterlogging stress significantly inhibited the growth and development of rapeseed, but the application of nitrogen fertilizer could effectively reduce the damage of waterlogging. The N-induced increase in waterlogging tolerance of rapeseed might be attributed to the strong antioxidant defense system, maintenance of photosynthetic pigments and the nutrient balance. [ABSTRACT FROM AUTHOR]

Stratigraphic lithology strongly influences the spatial heterogeneity of soil available selenium (ASe), however, it is often neglected in regional simulation. Therefore, taking the Jiangjin District, where the soil is richer in selenium (Se), as the research area, the changes of soil ASe at different spatial scales have been simulated by combining Geodetector and three popular models (Multiple linear regression (MLR), Random forest (RF) and BP neural network (BPN)). The results showed that modelling with 'Formation' as the spatial scale could reduce the influence of stratum lithology difference on the spatial heterogeneity of soil ASe and improve the model's prediction accuracy. Compared with the MLR (R2 = 0.52, root mean squares error (RMSE) = 13.217 μg kg−1) and BPN (R2 = 0.55, RMSE = 13.79 μg kg−1), the RF (R2 = 0.67, RMSE = 10.85 μg kg−1) exhibited higher R2 and smaller RMSE, and the simulation effect of soil ASe is the best in the Middle Jurassic Shaximiao Formation (J 2 s). The outcomes of variable importance analysis revealed that soil total selenium (TSe) and soil organic matter (SOM) were the imperative factors for predicting ASe. The scenario simulation prediction showed that in the next 40 years, due to the combined influence of SOM and pH, the content of ASe in soil developed in the J 2 s would decrease from 40.8 μg kg−1 to 37.8 μg kg−1, a 7.8 percent drop. The main areas of soil ASe loss were in the western farming areas. The ASe content in dry land and paddy fields decreased by 12.0% and 4.9%, respectively. Therefore, long-term agricultural production activities would lead to soil ASe loss. The present results could provide a new scheme for the simulation and prediction of regional soil ASe, which is helpful for scientific planning, utilization of selenium-rich soil resources, and development of regional agricultural economy. [Display omitted] • The bioavailability of Se in soil had spatial heterogeneity in stratum. • Soil TSe and SOM had significant effects on soil Se bioavailability. • The 'Formation' of the stratum is the basic unit for modelling. • The risk of soil ASe deficiency was predicted to increase under SOM decreased. [ABSTRACT FROM AUTHOR]

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and cerebrovascular disease events. Early aetiology identification can eliminate aetiologies and control blood pressure. However, inexperienced doctors often fail to diagnose secondary hypertension, and comprehensively screening for all causes of high blood pressure increases health care costs. To date, deep learning has rarely been involved in the differential diagnosis of secondary hypertension. Relevant machine learning methods cannot combine textual information such as chief complaints with numerical information such as the laboratory examination results in electronic health records (EHRs), and the use of all features increases health care costs. To reduce redundant examinations and accurately identify secondary hypertension, we propose a two-stage framework that follows clinical procedures. The framework carries out an initial diagnosis process in the first stage, on which basis patients are recommended for disease-related examinations, followed by differential diagnoses of different diseases based on the different characteristics observed in the second stage. We convert the numerical examination results into descriptive sentences, thus blending textual and numerical characteristics. Medical guidelines are introduced through label embedding and attention mechanisms to obtain interactive features. Our model was trained and evaluated using a cross-sectional dataset containing 11,961 patients with hypertension from January 2013 to December 2019. The F1 scores of our model were 0.912, 0.921, 0.869 and 0.894 for primary aldosteronism, thyroid disease, nephritis and nephrotic syndrome and chronic kidney disease, respectively, which are four kinds of secondary hypertension with high incidence rates. The experimental results show that our model can powerfully use the textual and numerical data contained in EHRs to provide effective decision support for the differential diagnosis of secondary hypertension. [Display omitted] According to the chief complaints (CCs) and history of present illness (HPI) of a patient, our model makes an initial diagnosis as one of 3 kinds of hypertension. Combining the CCs, HPI and recommended examination results, our model makes a differential diagnosis as one of 5 kinds of hypertension. • We build a two-stage model to diagnose of secondary hypertension, which conforms to clinical process. • We use NLP technology to take advantage of the rich information in unstructured text data and effectively integrate it with numerical data. • By converting numerical features into natural language, our model reduces the influence of missing values. • We obtain interactive characteristics of EHR text and medical guidelines through label embedding and attention mechanism. • Based on real-world data, our model exceed the baseline method and doctor team. [ABSTRACT FROM AUTHOR]

Purposes: We have previously reported that Ginsenoside Rb1 may effectively prevent HUVECs from senescence, however, the detailed mechanism has not demonstrated up to now. Recent studies have shown that sirtuin-1 (Sirt1) plays an important role in the development of endothelial senescence. The purpose of this study was to explore whether Sirt1 is involved in the action of Ginsenoside Rb1 regarding protection against H2O2-induced HUVEC Senescence. Methods and Results: Senescence induced by hydrogen peroxide (H2O2) in human umbilical vein endothelial cells (HUVECs) was examined by analyzing plasminogen activator inhibitor-1 (PAI-1) expression, cell morphology, and senescence-associated beta-galactosidase (SA-β-gal) activity. The results revealed that 42% of control-treated HUVECs were SA-β-gal positive after treatment by 60 µmol/L H2O2, however, this particular effect of H2O2 was decreased more than 2-fold (19%) in the HUVECs when pretreated with Rb1 (20 µmol/L) for 30 min. Additionally, Rb1 decreased eNOS acetylation, as well as promoted more NO production that was accompanied by an increase in Sirt1 expression. Furthermore, upon knocking down Sirt1, the effect of Rb1 on HUVEC senescence was blunted. Conclusions: The present study indicated that Ginsenoside Rb1 acts through stimulating Sirt1 in order to protect against endothelial senescence and dysfunction. As such, Sirt1 appears to be of particular importance in maintaining endothelial functions and delaying vascular aging. [ABSTRACT FROM AUTHOR]