Role of no table salt on hypertension and stroke based on large sample size from National Health and Nutrition Examination Survey database.

BACKGROUND: To assess the associations between no table salt and hypertension or stroke. METHODS: The data of 15,352 subjects were collected from National Health and Nutrition Examination Survey (NHANES) database. All subjects were divided into no hypertension or stroke group (n = 10,894), hypertension group (n = 5888), stroke group (n = 164) and hypertension and stroke group (n = 511). Univariate and multivariate logistic regression analysis was used to measure the associations of salt type used with hypertension and stroke and co-variables were respectively adjusted in different models. RESULTS: After adjusting age and gender, other salt intake was associated with 1.88-fold risk of hypertension (OR = 1.88, 95%CI: 1.44-2.46) and no table salt was associated with 1.30-fold risk of hypertension (OR = 1.30, 95%CI: 1.15-1.47). After adjusting age, gender, race, BMI, PIR, marital status, CVDs, whether doctors' told them to reduce salt, and diabetes, the risk of hypertension was 1.23-fold increase in no table salt group (OR = 1.23, 95%CI: 1.04-1.46). After the adjustment of age and gender, the risk of hypertension and stroke was 3.33-fold increase (OR = 3.33, 95%CI: 2.12-5.32) in other salt intake group and 1.43-fold increase (OR = 1.43, 95%CI:1.17-1.74) in no table salt group. CONCLUSION: Other salt intake or no table salt were associated with a higher risk of hypertension or hypertension and stroke.

A Single-Center Clinical Study to Evaluate Shenxiong Glucose Injection Combined with Edaravone in the Treatment of Acute Large-Area Cerebral Infarction.

OBJECTIVES: To investigate the clinical efficacy and safety of Shenxiong glucose injection combined with edaravone in the treatment of acute large-area cerebral infarction. METHODS: 156 patients with acute large-area cerebral infarction admitted to our hospital from July 2015 to January 2017 were included in the analysis. The patients were randomly divided into experimental (78 cases) and control (78 cases) groups. Patients in the experimental group were given a 30 mg injection of edaravone in 100 ml of 0.9% sodium chloride solution by intravenous drip, twice a day within 30 minutes and a daily 200 ml injection of Shenxiong glucose by intravenous drip. Patients in the control group were given a 30 mg edaravone injection in 100 ml of 0.9% sodium chloride solution by intravenous drip, twice a day, and the drip was completed within 30 minutes. Patients in both groups were treated for 2 weeks. The levels of fibrinogen (FIB), D-dimer, interleukin 6 (IL-6), P-selectin (CD62P), and hypersensitive C-reactive protein (hs-CRP) were evaluated in the two groups of patients. Neurological disability was evaluated using the modified Rankin scale (mRS) and the neurological deficit score (National Institute of Health Stroke Scale, NIHSS). Adverse reactions to the treatments were also recorded. RESULTS: No significant differences in age, gender, medical histories, and blood biochemical indices were observed between the two groups before treatment (P > 0.05). After treatment, the levels of FIB, D-dimer, IL-6, CD62P, and hs-CRP were significantly lower following treatment and compared to the control group (P < 0.05). Also, the mRS and NIHSS scores were significantly lower after treatment and compared with the control group (P < 0.05). The total effective rate of the treatment in the experimental group was significantly higher compared to the control group (P < 0.05). During the treatment period, no obvious adverse reactions were observed in the two groups of patients. CONCLUSIONS: In addition to the routine basic treatment of acute large-area cerebral infarction, the addition of Shenxiong glucose injection combined with edaravone injection can improve platelet aggregation and reduce inflammation by affecting P-selectin, D-dimer, and FIB. This treatment approach promotes the recovery of nerve defect function without obvious adverse reactions in patients with acute large-area cerebral infarction.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

A robust ordering strategy for retailers facing a free shipping option.

Free shipping with conditions has become one of the most effective marketing tools available. An increasing number of companies, especially e-businesses, prefer to offer free shipping with some predetermined condition, such as a minimum purchase amount by the customer. However, in practice, the demands of buyers are uncertain; they are often affected by many factors, such as the weather and season. We begin by modeling the centralized ordering problem in which the supplier offers a free shipping service and retailers face stochastic demands. As these random data are considered, only partial information such as the known mean, support, and deviation is needed. The model is then analyzed via a robust optimization method, and the two types of equivalent sets of uncertainty constraints that are obtained provide good mathematical properties with consideration of the robustness of solutions. Subsequently, a numerical example is used to compare the results achieved from a robust optimization method and the linear decision rules. Additionally, the robustness of the optimal solution is discussed, as it is affected by the minimum quantity parameters. The increasing cost-threshold relationship is divided into three periods. In addition, the case study shows that the proposed method achieves better stability as well as computational complexity.