Effects of Two-by-Two Combination Therapy with Valproic Acid, Lithium Chloride, and Celecoxib on the Angiogenesis of the Chicken Chorioallantoic Membrane

Background: The synergistic effects of valproic acid (VPA), lithium (Li), and celecoxib (CX) have been shown in combination therapy against the proliferation and metastasis of numerous cancers. Angiogenesis plays a critical role in the pathogenesis of tumor growth and metastasis. The aim of the present study was to evaluate the antiangiogenic effects of VPA, lithium chloride (LiCl), and CX, alone or in 2-by-2 combinations, using the chicken chorioallantoic membrane (CAM) assay. Methods: Fertilized chicken eggs were randomly divided into 10 groups: control, VPA (1.8 and 3.6 µmol/CAM), Li (0.15 and 0.60 µmol/CAM), CX (0.02 and 0.08 µmol/CAM), VPA+Li, VPA+CX, and CX+Li (n=10 per group). A window was made on the eggshells and the CAMs were exposed to a filter disk containing VPA, LiCl, and CX, alone or in 2-by-2 combinations. The control CAMs were treated with distilled water (vehicle). Three days after the treatment, the number of vessel branch points was counted in each CAM. The data were analyzed using SPSS, version 15.One-way ANOVA, followed by the Tukey tests, was used to compare the groups. A P<0.05 was considered a statistically significant difference between the groups. Results: According to the results, all the tested drugs decreased the number of the vessel branch points in a dose-dependent manner compared to the control group (P<0.001). In addition, combinations of the drugs were more effective in decreasing angiogenesis than the use of each drug alone. Conclusion: These findings suggest that 2-by-2 combinations of VPA, CX, and LiCl can be considered an effective antiangiogenesis therapeutic modality

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

New methods and applications in multiple attribute decision making (MADM)

This book presents 27 methods of the Multiple Attribute Decision Making (MADM), which are not discussed in existing books, nor studied in details, using various applications. Nowadays, decision making is one of the most important and fundamental tasks of management as an organizational goal achievement that depends on its quality. Decision making includes the correct expression of objectives, determining different and possible solutions, evaluating their feasibility, assessing the consequences, and the results of implementing each solution, and finally, selecting and implementing the solution. Multiple Criteria Decision Making (MCDM) is sum of the decision making techniques. MCDM is divided into the Multiple Objective Decision Making (MODM) for designing the best solution and MADM for selecting the best alternative. Given that the applications of MADM are mostly more than MODM, wide various techniques have been developed for MADM by researchers over the last 60 years, and the current book introduces some of the other new MADM methods

Performance Evaluation in Green Supply Chain Using BSC, DEA and Data Mining

Efficiency is regarded as an important factor for both managers in different companies and organizations and customers who are interested in using the services related to these companies and organizations. However, the biggest challenges managers are coping with include an increase in the competition between companies and manufacturing centers, an increase in the efficiency of production, and finding suitable suppliers. The present study aimed to investigate the efficiency of green supply chain (GSC) by using Malmquist productivity index (MPI) based on the input and output indicators of the BSC model and accordingly providing some rules using the decision tree. To this aim, the efficiency of 15 automotive parts manufacturer firms in Iran was evaluated in the state of constant returns to scale during 2013-2016. Then, the obtained results were used as the class label of Decision Making Units (DMUs) which are regarded as the inputs of decision tree method. Finally, the implicit rules in the data were extracted by using the decision tree. The results indicated that the proposed model had a high degree of accuracy and interpretation in evaluating performance compared to previous models and helps managers to make better decisions to increase the efficiency

Presenting a Bi-objective Integrated Model for Production-Distribution Problem in a Multi-level Supply Chain Network

In this study, a bi-objective model for integrated planning of production-distribution in a multi-level supply chain network with multiple product types and multi time periods is presented. The supply chain network including manufacturers, distribution centers, retailers and final customers is proposed. The proposed model minimizes the total supply chain costs and transforming time of products for customers in the chain. The proposed model is in the class of linear integer programming problems. The complexity of the problem is large and in the literatur, this problem has been shown to be NP-hard. Therefore, for solving this problem, two multi objective meta-heuristic approaches based on Pareto method including non-dominated Sorting Genetic Algorithm-II (NSGA-II) and non-dominated Ranking Genetic Algorithm (NRGA) have been suggested. Since the output of meta- heuristic algorithms are highly dependent on the input parameters of the algorithm, Taguchi method (Taguchi) is used to tune the parameters. Finally, in order to evaluate the performance of the proposed solution methods, different test problems with different dimensions have been produced and the performances of the proposed algorithms on the test problems have been analyzed

Data for atmospheric arsenic deposition: A case study- northeast of Iran

Air pollution is the major health concern in modern societies, especially in countries with arid and aggressive climate. Nowadays extensive research has been carried out to identify air pollution and its control. The main aim of this study is determine the atmospheric arsenic deposition concentration in Gonabad County in northeast Iran. In this cross-sectional study, the concentration of arsenic was measured by collecting of PM10 deposition from the ambient air of Gonabad urban areas. Samples were firstly taken by jar test method in four one-month periods in 2016 from Taleghani st., Imam Khomeini sq., Mend sq., Ghaffari st., and Sadi st., and arsenic concentration in the particles were determined by the Graphite furnace atomic absorption spectroscopy (GFAAS). The results indicated that the maximum and minimum concentrations (average) of particles PM10 depositing was observed in Taleghani st. about 10.395 ± 1.183 µg/kg and Imam Khomeini sq. about 4.394 ± 0.961 µg/kg, respectively. The maximum and minimum concentration of arsenic concentrations were estimated to be respectively 12.080 and 3.560 µg/kg in December and September, respectively. The results showed that in the northern part of the city, due to the wind blow, there are more particles in the air and people living in these areas are more exposed to arsenic. Therefore, residents of these areas need more actions that are preventive. Keywords: Atmospheric arsenic, Air pollution, Air particle, PM10, Gonabad cit

Effects of Ramadan fasting on ambulatory blood pressure in hypertensive patients

Background: Previous studies have indicated that Ramadan fasting has beneficial effects on cardiovascular risk factors, specially blood pressure and heart rate (1). In the present study, the effect of Ramadan fasting on 24-hour ambulatory blood pressure and heart rate has been investigated. Materials and Methods: This prospective observational study was conducted on two groups of individuals. Six patients under hypertension treatment were allocated to the case group and 12 healthy individuals were selected as the control group. Twenty-four-hour blood pressure monitoring was carried out during four periods: prior to Ramadan, during the first ten days and the last ten days of Ramadan, and one month after it. All patients continued their medication, which was administered twice per day. Twenty-four-hour mean blood pressure, weight, body mass index (BMI), and waist circumference were compared among the groups. Results: In the case group, there was a significant reduction in subjects’ weight during the third period of the experiment; also, a significant improvement was observed in the heart rate during the second and third periods in the case group (