p. maleki

Considering high prevalence of type 2 diabetes and predisposition of obesity to metabolic disorders and cardiovascular diseases, the aim of the present study was to investigate effects of starch resistance on cardiometabolic factors, liver enzymes and calcium homeostasis in obese patients with type 2 diabetes.

In this clinical trial, 70 obese patients with type 2 diabetes were assigned to one of the two major groups. The experimental group received 10g/d resistant starch and the control group received 10 g/d maltodextrins for three months. Anthropometric measurements, body composition, blood pressure, hs-CRP, serum lipids, calcium homeostasis and liver enzymes were assessed at the baseline and end of the study. Unpaired sample Student’s t test and analysis of covariance were used to compare the quantitative variables between the groups.

Supplementation with resistant starch led to significant changes in total cholesterol (TC) (- 16.96%), triglyceride (TG) (-16.85%), low density lipoprotein cholesterol (LDL-c) (-14.90%), TC/HDL-c ratio (-25.91%), LDL-c/HDL-c ratio (-26.00%), plasma atherogenic index (-17.85%), hsCRP (-53.03%), alkaline phosphatase concentration (-13.74%), calcium (6.99%) and alanine aminotransferase (-10.98%) in resistant starch group, compared to maltodextrin group (p < 0.05). Decreases in waist to hip ratio, diastolic blood pressure, glucose, aspartate aminotransferase, phosphorus, creatinine and uric acid and increases in high density lipoprotein chelestrol (HDL-c) were not significant in resistant starch group, compared to maltodextrin group.

Possibly, resistant starch prebiotics help control of metabolic disorders of type 2 diabetes and its complications via modulating cardiometabolic risk factors, liver enzymes and calcium homeostasis in obese type 2 diabetics.

The accuracy of each simulating beta-voltaic battery parameter is very important, especially in micro-batteries. The aim of this study is to improve the calculation of beta-battery parameters’ accuracy. For this purpose, at first, using the Monte Carlo N-Particle code (MCNPX), the energy accumulation distribution of the 63Ni beta particle spectrum inside a silicon semiconductor has been simulated. Then, the ATLAS C-Interpreter function in C ++ was defined, using one of the SILVACO code abilities (the parameter F.RADIATE BEAM statement). Finally, the device electric parameters have been obtained using ATLAS-SILVACO based on the location-dependent of MCNPX results. For validation, the calculations were performed for a battery sample made of 16 mm2 cross-section and 1 mCi activity of radioisotope 63Ni as a source, and finally, the results were compared with one experimental result and two analytical methods. The calculations repeated for the other sample with 100 mCi activity and 1 cm2 of geometry, and compared its results with an analytical method results. The results showed that the simulation of micro-battery characteristics by the MCNPX-SILVACO hybrid code using three-dimensional electron-hole pairs’ distribution in semiconductor and the full spectrum of beta particles creates a significant increase in the accuracy of the computation, and provides a good capability to optimize the design of the battery.

The problem of pollution in the Caspian sea has attracted increasing scientific concerns in recent years, but still, there is limited data relevant to the Gorgan bay. The current study aimed to evaluate the organic pollution of the Gorgan Bay, using Palmer Algal Index. Sampling was conducted seasonally in triplicate from summer 2017 to spring 2018. Phytoplankton samples were collected from surface water (maximum depth of 50cm), using a one-liter sampling bottle and fixed in 2.5% formaldehyde buffer solution. A total of 23 stations were selected including, seven stations in the eastern areas, eight stations in the centre, and eight stations in the western part of the bay. The Palmer Index indicated that all parts of the bay are highly polluted, in the four seasons. Comparison of the index among the three parts of the bay indicated that the central areas are more polluted than other areas in the three seasons, from summer to winter, while only in the spring, the western area of the bay showed the highest value of the index. The predominance of the pollution resistant Phyto-genera such as Oscillatoria, Euglena, Cyclotella, Navicula, Nitzschia, and Synedra supports the classification of the bay as eutrophic. Generally, the results of the algal index revealed that the water quality of the bay has reached a critical level.

Phosphorus (P) is a key element in many biological processes of plants and animals. We aimed to investigate the effect of different salinity levels and Ca:Mg ratios of irrigation water arid lands on soil available P, soluble P, and P absorbed by the pistachio plant. For this purpose, a greenhouse experiment was conducted by sowing the seeds of pistachio in a factorial randomized block design with four soil salinity levels (S1 (6 dS.m-1irrigation water salinity, leaching fraction (LF) = 50), S2, S3, and S4 (9 dS.m-1 irrigation water salinity, LF = 50, 30 and 20, respectively)) and three Ca:Mg ratios (M1, M2, and M3 equal to 1, 0.5, and 0.25, respectively). After harvesting the plants, the amount of soil available P (Po), water-soluble P (Pw), and total P (Pt) at soil depths of 0-5, 5-25, 25-50, and 50-75 cm, and P concentration in the leaves of Pistachio seedlings were measured.The results showed that the salinity of soil saturated extract had no significant effect on Po, Pw, and Pt. The reduction in Ca:Mg ratio increased Po and Pw in soil surface but it did not affect Pt. Increasing salinity from S1 to S2 augmented plant P uptake but at higher salinity levels, P uptake was reduced. The decrease in Ca:Mg ratio had no significant effect on plant P contents.