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Research subject: Parkinson’s disease is a neurodegnerative disorder with no treatment due to the blood brain barrier (BBB) existence. The cure for this disease is Dopamine a chemical molecule.
Research approach: This study investigates biodegradable naoparticles (NPs) carrying dopamine (DA) across the blood–brain barrier. Ion polymerization and solvent methods were used to achieve this goal. Particle size, zeta potential, entrapment efficiency and in vitro drug release behavior, at pH 7 were examined.
Main results: The empty nanoparticles and drug-loaded nanoparticles were found to be spherical in shape and fluffy exterior, with mono-modal size distribution and negative zeta-potentials of increasing average sizes 90 to 120 nm simultaneously. Fourier transform infrared (FTIR) spectra demonstrated the polymerization of nBCA monomers and encapsulation of DA inside poly (butylcyanoacrylate) (PBCA).Thermal characteristics of the copolymer were investigated by Fourier-transform infrared spectroscopy (FTIR). Drug loading efficiency was around 25%.The in-vitro drug release profile of DA -loaded PBCA nanoparticles prepared from ion polymerization following solution techniques exhibited a gradual release; more than 20 ٪w/w of the drug was released after 51 h. The results showed that the DA–PBCA nanocapsules could be an effective carrier for hydrophilic agents. In this study, PBCA-NSPs were successfully generated as a delivery system for DA, providing a promising approach to improve the therapy of PDs.

 
 

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To evaluate the yield and quality of barley (Hordeum vulgare)–vetch (Vicia desycarpa) intercropping, a series of experiments were conducted at the Experimental Field of the College of Agriculture, University of Tehran, in Karaj (Iran) from 2003 to 2005. The ex-periments were arranged in a randomized complete block with a split plot design and four replications. Three levels (0, 45 and 90 Kg N ha-1) of nitrogen fertilizer and three cropping systems (sole barley, sole vetch and barley-vetch intercropping) were allocated to the main and sub plots, respectively. The barley-vetch intercropping treatment had a replacement arrangement (50: 50) with single alternate rows. Land equivalent ratio (LER), was used to compare sole cropping with intercropping systems. Results showed the supremacy of intercropping of barley and vetch over single crops. Generally, increas-ing nitrogen fertilizer caused a decreasing trend in the biological efficiency of intercrop-ping. The highest LER for grain was obtained in control (N fertilizer free) plots (LER= 1.145). Nitrogen fertilizer increased the forage yield, grain yield, crude protein content, and crude protein yield of barley and vetch in sole and intercrops. Nitrogen application increased water use efficiency. In this study, barley was the dominant crop. The inter-cropping vetch and barley had the highest productivity and crude protein yield.

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 Optimum cropping pattern increases productivity where input resources are limited. An optimized cropping pattern was developed for a region in Moghan Plain, located in the northwestern Iran, to help water supplier in pre-season decision making on water and land allocation. AquaCrop simulation model was calibrated and executed for yield predictions for 11 different crops and 13 diverse soil types. Evaluation of AquaCrop model showed great robustness for a broad range of crops, even for the crops like canola and alfalfa that were undefined for the model. The precise generated crop water functions revealed the ideal conditions for water allocation by considering the impact of the existing limitation in monthly water availability on optimum cropping pattern without imposing any manipulation. Optimum cropping pattern based on water productivity (OCPWP) was identified by LINGO software. Integrating AquaCrop model and LINGO optimization problem solver created a Decision Support System (DSS) for technical analysis at the regional level. The created DSS is able to support the OCPWP in terms of the complex regional crop-mixture acreage. The ecological considerations introduced diverse winter crops to benefit from autumn precipitations. This strategy decreases irrigation requirement and saves some water for spring/summer high water-demanding crops like alfalfa and cotton, which generally enhances the system resiliency. The generated DSS revealed that 8,762 m³ water ha^-1 was required for optimum cropping pattern, which is 8% lower than the maximum and 3% more than the average available water.