Nanotechnology is a relatively new branch of science that involves harnessing the unique properties of particles that are nanometers in scale (nanoparticles). Nanoparticles can be engineered in a precise fashion where their size, composition and surface chemistry can be carefully controlled. This enables unprecedented freedom to modify some of the fundamental properties of their cargo, such as solubility, diffusivity, biodistribution, release characteristics and immunogenicity. Since their inception, nanoparticles have been utilized in many areas of science and medicine, including drug delivery, imaging, and cell biology 1-4 . However, it has not been fully utilized outside of "nanotechnology laboratories" due to perceived technical barrier. In this article, we describe a simple method to synthesize a polymer based nanoparticle platform that has a wide range of potential applications.The first step is to synthesize a diblock co-polymer that has both a hydrophobic domain and hydrophilic domain. Using PLGA and PEG as model polymers, we described a conjugation reaction using EDC/NHS chemistry 5 (Fig 1). We also discuss the polymer purification process. The synthesized diblock co-polymer can self-assemble into nanoparticles in the nanoprecipitation process through hydrophobic-hydrophilic interactions.The described polymer nanoparticle is very versatile. The hydrophobic core of the nanoparticle can be utilized to carry poorly soluble drugs for drug delivery experiments6. Furthermore, the nanoparticles can overcome the problem of toxic solvents for poorly soluble molecular biology reagents, such as wortmannin, which requires a solvent like DMSO. However, DMSO can be toxic to cells and interfere with the experiment. These poorly soluble drugs and reagents can be effectively delivered using polymer nanoparticles with minimal toxicity. Polymer nanoparticles can also be loaded with fluorescent dye and utilized for intracellular trafficking studies. Lastly, these polymer nanoparticles can be conjugated to targeting ligands through surface PEG. Such targeted nanoparticles can be utilized to label specific epitopes on or in cells [7][8][9][10] .
Image denoising has become one of the major forms of image enhancement methods that form the basis of image processing. Due to the inconsistencies in the machinery producing these signals, medical images tend to require these techniques. In real time, images do not contain a single noise, and instead they contain multiple types of noise distributions in several indistinct regions. This paper presents an image denoising method that uses Metaheuristics to perform noise identification. Adaptive block selection is used to identify and correct the noise contained in these blocks. Though the system uses a block selection scheme, modifications are performed on pixelto-pixel basis and not on the entire blocks; hence the image accuracy is preserved. PSO is used to identify the noise distribution, and appropriate noise correction techniques are applied to denoise the images. Experiments were conducted using salt and pepper noise, Gaussian noise and a combination of both the noise in the same image. It was observed that the proposed method performed effectively on noise levels up-to 0.5 and was able to produce results with PSNR values ranging from 20 to 30 in most of the cases. Excellent reduction rates were observed on salt and pepper noise and moderate reduction rates were observed on Gaussian noise. Experimental results show that our proposed system has a wide range of applicability in any domain specific image denoising scenario, such as medical imaging, mammogram etc.
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