Synthetic and natural antimicrobials as a control against food borne pathogens: A review.

Food borne pathogens are one of the most common yet concerning cause of illnesses around the globe. These microbes invade the body via food items, through numerous mediums of contamination and it is impossible to completely eradicate these organisms from food. Extensive research has been made regarding their treatment. Unfortunately, the only available treatment currently is by antibiotics. Recent exponential increase in antibiotic resistance and the side effect of synthetic compounds have established a need for alternate therapies that could be utilized either on their own or along with antibiotics to provide protection against food-borne diseases. The aim of this review is to provide information regarding some common food borne diseases, their current and possible natural treatment. It will include details regarding some common foodborne pathogens, the disease they cause, prevalence, manifestations and treatment of the respective disease. Some natural modes of potential treatment will be summarized, which including phytochemicals, derived from plants either as crude extracts or as purified form and Bacteriocins as microbial based treatment, obtained from various types of bacteria. The paper will describe their mechanism of action, classification, susceptible organisms, some antimicrobial compounds and producing organisms, application in food systems and as potential treatment. Along with that, synthetic treatment i.e., antibiotics will be discussed including the first-line treatment of some common food borne infections, prevalence and mechanism of resistance against antibiotics in the pathogens.

Hybrid Features and Mediods Classification based Robust Segmentation of Blood Vessels.

Retinal blood vessels are the source to provide oxygen and nutrition to retina and any change in the normal structure may lead to different retinal abnormalities. Automated detection of vascular structure is very important while designing a computer aided diagnostic system for retinal diseases. Most popular methods for vessel segmentation are based on matched filters and Gabor wavelets which give good response against blood vessels. One major drawback in these techniques is that they also give strong response for lesion (exudates, hemorrhages) boundaries which give rise to false vessels. These false vessels may lead to incorrect detection of vascular changes. In this paper, we propose a new hybrid feature set along with new classification technique for accurate detection of blood vessels. The main motivation is to lower the false positives especially from retinal images with severe disease level. A novel region based hybrid feature set is presented for proper discrimination between true and false vessels. A new modified m-mediods based classification is also presented which uses most discriminating features to categorize vessel regions into true and false vessels. The evaluation of proposed system is done thoroughly on publicly available databases along with a locally gathered database with images of advanced level of retinal diseases. The results demonstrate the validity of the proposed system as compared to existing state of the art techniques.