PREDICTING THE COMBINED EFFECT OFZATARIA MULTIFLORAESSENTIAL OIL, PH AND TEMPERATURE ON THE GROWTH OFSTAPHYLOCOCCUS AUREUSUSING ARTIFICIAL NEURAL NETWORKS

Comprehensive study on applications of artificial neural network in food process modeling

Artificial neural network (ANN) is a simplified model of the biological nervous system consisting of nerve cells or neurons. The application of ANN to food process engineering is relatively novel. ANN had been employed in diverse applications like food safety and quality analyses, food image analysis, and modeling of various thermal and non-thermal food-processing operations. ANN has the ability to map nonlinear relationships without any prior knowledge and predicts responses even with incomplete information. Every neural network possesses data in the form of connection weights interconnecting lines between the input to hidden layer neurons and weights of hidden to output layer neurons, which has a significant role in predicting the output data. The applications of ANN in different unit operations in food processing were described that includes theoretical developments using intelligent characteristics for adaptability, automatic learning, classification, and prediction. The parallel architecture of ANN resulted in a fast response and low computational time making it suitable for application in real-time systems of different food process operations. The predicted responses obtained by the ANN model exhibited high accuracy due to lower relative deviation and root mean squared error and higher correlation coefficient. This paper presented the various applications of ANN for modeling nonlinear food engineering problems. The application of ANN in the modeling of the processes such as extraction, extrusion, drying, filtration, canning, fermentation, baking, dairy processing, and quality evaluation was reviewed.HIGHLIGHTS1. This paper discusses application of ANN in different emerging trends in food process.2. Application of ANN to develop non-linear multivariate modeling is illustrated.3. ANNs have been shown to be useful tool for prediction of outcomes with high accuracy.4. ANN resulted in fast response making it suitable for application in real time systems.

Natural products against Alzheimer's disease: Pharmaco-therapeutics and biotechnological interventions

Alzheimer's disease (AD) is a severe, chronic and progressive neurodegenerative disease associated with memory and cognition impairment ultimately leading to death. It is the commonest reason of dementia in elderly populations mostly affecting beyond the age of 65. The pathogenesis is indicated by accumulation of the amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFT) in brain tissues and hyperphosphorylation of tau protein in neurons. The main cause is considered to be the formation of reactive oxygen species (ROS) due to oxidative stress. The current treatment provides only symptomatic relief by offering temporary palliative therapy which declines the rate of cognitive impairment associated with AD. Inhibition of the enzyme acetylcholinesterase (AChE) is considered as one of the major therapeutic strategies offering only symptomatic relief and moderate disease-modifying effect. Other non-cholinergic therapeutic approaches include antioxidant and vitamin therapy, stem cell therapy, hormonal therapy, use of antihypertensive or lipid-lowering medications and selective phosphodiesterase (PDE) inhibitors, inhibition of β-secretase and γ-secretase and Aβ aggregation, inhibition of tau hyperphosphorylation and intracellular NFT, use of nonsteroidal anti-inflammatory drugs (NSAIDs), transition metal chelators, insulin resistance drugs, etanercept, brain-derived neurotrophic factor (BDNF) etc. Medicinal plants have been reported for possible anti-AD activity in a number of preclinical and clinical trials. Ethnobotany, being popular in China and in the Far East and possibly less emphasized in Europe, plays a substantial role in the discovery of anti-AD agents from botanicals. Chinese Material Medica (CMM) involving Chinese medicinal plants has been used traditionally in China in the treatment of AD. Ayurveda has already provided numerous lead compounds in drug discovery and many of these are also undergoing clinical investigations. A number of medicinal plants either in their crude forms or as isolated compounds have exhibited to reduce the pathological features associated with AD. In this present review, an attempt has been made to elucidate the molecular mode of action of various plant extracts, phytochemicals and traditional herbal formulations investigated against AD as reported in various preclinical and clinical tests. Herbal synergism often found in polyherbal formulations were found effective to combat disease heterogeneity as found in complex pathogenesis of AD. Finally a note has been added to describe biotechnological improvement, genetic and genomic resources and mathematical and statistical techniques for empirical model building associated with anti-AD plant secondary metabolites and their source botanicals.