COMPARISON OF AMINO ACIDS IN 8 DIFFERENT BOILED TROPICAL FRUITS

Objective: To determine the protein quality, especially the amino acid content of 8 tropical fruits both raw and boiled samples. Eight different tropical fruits were used in the study (Apricot, Jamun, Dragonfruit, Pomegranate, Mangustan, Litchi, Jackfruit, and Kiwi.Methods: Ninhydrin method was used for the estimation of the concentration of amino acids present in the above fruits. Raw and boiled fruits were used for the study.Results: Both raw and boiled forms which showed thats Jamun and Mangustan contained highest concentration amino acids whereas apricot shows the lowest concentration of amino acids except in Jamun which showed higher values in the raw fruit whereas in others the boiled samples showed higher values.Conclusion: It was evident that tropical fruits have a good balance of the essential amino acids (both raw and boiled fomr) which provide significant sources of protein in our diet

Pharmacokinetic evaluation of newly developed isradipine sustained release formulation

A specific and efficient method using High Performance Liquid Chromatography (HPLC) has been developed to validate the pharmacokinetics of sustained-release formulation containing Isradipine. The objective of the present study is to develop and validate PK of sustained release formulation containing Isradipine. The plasma samples of Isradipine were extracted using the protein precipitation technique (PPT). The detection wavelength of Isradipine, which was 325nm, was determined using UV spectrophotometer. Reversed phase Thermos c18 column was used for separation. 10mM ammonium acetate buffer (pH 4) and acetonitrile at a ratio of 20:80% v/v was used as the mobile phase with the flow rate of 1.0 ml/min. The linearity achieved in this method was in the range of 10-120 ng/ml. HPLC method provides extremely precise results and is an excellent and efficient method compared to others. The development of a sustained release formulation offers advantages such as prolonged blood levels of the drug and improved patient compliance. The formulated sustained release tablets containing Isradipine is capable of exhibiting sustained release properties, stable and feasible for industrial scale production. Thus they are capable of reducing the dose intake, minimize the blood level oscillations, dose related adverse effects, cost and ultimately improve the patient compliance in the hypertension

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

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Modified CNN with Adam and Nadam optimizers for emotion recognition using facial expressions

People communicate using one of the communication types of facial expressions. Human feelings are detected through facial expressions to interpret their present state of mood. It stimulates researchers to work in the field of emotion recognition. The design of deep learning models is essential to interpret the human current mind state by capturing the pattern of the facial gesture through their facial expressions. This study proposed a customized Convolutional Neural Network (CNN) with various optimizers Adaptive Moment Estimation (Adam) and Nesterov-accelerated Adaptive Moment Estimation (Nadam) to improve emotion recognition using the dataset FER-2013. The customized proposed model is designed by varying the number of convolution layers, filters, filter sizes, and optimizers. The emotions are recognized using softmax activation in the output layer. The experimental results have proved that the proposed model classified the facial expressions with accuracy of 0.841, 0.826 using Nadam and Adam optimizers respectively