EFFECT OF COPPER ON THE GENERATION TIME AND ANTIOXIDANT POTENTIAL OF A NOVEL ISOLATE OF CHLORELLA EMERSONII KJ725233

Objective: At low concentrations copper is an essential micronutrient for algal growth wherein it plays a vital role as an enzyme cofactor for photosynthetic processes but at high concentrations it functions as a toxic heavy metal. Copper exposure to microalga increases the activity of antioxidative enzymes–catalase, superoxide dismutase, peroxidase along with the induction of chlorosis at higher concentrations. The objective of the present study is to determine the effect of suboptimal concentration of copper on the generation time as well as the antioxidant potential of a novel strain-Chlorella emersonii KJ725233.Methods: The growth of the microalga at the different copper concentrations was monitored by measuring the absorbance at 684 nm. Once the suboptimum copper concentration for the growth of the microalga was determined, the methanolic extracts were evaluated for Total Phenolic Content, Total Flavonoid Contents as well as the antioxidant potential by employing standard methods such as phospho- molybdenum method for Total Antioxidant Capacity and Ferric Reducing Antioxidant Potential.Results: Results indicated that 0.1 µmol of copper stimulated the growth of Chlorella emersonii KJ725233, which was evident from the reduced generation time of the microalga as compared to that of the control and other copper concentrations. The study also proved a 45.69% increase in the antioxidant activity of the microalga on exposure to 0.1 µmol of copper.Conclusion: The present study indicated copper at 0.1 µmol concentration not only acts as a micronutrient but also levies stress resulting in increased antioxidant activity of this novel isolate Chlorella emersonii KJ725233.Keywords: Chlorella emersonii KJ725233, Copper, Generation time, Antioxidan

NUTRITIONAL PROFILE, ANTIOXIDANT, ANTIMICROBIAL POTENTIAL, AND BIOACTIVES PROFILE OF CHLORELLA EMERSONII KJ725233

 Objective: The present study revolved around the nutritional evaluation of Chlorella emersonii KJ725233, a novel non-fastidious Chlorella strain that was isolated from the Western regions of Maharashtra, India, for a probable use as a food supplement.Methods: The nutritional composition of C. emersonii KJ725233 was evaluated in terms of total protein, total lipids, and total carbohydrates content along with its mineral composition. Furthermore, the effect of different solvents on the extraction of the bioactives and hence the antioxidant and antimicrobial activity of C. emersonii KJ725233 was also analyzed. The bioactives extracted in the organic solvents were further identified by gas chromatography–high-resolution mass spectrometry (GC-HRMS).Results: As reported in the literature for commercial Chlorella powder, C. emersonii KJ725233 was found to contain an equivalent concentration of protein, three-fold lipid content, i.e. 36.48±0.52% and 43.58±0.72%, respectively; along with 17.17±0.91% carbohydrates and 6.62±0.16% mineral content. Methanolic content was not only found to contain the highest antioxidant, radical scavenging potential as well as total phenolic content but also exhibited a strong antimicrobial potential against the tested Gram-positive, Gram-negative bacterial and fungal strains. Moreover, sterols, hydrocarbons, and fatty acid methyl esters known antimicrobials and antioxidants were identified when the organic extracts of the microalgae dried biomass were subjected to GC-HRMS analysis.Conclusion: With a well-balanced nutritional composition together with the reservoir of antioxidants and antimicrobials, this native novel isolate of Chlorella thus emerges as a potential food supplement whose consumption would not only enhance the dietary value along with providing antiaging benefits

Correlation of Thyroid Hormones in the Prognosis of Critically Ill Patients

Objective: Non-thyroidal illness syndrome (NTIS) is associated with outcomes in Intensive Care Unit(ICU) patients. The objectives of the study were to assess the prognostic value of complete thyroid profile in critically ill patients and to determine the effect of thyroid hormone level in predicting mortality when used along with acute physiology and chronic health evaluation (APACHE) II score. Methods: The observational study was conducted at a tertiary care centre in Kolhapur, India. Critically ill adult patients admitted to intensive care units with APACHE II >10 was included(n=50). Relevant clinical investigations along with thyroid profile evaluation was carried out and APACHE II was calculated.  Baseline characteristics of patients were compared.  Performance of variables in predicting mortality was analysed. Correlation of APACHE II score with thyroid was also assessed in R software v-3.6.1. Results: The survival rate at ICU discharge was 54%. Mean T3, FT3, and T4 levels were significantly low in non-survivors(p=0.006758, p=0.0245 and p=0.00070 respectively).  Mean APACHE II score was significantly high in non- survivor(p=2.94E-06). APACHE II score was significantly associated with the severity of disease (p=0.0235). APACHE II scores and FT3 were better predictors of mortality compared to other thyroid hormones (AUC =0.8519±0.0535). FT3 showed high correlation with APACHE II score(r=-0.4083; p=0.0032). Inclusion of thyroid hormone levels with APACHE II scores improved the prediction of mortality in critically ill patients by 5.63%. Conclusion: Among thyroid hormones, FT3 is a better predictor of mortality. Use of thyroid hormone levels in conjunction with APACHE II scores improves the prognostication

E-COMMERCE WEBSITE

The business to consumer aspect of electronic commerce (e-commerce) is the most visible business use of the Word Wide Web. Theprimary goal of an e-commerce site is to sell goods and services online.This project is a web based shopping system for an existing shop. The project objective is to deliver the online shopping application.This project is an attempt to provide the advantages of online shopping to customers of a real shop. It helps buying the products in the shop anywhere through internet by using a web site. Thus the customer will get the service of online shopping and home delivery from this shop. This system can be implemented to Sai Supermarket in the locality.If shops are providing an online portal where their customers can enjoy easy shoppingfrom anywhere, the shops won’t be losing any more customers to the trending online shops such asflipkartoreBay.Sincetheapplicationisavailableinthegivensiteitiseasilyaccessibleand always available

E-COMMERCE WEBSITE

The business to consumer aspect of electronic commerce (e-commerce) is the most visible business use of the Word Wide Web. Theprimary goal of an e-commerce site is to sell goods and services online.This project is a web based shopping system for an existing shop. The project objective is to deliver the online shopping application.This project is an attempt to provide the advantages of online shopping to customers of a real shop. It helps buying the products in the shop anywhere through internet by using a web site. Thus the customer will get the service of online shopping and home delivery from this shop. This system can be implemented to Sai Supermarket in the locality.If shops are providing an online portal where their customers can enjoy easy shoppingfrom anywhere, the shops won’t be losing any more customers to the trending online shops such asflipkartoreBay.Sincetheapplicationisavailableinthegivensiteitiseasilyaccessibleand always available

Disease Detection Using Artificial Intelligence

Currently, artificial intelligence is widely used to aid humans in a variety of ways. One area where artificial intelligence is particularly beneficial is medical image detection where diagnostic procedures require the collection and processing of large amounts of data for particular diseases. The topics covered in this paper include Pneumonia, Lung Cancer, and Brain Tumors. Early detection and treatment are crucial when treating these types of diseases. The paper describes the use of a convolutional neural network algorithm in order to process medical images so that it can aid in decision making process and help save time. Machine learning is useful in increasing consistency and accuracy in detection. The highest accuracy that the model has achieve 94.297%

FACIAL FEATURE EXTRACTION USING LBP WITH GABOR FILTER

A Facial Feature Extraction approach is proposed here using LBP. The system first pre-processesthe input image for illumination changes and noise invariance with the helpof Adaptive Histogram Equalization. Then Face detection is proposed and Gabor filter is also applied to produce magnitude pictures. Finally, the proposed LBP is used to extract features of the facial image