A REVIEW ON THE PHARMACOLOGICAL AND TRADITIONAL PROPERTIES OF MIMOSA PUDICA

Consumption of fruits and vegetables fight against oxidative damage by inhibiting or reducing free radicals and reactive oxygen species. Mimosa pudica is a perennial herb and belongs to the family Fabaceae. Epidemiological studies have shown that M. pudica contains metabolites such as phenols and flavonoid compounds which possess pharmacological properties such as antidiabetic, antimicrobial, antiulcer, antidepressants and anti-inflammatory. Ecological studies have shown that M. pudica grows in all types of soil which can survive in soil with low nutrient concentration. It usually requires disturbed soil to establish itself. It is commonly seen in the wastelands and along roadsides, which is an ethnomedical plant that may be used in managing various types of disease. Valuable information and literature on M. pudica are analysed and consulted using a different database such as Google Scholar, Google, Science Direct, Web of Science, Academic Journals and Pubmed. This review article summarises the pharmacological properties of M. pudica

PHYLOGENETIC ANALYSIS OF COLD SHOCK PROTEINS IN PSEUDOMONAS SPECIES

Objective: The present study focuses on the determination of the relativity of the different types of cold shock proteins.Methods: Our study was to determine the relationship among the types of CSPs. Three different strains of pseudomonas genus, Pseudomonas fluorescens, Pseudomonas aeruginosa and Pseudomonas putida were chosen and molecular profiling was performed. The sequences thus obtained were subjected to multiple sequence analysis in ClustalW database. The molecular evolution and phylogenetic study have been carried out using phylodraw.Results: The phylogenetic analysis has clearly revealed the evolutionary pattern of cold shock proteins in pseudomonas species and the current stress of mutation among the strains.Conclusion: Phylogenetic analysis of cold shock proteins has clearly shown that important conserved sequences can be very useful to study the phylogeny of bacteria

ANTI-INFLAMMATORY EFFECT OF ZINGIBER OFFICINALE ON SPRAGUE DAWLEY RATS

ABSTRACTObjective: To investigate the anti-inflammatory effect of aqueous extract of Zingiber officinale on carrageenan-induced inflammation on SpragueDawley (SD) rats.Methods: SD rats were divided into six of five groups and allowed to acclimatize for 1 week. Inflammation was induced on the animal by injecting theright hand paw with carrageenan (0.1 ml of 1%). Group 1 was given normal saline and served as a control. Group 2 was fed with food and water andserved as the carrageenan control. Group 3 was given 200 mg/kg aqueous extract of ginger, Group 4 with 400 mg/kg aqueous extract of ginger, andGroup 5 with 150 mg/kg diclofenac sodium (reference drug for inflammation).Results: The paw edema in carrageenan-induced SD rats was considerably reduced by treating with 400 mg/kg aqueous ginger extracts whencompared to the untreated SD rats (p<0.001).Conclusion: This study indicates that aqueous extract of Z. officinale possesses anti-inflammatory properties.Keywords: Anti-inflammatory, Sprague Dawley rats, Zingiber officinale, Carrageenan, Edem

Cardiovascular diseases prediction by machine learning incorporation with deep learning

It is yet unknown what causes cardiovascular disease (CVD), but we do know that it is associated with a high risk of death, as well as severe morbidity and disability. There is an urgent need for AI-based technologies that are able to promptly and reliably predict the future outcomes of individuals who have cardiovascular disease. The Internet of Things (IoT) is serving as a driving force behind the development of CVD prediction. In order to analyse and make predictions based on the data that IoT devices receive, machine learning (ML) is used. Traditional machine learning algorithms are unable to take differences in the data into account and have a low level of accuracy in their model predictions. This research presents a collection of machine learning models that can be used to address this problem. These models take into account the data observation mechanisms and training procedures of a number of different algorithms. In order to verify the efficacy of our strategy, we combined the Heart Dataset with other classification models. The proposed method provides nearly 96 percent of accuracy result than other existing methods and the complete analysis over several metrics has been analysed and provided. Research in the field of deep learning will benefit from additional data from a large number of medical institutions, which may be used for the development of artificial neural network structures

An Understanding of the Latest Pathophysiological Mechanisms of Pancreatic Cells in Diabetes

Beta cell multiplication happens because of insulin opposition during the advancement of diabetes. Since beta cells have a low limit with regards to generation, this compensatory multiplication could rush cell maturing and eventually cause diabetes. After beta cell development in lipoglucotoxicity, we checked out at the chance of cell senescence. High-fat eating routine incited diabetic C57BL/6J mice were read up for senescence-related beta cell markers. After 4 and 1 years of consuming a high-fat diet, intraperitoneal glucose resilience tests (IPGTTs), histochemical validation of Ki-67 and p38, senescence-associated -galactosidase, and -cell mass were conducted. There was a 2.2-overlay expansion in beta cell multiplication and a 3.1-overlap expansion in beta cell mass contrasted with the benchmark group following 4 months in the IPGTT. Following 1 year, AUC insulin was plainly lower, Ki-67-positive beta-cell repeat rate was 33% contrasted with the benchmark gathering, and senescence-related beta-galactosidase-positive region was 4.7 times higher than the benchmark bunch. about its necessity and its importance in the development of society are highlighte

Transcriptome analysis during fruit developmental stages in durian (Durio zibethinus Murr.) var. D24

Abstract Durian (Durio zibethinus Murr.) fruits are famous for their unique aroma. This study analysed the Durian fruit transcriptome to discover the expression patterns of genes and to understand their regulation. Three developmental stages of Durian fruit, namely, early [90 days post-anthesis (DPA)], mature (120 DPA), and ripen (127 DPA), were studied. The Illumina HiSeq platform was used for sequencing. The sequence data were analysed using four different mapping aligners and statistical methods: CLC Genomic Workbench, HISAT2+DESeq2, Tophat+Cufflinks, and HISAT2+edgeR. The analyses showed that over 110 million clean reads were mapped to the Durian genome, yielding 19,976, 11,394, 17,833, and 24,351 differentially expressed genes during 90-127 days post-anthesis. Many identified differentially expressed genes were linked to the fruit ripening processes. The data analysis suggests that most genes with increased expression at the ripening stage were primarily involved in the metabolism of cofactors and vitamins, nucleotide metabolism, and carbohydrate metabolism. Significantly expressed genes from the young to mature stage were mainly associated with carbohydrate metabolism, amino acid metabolism, and cofactor and vitamin metabolism. The transcriptome data will serve as a foundation for understanding Durian fruit development-specific genes and could be helpful in fruit’s trait improvement

Identification of Metabolites Changes and Quality in Strawberry Fruit: Effect of Cultivation in High Tunnel and Open Field

Strawberry has gained increasing popularity all over the world due to its fruit properties. This popularity is due to the phytochemicals that strawberries have. The aim of this study is to reveal the effect of cultivation in open field and high tunnel on agromorphological and biochemical properties of strawberries. In this study, fruit yield and fruit quality characteristics of some strawberry varieties grown in open field and high tunnel were investigated. The highest fruit yield, fruit weight and titratable acidity were obtained in high tunnel grown Albion cultivar (542.743 g/plant, 14.927 g/fruit and 1.047%, respectively). While there was no statistical difference between cultivars and treatments in terms of soluble solids content and pH, fruit count was higher in Albion and Kabarla cultivars in both treatments compared to other cultivars (p < 0.05). Among the phenolic compounds, gallic acid was determined to be higher (between 9.246–31.680 mg/100 g) than other phenolics. Considering the organic acid content, malic acid was determined as the dominant organic acid in Kabarla cultivar (870.729 mg/100 g). In addition, in terms of vitamin C content, Rubygem cultivar stood out in both applications. Phenolic compound and organic acid contents varied in terms of varieties and applications. As a result, strawberry fruit, which is an important fruit in terms of fruit quality and consumption diversity, has been found to have high phenolic compounds and organic acid content, although it varies in all varieties and applications

Integration of Innovative Technologies in the Agri-Food Sector: The Fundamentals and Practical Case of DNA-Based Traceability of Olives from Fruit to Oil

Several socio-economic problems have been hidden by the COVID-19 pandemic crisis. Particularly, the agricultural and food industrial sectors have been harshly affected by this devastating disease. Moreover, with the worldwide population increase and the agricultural production technologies being inefficient or obsolete, there is a great need to find new and successful ways to fulfill the increasing food demand. A new era of agriculture and food industry is forthcoming, with revolutionary concepts, processes and technologies, referred to as Agri-food 4.0, which enables the next level of agri-food production and trade. In addition, consumers are becoming more and more aware about the origin, traceability, healthy and high-quality of agri-food products. The integration of new process of production and data management is a mandatory step to meet consumer and market requirements. DNA traceability may provide strong approach to certify and authenticate healthy food products, particularly for olive oil. With this approach, the origin and authenticity of products are confirmed by the means of unique nucleic acid sequences. Selected tools, methods and technologies involved in and contributing to the advance of the agri-food sector are presented and discussed in this paper. Moreover, the application of DNA traceability as an innovative approach to authenticate olive products is reported in this paper as an application and promising case of smart agriculture

Sustainable Mulberry (<i>Morus nigra</i> L., <i>Morus alba</i> L. and <i>Morus rubra</i> L.) Production in Eastern Turkey

In this study, a total of 55 wild-grown mulberry landraces belonging to Morus alba L., Morus rubra L., and Morus nigra L. species (Rosales order, Moraceae family, Morus L. genus) were sampled around the Van Lake basin, and some fruit characteristics were determined. All landraces are naturally grown in the Lake Van basin under pesticide-free conditions. As fruit character, phenolic compounds (gallic acid, catechin, quercetin, protocatechuic acid, vanillic acid, rutin, chlorogenic acid, caffeic acid, syringic acid, p-coumaric acid, ferulic acid, and phlorizin) and organic acids (malic acid, citric acid, tartaric acid, succinic acid, fumaric acid and ascorbic acid) were determined. Principal component analysis (PCA) was performed to determine the correlation between mulberry species in terms of biochemical compounds. As a result of PCA-biplot analysis, two variations were sufficient to explain the correlation between phenolic compounds and organic acids. This ratio reveals that mulberry species are separated with sharp boundaries in terms of biochemical compounds. Chlorogenic acid and rutin content were high in all mulberry landraces. The highest chlorogenic acid content was detected in landrace 65VN03 belonging to M. rubra (3.778 mg/g), 65GV12 belonging to M. nigra (3.526 mg/g), 13AD08 belonging to M. rubra (2.461 mg/g), and 13AH02 belonging to M. rubra (6.246 mg/g) landraces. In terms of organic acid content, malic acid was the dominant organic acid for genotypes. The rich bioactive compounds make M. alba, M. rubra, and M. nigra landraces as cultivar candidates for breeding purposes. It is a valuable source of bioactive agents that may have prevented humans from oxidative-stress-related diseases

Identification of key biomarkers and associated pathways of pancreatic cancer using integrated transcriptomic and gene network analysis

Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the CDKN1A, IL6, and MYC genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer