STUDIES ON KINETIC PARAMETERS AND BIOCHEMICAL CHARACTERISTICS OF POLYPHENOL OXIDASE PURIFIED FROM JACKFRUIT (ARTOCARPUS HETEROPHYLLUS) WASTE

Objectives: Polyphenol oxidase activity was extensively studied in jackfruit for its role in enzymatic browning. PPO and the phenolic compound play a vital role in defensive mechanism against pest and diseases. Thus, to facilitate further studies in jack fruit waste, Polyphenol oxidase [PPO] was purified and characterized.Methods: Partial Purification of PPO from waste done through a sequential process of ammonium sulfate precipitation, dialysis and ion-exchange chromatography [DEAE- Cellulose]. Then the partially purified PPO was subjected to check various parameters like molecular weight and kinetic activity, the following characteristics of enzyme are checked: SDS-PAGE, pH, temperature, thermal stability, heat inactivation, metal ions, surfactants and inhibitor.Results: Purified PPO resulted in ~23 folds enriched in the specific activity of 1360 [µkat/mg] and it was found to be the monomer with a molecular weight of 63 kDa revealed by Coomasie Brilliant Blue staining. PPO exhibited optimum activity at pH 7.0 and temperature 20oC. PPO showed the maximum stability between pH 6.4- 7.6 at 10 oC - 40 oC. PPO showed the enzyme activity towards Diphenol> Triphenol> Monophenol, the substrate specificity was especially high towards the catechol at 0.1 M. The PPO activity was activated by Mn2+, Triton X- 100, EDTA, Sorbic acid and Citric acid, but inhibited by L- cysteine, Ascorbic acid, SDS, Cetyl trimethyl ammonium bromide [CTAB], K+, Zn2+, Ca2+ and Mg2+. Kinetic constant for PPO was found to be km= 15.82 mM and Vmax= 2182 U/ml min using catechol as substrate.Conclusion: Partial Purification of PPO from waste done through a sequential process of ammonium sulfate precipitation, dialysis and ion-exchange chromatography [DEAE- Cellulose]. The best substrate for PPO was identified as catechol [diphenol] and best inhibitor was L-cysteine and ascorbic acid. Â

Identification of Nephelium lappaceum leaves phenolic and flavonoid component with radical scavenging, antidiabetic and antibacterial potential

360-365Nephelium lappaceum Linn. (Rambutan) is traditionally claimed, as a source of natural antioxidants and for its use in the treatment of diabetes and bacterial infections. The present study investigates the in vitro effect of ethanolic Rambutan leaves extract (NL) for its antioxidant effect, α-glucosidase, α-amylase enzyme inhibition, and antibacterial potentials. The total phenolic, total flavonoid content of NL was quantified and were expressed in terms of gallic acid (19.6±0.04 mg GAE/g) and rutin equivalents (16.7±0.01 mg RUE/g) respectively. The antioxidant assay revealed that NL exhibited significant inhibition of DPPH (IC50±SEM: 1.52±0.03 μg/mL) and ABTS (IC50±SEM: 1.295±0.05 μg/mL) radicals. NL also inhibited both α-amylase (IC50±SEM: 2.624±0.07 μg/mL), α-glucosidase (IC50±SEM: 2.416±0.06 μg/mL) enzyme activities, supported by its antioxidant potential and its phenolic and flavonoid content. The antibacterial activity was screened against seven human pathogenic ATCC strains for which the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were recorded. The selected MIC dose was tested, confirmed by Kirby-Bauer agar well diffusion method. NL exhibited MIC and MBC of 62.5 μg/mL and 125 μg/mL against B.subtilis and E.coli respectively. The results support the scientific claim of NL for its antioxidant, antidiabetic and antibacterial potential

Identification of Nephelium lappaceum leaves phenolic and flavonoid component with radical scavenging, antidiabetic and antibacterial potential

360-365Nephelium lappaceum Linn. (Rambutan) is traditionally claimed, as a source of natural antioxidants and for its use in the treatment of diabetes and bacterial infections. The present study investigates the in vitro effect of ethanolic Rambutan leaves extract (NL) for its antioxidant effect, α-glucosidase, α-amylase enzyme inhibition, and antibacterial potentials. The total phenolic, total flavonoid content of NL was quantified and were expressed in terms of gallic acid (19.6±0.04 mg GAE/g) and rutin equivalents (16.7±0.01 mg RUE/g) respectively. The antioxidant assay revealed that NL exhibited significant inhibition of DPPH (IC50±SEM: 1.52±0.03 μg/mL) and ABTS (IC50±SEM: 1.295±0.05 μg/mL) radicals. NL also inhibited both α-amylase (IC50±SEM: 2.624±0.07 μg/mL), α-glucosidase (IC50±SEM: 2.416±0.06 μg/mL) enzyme activities, supported by its antioxidant potential and its phenolic and flavonoid content. The antibacterial activity was screened against seven human pathogenic ATCC strains for which the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were recorded. The selected MIC dose was tested, confirmed by Kirby-Bauer agar well diffusion method. NL exhibited MIC and MBC of 62.5 μg/mL and 125 μg/mL against B.subtilis and E.coli respectively. The results support the scientific claim of NL for its antioxidant, antidiabetic and antibacterial potential

Reliable water quality prediction and parametric analysis using explainable AI models

The consumption of water constitutes the physical health of most of the living species and hence management of its purity and quality is extremely essential as contaminated water has to potential to create adverse health and environmental consequences. This creates the dire necessity to measure, control and monitor the quality of water. The primary contaminant present in water is Total Dissolved Solids (TDS), which is hard to filter out. There are various substances apart from mere solids such as potassium, sodium, chlorides, lead, nitrate, cadmium, arsenic and other pollutants. The proposed work aims to provide the automation of water quality estimation through Artificial Intelligence and uses Explainable Artificial Intelligence (XAI) for the explanation of the most significant parameters contributing towards the potability of water and the estimation of the impurities. XAI has the transparency and justifiability as a white-box model since the Machine Learning (ML) model is black-box and unable to describe the reasoning behind the ML classification. The proposed work uses various ML models such as Logistic Regression, Support Vector Machine (SVM), Gaussian Naive Bayes, Decision Tree (DT) and Random Forest (RF) to classify whether the water is drinkable. The various representations of XAI such as force plot, test patch, summary plot, dependency plot and decision plot generated in SHAPELY explainer explain the significant features, prediction score, feature importance and justification behind the water quality estimation. The RF classifier is selected for the explanation and yields optimum Accuracy and F1-Score of 0.9999, with Precision and Re-call of 0.9997 and 0.998 respectively. Thus, the work is an exploratory analysis of the estimation and management of water quality with indicators associated with their significance. This work is an emerging research at present with a vision of addressing the water quality for the future as well

Key stages in mammary gland development - Involution: apoptosis and tissue remodelling that convert the mammary gland from milk factory to a quiescent organ

Involution of the mammary gland is an essential process that removes the milk-producing epithelial cells when they become redundant at weaning. It is a two-step process that involves the death of the secretory epithelium and its replacement by adipo-cytes. During the first phase, remodelling is inhibited and apoptotic cells can be seen in the lumena of the alveoli. In the second phase, apoptosis is accompanied by remodelling of the surrounding stroma and re-differentiation of the adipocytes. Considerable effort has been directed towards understanding the molecular mechanisms of the involution process and this has resulted in the identification of the principal signalling pathways involved

Single-Cell Epigenomics and Functional Fine-Mapping of Atherosclerosis GWAS Loci

Rationale: Genome-wide association studies have identified hundreds of loci associated with coronary artery disease (CAD). Many of these loci are enriched in cisregulatory elements but not linked to cardiometabolic risk factors nor to candidate causal genes, complicating their functional interpretation. Objective: Single-nucleus chromatin accessibility profiling of the human atherosclerotic lesions was used to investigate cell type-specific patterns of cisregulatory elements, to understand transcription factors establishing cell identity, and to interpret CAD-relevant, noncoding genetic variation. Methods and Results: We used single-nucleus ATAC-seq (assay for transposase-accessible chromatin with sequencing) to generate DNA accessibility maps in >7000 cells derived from human atherosclerotic lesions. We identified 5 major lesional cell types including endothelial cells, smooth muscle cells, monocyte/macrophages, natural killer/T cells, and B cells and further investigated subtype characteristics of macrophages and smooth muscle cells transitioning into fibromyocytes. We demonstrated that CAD-associated genetic variants are particularly enriched in endothelial and smooth muscle cell-specific open chromatin. Using single-cell coaccessibility and cis-expression quantitative trait loci information, we prioritized putative target genes and candidate regulatory elements for approximate to 30% of all known CAD loci. Finally, we performed genome-wide experimental fine-mapping of the CAD variants identified in genome-wide association studies using epigenetic quantitative trait loci analysis in primary human aortic endothelial cells and self-transcribing active regulatory region sequencing (STARR-Seq) massively parallel reporter assay in smooth muscle cells. This analysis identified potential causal single-nucleotide polymorphisms (SNPs) and the associated target gene for over 30 CAD loci. We present several examples where the chromatin accessibility and gene expression could be assigned to one cell type predicting the cell type of action for CAD loci. Conclusions: These findings highlight the potential of applying single-nucleus ATAC-seq to human tissues in revealing relative contributions of distinct cell types to diseases and in identifying genes likely to be influenced by noncoding genome-wide association study variants.</p

MGEx-Udb: A Mammalian Uterus Database for Expression-Based Cataloguing of Genes across Conditions, Including Endometriosis and Cervical Cancer

Gene expression profiling of uterus tissue has been performed in various contexts, but a significant amount of the data remains underutilized as it is not covered by the existing general resources.). The database can be queried with gene names/IDs, sub-tissue locations, as well as various conditions such as the cervical cancer, endometrial cycles and disorders, and experimental treatments. Accordingly, the output would be a) transcribed and dormant genes listed for the queried condition/location, or b) expression profile of the gene of interest in various uterine conditions. The results also include the reliability score for the expression status of each gene. MGEx-Udb also provides information related to Gene Ontology annotations, protein-protein interactions, transcripts, promoters, and expression status by other sequencing techniques, and facilitates various other types of analysis of the individual genes or co-expressed gene clusters.In brief, MGEx-Udb enables easy cataloguing of co-expressed genes and also facilitates bio-marker discovery for various uterine conditions

SPARC functions as an inhibitor of adipogenesis

Adipogenesis, a key step in the pathogenesis of obesity, involves extensive ECM remodeling, changes in cell-ECM interactions, and cytoskeletal rearrangement. Matricellular proteins regulate cell-cell and cell-ECM interactions. Evidence in vivo and in vitro indicates that the prototypic matricellular protein, SPARC, inhibits adipogenesis and promotes osteoblastogenesis. Herein we discuss mechanisms underlying the inhibitory effect of SPARC on adipogenesis. SPARC enhances the Wnt/β-catenin signaling pathway and regulates the expression and posttranslational modification of collagen. SPARC might drive preadipocytes away from the status of growth arrest and therefore prevent terminal differentiation. SPARC could also decrease WAT deposition through its negative effects on angiogenesis. Therefore, several stages of white adipose tissue accumulation are sensitive to the inhibitory effects of SPARC