Amino acid composition of azolla as affected by strains and population density

1989 ◽  
Vol 117 (2) ◽  
pp. 263-267 ◽  
Author(s):  
N. Sanginga ◽  
C. Van Hove
Keyword(s):  
Amino Acid ◽  
Population Density ◽  
Amino Acid Composition ◽  
Acid Composition

Subcellular immuno-localization, amino acid composition and partial amino acid sequences of alpha-1,4-glucan phosphorylase of Gracilarria spp (Rhodophyta)

1993 ◽  
Vol 89 (1) ◽  
pp. 11-20
Author(s):  
S. Yu ◽  
J.-L. Gomez-Pinchetti ◽  
B. Ek ◽  
G. Garcia-Reina ◽  
M. Pedersen
Keyword(s):  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Amino Acid Sequences ◽  
Glucan Phosphorylase

Effect of maternal diet on the amino acid composition of human uterine fluid

2014 ◽  
Author(s):  
Alexandra Jayne Kermack ◽  
Ying Cheong ◽  
Nick Brook ◽  
Nick Macklon ◽  
Franchesca D Houghton
Keyword(s):  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Maternal Diet ◽  
Uterine Fluid

CHLOROPLAST ULTRASTRUCTURE AND AMINO ACID COMPOSITION OF RESERVE PROTEIN IN GRAIN OF BARLEY AND WHEAT TREATED WITH N,N-DIPHENYLUREA

2013 ◽  
pp. 66-72
Author(s):  
N.P. Tatarintsev ◽  
◽  
G.A. Semenova ◽  
V.D. Kreslavskii ◽  
◽  
...  
Keyword(s):  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Chloroplast Ultrastructure ◽  
Reserve Protein

Changes in Milk Protein and Amino Acid Composition of Dairy Cows in Response to Fatty Liver and Intravenous Glucagon

2008 ◽  
Author(s):  
Gerd Bobe ◽  
Gary L. Lindberg ◽  
Jerry Young ◽  
Donald C. Beitz
Keyword(s):  
Amino Acid ◽  
Fatty Liver ◽  
Dairy Cows ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Milk Protein

Biological Processing of Pea Grain and Secondary Starch Raw Materials to Produce Food and Feed Protein Concentrates

2020 ◽  
Vol 36 (4) ◽  
pp. 49-58
Author(s):  
V.V. Kolpakova ◽  
R.V. Ulanova ◽  
L.V. Chumikina ◽  
V.V. Bessonov
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Mass Fraction ◽  
Geotrichum Candidum ◽  
Protein Concentrate ◽  
Protein Concentrates ◽  
Pea Flour ◽  
Nitrogenous Substances

The goal of the study was to develop a biotechnological process for the production of protein concentrates via bioconversion of pea flour and whey, a secondary product of starch manufacture. Standard and special methods were used to analyze the chemical and biochemical composition of protein concentrates (amino acid, carbohydrate, and fractional) of flour, whey and protein concentrates. It was established that pea flour contains 52.28-57.05% water-soluble nitrogenous substances, 23.04-25.50% salt-soluble, 2.94-4.69% alcohol-soluble compounds, 0-0.61% of soluble glutenine, 6.67-10.40% alkali-soluble glutenine and 5.96-10.86% insoluble sclerotic substances. A mathematical model and optimal parameters of the enzymatic extraction of pea protein with a yield of 65-70% were developed. Ultrasonic exposure increased the yield of nitrogenous substances by 23.16 ± 0.69%, compared with the control without ultrasound. The protein concentrate had a mass fraction of nitrogenous substances of 72.48 ± 0.41% (Nx6.25) and a complete amino acid composition. The microbial conversion by the Saccharomyces cerevisiae 121 and Geotrichum candidum 977 cultures of starch whey which remained after protein precipitation allowed us to obtain feed concentrates from biomass and culture liquid with a protein mass fraction of 61.68-70.48% (Nx6.25). Protein concentrates positively affected the vital signs of rats and their excretory products. A technological scheme was developed to test the complex pea grain and starch whey processing under pilot conditions. pea, protein concentrate, extracts, whey, bioconversion, Geotrichum candidum, Saccharomyces cerevisiae, chemical composition, amino acid composition

Exploring the Potential of Capsaicin Against Cancer Metastasis Based on TGF-β Signaling Modulation Through Module-based Network Pharmacology Approach

2020 ◽  
Vol 17 (5) ◽  
pp. 647-660 ◽  
Author(s):  
Shivananda Kandagalla ◽  
Sharath Belenahalli Shekarappa ◽  
Gollapalli Pavan ◽  
Umme Hani ◽  
Manjunatha Hanumanthappa
Keyword(s):  
Amino Acid ◽  
Amino Acid Composition ◽  
Signaling Pathway ◽  
Acid Composition ◽  
Protein Interaction ◽  
Cancer Metastasis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Mode Analysis ◽  
Network Pharmacology

Background: Capsaicin is an active alkaloid /principal component of red pepper responsible for the pungency of chili pepper. Capsaicin by changing the intracellular redox homeostasis regulate a variety of signaling pathways ultimately producing a divergent cellular outcome. Several reports showed the potential of capsaicin against cancer metastasis, however unexplored molecular mechanism is still an active part of the research. Several growth factors have a critical role during cancer metastasis among them TGF- β signaling play a vital role. Methods: The present study aimed at analyzing capsaicin modulation of TGF-β signaling using network pharmacology approach. The chemical and protein interaction data of capsaicin was curated and abstracted using STITCH4.0, PubChem and ChEMBL database. Further, the compiled data set was subjected to the pathway and functional enrichment analysis using Protein Analysis THrough Evolutionary Relationship (PANTHER) and, Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Meanwhile, the pattern of amino acid composition across the capsaicin targets was analyzed using the EMBOSS Pepstat tool. Capsaicin targets involved in TGF- β were identified and their Protein-Protein Interaction (PPI) network constructed using STRING v10 and Cytoscape (v 3.2.1). From the above-constructed network, the clusters were mined using the MCODE clustering algorithm and finally binding affinity of capsaicin with its targets involved in TGF-β signaling pathway was analyzed using Autodock Vina. Results: The analysis explored capsaicin targets and, their associated functional and pathway annotations. Besides, the analysis also provides a detailed distinct pattern of amino acid composition across the capsaicin targets. The capsaicin targets described as MAPK14, JUN, SMAD3, MAPK3, MAPK1 and MYC involved in TGF-β signaling pathway through pathway enrichment analysis. The binding mode analysis of capsaicin with its targets has shown high affinity with MAPK3, MAPK1, JUN and MYC. Conclusion: The study explores the potential of capsaicin as a potent modulator of TGF-β signaling pathway during cancer metastasis and proposes new methodology and mechanism of action of capsaicin against TGF- β signaling pathway.

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