Literature DB >> 30948062

Studies on olive-and silicone-oils-based Janus macroemulsions containing ginger to manage primary dysmenorrheal pain.

Diksha Puri1, Gopal Lal Khatik1, Tamilvanan Shunmugaperumal2.   

Abstract

Ginger (GIN) powder-loaded oil-in-water (o/w) macroemulsions were prepared based on olive-and silicone-oils. The dispersed oil droplets with paired-beans structure were evident and thus the final emulsion can be termed as Janus macroemulsions. The objectives of the present study are (1) to identify the marker compound present in GIN powder via HPLC analysis, (2) to process the GIN powder via anti-solvent precipitation technique, (3) to see the solubility of GIN powder in various single oils or oil combination, (4) to optimize the GIN-loaded o/w macroemulsions using the central composite design (CCD) with respect to mean particle size of dispersed oil droplets and highest percentage drug entrapment efficiency values (DEE) and (5) to evaluate the pain reducing activity of optimized GIN-loaded macroemulsion via in vivo primary dysmenorrhea (PD) mice model. Both predicted and obtained values of percentage DEE (76.29 Vs.76.09) and mean particle size (245.99 Vs. 272.51 μm) were almost the same indicating the CCD statistical design applicability. The optimized Janus macroemulsion was stable at 4 °C for over a period of 90 days. Using the PD mice model, the counting of writhing reaction produced by the tested GIN-loaded macroemulsions at low and high doses did not reveal significant difference in comparison to the positive control (aspirin treated). Only the high dose of GIN-loaded macroemulsion was able to restore the uterine tissue's normal histomorphological structure after the H & E staining. Nevertheless, the paired beans structure should be tested for entrapping the plant-derived drugs having dissimilar physicochemical characteristics but similar therapeutic activity.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Central composite design; Ginger; Janus macroemulsion; Marker compound; Pain; Primary dysmenorrhea mice model

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Year:  2019        PMID: 30948062     DOI: 10.1016/j.msec.2019.01.137

Source DB:  PubMed          Journal:  Mater Sci Eng C Mater Biol Appl        ISSN: 0928-4931            Impact factor:   7.328


  1 in total

1.  Application of Design of Experiments® Approach-Driven Artificial Intelligence and Machine Learning for Systematic Optimization of Reverse Phase High Performance Liquid Chromatography Method to Analyze Simultaneously Two Drugs (Cyclosporin A and Etodolac) in Solution, Human Plasma, Nanocapsules, and Emulsions.

Authors:  Syed Nazrin Ruhina Rahman; Oly Katari; Datta Maroti Pawde; Gopi Sumanth Bhaskar Boddeda; Abhinab Goswami; Srinivasa Rao Mutheneni; Tamilvanan Shunmugaperumal
Journal:  AAPS PharmSciTech       Date:  2021-05-13       Impact factor: 3.246

  1 in total

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