scholarly journals Effects of hydroalcoholic extract of Glycyrrhiza glabra and glycyrrhizic acid on promastigote and amastigote of Leishmania major (MRHO/IR/75/ER)

2020 ◽  
Vol 19 (74) ◽  
pp. 73-83
Author(s):  
Shima Sheikhi ◽  
Ali Khamesipour ◽  
Tayebeh Radjabian ◽  
Zahra Mojallal Tabatabaei ◽  
Tooba Ghazanfari ◽  
...  
Keyword(s):  
Glycyrrhizic Acid ◽  
Leishmania Major ◽  
Glycyrrhiza Glabra ◽  
Hydroalcoholic Extract

Immunotherapeutic Effects of Glycyrrhiza glabra and Glycyrrhizic Acid on Leishmania major Infected BALB/C Mice

2021 ◽  
Author(s):  
Shima Sheikhi ◽  
Ali Khamesipour ◽  
Tayebeh Radjabian ◽  
Tooba Ghazanfari ◽  
Akram Miramin Mohammadi
Keyword(s):  
Glycyrrhizic Acid ◽  
Leishmania Major ◽  
Glycyrrhiza Glabra

High Heritability of Glycyrrhizic Acid, Glabridin, Liquiritin and Liquiritigenin in Licorice (Glycyrrhiza Glabra L.) Populations of Iran

2021 ◽  
Author(s):  
Ghasem Eghlima ◽  
Mohsen Sanikhani ◽  
Azizollah Kheiry ◽  
Javad Hadian
Keyword(s):  
Coefficient Of Variation ◽  
Morphological Traits ◽  
Glycyrrhizic Acid ◽  
Correlation Coefficients ◽  
Glycyrrhiza Glabra ◽  
Broad Sense ◽  
Phenotypic Correlation ◽  
Broad Sense Heritability ◽  
Narrow Sense Heritability ◽  
Perennial Plant

Abstract Glycyrrhiza glabra L. is an herbaceous, perennial plant with high distribution in Iran. Genetic variability, heritability and correlation among characters in 22 populations of G. glabra L. were studied. The genetic parameters among the traits including phenotypic variances, genotypic variances, genotype by environment variances, broad-sense heritability and genotypic and phenotypic correlation coefficients were studied. Variance components analysis showed that the extent of phenotypic coefficient of variation (PCV) was fairly higher for all the examined traits compared with genotypic coefficient of variation (GCV). Glabridin (GLA) exhibited high GCV and PCV (156.07% and 156.68%, respectively). The broad sense heritability varied from 38.92–99.79% and narrow sense heritability ranged from 9.70 % to 24.94%. Heritability of GLA, glycyrrhizic acid (GLY), liquiritin (LI), liquiritigenin (LIQ), rutin (RU) and rosmarinic acid (RA) were very high, exhibiting more than 97% heritability. Therefore, these critical characteristics can efficiently be selected and inherited in breeding programs. In most traits, the genotypic correlations showed the same direction as the phenotypic correlations. The contents of GLA and LIQ showed a positive correlation with majority of morphological traits. Therefore, selecting individual plants having desired morphological traits can be correlated with high contents of bioactive compounds in the harvested root.

Effect of topical gel prepared with hydroalcoholic extract of Echinacea purpurea on treatment of Leishmania major-induced cutaneous leishmaniasis in BALB/C mice

2016 ◽  
Vol 7 (1) ◽  
pp. 12 ◽  
Author(s):  
Bahador Sarkari ◽  
Hossein Sattari ◽  
MahmoudReza Moein ◽  
AliMohammad Tamadon ◽  
RezaShahriari Rad ◽  
...  
Keyword(s):  
Cutaneous Leishmaniasis ◽  
Leishmania Major ◽  
Echinacea Purpurea ◽  
Hydroalcoholic Extract ◽  
Topical Gel

Enhancement of Glycyrrhizic Acid and Microbial Decontamination of Glycyrrhiza glabra (licorice) by Gamma Radition

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Wachiraporn Pewlong ◽  
Surasak Sajjabut ◽  
Jaruratana Eamsiri ◽  
Sirilak Chookaew ◽  
Kanokporn Boonsirichai
Keyword(s):  
Glycyrrhizic Acid ◽  
Glycyrrhiza Glabra

scholarly journals Chromolithic Method Development, Validation and System Suitability Analysis of Ultra-Sound Assisted Extraction of Glycyrrhizic Acid and Glycyrrhetinic Acid from Glycyrrhiza glabra

2012 ◽  
Vol 7 (8) ◽  
pp. 1934578X1200700 ◽  
Author(s):  
Suphla Gupta ◽  
Rajni Sharma ◽  
Pankaj Pandotra ◽  
Sundeep Jaglan ◽  
Ajai Prakash Gupta
Keyword(s):  
Method Development ◽  
Glycyrrhizic Acid ◽  
Glycyrrhetinic Acid ◽  
Glycyrrhiza Glabra ◽  
Ultra Sound ◽  
Root Extract ◽  
Suitability Analysis ◽  
Ultrasound Assisted Extraction ◽  
Assisted Extraction ◽  
Quantitative Results

An ultrasound-assisted extraction and chromolithic LC method was developed for simultaneous determination of glycyrrhizic acid (GA) and glycyrrhetinic acid (GL) from the root extract of Glycyrrhiza glabra using RPLC-PDA. The developed method was validated according to the International Conference on Harmonisation. The method exhibited good linearity (r2 >0.9989) with high precision and achieved good accuracies between 97.5 to 101.3% of quantitative results. The method is more sensitive and faster (resolved within ten minutes) than the earlier developed methods using normal LC columns.

Artificial Neural Network and Adaptive Neuro-Fuzzy Interface System Modeling of Supercritical CO2 Extraction of Glycyrrhizic Acid from Glycyrrhiza glabra L

2016 ◽  
Vol 11 (3) ◽  
pp. 217-230 ◽  
Author(s):  
Ali Hedayati ◽  
S. M. Ghoreishi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Membership Function ◽  
Glycyrrhizic Acid ◽  
Glycyrrhiza Glabra ◽  
Licorice Root ◽  
Extraction Recovery ◽  
Neuro Fuzzy ◽  
Artificial Neural ◽  
Hidden Layer

Abstract In this study, the extraction of Glycyrrhizic acid (GA) from Glycyrrhiza glabra (licorice) root was investigated by Soxhlet extraction and modified supercritical CO2 with water as co-solvents and 30 min of static extraction time. The high performance liquid chromatography (HPLC) was used to identify and quantitatively determine the amount of extracted GA recovery of supercritical CO2 extraction of GA. The extraction recovery was modeled by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN). Different ANFIS networks (by changing the type of membership functions) were compared with evaluation of networks accuracy in GA recovery prediction and subsequently the suitable network was determined. A three-layer artificial neural network was also developed for modeling of GA extraction from licorice plant root. In this regard, different networks (by changing the number of neurons in the hidden layer and algorithm of network training) were compared with evaluation of networks accuracy in extraction recovery prediction. One-step secant back propagation algorithm with six neurons in hidden layer was found to be the most suitable network and the coefficient of determination (R2) was 98.5 %. Gaussian combination membership function (gauss2mf) using 2 membership function to each input was obtained to be optimum ANFIS architecture with mean square error (MSE) of 0.05,0.17 and 0.07 for training, testing and checking data, respectively.

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