Coumarins and a Naphthyl Labdanoate Diarabinoside from the Fruits of Peucedanum grande C. B. Clarke

2012 ◽  
Vol 67 (11-12) ◽  
pp. 580-586 ◽  
Author(s):  
Mohammad Aslam ◽  
Mohammed Ali ◽  
Rameshwar Dayal ◽  
Kalim Javed
Keyword(s):  
Data Analysis ◽  
Spectral Data ◽  
Chemical Reactions ◽  
Wistar Rats ◽  
Methanolic Extract ◽  
Nephroprotective Activity ◽  
Coumarin 1 ◽  
Spectral Data Analysis

Phytochemical investigations of the methanolic extract of the fruits of Peucedanum grande C. B. Clarke (Apiaceae) led to the identification of three coumarins and a naphthyl labdanoate diarabinoside characterized as 5-hydroxy-6-isopranyl coumarin (1), 5,6-furanocoumarin (2), 7-methoxy-5,6-furanocoumarin (3), and labdanyl-3α-ol-18-(3’’’-methoxy-2’’’- naphthyl-oate)-3α-L-arabinofuranosyl-(2’→1’’)-α-L-arabinofuranoside (4). The structures of these compounds were identified on the basis of spectral data analysis and chemical reactions. The methanolic extract and 4 showed nephroprotective activity against gentamicininduced nephrotoxicity in Wistar rats.

PHYTOCHEMICAL INVESTIGATIONS OF THE LEAVES AND FLOWERS OF HIBISCUS ROSA-SINENSIS L.

INDIAN DRUGS ◽  
2017 ◽  
Vol 54 (10) ◽  
pp. 30-37
Author(s):  
M. Ali ◽  
◽  
P Alam ◽  
V Singh ◽  
M Jameel ◽  
...  
Keyword(s):  
Data Analysis ◽  
Medicinal Plant ◽  
Spectral Data ◽  
Chemical Reactions ◽  
Hair Loss ◽  
Methanolic Extract ◽  
Chemical Constituents ◽  
Hibiscus Rosa Sinensis ◽  
Spectral Data Analysis ◽  
H 30

Hibiscus rosa-sinensis L. (Malvaceae) is an ornamental and medicinal plant used to treat asthma, cough, boils, wounds, ringworm, gynecological conditions, hair loss, dandruff, itchy scalp, obesity, sexual diseases, cough, cold and venereal diseases. This study was designed to isolate chemical constituents from the leaves and flowers of H. rosa-sinensis and to characterize their structures. A methanolic extract of the leaves afforded isolation of n-tetracosanyl cyclopentylcarboxylate (1), taraxerol acetate (2) and 26β- cyclopentanyl n-hexacosan-5β-ol (3) along with n-hexatetracontane (4), β-sitosterol (5), stigmasterol (6), urs-12-en-3β-ol-18β-H-30-oic acid, dulcioic acid, 7), urs-12-en-3β-ol-18β-H-27-oic acid, peltoboykinolic acid, 8), urs-12-en-3β-ol-18β-H-29-oic acid, maprounic acid, 9), oleanolic acid (10) and β-sitosterol 3-O- β-D-xylopyranoside (11) from methanolic fractions of flowers. The structures of these compounds were elucidated on the basis of spectral data analysis and by chemical reactions.

New Antifungal Xanthones from the Seeds of Rhus coriaria L.

2011 ◽  
Vol 66 (1-2) ◽  
pp. 17-23 ◽  
Author(s):  
Onkar Singh ◽  
Mohammed Ali ◽  
Nida Akhtar
Keyword(s):  
Data Analysis ◽  
Carboxylic Acid ◽  
Dicarboxylic Acid ◽  
Spectral Data ◽  
Aspergillus Flavus ◽  
Chemical Reactions ◽  
Ethanolic Extract ◽  
Rhus Coriaria ◽  
Spectral Data Analysis

Phytochemical investigations of the ethanolic extract of the seeds of Rhus coriaria L. (Anacardiaceae) led to the identification of four new xanthones, characterized as 2,3-dihydroxy- 7-methyl xanthone (1), 2,3,6-trihydroxy-7-hydroxymethylene xanthone-1-carboxylic acid (2), 2-methoxy-4-hydroxy-7-methyl-3-O-β-D-glucopyranosyl xanthone-1,8-dicarboxylic acid (4), and 2-hydroxy-7-hydroxymethylene xanthone-1,8-dicarboxylic acid 3-O-β-D-glucopyranosyl- (2’ → 3’’)-3’’-O-stigmast-5-ene (5), along with the known steroidal glucoside β-sitosterol-β-Dglucoside (3). The structures of the isolated compounds have been identifi ed on the basis of spectral data analysis and chemical reactions. All xanthones were active against Aspergillus flavus.

NEW FATTY ACID DERIVATIVES FROM OCIMUM SANCTUM L. LEAVES

INDIAN DRUGS ◽  
2012 ◽  
Vol 49 (11) ◽  
pp. 13-18
Author(s):  
A. Ali ◽  
◽  
M Ali
Keyword(s):  
Fatty Acid ◽  
Data Analysis ◽  
Spectral Data ◽  
Chemical Reactions ◽  
Vanillic Acid ◽  
Ocimum Sanctum ◽  
Fatty Acid Derivatives ◽  
Spectral Data Analysis

Two new fatty acid derivatives characterized as dotriacont-20-en-14-ol-1-oic acid (sanctumoic acid) and 4'-benzoylglucopyranosyl octadec-9-enoate (benzoyl gluco-oleate) were isolated from the leaves of Ocimum sanctum L. (Lamiaceae) together with five known compounds, vanillic acid, ocimumnapthanoic acid, β-sitostero glucoside, oleiyl glucoside and diglucosyl oleate. The structures of isolated compounds have been established on the basis of spectral data analysis and chemical reactions.

NEW LANOSTENE-LINKED DEHYDROABIETIC ACID DERIVATIVES FROM THE OLEO-RESIN OF PINUS ROXBURGHII SARG. (PINACEAE)

INDIAN DRUGS ◽  
2013 ◽  
Vol 50 (05) ◽  
pp. 23-31
Author(s):  
M Shuaib ◽  
◽  
M Ali ◽  
K. J. Naquvi
Keyword(s):  
Data Analysis ◽  
Spectral Data ◽  
Chemical Reactions ◽  
Dehydroabietic Acid ◽  
Himalayan Region ◽  
Pinus Roxburghii ◽  
Dioic Acid ◽  
Phytochemical Investigation ◽  
Triterpenic Acids ◽  
Spectral Data Analysis

Pinus roxburghii Sarg.; syn. Pinus longifolia Roxb. (Pinaceae), found in the Himalayan region, furnishes an oleo-resin which is used as insecticides, disinfectants and to treat boils and gastric troubles. Phytochemical investigation of the oleo-resin gave four new triterpenic acids linked with dehydroabietic acid derivatives characterised as lanost-5,20(21),22,25(27)-tetraen-26-oic acid-3β-olyl (3→19')-3'- oxodehydroabietic acid (roxburghianoic acid A, 2), lanost-5,9(11), 20(21), 22,25(27)-pentaen-26-oic acid 3β-olyl-(3→19')-3'-oxodehydroabietic acid (roxburghianoic acid B, 3), lanost-5,7,20(21),22,25(27)- pentaenyl-26-oic acid (3→19')-3'-oxodehydroabietic acid (roxburghianoic acid C, 4), lanost- 5,7,20,22,25(27)-pentaen-26-oic acid 3β-olyl-(3→19')-3'-oxodehydroabietic 16'-dioic acid (roxburghianoic acid D, 5) along with the known phytoconstituent identified a dehydroabietic acid (1). The structures of all the isolated compounds were elucidated on the basis of spectral data analysis and chemical reactions.

Chemical components of the rhizomes of Drynaria fortunei (KUNZE) J. Sm. (polypodiaceae) in Vietnam

2011 ◽  
Vol 76 (9) ◽  
pp. 1133-1139 ◽  
Author(s):  
Pham Thi Nhat Trinh ◽  
Nguyen Cong Hao ◽  
Phan Thanh Thao ◽  
Le Tien Dung
Keyword(s):  
Data Analysis ◽  
Spectral Data ◽  
Phenolic Acid ◽  
Ethanol Extract ◽  
Chemical Components ◽  
Spectroscopic Methods ◽  
Phenylpropanoid Glycoside ◽  
Spectral Data Analysis ◽  
First Time

From the ethanol extract of Drynaria fortunei (KUNZE) J. Sm., a new phenylpropanoid glycoside, fortunamide (1), was isolated and characterized by spectroscopic methods. Together with a new glycoside, 9 known compounds, including three curcuminoids (2–4), two isoprenylated flavonoids (5, 6), two flavonoids (7, 8), one monoterpenoid (9) and one phenolic acid (10) were isolated and identified by spectral data analysis from the rhizomes of Drynaria fortunei (KUNZE) J. Sm. Eight of them were isolated from Drynaria fortunei (KUNZE) J. Sm. for the first time.

scholarly journals Quantitative Spectral Data Analysis Using Extreme Learning Machines Algorithm Incorporated with PCA

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 18
Author(s):  
Michael Li ◽  
Santoso Wibowo ◽  
Wei Li ◽  
Lily D. Li
Keyword(s):  
Data Analysis ◽  
Conceptual Framework ◽  
Spectral Data ◽  
Learning Algorithm ◽  
Structural Parameters ◽  
Inverse Function ◽  
Principal Component ◽  
Learning Task ◽  
Classification Problems ◽  
Spectral Data Analysis

Extreme learning machine (ELM) is a popular randomization-based learning algorithm that provides a fast solution for many regression and classification problems. In this article, we present a method based on ELM for solving the spectral data analysis problem, which essentially is a class of inverse problems. It requires determining the structural parameters of a physical sample from the given spectroscopic curves. We proposed that the unknown target inverse function is approximated by an ELM through adding a linear neuron to correct the localized effect aroused by Gaussian basis functions. Unlike the conventional methods involving intensive numerical computations, under the new conceptual framework, the task of performing spectral data analysis becomes a learning task from data. As spectral data are typical high-dimensional data, the dimensionality reduction technique of principal component analysis (PCA) is applied to reduce the dimension of the dataset to ensure convergence. The proposed conceptual framework is illustrated using a set of simulated Rutherford backscattering spectra. The results have shown the proposed method can achieve prediction inaccuracies of less than 1%, which outperform the predictions from the multi-layer perceptron and numerical-based techniques. The presented method could be implemented as application software for real-time spectral data analysis by integrating it into a spectroscopic data collection system.

Spectral data analysis approaches for improved provenance classification

2015 ◽  
Author(s):  
Kellen J. Sorauf ◽  
Amy J. R. Bauer ◽  
Andrzej W. Miziolek ◽  
Frank C. De Lucia
Keyword(s):  
Data Analysis ◽  
Spectral Data ◽  
Spectral Data Analysis
Sign in / Sign up

Export Citation Format

Share Document