scholarly journals Genetic Variability of Immunomodulatory Genes in Ectromelia Virus Isolates Detected by Denaturing High-Performance Liquid Chromatography

2003 ◽  
Vol 77 (18) ◽  
pp. 10139-10146 ◽  
Author(s):  
Gloria Ribas ◽  
Jose Rivera ◽  
Margarida Saraiva ◽  
R. Duncan Campbell ◽  
Antonio Alcami
Keyword(s):  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Genetic Variability ◽  
High Performance ◽  
Ectromelia Virus ◽  
Virus Isolates

ABSTRACT The genetic variability of nine genes in 12 isolates and strains of ectromelia virus, which causes a smallpox-like disease (mousepox) in mice, was determined and allows for classification of ectromelia viruses. The low genetic variability suggests that evolutionary pressure maintains the activity of immunomodulatory genes in natural poxvirus infections.

scholarly journals Non-Targeted Ultra-High Performance Liquid Chromatography-High-Resolution Mass Spectrometry (UHPLC-HRMS) Fingerprints for the Chemometric Characterization and Classification of Turmeric and Curry Samples

Separations ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 32
Author(s):  
Nerea Núñez ◽  
Oscar Vidal-Casanella ◽  
Sonia Sentellas ◽  
Javier Saurina ◽  
Oscar Núñez
Keyword(s):  
Mass Spectrometry ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Resolution ◽  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Curcuma Longa ◽  
Chemical Descriptors ◽  
Resolution Mass

In this work, non-targeted ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) fingerprints obtained by C18 reversed-phase chromatography were proposed as sample chemical descriptors for the characterization and classification of turmeric and curry samples. A total of 21 turmeric and 9 curry commercially available samples were analyzed in triplicate after extraction with dimethyl sulfoxide (DMSO). The results demonstrated the feasibility of non-targeted UHPLC-HRMS fingerprints for sample classification, showing very good classification capabilities by partial least squares regression-discriminant analysis (PLS-DA), with 100% classification rates being obtained by PLS-DA when randomly selected samples were processed as “unknown” ones. Besides, turmeric curcuma species (Curcuma longa vs. Curcuma zedoaria) and turmeric Curcuma longa varieties (Madras, Erodes, and Alleppey) discrimination was also observed by PLS-DA when using the proposed fingerprints as chemical descriptors. As a conclusion, non-targeted UHPLC-HRMS fingerprinting is a suitable methodology for the characterization, classification, and authentication of turmeric and curry samples, without the requirement of using commercially available standards for quantification nor the necessity of metabolite identification.

scholarly journals Application of Pattern Recognition Method for Color Assessment of Oriental Tobacco based on HPLC of Polyphenols

2003 ◽  
Vol 20 (5) ◽  
pp. 356-359 ◽  
Author(s):  
S Dagnon ◽  
A Edreva
Keyword(s):  
Pattern Recognition ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Chlorogenic Acid ◽  
High Performance ◽  
Pattern Recognition Method ◽  
Recognition Method ◽  
Additional Tool ◽  
Hplc Profiles

AbstractThe color of Oriental tobaccos was organoleptically assayed, and high performance liquid chromatography (HPLC) of polyphenols was performed. The major tobacco polyphenols (chlorogenic acid, its isomers, and rutin), as well as scopoletin and kaempferol-3-rutinoside were quantified. HPLC polyphenol profiles were processed by pattern recognition method (PRM), and the values of indexes of similarity (Is,%) between the cultivars studied were determined. It was shown that data from organoleptic color assessment and from PRM based on HPLC profiles of polyphenols of the cultivars studied are largely compatible. Hence, PRM can be suggested as an additional tool for objective color evaluation and classification of Oriental tobacco.

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