2015
DOI: 10.15386/cjmed-473
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Synthesis, lipophilicity and antimicrobial activity evaluation of some new thiazolyl-oxadiazolines

Abstract: Background and aimsSynthesis of new potential antimicrobial agents and evaluation of their lipophilicity.MethodsTen new thiazolyl-oxadiazoline derivatives were synthesized and their structures were validated by 1H-NMR and mass spectrometry. The lipophilicity of the compounds was evaluated using the principal component analysis (PCA) method. The necessary data for applying this method were obtained by reverse-phase thin-layer chromatography (RP-TLC). The antimicrobial activities were tested in vitro against fou… Show more

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(2 citation statements)
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“…Therefore, the first component will be uncorrelated with the second component. For a better interpretation of the information, the matrices are graphically plotted in order to obtain a 2D plot and loading scores, which allows us to represent the relative position of the objects of the original variables (Ionuț, Tiperciuc, & Oniga, ; Onișor, Palage, & Sârbu, ; Palage et al, ; C. I. Stoica et al, ; Tiperciuc & Sârbu, ). PCA was performed using the XL‐STAT extension (XLSTAT, ).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Therefore, the first component will be uncorrelated with the second component. For a better interpretation of the information, the matrices are graphically plotted in order to obtain a 2D plot and loading scores, which allows us to represent the relative position of the objects of the original variables (Ionuț, Tiperciuc, & Oniga, ; Onișor, Palage, & Sârbu, ; Palage et al, ; C. I. Stoica et al, ; Tiperciuc & Sârbu, ). PCA was performed using the XL‐STAT extension (XLSTAT, ).…”
Section: Methodsmentioning
confidence: 99%
“…The second component will account for the maximal amount of variance in the dataset that did not display strong correlation with the first component. Therefore, the first component will be uncorrelated with the second component.For a better interpretation of the information, the matrices are graphically plotted in order to obtain a 2D plot and loading scores, which allows us to represent the relative position of the objects of the original variables(Ionuț, Tiperciuc, & Oniga, 2017;Onișor, Palage, & Sârbu, 2010;Palage et al, 2011;C. I. Stoica et al, 2015;Tiperciuc & Sârbu, 2006).…”
mentioning
confidence: 99%