Ponatinib alone or with chemo-immunotherapy in heavily pre-treated Philadelphia-like acute lymphoblastic leukemia: a CAMPUS ALL real-life study

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Geographical classification of some Australian wines by discriminant analysis using HPLC with UV and chemiluminescence detection

HPLC with UV and acidified potassium permanganate chemiluminescence detection, combined with multivariate data analysis techniques, were used for the geographical classification of some Australian red (Cabernet Sauvignon) and white (Chardonnay) wines from two regions (Coonawarra and Geelong). Identification of the wine constituents prominent in the chromatography was performed by mass spectrometry. Principal components analysis and linear discriminant analysis were used to classify the wines according to region of production. Separation between regions was achieved with both detection systems and key components leading to discrimination of the wines were identified. Using two principal components, linear discriminant analysis with UV detection correctly classified 100% of the Chardonnay wines and, overall 91% of the Cabernet Sauvignon wines. With acidified potassium permanganate chemiluminescence detection, 75% of the Chardonnay wines and 94% of the Cabernet Sauvignon wines werecorrectly classified using two factors

Partial least squares and principal components analysis of wine vintage by high performance liquid chromatography with chemiluminescence detection

HPLC with acidic potassium permanganate chemiluminescence detection was employed to analyse 17 Cabernet Sauvignon wines across a range of vintages (1971–2003). Partial least squares regression analysis and principal components analysis was used in order to investigate the relationship between wine composition and vintage. Tartaric acid, vanillic acid, catechin, sinapic acid, ethyl gallate, myricetin, procyanadin B and resveratrol were found to be important components in terms of differences between the vintages