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A method has been optimised for the separation of glycoforms of human serum transferrin, using a high-performance pellicular anion-exchange chromatographic column. The effect of the eluent pH and of the column temperature on the separation of transferrin glycoforms was studied using a standard solution of commercially available human serum transferrin. An HPLC system equipped with an ultraviolet detector was used for the analysis. No immunoassay was used after the anion-exchange chromatographic separation of the glycoforms, in contrast with most currently used methods. The method was applied to the separation and quantification of transferrin glycoforms in serum from a healthy, non-pregnant woman, after saturation of transferrin with iron and further precipitation of lipoproteins. The whole chromatographic run, including re-equilibration of the column, took 35 min.

Honey is one of the food commodities most frequently affected by fraud. Although addition of extraneous sugars is the most common type of fraud, analytical methods are also needed to detect origin masking and misdescription of botanical variety. In this work, multivariate analysis of the content of certain macro-and trace elements, determined by energy-dispersive X-ray fluorescence (ED-XRF) without any type of sample treatment, were used to classify honeys according to botanical variety and geographical origin. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to create classification models for nine different botanical varieties-orange, robinia, lavender, rosemary, thyme, lime, chestnut, eucalyptus and manuka-and seven different geographical origins-Italy, Romania, Spain, Portugal, France, Hungary and New Zealand. Although characterised by 100% sensitivity, PCA models lacked specificity. The PLS-DA models constructed for specific combinations of botanical variety-country (BV-C) allowed the successful classification of honey samples, which was verified by external validation samples.