A novel microextraction method based on vortex- and CO2 -assisted liquid-liquid microextraction with salt addition for the isolation of furanic compounds (5-hydroxymethyl-2-furaldehyde, 5-methyl-2-furaldehyde, 2-furaldehyde, 3-furaldehyde, 2-furoic and 3-furoic acids) was developed. Purging the sample with CO2 was applied after vortexing to enhance the phase separation and mass transfer of the analytes. The optimum extraction conditions were: extraction solvent (volume), propyl acetate (125 μL); sample pH, 2.4; vortexing time, 45 s; salt concentration, 25% w/v and purging time, 5 min. The analytes were separated using an ODS Hypersil C18 column (250×4.6 mm i.d, 5 μm) under gradient flow. The proposed method showed good linearities (r(2) >0.999), low detection limits (0.08-1.9 μg/L) and good recoveries (80.7-122%). The validated method was successfully applied for the determination of the furanic compounds in concentrated juice (mango, date, orange, pomegranate, roselle, mangosteen and soursop) and dried fruit (prune, date and apricot paste) samples.
A fast and simple solvent microextraction technique using salting out-vortex-assisted liquid-liquid microextraction (salting out-VALLME) was developed for the extraction of furfurals (2-furfural (2-F), 3-furfural (3-F), 5-methylfurfural (5-MF) and 5-hydroxymethylfurfural (5-HMF)) and patulin (PAT) in fruit juice samples. The optimum extraction conditions for 5 mL sample were: extraction solvent, 1-hexanol; volume of extractant, 200 µL; vortex time, 45 s; salt addition, 20%. The simultaneous determination of the furfurals and PAT were investigated using high performance liquid chromatography coupled with diode array detector (HPLC-DAD). The separation was performed using ODS Hypersil C18 column (4.6 mm i.d × 250 mm, 5 μm) under gradient elution. The detection wavelengths used for all compounds were 280 nm except for 3-F (210 nm). The furfurals and PAT were successfully separated in less than 9 min. Good linearities (r(2)>0.99) were obtained within the range 1-5000 μg L(-1) for all compounds except for 3-F (10-5000 µg L(-1)) and PAT (0.5-100 μg L(-1)). The limits of detection (0.28-3.2 µg L(-1)) were estimated at S/N ratio of 3. The validated salting out-VALLME-HPLC method was applied for the analysis of furfurals and PAT in fruit juice samples (apple, mango and grape).
An in-vial liquid-liquid microextraction method was developed for the selective extraction of the phenolic acids (caffeic, gallic, cinnamic, ferulic, chlorogenic, syringic, vanillic, benzoic, p-hydroxybenzoic, 2,4-dihydroxybenzoic, o-coumaric, m-coumaric and p-coumaric) in vegetable oil samples. The optimised extraction conditions for 20 g sample were: volume of diluent (n-hexane), 2 mL; extractant, methanol: 5 mM sodium hydroxide (60:40; v/v); volume of extractant, 300 μL (twice); vortex, 1 min; centrifugation, 5 min. Recoveries for the studied phenolic acids were 80.1-119.5%. The simultaneous determination of the phenolic acid extracts was investigated by capillary electrophoresis (CE). Separations were carried out on a bare fused-silica capillary (50 μm i.d.× 40 cm length) involving 25 mM sodium tetraborate (pH 9.15) and 5% methanol as CE background electrolyte in the normal polarity mode, voltage of 30 kV, temperature of 25°C, injection time of 4s (50 mbar) and electropherograms were recorded at 200 nm. The phenolic acids were successfully separated in less than 10 min. The validated in-vial LLME-CE method was applied to the determination of phenolic acids in vegetable oil samples (extra virgin olive oil, virgin olive oil, pure olive oil, walnut oil and grapeseed oil). The developed method shows significant advantages over the current methods as lengthy evaporation step is not required.
Numerous studies have shown the importance of physical activity in reducing the morbidity and mortality rates caused by cardiovascular disease (CVD). However, most of these studies emphasise little on the cumulative effect of CVD risk factors. Hence, this study investigates the association between physical exercise and cumulative CVD risk factors among adults in three different age groups.