Obesity is associated with many chronic disease states, such as diabetes mellitus, coronary disease and certain cancers, including those of the breast and colon. There is a growing body of evidence that links phytochemicals with the inhibition of adipogenesis and protection against obesity. Mangoes (Mangifera indica L.) are tropical fruits that are rich in a diverse array of bioactive phytochemicals. In this study, methanol extracts of peel and flesh from three archetypal mango cultivars; Irwin, Nam Doc Mai and Kensington Pride, were assessed for their effects on a 3T3-L1 pre-adipocyte cell line model of adipogenesis. High content imaging was used to assess: lipid droplets per cell, lipid droplet area per cell, lipid droplet integrated intensity, nuclei count and nuclear area per cell. Mango flesh extracts from the three cultivars did not inhibit adipogenesis; peel extracts from both Irwin and Nam Doc Mai, however, did so with the Nam Doc Mai extract most potent at inhibiting adipogenesis. Peel extract from Kensington Pride promoted adipogenesis. The inhibition of adipogenesis by Irwin (100 μg mL(-1)) and Nam Doc Mai peel extracts (50 and 100 μg mL(-1)) was associated with an increase in the average nuclear area per cell; similar effects were seen with resveratrol, suggesting that these extracts may act through pathways similar to resveratrol. These results suggest that differences in the phytochemical composition between mango cultivars may influence their effectiveness in inhibiting adipogenesis, and points to mango fruit peel as a potential source of nutraceuticals.

Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.