An inverse correlation between peripheral gustatory FTY720 162359-56-0 sensitivity to poly-unsaturated fatty acids and preference for lipid-rich foods was reported in rats. Recently, experiments performed in healthy humans have highlighted the relationship between the oro-sensory fat perception and the body mass index. Hypersensitivity to lipids was associated with lower energy consumption, fat intake and body mass index. Whether threshold of sensitivity to dietary lipids is dependent of CD36 and/ or GPR120 in humans remains to be determined. A better understanding of molecular mechanisms responsible for the orosensory reception of dietary lipids and their physiological impacts on the feeding behaviour should allow the development of new therapeutic and nutritional strategies for mitigating excess food intake. Quantitative real-time PCR is the method of choice for gene expression research and analysis of biological pathways for several reasons: the technique is fast, extremely sensitive, highly reproducible and can be integrated in high-throughput systems. Therefore, it is routinely applied in many research areas. Despite the advantages and its apparent simplicity, qPCR expression analysis also has a number of caveats, for example the need for a proper endogenous control to normalize relative gene expression data. Although many studies have warned against the use of a single reference gene for gene expression normalization, the expression of reference genes, such as glyceraldehyde-3-phosphate dehydrogenase or beta-actin, or the amount of 18S ribosomal RNA are still frequently used as a single endogenous control. However, the use of a single unvalidated reference gene may give rise to biased study results, especially when study conditions are changed or experimental variability is increased. The increase in reference gene variability becomes even more problematic if genes with relatively small expression differences are studied. In the setting of myocardial infarction and congestive heart failure, this instability in reference gene expression has already been described. For instance, Brattelid et al. reported that the reduced expression of Gapdh compared to 18S rRNA significantly influenced the outcome and interpretation of mRNA expression levels. In another in vitro reference gene study, the expression levels of either beta-2 microglobulin, Gapdh, Actb, or 18S rRNA were found to be highly dependent upon the experimental conditions. This implicated that the choice for a given reference gene for gene expression normalization could potentially bias relative mRNA expression results and alter the study outcome. These problems on the validity of single reference genes for qPCR gene expression normalization led Vandesompele et al. to propose an innovative strategy by using the geometric mean of an optimal number of stably expressed reference genes. This approach has subsequently been used by numerous researchers for the optimization of reference gene normalization strategies in distinct research applications. This is particularly true when reference gene variability is expected to be high, as in the case of myocardial infarction or CHF studies.