Identification of flavour additives in tobacco products to develop a flavour library.

OBJECTIVES: This study combines chemical analysis and flavour descriptions of flavour additives used in tobacco products, and provides a starting point to build an extensive library of flavour components, useful for product surveillance. METHODS: Headspace gas chromatography-mass spectrometry (GC-MS) was used to compare 22 commercially available tobacco products (cigarettes and roll-your-own) expected to have a characterising flavour and 6 commercially available products not expected to have a characterising flavour with 5 reference products (natural tobacco leaves and research cigarettes containing no flavour additives). The flavour components naturally present in the reference products were excluded from components present in commercially available products containing flavour additives. A description of the remaining flavour additives was used for categorisation. RESULTS: GC-MS measurements of the 33 tobacco products resulted in an overview of 186 chemical compounds. Of these, 144 were solely present in commercially available products. These 144 flavour additives were described using 62 different flavour descriptors extracted from flavour databases, which were categorised into eight groups largely based on the definition of characterising flavours from the European Tobacco Product Directive: fruit, spice, herb, alcohol, menthol, sweet, floral and miscellaneous. CONCLUSIONS: We developed a method to identify and describe flavour additives in tobacco products. Flavour additives consist of single flavour compounds or mixtures of multiple flavour compounds, and different combinations of flavour compounds can cause a certain flavour. A flavour library helps to detect flavour additives that are characteristic for a certain flavour, and thus can be useful for regulation of flavours in tobacco and related products.

An Integrated Human/Murine Transcriptome and Pathway Approach To Identify Prenatal Treatments For Down Syndrome.

Anatomical and functional brain abnormalities begin during fetal life in Down syndrome (DS). We hypothesize that novel prenatal treatments can be identified by targeting signaling pathways that are consistently perturbed in cell types/tissues obtained from human fetuses with DS and mouse embryos. We analyzed transcriptome data from fetuses with trisomy 21, age and sex-matched euploid controls, and embryonic day 15.5 forebrains from Ts1Cje, Ts65Dn, and Dp16 mice. The new datasets were compared to other publicly available datasets from humans with DS. We used the human Connectivity Map (CMap) database and created a murine adaptation to identify FDA-approved drugs that can rescue affected pathways. USP16 and TTC3 were dysregulated in all affected human cells and two mouse models. DS-associated pathway abnormalities were either the result of gene dosage specific effects or the consequence of a global cell stress response with activation of compensatory mechanisms. CMap analyses identified 56 molecules with high predictive scores to rescue abnormal gene expression in both species. Our novel integrated human/murine systems biology approach identified commonly dysregulated genes and pathways. This can help to prioritize therapeutic molecules on which to further test safety and efficacy. Additional studies in human cells are ongoing prior to pre-clinical prenatal treatment in mice.