Characterization of volatile compounds of Daucus crinitus Desf. Headspace Solid Phase Microextraction as alternative technique to Hydrodistillation

<p>Abstract</p> <p>Background</p> <p>Traditionally, the essential oil of aromatic herbs is obtained using hydrodistillation (HD). Because the emitted volatile fraction plays a fundamental role in a plant's life, various novel techniques have been developed for its extraction from plants. Among these, headspace solid phase microextraction (HS-SPME) can be used to obtain a rapid fingerprint of a plant's headspace. <it>Daucus crinitus </it>Desf. is a wild plant that grows along the west coast of Algeria. Only a single study has dealt with the chemical composition of the aerial part oils of Algerian <it>D. crinitus</it>, in which isochavicol isobutyrate (39.0%), octyl acetate (12.3%), and β-caryophyllene (5.4%) were identified. Using GC-RI and GC-MS analysis, the essential oils and the volatiles extracted from separated organs of <it>D. crinitus </it>Desf. were studied using HS-SPME.</p> <p>Results</p> <p>GC-RI and GC-MS analysis identified 72 and 79 components in oils extracted using HD and in the volatile fractions extracted using SPME, respectively. Two types of essential oils were produced by the plant: the root oils had aliphatic compounds as the main component (87.0%-90.1%), and the aerial part oils had phenylpropanoids as the main component (43.1%-88.6%). HS-SPME analysis showed a more precise distribution of compounds in the organs studied: oxygenated aliphatic compounds were well represented in the roots (44.3%-84.0%), hydrocarbon aliphatic compounds were in the leaves and stems (22.2%-87.9%), and phenylpropanoids were in the flowers and umbels (47.9%-64.2%). Moreover, HS-SPME allowed the occurrence of isochavicol (29.6 - 34.7%) as main component in <it>D. crinitus </it>leaves, but it was not detected in the oils, probably because of its solubility in water.</p> <p>Conclusions</p> <p>This study demonstrates that HD and HS-SPME modes could be complimentary extraction techniques in order to obtain the complete characterization of plant volatiles.</p

Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability

True versus False Parasite Interactions: A Robust Method to Take Risk Factors into Account and Its Application to Feline Viruses

International audienceBACKGROUND: Multiple infections are common in natural host populations and interspecific parasite interactions are therefore likely within a host individual. As they may seriously impact the circulation of certain parasites and the emergence and management of infectious diseases, their study is essential. In the field, detecting parasite interactions is rendered difficult by the fact that a large number of co-infected individuals may also be observed when two parasites share common risk factors. To correct for these "false interactions", methods accounting for parasite risk factors must be used. METHODOLOGY/PRINCIPAL FINDINGS: In the present paper we propose such a method for presence-absence data (i.e., serology). Our method enables the calculation of the expected frequencies of single and double infected individuals under the independence hypothesis, before comparing them to the observed ones using the chi-square statistic. The method is termed "the corrected chi-square." Its robustness was compared to a pre-existing method based on logistic regression and the corrected chi-square proved to be much more robust for small sample sizes. Since the logistic regression approach is easier to implement, we propose as a rule of thumb to use the latter when the ratio between the sample size and the number of parameters is above ten. Applied to serological data for four viruses infecting cats, the approach revealed pairwise interactions between the Feline Herpesvirus, Parvovirus and Calicivirus, whereas the infection by FIV, the feline equivalent of HIV, did not modify the risk of infection by any of these viruses. CONCLUSIONS/SIGNIFICANCE: This work therefore points out possible interactions that can be further investigated in experimental conditions and, by providing a user-friendly R program and a tutorial example, offers new opportunities for animal and human epidemiologists to detect interactions of interest in the field, a crucial step in the challenge of multiple infections