2 resultados para Heyn, Piet, 1578-1629.

em University of Queensland eSpace - Australia


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It has been reported that mutations in the quorum-sensing genes lasI and rhlI in Pseudomonas aeruginosa result in, among many other things, loss of twitching motility (A. Glessner, R. S. Smith, B. H. Iglewski, and J. B. Robinson, J. Bacteriol. 181:1623-1629, 1999). We constructed knockouts of lasI and rhlI and the corresponding regulatory genes lasR and rhlR and found no effect on twitching motility. However, twitching-defective variants accumulated during culturing of lasI and rhlI mutants. Further analysis showed that the stable twitching-defective variants of lasI and rhlI mutants had arisen as a consequence of secondary mutations in vfr and algR, respectively, both of which encode key regulators affecting a variety of phenotypes, including twitching motility. In addition, when grown in shaking broth culture, lasI and rhlI mutants, but not the wild-type parent, also accumulated unstable variants that lacked both twitching motility and swimming motility and appeared to be identical in phenotype to the S1 and S2 variants that were recently reported to occur at high frequencies in P. aeruginosa strains grown as a biofilm or in static broth culture (E. Deziel, Y. Comeau, and R. Villemur, J. Bacteriol. 183:1195-1204, 2001). These results indicate that mutations in one regulatory system may create distortions that select during subsequent culturing for compensatory mutations in other regulatory genes within the cellular network. This problem may have compromised some past studies of regulatory hierarchies controlled by quorum sensing and of bacterial regulatory systems in general.

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Aim To assess the effectiveness of a program of computer-generated tailored advice for callers to a telephone helpline, and to assess whether it enhanced a series of callback telephone counselling sessions in aiding smoking cessation. Design Randomized controlled trial comparing: (1) untailored self-help materials; (2) computer-generated tailored advice only, and (3) computer-generated tailored advice plus callback telephone counselling. Assessment surveys were conducted at baseline, 3, 6 and 12 months. Setting Victoria, Australia. Participants A total of 1578 smokers who called the Quitline service and agreed to participate. Measurements Smoking status at follow-up; duration of cessation, if quit; use of nicotine replacement therapy; and extent of participation in the callback service. Findings At the 3-month follow-up, significantly more (chi(2)(2) = 16.9; P < 0.001) participants in the computer-generated tailored advice plus telephone counselling condition were not smoking (21%) than in either the computer-generated advice only (12%) or the control condition (12%). Proportions reporting not smoking at the 12-month follow-up were 26%, 23% and 22%, respectively (NS) for point prevalence, and for 9 months sustained abstinence; 8.2, 6.0, and 5.0 (NS). In the telephone counselling group, those receiving callbacks were more likely than those who did not to have sustained abstinence at 12 months (10.2 compared with 4.0, P < 0.05). Logistic regression on 3-month data showed significant independent effects on cessation of telephone counselling and use of NRT, but not of computer-generated tailored advice. Conclusion Computer-generated tailored advice did not enhance telephone counselling, nor have any independent effect on cessation. This may be due to poor timing of the computer-generated tailored advice and poor integration of the two modes of advice.