New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Something real: A social marketing approach to smoking prevention among Montevideo youth

Uruguay has some of the strictest tobacco-control laws in Latin America. Despite this, youth smoking rates in Uruguay are amongst the highest in South America. Thus, it is important to identify strategies to prevent youth smoking in Uruguay. The current qualitative research study sought to identify intrapersonal and socioenvironmental factors that are associated with smoking among middle school youth in Uruguay. It also sought to develop potential prevention strategies and media messages that would resonate with youth for a social media campaign. The study was grounded in social cognitive theory and the theory of reasoned action/planned behavior, among other behavioral science theories; anthropological perspectives were also considered. To achieve these goals, 29 group and individual structured interviews were conducted in two private middle schools catering to lower and higher SES youth in Montevideo, Uruguay during the summer of 2012. One hundred and three study participants, including students, parents, and teachers, were interviewed. The structured interviews were recorded, transcribed, translated, back translated, coded and analyzed. The study findings show that positive attitudes towards smoking (i.e. to be seen, to increase status, to ensure women's equality, to looking old, and to service as a rite of passage), delinquent behavior (i.e. transgression/deviant behavior), social norms that support smoking (i.e. peer pressure and modeling, group membership/sense of belonging, parental modeling, and family support), easy access and availability to tobacco (i.e. retails stores) were factors associated with youth smoking. Potential protective factors may include parental support, negative attitudes towards smoking, sports/music, and smoke-free environments. Because study participants are accustomed to government-sponsored strong countermarketing graphic imaging, study participants selected even stronger images and messages as the preferred way to receive tobacco prevention messages. Something Real ("Algo Real") was a theme that resonated with the participants and chosen as the name for the proposed campaign. This campaign was designed as a multiple component intervention that included mass, school base, and family based strategies to prevent tobacco use. Some intervention materials specific to these intervention components were developed to target relevant intrapersonal and socioenvironmental factors identified above. These materials will be tested in future pilot studies and larger scale evaluation with this population, outside the scope of this dissertation. ^