Inverse association of NSAID use and ovarian cancer in relation to oral contraceptive use and parity

We examined the association between non-steroidal anti-inflammatory drug (NSAID) use and ovarian cancer by potential effect modifiers, parity and oral contraceptive use, in a population-based case–control study conducted in Wisconsin and Massachusetts. Women reported prior use of NSAIDs and information on risk factors in a telephone interview. A total of 487 invasive ovarian cancer cases and 2653 control women aged 20–74 years were included in the analysis. After adjustment for age, state of residence and other covariates, ever use of NSAIDs was inversely associated with ovarian cancer in never users of oral contraceptives (odds ratio (OR)=0.58, 95% confidence interval (CI) 0.42–0.80) but not for ever users (OR=0.98, 95% CI 0.71–1.35) (P-interaction=0.03). A reduced risk with NSAID use was also noted in nulliparous women (OR=0.47, 95% CI 0.27–0.82) but not among parous women (OR=0.81, 95% CI 0.64–1.04) (P-interaction=0.05). These results suggest that use of NSAIDs were beneficial to women at greatest risk for ovarian cancer

Genome-Wide Functional Profiling Identifies Genes and Processes Important for Zinc-Limited Growth of Saccharomyces cerevisiae

Zinc is an essential nutrient because it is a required cofactor for many enzymes and transcription factors. To discover genes and processes in yeast that are required for growth when zinc is limiting, we used genome-wide functional profiling. Mixed pools of ∼4,600 deletion mutants were inoculated into zinc-replete and zinc-limiting media. These cells were grown for several generations, and the prevalence of each mutant in the pool was then determined by microarray analysis. As a result, we identified more than 400 different genes required for optimal growth under zinc-limiting conditions. Among these were several targets of the Zap1 zinc-responsive transcription factor. Their importance is consistent with their up-regulation by Zap1 in low zinc. We also identified genes that implicate Zap1-independent processes as important. These include endoplasmic reticulum function, oxidative stress resistance, vesicular trafficking, peroxisome biogenesis, and chromatin modification. Our studies also indicated the critical role of macroautophagy in low zinc growth. Finally, as a result of our analysis, we discovered a previously unknown role for the ICE2 gene in maintaining ER zinc homeostasis. Thus, functional profiling has provided many new insights into genes and processes that are needed for cells to thrive under the stress of zinc deficiency

Regression analysis for discrete event history or failure time data

The paper deals with discrete-time regression models to analyze multistate—multiepisode models for event history data or failure time data collected in follow-up studies, retrospective studies, or longitudinal panels. The models are applicable if the events are not dated exactly but only a time interval is recorded. The models include individual specific parameters to account for unobserved heterogeneity. The explantory variables may be time-varying and random with distributions depending on the observed history of the process. Different estimation procedures are considered: Estimation of structural as well as individual specific parameters by maximization of a joint likelihood function, estimation of the structural parameters by maximization of a conditional likelihood function conditioning on a set of sufficient statistics for the individual specific parameters, and estimation of the structural parameters by maximization of a marginal likelihood function assuming that the individual specific parameters follow a distribution. The advantages and limitations of the different approaches are discussed