A reduced model clarifies the role of feedback loops and time delays in the Drosophila circadian oscillator.

Although several detailed models of molecular processes essential for circadian oscillations have been developed, their complexity makes intuitive understanding of the oscillation mechanism difficult. The goal of the present study was to reduce a previously developed, detailed model to a minimal representation of the transcriptional regulation essential for circadian rhythmicity in Drosophila. The reduced model contains only two differential equations, each with time delays. A negative feedback loop is included, in which PER protein represses per transcription by binding the dCLOCK transcription factor. A positive feedback loop is also included, in which dCLOCK indirectly enhances its own formation. The model simulated circadian oscillations, light entrainment, and a phase-response curve with qualitative similarities to experiment. Time delays were found to be essential for simulation of circadian oscillations with this model. To examine the robustness of the simplified model to fluctuations in molecule numbers, a stochastic variant was constructed. Robust circadian oscillations and entrainment to light pulses were simulated with fewer than 80 molecules of each gene product present on average. Circadian oscillations persisted when the positive feedback loop was removed. Moreover, elimination of positive feedback did not decrease the robustness of oscillations to stochastic fluctuations or to variations in parameter values. Such reduced models can aid understanding of the oscillation mechanisms in Drosophila and in other organisms in which feedback regulation of transcription may play an important role.

Risk factors for encephalitis and death from West Nile virus infection: An analysis of hospitalized cases in Houston, Texas from 2002--2008

We conducted a nested case-control study to determine the significant risk factors for developing encephalitis from West Nile virus (WNV) infection. The purpose of this research project was to expand the previously published Houston study of 2002–2004 patients to include data on Houston patients from four additional years (2005–2008) to determine if there were any differences in risk factors shown to be associated with developing the more severe outcomes of WNV infection, encephalitis and death, by having this larger sample size. A re-analysis of the risk factors for encephalitis and death was conducted on all of the patients from 2002–2008 and was the focus of this proposed research. This analysis allowed for the determination to be made that there are differences in the outcome in the risk factors for encephalitis and death with an increased sample size. Retrospective medical chart reviews were completed for the 265 confirmed WNV hospitalized patients; 153 patients had encephalitis (WNE), 112 had either viral syndrome with fever (WNF) or meningitis (WNM); a total of 22 patients died. Univariate logistic regression analyses on demographic, comorbidities, and social risk factors was conducted in a similar manner as in the previously conducted study to determine the risk factors for developing encephalitis from WNV. A multivariate model was developed by using model building strategies for the multivariate logistic regression analysis. The hypothesis of this study was that there would be additional risk factors shown to be significant with the increase in sample size of the dataset. This analysis with a greater sample size and increased power supports the hypothesis in that there were additional risk factors shown to be statistically associated with the more severe outcomes of WNV infection (WNE or death). Based on univariate logistic regression results, these data showed that even though age of 20–44 years was statistically significant as a protecting effect for developing WNE in the original study, the expanded sample lacked significance. This study showed a significant WNE risk factor to be chronic alcohol abuse, when it was not significant in the original analysis. Other WNE risk factors identified in this analysis that showed to be significant but were not significant in the original analysis were cancer not in remission > 5 years, history of stroke, and chronic renal disease. When comparing the two analyses with death as an outcome, two risk factors that were shown to be significant in the original analysis but not in the expanded dataset analysis were diabetes mellitus and immunosuppression. Three risk factors shown to be significant in this expanded analysis but were not significant in the original study were illicit drug use, heroin or opiate use, and injection drug use. However, with the multiple logistic regression models, the same independent risk factors for developing encephalitis of age and history of hypertension including drug induced hypertension were consistent in both studies.^