Publications

Candida albicans is a normal resident of the gastrointestinal tract and also the most prevalent fungal pathogen of humans. It last shared a common ancestor with the model yeast Saccharomyces cerevisiae over 300 million years ago. We describe a collection of 143 genetically matched strains of C. albicans, each of which has been deleted for a specific transcriptional regulator. This collection represents a large fraction of the non-essential transcription circuitry. A phenotypic profile for each mutant was developed using a screen of 55 growth conditions. The results identify the biological roles of many individual transcriptional regulators; for many, this work represents the first description of their functions. For example, a quarter of the strains showed altered colony formation, a phenotype reflecting transitions among yeast, pseudohyphal, and hyphal cell forms. These transitions, which have been closely linked to pathogenesis, have been extensively studied, yet our work nearly doubles the number of transcriptional regulators known to influence them. As a second example, nearly a quarter of the knockout strains affected sensitivity to commonly used antifungal drugs; although a few transcriptional regulators have previously been implicated in susceptibility to these drugs, our work indicates many additional mechanisms of sensitivity and resistance. Finally, our results inform how transcriptional networks evolve. Comparison with the existing S. cerevisiae data (supplemented by additional S. cerevisiae experiments reported here) allows the first systematic analysis of phenotypic conservation by orthologous transcriptional regulators over a large evolutionary distance. We find that, despite the many specific wiring changes documented between these species, the general phenotypes of orthologous transcriptional regulator knockouts are largely conserved. These observations support the idea that many wiring changes affect the detailed architecture of the circuit, but not its overall output.

Food insecurity refers to the inability to afford enough food for an active, healthy life. Numerous studies have shown associations between food insecurity and adverse health outcomes among children. Studies of the health effects of food insecurity among adults are more limited and generally focus on the association between food insecurity and self-reported disease. We therefore examined the association between food insecurity and clinical evidence of diet-sensitive chronic disease, including hypertension, hyperlipidemia, and diabetes. Our population-based sample included 5094 poor adults aged 18-65 y participating in the NHANES (1999-2004 waves). We estimated the association between food insecurity (assessed by the Food Security Survey Module) and self-reported or laboratory/examination evidence of diet-sensitive chronic disease using Poisson regression. We adjusted the models to account for differences in age, gender, race, educational attainment, and income. Food insecurity was associated with self-reported hypertension [adjusted relative risk (ARR) 1.20; 95% CI, 1.04-1.38] and hyperlipidemia (ARR 1.30; 95% CI, 1.09-1.55), but not diabetes (ARR 1.19; 95% CI, 0.89-1.58). Food insecurity was associated with laboratory or examination evidence of hypertension (ARR 1.21; 95% CI, 1.04-1.41) and diabetes (ARR 1.48; 95% CI, 0.94-2.32). The association with laboratory evidence of diabetes did not reach significance in the fully adjusted model unless we used a stricter definition of food insecurity (ARR 2.42; 95% CI, 1.44-4.08). These data show that food insecurity is associated with cardiovascular risk factors. Health policy discussions should focus increased attention on ability to afford high-quality foods for adults with or at risk for chronic disease.

Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representation that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of these aspects (expression language, codification of eligibility concepts, and patient data modeling) to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward knowledge representation for sharable and computable eligibility criteria.

CONTEXT

Medical devices are common in clinical practice and have important effects on morbidity and mortality, yet there has not been a systematic examination of evidence used by the US Food and Drug Administration (FDA) for device approval.

OBJECTIVES

To study premarket approval (PMA)--the most stringent FDA review process--of cardiovascular devices and to characterize the type and strength of evidence on which it is based.

DATA SOURCES AND STUDY SELECTION

Systematic review of 78 summaries of safety and effectiveness data for 78 PMAs for high risk cardiovascular devices that received PMA between January 2000 and December 2007 [corrected].

DATA EXTRACTION

Examination of the methodological characteristics considered essential to minimize confounding and bias, as well as the primary end points of the 123 studies supporting the PMAs.

RESULTS

Thirty-three of 123 studies (27%) used to support recent FDA approval of cardiovascular devices were randomized and 17 of 123 (14%) were blinded. Fifty-one of 78 PMAs (65%) were based on a single study. One hundred eleven of 213 primary end points (52%) were compared with controls and 34 of 111 controls (31%) were retrospective. One hundred eighty-seven of 213 primary end points (88%) were surrogate measures and 122 of 157 (78%) had a discrepancy between the number of patients enrolled in the study and the number analyzed.

CONCLUSION

Premarket approval of cardiovascular devices by the FDA is often based on studies that lack adequate strength and may be prone to bias.