Objective. To determine if levels of endogenous estrogen or estrogen metabolites are associated with an increased risk of developing knee osteoarthritis (OA) in women.Methods. Serum estradiol (E 2 ) and 2 urinary estrogen metabolites (2-hydroxyestrone and 16␣-hydroxyestrone) with radiographically defined prevalent and incident knee OA in 842 white and African American women from the Southeast Michigan Arthritis Cohort.Results . Conclusion. There were significant associations of lower baseline serum estradiol and urinary 2-hydroxyestrone with developing knee OA in middle-aged women.

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Along with the increasing adoption of electronic health records (EHRs) are expectations that data collected within EHRs will be readily available for outcomes and comparative effectiveness research. Yet the ability to effectively share and reuse data depends on implementing and configuring EHRs with these goals in mind from the beginning. Data sharing and integration must be planned both locally as well as nationally. The rich data transmission and semantic infrastructure developed by the National Cancer Institute (NCI) for research provides an excellent example of moving beyond paper-based paradigms and exploiting the power of semantically robust, network-based systems, and engaging both domain and informatics expertise. Similar efforts are required to address current challenges in sharing EHR data.

Science studies has long been concerned with the theoretical and methodological challenge of mess—the inevitable tendency of technoscientific objects and practices to spill beyond the neat analytic categories we (or their actors) construct for them. Nowhere is this challenge greater than in the messy world of large-scale collaborative science projects, particularly though not exclusively in their start-up phases. This article examines the complicated life and death of the WATERS Network, an ambitious and ultimately abandoned effort at collaborative infrastructure development among hydrologists, engineers, and social scientists studying water. We argue in particular against the “forensic imagination,” a particular style of accounting for failure in the messy world of large-scale network development, and against two common conceptual and empirical pitfalls that it gives rise to: defaults to formalism and defaults to the future. We argue that alternative postforensic approaches to “failures” like the WATERS Network can support forms of learning and accountability better attuned to the complexities of practice and policy in the real world of scientific collaboration and network formation.

This paper explores the relationship between CSCW studies of scientific collaboration and the larger worlds of science practice and policy they are embedded in. We argue that CSCW has much to learn from debates in science policy, including questions around the changing nature of science and science-society relations that are partly but obliquely referenced in technology-or data-centered accounts of scientific change. At the same time, science policy has much to learn from CSCW -about design, infrastructure, and the organizational complexities of distributed collaborative practice. We conclude with recommendations for a better integration of the CSCW and science policy literatures around collaboration and new infrastructure development in the sciences, and speculation around what a post-normal cyberinfrastructure -and post-normal CSCWmight look like.