Causal Diagram Techniques for Urologic Oncology Research

Large quantities of data are now available to medical researchers; however, observational studies are plagued by bias and confounding. Additionally, much of this research only speculates on variable associations, leaving prospective randomized clinical trials as the sole purveyors of claims about causal relations between variables. There has been a growing movement of causal inference that uses new techniques to investigate causality using observational data. These techniques include the implementation of directed acyclic graphs, which allow researchers to explicitly and reproducibly define the causal relationships between study variables, thus making statistical analysis more robust. Directed acyclic graphs further allow researchers to identify confounding and other sources of bias and to discover causal effects among complex networks of variables. This review aims to introduce these techniques to the general urology and urologic oncology research communities in order to provide a basic understanding of causal inference and analysis and call for integration of these practices more generally in research methodology.     

应用多方法联合质控丙戊酸血药浓度监测

目的：对丙戊酸血药浓度质控监测数据绘制质控图,并进行连续性评估与分析,积累本实验室的质控趋势,提高误差检测灵敏度,确保药物浓度检测的准确性。方法对2013年8月—2014年7月丙戊酸低、中、高质控浓度133个监测数据绘制质控图,并采用Levey‐Jennings质控方法结合Westgard多规则进行统计分析。结果不同的质控方法失控率不同,基于药典要求的质控失控率最高;依据说明书中的质控范围,失控率略低;而根据Levey‐Jennings质控图结合Westgard多规则进行质控分析发现,失控率明显降低。结论通过对不同质控方法的对比分析,在长期进行血药浓度检测过程中,为提高检测结果的准确度,不能单一使用一种质控方法,应使用多种方法联合质控。     

Social Network Analysis to Assess the Impact of the CTSA on Biomedical Research Grant Collaboration

Success of the Clinical Translational Science Award (CTSA) program implicitly demands team science efforts and well‐orchestrated collaboration across the translational silos (T1–T4). Networks have proven to be useful abstractions of research collaborations. Networks provide novel system‐level insights and exhibit marked changes in response to external interventions, making them potential evaluation tools that complement more traditional approaches. This study is part of our ongoing efforts to assess the impact of the CTSA on Biomedical Research Grant Collaboration (BRGC). Collaborative research grants are a complex undertaking and an outcome of sustained interaction among researchers. In this report, BRGC networks representing collaborations among CTSA‐affiliated investigators constructed from grants management system data at the University of Kentucky across a period of six years (2007–2012) corresponding to pre‐ and post‐CTSA are investigated. Overlapping community structure detection algorithms, in conjunction with surrogate testing, revealed the presence of intricate research communities rejecting random graphs as generative mechanisms. The deviation from randomness was especially pronounced post‐CTSA, reflecting an increasing trend in collaborations and team‐science efforts potentially as a result of CTSA. Intercommunity cross talk was especially pronounced post‐CTSA.     

Dynamic path analysis – a useful tool to investigate mediation processes in clinical survival trials

When it comes to clinical survival trials, regulatory restrictions usually require the application of methods that solely utilize baseline covariates and the intention‐to‐treat principle. Thereby, much potentially useful information is lost, as collection of time‐to‐event data often goes hand in hand with collection of information on biomarkers and other internal time‐dependent covariates. However, there are tools to incorporate information from repeated measurements in a useful manner that can help to shed more light on the underlying treatment mechanisms. We consider dynamic path analysis, a model for mediation analysis in the presence of a time‐to‐event outcome and time‐dependent covariates to investigate direct and indirect effects in a study of different lipid‐lowering treatments in patients with previous myocardial infarctions. Further, we address the question whether survival in itself may produce associations between the treatment and the mediator in dynamic path analysis and give an argument that because of linearity of the assumed additive hazard model, this is not the case. We further elaborate on our view that, when studying mediation, we are actually dealing with underlying processes rather than single variables measured only once during the study period. This becomes apparent in results from various models applied to the study of lipid‐lowering treatments as well as our additionally conducted simulation study, where we clearly observe that discarding information on repeated measurements can lead to potentially erroneous conclusions. Copyright © 2015 John Wiley & Sons, Ltd.     

Learning from nature – Novel synthetic biology approaches for biomaterial design

Many biomaterials constructed today are complex chemical structures that incorporate biologically active components derived from nature, but the field can still be said to be in its infancy. The need for materials that bring sophisticated properties of structure, dynamics and function to medical and non-medical applications will only grow. Increasing appreciation of the functionality of biological systems has caused biomaterials researchers to consider nature for design inspiration, and many examples exist of the use of biomolecular motifs. Yet evolution, nature’s only engine for the creation of new designs, has been largely ignored by the biomaterials community. Molecular evolution is an emerging tool that enables one to apply nature’s engineering principles to non-natural situations using variation and selection. The purpose of this review is to highlight the most recent advances in the use of molecular evolution in synthetic biology applications for biomaterial engineering, and to discuss some of the areas in which this approach may be successfully applied in the future.     

日本血吸虫(中国大陆株)表达基因的分离和EST序列测定

目的 运用表达标签技术（ＥＳＴ方法）,从ＳｊｃＤＮＡ文库中分离、鉴定血吸虫表达基因序列。方法 应用ＥＳＴ方法,人ＳｊｃＤＮＡ文库中随机挑出单个重组克陲 ＰＣＲ直接序列分析,通过互联网将获得的ＥＳＴ序列送入ＮＣＢＩＧｅｎＢａｎｋ进行同源性检素,并将发现的未知基因ＥＳＴ序列送入ＮＣＢＩｄｂＥＳＴ以获得ＧｅｎＢａｎｋ进入号。结果 分离了１００个ＳｊＧｅｎＢａｎｋ中已知的血吸虫基因序列,１９个为未知基因序     

Periodically Grafted Linear–Hyperbranched Copolymers Based on Polyethylene and Polyglycidol: Importance of the Architecture on Properties

Here, the periodically grafted linear–hyperbranched copolymers (LHGCs) based on polyethylene (PE) and hyperbranched polyglycidol is synthesized via acyclic diene metathesis polymerization and anionic ring‐opening multibranching polymerization. The chemical composition of LHGCs can be controlled by changing the amount of the initial monomer. For the first time this allows to control the architecture (composition and sequence distribution), in which the run length between adjacent hyperbranched pendants is exact along PE backbone. By comparing with aperiodically grafted analogues, the results clearly show the composition and the sequence distribution of LHGCs is identified as the major factor to influence the thermal stability, crystallinity as well as hydrophilicity.