Project description:BackgroundAlthough tissue microarrays (TMAs) are commonly employed in clinical and basic-science research, there are no guidelines for evaluating the appropriateness of a TMA for a given biomarker and tumor type. Furthermore, TMA performance across multiple biomarkers has not been systematically explored.MethodsA simulated TMA with between 1 and 10 cores was designed to study tumor expression of 6 biomarkers with varied expression patterns (B7-H1, B7-H3, survivin, Ki-67, CAIX, and IMP3) using 100 patients with clear cell renal cell carcinoma (RCC). We evaluated agreement between whole tissue section and TMA immunohistochemical biomarker quantification to assess how many TMA cores are necessary to adequately represent RCC whole tissue section expression. Additionally, we evaluated associations of whole tissue section and TMA expression with RCC-specific death.ResultsThe number of simulated TMA cores necessary to adequately represent whole tissue section quantification is biomarker specific. Although 2-3 cores appeared adequate for B7-H3, Ki-67, CAIX, and IMP3, even as many as 10 cores resulted in poor agreement for B7-H1 and survivin compared to RCC whole tissue sections. While whole tissue section B7-H1 was significantly associated with RCC-specific death, no significant associations were detected using as many as 10 TMA cores, suggesting that TMAs can result in false-negative findings if the TMA is not optimally designed.ConclusionsPrior to TMA analysis, the number of TMA cores necessary to accurately represent biomarker expression on whole tissue sections should be established as there is not a one-size-fits-all TMA. We illustrate the use of a simulated TMA as a cost-effective tool for this purpose.
Project description:The time is ripe to assess whether pharmacogenomics research--the study of the genetic basis for variation in drug response--has provided important insights into a personalized approach to prescribing and dosing medications. Here, we describe the status of the field and approaches for addressing some of the open questions in pharmacogenomics research and use of genetic testing in guiding drug therapy.
Project description:Well-being and burnout are concepts that have become well described throughout emergency medicine. In the past, both well-being and burnout have been defined and addressed as a singular phenomenon, similar for all physicians, regardless of career stage. However, unique stressors may exist for physicians, as a function of their work environment and stage. In this concepts article we present clinician well-being as a dynamic and continuous process, subject to unique factors along the professional lifespan. Specific individual and system-level factors are discussed, ranging from demographic variables, to evolving administrative and professional responsibilities depending on the career stage of a clinician. This detailed description of stressors spanning an emergency physician's professional career may help create more targeted physician well-being and burnout interventions.
Project description:High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.
Project description:HypothesisThis study tests the hypothesis that it is possible to find tone or noise vocoders that sound similar and result in similar speech perception scores to a cochlear implant (CI). This would validate the use of such vocoders as acoustic models of CIs. We further hypothesize that those valid acoustic models will require a personalized amount of frequency mismatch between input filters and output tones or noise bands.BackgroundNoise or tone vocoders have been used as acoustic models of CIs in hundreds of publications but have never been convincingly validated.MethodsAcoustic models were evaluated by single-sided deaf CI users who compared what they heard with the CI in one ear to what they heard with the acoustic model in the other ear. We evaluated frequency-matched models (both all-channel and 6-channel models, both tone and noise vocoders) as well as self-selected models that included an individualized level of frequency mismatch.ResultsSelf-selected acoustic models resulted in similar levels of speech perception and similar perceptual quality as the CI. These models also matched the CI in terms of perceived intelligibility, harshness, and pleasantness.ConclusionValid acoustic models of CIs exist, but they are different from the models most widely used in the literature. Individual amounts of frequency mismatch may be required to optimize the validity of the model. This may be related to the basalward frequency mismatch experienced by postlingually deaf patients after cochlear implantation.