MOBILE ENCHANTMENT: THE VIRGINIA THEATRE MACHINE LLC, A NEW TWIST ON DRIVE-IN THEATRE

A disassembling of the Virginia Theatre Machine (VTM), LLC and its annual restaging of an adaption of Charles Dickens’ novella, A Christmas Carol. The VTM is a custom-built trailer theater that combines the performance energy of street theater with the magic and wonder of a fully designed theatrical production. I provide a historical context for this 21st century revising of mobile theater that switches the paradigm of the traditional theater experience by bringing the stage to audiences, for free. I draw from critical social and cultural theory to make sense of the audience impact in public and private outdoor spaces. I examine how each new performance environment brings its own resonance to bear on the wonder of the presentation at hand. I present the VTM as an alternative business model and form of theater outreach to inspire a new generation of theater-makers to rethink the traditional constraints of producing theatre

Inequivalent contact structures on Boothby-Wang 5-manifolds

We consider contact structures on simply-connected 5-manifolds which arise as circle bundles over simply-connected symplectic 4-manifolds and show that invariants from contact homology are related to the divisibility of the canonical class of the symplectic structure. As an application we find new examples of inequivalent contact structures in the same equivalence class of almost contact structures with non-zero first Chern class.Comment: 27 pages; to appear in Math. Zeitschrif

Exploiting data semantics to discover, extract, and model web sources

We describe DEIMOS, a system that automatically discovers and models new sources of information. The system exploits four core technologies developed by our group that makes an end-to-end solution to this problem possible. First, given an example source, DEIMOS finds other similar sources online. Second, it invokes and extracts data from these sources. Third, given the syntactic structure of a source, DEIMOS maps its inputs and outputs to semantic types. Finally, it infers the source’s semantic definition, i.e., the function that maps the inputs to the outputs. DEIMOS is able to successfully automate these steps by exploiting a combination of background knowledge and data semantics. We describe the challenges in integrating separate components into a unified approach to discovering, extracting and modeling new online sources. We provide an end-toend validation of the system in two information domains to show that it can successfully discover and model new data sources in those domains. 1

Automated recognition of malignancy mentions in biomedical literature

BACKGROUND: The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of interest. Automated information extraction procedures can assist in the acquisition and management of this knowledge. Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related objects and concepts. Furthermore, promise has been tempered by an inability to efficiently scale approaches in ways that minimize manual efforts and still perform with high accuracy. Here, we have applied a machine-learning approach previously successful for identifying molecular entities to a disease concept to determine if the underlying probabilistic model effectively generalizes to unrelated concepts with minimal manual intervention for model retraining. RESULTS: We developed a named entity recognizer (MTag), an entity tagger for recognizing clinical descriptions of malignancy presented in text. The application uses the machine-learning technique Conditional Random Fields with additional domain-specific features. MTag was tested with 1,010 training and 432 evaluation documents pertaining to cancer genomics. Overall, our experiments resulted in 0.85 precision, 0.83 recall, and 0.84 F-measure on the evaluation set. Compared with a baseline system using string matching of text with a neoplasm term list, MTag performed with a much higher recall rate (92.1% vs. 42.1% recall) and demonstrated the ability to learn new patterns. Application of MTag to all MEDLINE abstracts yielded the identification of 580,002 unique and 9,153,340 overall mentions of malignancy. Significantly, addition of an extensive lexicon of malignancy mentions as a feature set for extraction had minimal impact in performance. CONCLUSION: Together, these results suggest that the identification of disparate biomedical entity classes in free text may be achievable with high accuracy and only moderate additional effort for each new application domain

A Mediterranean Low-Glycemic-Load Diet alone or in Combination with a Medical Food Improves Insulin Sensitivity and Reduces Inflammation in Women with Metabolic Syndrome

Aim: To determine the effects of a Mediterranean-style low-glycemic load diet alone or in combination with a medical food (MF) on insulin resistance and inflammation in women with metabolic syndrome (MetS). Study design: Two groups, Parallel study with control. Place and Duration of Study: Department of Nutritional Sciences, University of Connecticut, Storrs, CT; Department of Emergency Medicine, University of Florida, Jacksonville, FL; Department of Medicine, University of California, Irvine, CA. The study was carried out from September of 2009 to May 2010. Methodology: Eighty three women (20-75 y) with MetS. Participants were randomly allocated to consume diet alone (control group) or the diet plus the MF (MF group) for 12 wk. Body composition was measured at baseline, week 8 and week 12 by use of bioelectrical impedance in all participants while Dual-emission X-ray absorptiometry was used for 37 of the subjects. Insulin resistance, plasma insulin, leptin, adiponectin and the inflammatory cytokines, tumor necrosis factor (TNF)-α, interleukin-6 (IL-6), adhesion molecules, sICAM-1 and sVCAM-1, were measured at the same time points. Results: Independent of group allocation, women had decreases in body mass index (p \u3c 0.0001) and body and trunk fat (p \u3c 0.0001). Plasma insulin, insulin resistance, and leptin were also significantly decreased over time (p \u3c 0.0001), while plasma adiponectin levels did not change. Regarding inflammatory markers, significant reductions were found in TNF-α (p \u3c 0.0001) and sICAM-1 levels (p \u3c 0.001), but not in IL-6 or sVCAM-1. At 12 wk, sICAM was reduced only in the MF group (

Complementary and alternative medicine use among women at increased genetic risk of breast and ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Complementary and alternative medicine (CAM) use is well documented among breast cancer patients and survivors, but little evidence is available to describe rates and patterns of use among women at increased genetic risk of breast cancer.</p> <p>Methods</p> <p>A pre-visit telephone interview was conducted to ascertain CAM use among the <it>BRCA </it>mutation carriers enrolled in a high-risk breast cancer screening study. Participants were asked to report on their use of thirteen therapies within the year prior to enrollment into the study. Logistic regression was used to evaluate the association between various factors and CAM use in this population.</p> <p>Results</p> <p>Among the 164 <it>BRCA1 </it>or <it>BRCA2 </it>mutation-positive (<it>BRCA</it>+) women in this analysis, 78% reported CAM use, with prayer and lifestyle diet being the two most commonly reported modalities. Many subjects used multiple CAM therapies, with 34% reporting use of three or more modalities. The most commonly used modalities were mind-body therapies and biologically-based practices, 61.6% and 51.8%, respectively. High-risk women were more likely to use CAM if they were older, more educated, more worried about ovarian cancer risk, or had a previous cancer diagnosis.</p> <p>Conclusion</p> <p>This study suggests that the prevalence of CAM use is high among <it>BRCA </it>mutation carriers, with frequency of use comparable to that of breast cancer patients and survivors. Given the high prevalence of CAM use in our subjects, especially biologically-based therapies including herbal supplements, whose safety and efficacy in relation to cancer risk are unknown, our study suggests that future research is necessary to clarify these risks, and that it is important for providers to inquire about and to discuss the pros and cons of CAM use with their <it>BRCA+ </it>patients.</p

Opisthorchiasis from Imported Raw Fish

Acute liver fluke infection results from eating raw fish illegally imported from Siberia

Measuring the psychosocial burden in women with low-grade abnormal cervical cytology in the TOMBOLA trial: psychometric properties of the Process and Outcome Specific Measure (POSM)

Background There is a need for an instrument to measure the psychosocial burden of receiving an abnormal cervical cytology result which can be used regardless of the clinical management women receive. Methods 3331 women completed the POSM as part of baseline psychosocial assessment in a trial of management of low grade cervical cytological abnormalities. Factor analysis and reliability assessment of the POSM were conducted. Results Two factors were extracted from the POSM: Factor 1, containing items related to worry; and Factor 2 containing items relating to satisfaction with information and support received and change in the way women felt about themselves. Factor 1 had good reliability (Cronbach’s alpha 0.769), however reliability of the Factor 2 was poorer (0.482). Data collected at four subsequent time points demonstrated that the factor structure was stable over time. Conclusion This study demonstrates the presence and reliability of a scale measuring worries within the POSM. This analysis will inform its future use in this population and in other related contexts

Toward Composite Pain Biomarkers of Neuropathic Pain—Focus on Peripheral Neuropathic Pain

Chronic pain affects ~10–20% of the U.S. population with an estimated annual cost of $600 billion, the most significant economic cost of any disease to-date. Neuropathic pain is a type of chronic pain that is particularly difficult to manage and leads to significant disability and poor quality of life. Pain biomarkers offer the possibility to develop objective pain-related indicators that may help diagnose, treat, and improve the understanding of neuropathic pain pathophysiology. We review neuropathic pain mechanisms related to opiates, inflammation, and endocannabinoids with the objective of identifying composite biomarkers of neuropathic pain. In the literature, pain biomarkers typically are divided into physiological non-imaging pain biomarkers and brain imaging pain biomarkers. We review both types of biomarker types with the goal of identifying composite pain biomarkers that may improve recognition and treatment of neuropathic pain