498 research outputs found

    ENHANCING DYNAMICS COURSES WITH MODEL ELICITING ACTIVITIES

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    Model eliciting activities are assignments which require students to develop models to describe realistic situations. Every MEA follows six principles: model-construction, reality, self-assessment, model documentation, generalizability, and effective prototype. The six principles provide a solid guideline in which instructors can develop more MEAs, which can then be shared and used among several participating universities. Under NSF CCLI Grant #0717595, Cal Poly is currently developing Model Eliciting Activities for the subject of Mechanical Engineering. This report documents the undertakings to implement and enhance two Model Eliciting Activities (MEAs) into the Cal Poly curriculum. Specifically, the development of the Vehicle Accident Reconstruction (VAR) MEA and the Catapult MEA will be covered in detail. The VAR MEA was a project assigned in ME212 “Engineering Dynamics,” which required students to apply momentum principles to a two-vehicle collision. Because of the heavy development time experienced by the MEA research team, a MatLab program which accepted user inputs via a graphical user interface (GUI) was developed. This GUI solved for initial velocities during two-vehicle collisions by applying appropriate momentum and work-energy principles. With this program, instructors can more easily develop crash scenarios, as well as check student work. The Catapult MEA was also a project assigned to ME212 students. It required them to analyze the launch trajectory of an actual scaled catapult using angular motion and work-energy principles. This scaled-catapult was instrumented with one ADXL278 dual-axis accelerometer and four CEA-06-240UZ-120 strain gages. This instrumentation allowed for the experimental data acquisition of the catapult angular velocity, acceleration, and strains. By postprocessing this experimental data using a MatLab program, the experimental results can then be compared to theoretical results. The overall goal for the VAR MEA GUI programming was to reduce instructor workload in order to promote usage the MEA through a broader range of universities. The goal of the Catapult instrumentation was to provide students with actual experimental data, which could then be used to confirm their theoretical model. The system was set up so that they could easily record their own experimental data for each catapult launch

    The Society for Immunotherapy of Cancer consensus statement on immunotherapy for the treatment of prostate carcinoma.

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    Prostate cancer is the most commonly diagnosed malignancy and second leading cause of cancer death among men in the United States. In recent years, several new agents, including cancer immunotherapies, have been approved or are currently being investigated in late-stage clinical trials for the management of advanced prostate cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) convened a multidisciplinary panel, including physicians, nurses, and patient advocates, to develop consensus recommendations for the clinical application of immunotherapy for prostate cancer patients. To do so, a systematic literature search was performed to identify high-impact papers from 2006 until 2014 and was further supplemented with literature provided by the panel. Results from the consensus panel voting and discussion as well as the literature review were used to rate supporting evidence and generate recommendations for the use of immunotherapy in prostate cancer patients. Sipuleucel-T, an autologous dendritic cell vaccine, is the first and currently only immunotherapeutic agent approved for the clinical management of metastatic castrate resistant prostate cancer (mCRPC). The consensus panel utilized this model to discuss immunotherapy in the treatment of prostate cancer, issues related to patient selection, monitoring of patients during and post treatment, and sequence/combination with other anti-cancer treatments. Potential immunotherapies emerging from late-stage clinical trials are also discussed. As immunotherapy evolves as a therapeutic option for the treatment of prostate cancer, these recommendations will be updated accordingly

    Systemic immunity is required for effective cancer immunotherapy

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    Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 T cells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection

    The Ultraviolet-Bright, Slowly Declining Transient PS1-11af as a Partial Tidal Disruption Event

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    We present the Pan-STARRS1 discovery of the long-lived and blue transient PS1-11af, which was also detected by Galaxy Evolution Explorer with coordinated observations in the near-ultraviolet (NUV) band. PS1-11af is associated with the nucleus of an early type galaxy at redshift z = 0.4046 that exhibits no evidence for star formation or active galactic nucleus activity. Four epochs of spectroscopy reveal a pair of transient broad absorption features in the UV on otherwise featureless spectra. Despite the superficial similarity of these features to P-Cygni absorptions of supernovae (SNe), we conclude that PS1-11af is not consistent with the properties of known types of SNe. Blackbody fits to the spectral energy distribution are inconsistent with the cooling, expanding ejecta of a SN, and the velocities of the absorption features are too high to represent material in homologous expansion near a SN photosphere. However, the constant blue colors and slow evolution of the luminosity are similar to previous optically selected tidal disruption events (TDEs). The shape of the optical light curve is consistent with models for TDEs, but the minimum accreted mass necessary to power the observed luminosity is only similar to 0.002 M-circle dot, which points to a partial disruption model. A full disruption model predicts higher bolometric luminosities, which would require most of the radiation to be emitted in a separate component at high energies where we lack observations. In addition, the observed temperature is lower than that predicted by pure accretion disk models for TDEs and requires reprocessing to a constant, lower temperature. Three deep non-detections in the radio with the Very Large Array over the first two years after the event set strict limits on the production of any relativistic outflow comparable to Swift J1644+57, even if off-axis.NSF Astronomy and Astrophysics Postdoctoral Fellowship AST-1302954National Aeronautics and Space Administration through the Planetary Science Division of the NASA Science Mission Directorate NNX08AR22GNational Science Foundation AST-1238877, AST-1211196,AST-1009749, AST-1009863(PI: Berger) at the Gemini Observatory GS-2011A-Q-29European Research Council under the European Union/ERC 291222NASA through the Astrophysics Theory Program NNX10AF62GFAS Science Division Research Computing Group at Harvard UniversityAstronom

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    The KCNJ11 E23K Polymorphism and Progression of Glycaemia in Southern Chinese: A Long-Term Prospective Study

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    Context: The KCNJ11 E23K variant is associated with type 2 diabetes mellitus (T2DM) in cross-sectional studies, but conflicting findings have been reported from prospective studies. Objective: This study aimed to evaluate whether the E23K variant could predict glycaemic progression in a Southern Chinese population. Methods/Principal Findings: We performed a long-term prospective study on 1912 subjects from the Hong Kong Cardiovascular Risk Factors Prevalence Study (CRISPS). The KCNJ11 E23K variant was associated with the progression to prediabetes after a median interval of 12 years on multinomial logistic regression analysis, even after adjustment for traditional risk factors (OR 1.29, P age, sex, BMI and fasting plasma glucose [FPG] adjusted = 0.02). Based on Cox proportional hazard regression analysis, the E23K variant also predicted incident prediabetes (HR 1.18, P age, sex, BMI and FPG adjusted = 0.021). However, E23K was not associated with the progression to T2DM in either multinomial or Cox regression analysis, and the association of E23K with glycaemic progression to either prediabetes or T2DM was significant only in unadjusted Cox regression analysis (P = 0.039). In a meta-analysis of eight prospective studies including our own, involving 15680 subjects, the E23K variant was associated with incident T2DM (fixed effect: OR 1.10, P = 4×10 -3; random effect: OR 1.11, P = 0.035). Conclusions: Our study has provided supporting evidence for the role of the E23K variant in glycaemic progression in Chinese, with its effect being more evident in the early stage of T2DM, as the subjects progressed from normal glucose tolerance to prediabetes. © 2011 Cheung et al.published_or_final_versio

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin
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