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Glioblastoma is a devastating disease with a dismal prognosis. While recent advancements in cancer immunotherapy have led to improvements in treating other types of cancer, patients with glioblastoma have not benefited from these new therapies and techniques. Fortunately, neurosurgeons and oncologists at Washington University School of Medicine conducting a cutting edge clinical trial are looking to overcome these persistent challenges in treating glioblastoma through combining a personalized vaccine with new immunotherapy drugs. Copyright 2020 by the Missouri State Medical Association.Maximal safe resection can improve patient outcomes for a variety of brain tumor types including low- and high-grade gliomas, pituitary adenomas, and other pathologies. Numerous intraoperative adjuncts exist to guide surgeons with maximizing extent of resection. Three distinct strategies exist including 1) surgical navigation; 2) intraoperative imaging; and 3) tumor fluorescence. Surgical navigation involves registration of high-resolution three-dimensional imaging to the patient's cranial surface anatomy, allowing real-time localization of tumor and brain structures. Intraoperative imaging devices like intraoperative magnetic resonance imaging (iMRI), intraoperative computed tomography (iCT), 3-D fluoroscopy, and intraoperative ultrasonography (iUS) allow near real time visualization to assess the extent of resection. Intraoperative fluorescence via intravenous fluorescein or oral 5-aminolevulinic acid (5-ALA) causes brain tumors to "light up", which can be viewed through surgical optics using selective filters and specific wavelength light sources. A general overview, as well as implementation and utilization of some of these image guidance strategies at Washington University and by Siteman Cancer Center neurosurgeons at Barnes Jewish Hospital, is discussed in this review. Copyright 2020 by the Missouri State Medical Association.The Gamma Knife Center of St. Louis has established itself as a key facility offering stereotactic radiosurgery (SRS) for a variety of neuro-oncologic disorders. Since the Gamma Knife unit was first brought to Washington University in 1997, we have treated 5,696 patients. In this review, we discuss the effective role of Gamma Knife SRS in the treatment strategies for patients with neuro-oncologic disorders including brain metastases, meningiomas, pituitary adenomas, and acoustic neuromas. While there is active ongoing research evaluating the most effective treatment for patients with these disorders, it is clear that best management practices may be tailored for individual patients utilizing SRS either alone or in conjunction alternative treatment strategies including open neurosurgical procedures, laser thermos-ablative surgery, and even new medical oncological treatment strategies. Stem Cells inhibitor Copyright 2020 by the Missouri State Medical Association.Automated scoring based on Latent Semantic Analysis (LSA) has been successfully used to score essays and constrained short answer responses. Scoring tests that capture open-ended, short answer responses poses some challenges for machine learning approaches. We used LSA techniques to score short answer responses to the Consequences Test, a measure of creativity and divergent thinking that encourages a wide range of potential responses. Analyses demonstrated that the LSA scores were highly correlated with conventional Consequence Test scores, reaching a correlation of .94 with human raters and were moderately correlated with performance criteria. This approach to scoring short answer constructed responses solves many practical problems including the time for humans to rate open-ended responses and the difficulty in achieving reliable scoring. © The Author(s) 2019.A procedure for evaluation of validity related coefficients and their differences is discussed, which is applicable when one or more frequently used assumptions in empirical educational, behavioral and social research are violated. The method is developed within the framework of the latent variable modeling methodology and accomplishes point and interval estimation of convergent and discriminant correlations as well as differences between them in cases of incomplete data sets with data not missing at random, nonnormality, and clustering effects. The procedure uses the full information maximum likelihood approach to model fitting and parameter estimation, does not assume availability of multiple indicators for underlying latent constructs, includes auxiliary variables, and accounts for within-group correlations on main response variables resulting from nesting effects involving studied respondents. The outlined procedure is illustrated on empirical data from a study using tertiary education entrance examination measures. © The Author(s) 2019.Student assessment nonparticipation (or opt out) has increased substantially in K-12 schools in states across the country. This increase in opt out has the potential to impact achievement and growth (or value-added) measures used for educator and institutional accountability. In this simulation study, we investigated the extent to which value-added measures of teacher quality are affected as a result of varying degrees of opt out, as well as a result of various types of nonrandom opt out. Results show that the magnitude of opt out and choice of classification scheme has a greater impact on value-added estimates than the type of opt-out patterns simulated in this study. Specifically, root mean square differences in value-added estimates increased as magnitude of opt out increased. In addition, teacher effectiveness classification agreement decreased as opt out magnitude increased. One type of opt out, where the highest achieving students in the highest achieving classrooms opted out, had the largest impact on stability than the other types of opt outs. © The Author(s) 2019.A mixture extension of Samejima's continuous response model for continuous measurement outcomes and its estimation through a heuristic approach based on limited-information factor analysis is introduced. Using an empirical data set, it is shown that two groups of respondents that differ both qualitatively and quantitatively in their response behavior can be revealed. In addition to the real data application, the effectiveness of the heuristic estimation approach under real data analytic conditions was examined through a Monte Carlo simulation study. The results showed that the heuristic estimation approach provided reliable parameter estimates and the model successfully converged above 80% when the sample size was 250 and above 90% when the sample size was 500 or 1,000 for most conditions. © The Author(s) 2019.
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