Fourth Ventricular Schwannoma: Identical Clinicopathologic Features as Schwann Cell-Derived Schwannoma with Unique Etiopathologic Origins

Background. To our knowledge, this is the sixth reported case in the literature of fourth ventricular schwannoma. The etiology and natural history of intraventricular schwannomas is not well understood. A thorough review of potential etiopathogenic mechanisms is provided in this case report. Case Description. A 69-year-old man presented with an incidentally found fourth ventricular tumor during an evaluation for generalized weakness, gait instability, and memory disturbance. Magnetic resonance imaging (MRI) revealed a heterogeneously enhancing lesion in the fourth ventricle. A suboccipital craniotomy was performed to resect the lesion. Histopathological examination confirmed the diagnosis of schwannoma (WHO grade I). Conclusions. Schwannomas should be considered in the differential diagnosis of intraventricular tumors. Although the embryologic origins may be different from nerve sheath-derived schwannomas, the histologic, clinical, and natural history appear identical and thus should be managed similarly

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Imaging of Convection Enhanced Delivery of Toxins in Humans

Drug delivery of immunotoxins to brain tumors circumventing the blood brain barrier is a significant challenge. Convection-enhanced delivery (CED) circumvents the blood brain barrier through direct intracerebral application using a hydrostatic pressure gradient to percolate therapeutic compounds throughout the interstitial spaces of infiltrated brain and tumors. The efficacy of CED is determined through the distribution of the therapeutic agent to the targeted region. The vast majority of patients fail to receive a significant amount of coverage of the area at risk for tumor recurrence. Understanding this challenge, it is surprising that so little work has been done to monitor the delivery of therapeutic agents using this novel approach. Here we present a review of imaging in convection enhanced delivery monitoring of toxins in humans, and discuss future challenges in the field

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

Monitoring Radiographic Brain Tumor Progression

Determining radiographic progression in primary malignant brain tumors has posed a significant challenge to the neuroncology community. Glioblastoma multiforme (GBM, WHO Grade IV) through its inherent heterogeneous enhancement, growth patterns, and irregular nature has been difficult to assess for progression. Our ability to detect tumor progression radiographically remains inadequate. Despite the advanced imaging techniques, detecting tumor progression continues to be a clinical challenge. Here we review the different criteria used to detect tumor progression, and highlight the inherent challenges with detection of progression

A primary care, multi-disciplinary disease management program for opioid-treated patients with chronic non-cancer pain and a high burden of psychiatric comorbidity

BACKGROUND: Chronic non-cancer pain is a common problem that is often accompanied by psychiatric comorbidity and disability. The effectiveness of a multi-disciplinary pain management program was tested in a 3 month before and after trial. METHODS: Providers in an academic general medicine clinic referred patients with chronic non-cancer pain for participation in a program that combined the skills of internists, clinical pharmacists, and a psychiatrist. Patients were either receiving opioids or being considered for opioid therapy. The intervention consisted of structured clinical assessments, monthly follow-up, pain contracts, medication titration, and psychiatric consultation. Pain, mood, and function were assessed at baseline and 3 months using the Brief Pain Inventory (BPI), the Center for Epidemiological Studies-Depression Scale scale (CESD) and the Pain Disability Index (PDI). Patients were monitored for substance misuse. RESULTS: Eighty-five patients were enrolled. Mean age was 51 years, 60% were male, 78% were Caucasian, and 93% were receiving opioids. Baseline average pain was 6.5 on an 11 point scale. The average CESD score was 24.0, and the mean PDI score was 47.0. Sixty-three patients (73%) completed 3 month follow-up. Fifteen withdrew from the program after identification of substance misuse. Among those completing 3 month follow-up, the average pain score improved to 5.5 (p = 0.003). The mean PDI score improved to 39.3 (p < 0.001). Mean CESD score was reduced to 18.0 (p < 0.001), and the proportion of depressed patients fell from 79% to 54% (p = 0.003). Substance misuse was identified in 27 patients (32%). CONCLUSIONS: A primary care disease management program improved pain, depression, and disability scores over three months in a cohort of opioid-treated patients with chronic non-cancer pain. Substance misuse and depression were common, and many patients who had substance misuse identified left the program when they were no longer prescribed opioids. Effective care of patients with chronic pain should include rigorous assessment and treatment of these comorbid disorders and intensive efforts to insure follow up

Separating content-specific retrieval from post-retrieval processing

According to cortical reinstatement accounts, neural processes engaged at the time of encoding are re-engaged at the time of memory retrieval. The temporal precision of event-related potentials (ERPs) has been exploited to assess this possibility, and in this study ERPs were acquired while people made memory judgments to visually presented words encoded in two different ways. There were reliable differences between the scalp distributions of the signatures of successful retrieval of different contents from 300 to 1100 ms after stimulus presentation. Moreover, the scalp distributions of these content-sensitive effects changed during this period. These findings are, to our knowledge, the first demonstration in one study that ERPs reflect content-specific processing in two separable ways: first, via reinstatement, and second, via downstream processes that operate on recovered information in the service of memory judgments

Ideological cultures and media discourses on scientific knowledge: re-reading news on climate change

Focusing on the representation of climate change in the British “quality press,” this article argues that the discursive (re)construction of scientific claims in the media is strongly entangled with ideological standpoints. Understood here as a set of ideas and values that legitimate a program of action vis-à-vis a given social and political order, ideology works as a powerful selection device in deciding what is scientific news, i.e. what the relevant “facts” are, and who are the authorized “agents of definition” of science matters. The representation of scientific knowledge has important implications for evaluating political programs and assessing the responsibility of both governments and the public in addressing climate change

Oncotarget, Advance Publications 2014 Mutations in IDH1, IDH2, and in the TERT promoter define clinically distinct subgroups of adult malignant gliomas

ABSTRACT: Frequent mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) and the promoter of telomerase reverse transcriptase (TERT) represent two significant discoveries in glioma genomics. Understanding the degree to which these two mutations co-occur or occur exclusively of one another in glioma subtypes presents a unique opportunity to guide glioma classification and prognosis. We analyzed the relationship between overall survival (OS) and the presence of IDH1/2 and TERT promoter mutations in a panel of 473 adult gliomas. We hypothesized and show that genetic signatures capable of distinguishing among several types of gliomas could be established providing clinically relevant information that can serve as an adjunct to histopathological diagnosis. We found that mutations in the TERT promoter occurred in 74.2% of glioblastomas (GBM), but occurred in a minority of Grade II-III astrocytomas (18.2%). In contrast, IDH1/2 mutations were observed in 78.4% of Grade II-III astrocytomas, but were uncommon in primary GBM. In oligodendrogliomas, TERT promoter and IDH1/2 mutations co-occurred in 79% of cases. Patients whose Grade III-IV gliomas exhibit TERT promoter mutations alone predominately have primary GBMs associated with poor median OS (11.5 months). Patients whose Grade III-IV gliomas exhibit IDH1/2 mutations alone predominately have astrocytic morphologies and exhibit a median OS of 57 months while patients whose tumors exhibit both TERT promoter and IDH1/2 mutations predominately exhibit oligodendroglial morphologies and exhibit median OS of 125 months. Analyzing gliomas based on their genetic signatures allows for the stratification of these patients into distinct cohorts, with unique prognosis and survival