Research methods for profile analysis: Introduction to the special issue.

The five articles that make up the bulk of this special issue collectively illustrate new methods for examining the utility of sub-test and scale-level profile analysis. By necessity they are preliminary, but they illustrate methods that may indeed prove useful and may help resolve this divide between research and practice. This special issue grew out of a symposium conceived and organized by Cecil Reynolds at the American Psychological Association in 1998. The articles and one of the commentaries in this special issue are extensions of that symposium. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Genetic Variants Associated with Long-Terminal Repeats Can Diagnostically Classify Cannabis Varieties

Cannabis sativa (Cannabis) has recently been legalized in multiple countries globally for either its recreational or medicinal use. This, in turn, has led to a marked increase in the number of Cannabis varieties available for use in either market. However, little information currently exists on the genetic distinction between adopted varieties. Such fundamental knowledge is of considerable value and underpins the accelerated development of both a nascent pharmaceutical industry and the commercial recreational market. Therefore, in this study, we sought to assess genetic diversity across 10 Cannabis varieties by undertaking a reduced representation shotgun sequencing approach on 83 individual plants to identify variations which could be used to resolve the genetic structure of the assessed population. Such an approach also allowed for the identification of the genetic features putatively associated with the production of secondary metabolites in Cannabis. Initial analysis identified 3608 variants across the assessed population with phylogenetic analysis of this data subsequently enabling the confident grouping of each variety into distinct subpopulations. Within our dataset, the most diagnostically informative single nucleotide polymorphisms (SNPs) were determined to be associated with the long-terminal repeat (LTRs) class of retroelements, with 172 such SNPs used to fully resolve the genetic structure of the assessed population. These 172 SNPs could be used to design a targeted resequencing panel, which we propose could be used to rapidly screen different Cannabis plants to determine genetic relationships, as well as to provide a more robust, scientific classification of Cannabis varieties as the field moves into the pharmaceutical sphere.     

Hyperinsulinemic Hypoglycemia Associated with a CaV1.2 Variant with Mixed Gain- and Loss-of-Function Effects

The voltage-dependent L-type calcium channel isoform Ca_V1.2 is critically involved in many physiological processes, e.g., in cardiac action potential formation, electromechanical coupling and regulation of insulin secretion by beta cells. Gain-of-function mutations in the calcium voltage-gated channel subunit alpha 1 C (CACNA1C) gene, encoding the Ca_V1.2 α₁-subunit, cause Timothy syndrome (TS), a multisystemic disorder that includes autism spectrum disorders and long QT (LQT) syndrome. Strikingly, TS patients frequently suffer from hypoglycemia of yet unproven origin. Using next-generation sequencing, we identified a novel heterozygous CACNA1C mutation in a patient with congenital hyperinsulinism (CHI) and associated hypoglycemic episodes. We characterized the electrophysiological phenotype of the mutated channel using voltage-clamp recordings and in silico action potential modeling experiments. The identified Ca_V1.2^L566P mutation causes a mixed electrophysiological phenotype of gain- and loss-of-function effects. In silico action potential modeling supports that this mixed electrophysiological phenotype leads to a tissue-specific impact on beta cells compared to cardiomyocytes. Thus, CACNA1C variants may be associated with non-syndromic hyperinsulinemic hypoglycemia without long-QT syndrome, explained by very specific electrophysiological properties of the mutated channel. We discuss different biochemical characteristics and clinical impacts of hypoglycemia in the context of CACNA1C variants and show that these may be associated with significant morbidity for Timothy Syndrome patients. Our findings underline that the potential of hypoglycemia warrants careful attention in patients with CACNA1C variants, and such variants should be included in the differential diagnosis of non-syndromic congenital hyperinsulinism.     

TWC LOGD: A portal for linked open government data ecosystems

International open government initiatives are releasing an increasing volume of raw government datasets directly to citizens via the Web. The transparency resulting from these releases not only creates new application opportunities but also imposes new burdens inherent to large-scale distributed data integration, collaborative data manipulation and transparent data consumption. The Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI) has developed the Semantic Web-based TWC LOGD portal to support the deployment of linked open government data (LOGD). The portal is both an open source infrastructure supporting linked open government data production and consumption and a vibrant community portal that educates and serves the growing international open government community of developers, data curators and end users. This paper motivates and introduces the TWC LOGD Portal and highlights innovative aspects and lessons learned.     

Some of these things are not like the others: Examining motivations and political predispositions among political Facebook activity

Political engagement via social media has evolved, and web sites including Facebook continue to be a place for individuals, especially young ones, to engage politically. Because politics on social media is diverse, it makes sense that the reasons for participating in it vary. In addition, because current events information and political news is accessible via social media, the role of attention to traditional news sources in this type of political engagement is debatable. The study takes up the opportunity to address these questions by examining young people’s attention to television, print, and online news, their engagement with four Facebook political activities, and their psychological motivations for using the website politically just prior to the 2012 U.S. Presidential election. The results suggest that the primary motivations for using Facebook politically are not universal, and indeed vary by activity. They revolve around connecting with others socially, sharing information with others, and presenting oneself to others. In addition, attention to offline and online news largely do not matter. The study moves research forward by describing the variety of psychological predispositions some Facebook users bring to their political engagement with the web site, and how these predispositions vary across different Facebook political behavior.     

Detection of aircraft below the horizon for vision‐based detect and avoid in unmanned aircraft systems

Vision‐based aircraft detection technology may provide a credible sensing option for automated detect and avoid in small‐to‐medium size fixed‐wing unmanned aircraft systems (UAS). Reliable vision‐based aircraft detection has previously been demonstrated in sky‐region sensing environments. This paper describes a novel vision‐based system for detecting aircraft below the horizon in the presence of ground clutter. We examine the performance of our system on a data set of 63 near collision encounters we collected between a camera‐equipped manned aircraft and a below‐horizon target. In these 63 encounters, our system successfully detects all aircraft, at an average detection range of 1890 m (with a standard error of 43 m and no false alarms in 1.1 h). Furthermore, our system does not require access to inertial sensor data (which significantly reduces system cost) and operates at over 12 frames per second.     

Glioblastoma Extracellular Vesicle-Specific Peptides Inhibit EV-Induced Neuronal Cytotoxicity

WHO Grade 4 IDH-wild type astrocytoma (GBM) is the deadliest brain tumor with a poor prognosis. Meningioma (MMA) is a more common “benign” central nervous system tumor but with significant recurrence rates. There is an urgent need for brain tumor biomarkers for early diagnosis and effective treatment options. Extracellular vesicles (EVs) are tiny membrane-enclosed vesicles that play essential functions in cell-to-cell communications among tumor cells. We aimed to identify epitopes of brain tumor EVs by phage peptide libraries. EVs from GBM plasma, MMA plasma, or brain tumor cell lines were used to screen phage-displayed random peptide libraries to identify high-affinity peptides. We purified EVs from three GBM plasma pools (23 patients), one MMA pool (10 patients), and four brain tumor cell lines. We identified a total of 21 high-affinity phage peptides (12 unique) specific to brain tumor EVs. The peptides shared high sequence homologies among those selected by the same EVs. Dose–response ELISA demonstrated that phage peptides were specific to brain tumor EVs compared to controls. Peptide affinity purification identified unique brain tumor EV subpopulations. Significantly, GBM EV peptides inhibit brain tumor EV-induced complement-dependent cytotoxicity (necrosis) in neurons. We conclude that phage display technology could identify specific peptides to isolate and characterize tumor EVs.     

The stochastic -hub center problem with service-level constraints

Small package delivery companies offer services where packages are guaranteed to be delivered within a given time-frame. With variability in travel time, the configuration on the hub-and-spoke delivery network is vital in ensuring a high probability of meeting the service-level guarantee. We present the stochastic p-hub center problem with chance constraints, which we use to model the service-level guarantees. We discuss analytical results, propose solution heuristics, and present the results from computational experiments.     

MegaViews: Scalable Many‐View Rendering With Concurrent Scene‐View Hierarchy Traversal

We present a scalable solution to render complex scenes from a large amount of viewpoints. While previous approaches rely either on a scene or a view hierarchy to process multiple elements together, we make full use of both, enabling sublinear performance in terms of views and scene complexity. By concurrently traversing the hierarchies, we efficiently find shared information among views to amortize rendering costs. One example application is many‐light global illumination. Our solution accelerates shadow map generation for virtual point lights, whose number can now be raised to over a million while maintaining interactive rates.