Pheo-type: A diagnostic gene-expression assay for the classification of pheochromocytoma and paraganglioma

Context: Pheochromocytomas and paragangliomas (PPGLs) are heritable neoplasms that can be classified into gene-expression subtypes corresponding to their underlying specific genetic drivers. Objective: This study aimed to develop a diagnostic and research tool (Pheo-type) capable of classifying PPGL tumors into gene-expression subtypes that could be used to guide and interpret genetic testing, determine surveillance programs, and aid in elucidation of PPGL biology. Design: A compendium of published microarray data representing 205 PPGL tumors was used for the selection of subtype-specific genes that were then translated to the Nanostring gene-expression platform. A support vector machine was trained on the microarray dataset and then tested on an independent Nanostring dataset representing 38 familial and sporadic cases of PPGL of known genotype (RET, NF1, TMEM127, MAX, HRAS, VHL, and SDHx). Different classifier models involving between three and six subtypes were compared for their discrimination potential. Results: A gene set of 46 genes and six endogenous controls was selected representing six known PPGL subtypes; RTK1–3 (RET, NF1, TMEM127, and HRAS), MAX-like, VHL, and SDHx. Of 38 test cases, 34 (90%) were correctly predicted to six subtypes based on the known genotype to gene-expression subtype association. Removal of the RTK2 subtype from training, characterized by an admixture of tumor and normal adrenal cortex, improved the classification accuracy (35/38). Consolidation of RTK and pseudohypoxic PPGL subtypes to four- and then three-class architectures improved the classification accuracy for clinical application. Conclusions: The Pheo-type gene-expression assay is a reliable method for predicting PPGL genotype using routine diagnostic tumor samples.

Systematic review of interventions to improve the provision of information for adults with primary brain tumours and their caregivers

Background: Adults with primary brain tumors and their caregivers have significant information needs. This review assessed the effect of interventions to improve information provision for adult primary brain tumor patients and/or their caregivers. Methods: We included randomized or nonrandomized trials testing educational interventions that had outcomes of information provision, knowledge, understanding, recall, or satisfaction with the intervention, for adults diagnosed with primary brain tumors and/or their family or caregivers. PubMed, MEDLINE, EMBASE and Cochrane Reviews databases were searched for studies published between 1980 and June 2014. Results: Two randomized controlled, one non-randomized controlled, and 10 single group pre-post trials enrolled more than 411 participants. Five group, four practice/process change and four individual interventions assessed satisfaction (12 studies), knowledge (four studies) or information provision (2 studies). Nine studies reported high rates of satisfaction. Three studies showed statistically significant improvements over time in knowledge and two showed greater information was provided to intervention than control group participants, although statistical testing was not performed. Discussion: The trials assessed intermediate outcomes such as satisfaction, and only 4/13 reported on knowledge improvements. Few trials had a randomized controlled design and risk of bias was either evident or could not be assessed in most domains.

Reasoning about discontinuance of information system use

While many studies have explored conditions and consequences of information systems adoption and use, few have focused on the final stages of the information system lifecycle. In this paper, I develop a theoretical and an initial empirical contribution to understanding individuals’ intentions to discontinue the use of an information system. This understanding is important because it yields implications about maintenance, retirement, and users’ switching decisions, which ultimately can affect work performance, system effectiveness, and return on technology investments. In this paper, I offer a new conceptualization of factors determining users’ intentions to discontinue the use of information systems. I then report on a preliminary empirical test of the model using data from a field study of information system users in a promotional planning routine in a large retail organization. Results from the empirical analysis provide first empirical support for the theoretical model. I discuss the work’s implications for theory on information systems continuance and dual-factor logic in information system use. I also provide suggestions for managers dealing with cessation of information systems and broader work routine change in organizations due to information system end-of-life decisions.

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Role of information and communication in redefining unmanned aerial vehicle autonomous control levels

Autonomous mission control, unlike automatic mission control which is generally pre-programmed to execute an intended mission, is guided by the philosophy of carrying out a complete mission on its own through online sensing, information processing, and control reconfiguration. A crucial cornerstone of this philosophy is the capability of intelligence and of information sharing between unmanned aerial vehicles (UAVs) or with a central controller through secured communication links. Though several mission control algorithms, for single and multiple UAVs, have been discussed in the literature, they lack a clear definition of the various autonomous mission control levels. In the conventional system, the ground pilot issues the flight and mission control command to a UAV through a command data link and the UAV transmits intelligence information, back to the ground pilot through a communication link. Thus, the success of the mission depends entirely on the information flow through a secured communication link between ground pilot and the UAV In the past, mission success depended on the continuous interaction of ground pilot with a single UAV, while present day applications are attempting to define mission success through efficient interaction of ground pilot with multiple UAVs. However, the current trend in UAV applications is expected to lead to a futuristic scenario where mission success would depend only on interaction among UAV groups with no interaction with any ground entity. However, to reach this capability level, it is necessary to first understand the various levels of autonomy and the crucial role that information and communication plays in making these autonomy levels possible. This article presents a detailed framework of UAV autonomous mission control levels in the context of information flow and communication between UAVs and UAV groups for each level of autonomy.

Mathematics, nature and cryptography: Insights from philosophy of information

One influential image that is popular among scientists is the view that mathematics is the language of nature. The present article discusses another possible way to approach the relation between mathematics and nature, which is by using the idea of information and the conceptual vocabulary of cryptography. This approach allows us to understand the possibility that secrets of nature need not be written in mathematics and yet mathematics is necessary as a cryptographic key to unlock these secrets. Various advantages of such a view are described in this article.

Charge density based classification of intermolecular interactions in molecular crystals

Evaluation of intermolecular interactions in terms of both experimental and theoretical charge density analyses has produced a unified picture with which to classify strong and weak hydrogen bonds, along with van der Waals interactions, into three regions.

A Framework for Classification of Prokaryotic Protein Kinases

Background:Overwhelming majority of the Serine/Threonine protein kinases identified by gleaning archaeal and eubacterial genomes could not be classified into any of the well known Hanks and Hunter subfamilies of protein kinases. This is owing to the development of Hanks and Hunter classification scheme based on eukaryotic protein kinases which are highly divergent from their prokaryotic homologues. A large dataset of prokaryotic Serine/Threonine protein kinases recognized from genomes of prokaryotes have been used to develop a classification framework for prokaryotic Ser/Thr protein kinases. Methodology/Principal Findings: We have used traditional sequence alignment and phylogenetic approaches and clustered the prokaryotic kinases which represent 72 subfamilies with at least 4 members in each. Such a clustering enables classification of prokaryotic Ser/Thr kinases and it can be used as a framework to classify newly identified prokaryotic Ser/Thr kinases. After series of searches in a comprehensive sequence database we recognized that 38 subfamilies of prokaryotic protein kinases are associated to a specific taxonomic level. For example 4, 6 and 3 subfamilies have been identified that are currently specific to phylum proteobacteria, cyanobacteria and actinobacteria respectively. Similarly subfamilies which are specific to an order, sub-order, class, family and genus have also been identified. In addition to these, we also identify organism-diverse subfamilies. Members of these clusters are from organisms of different taxonomic levels, such as archaea, bacteria, eukaryotes and viruses.Conclusion/Significance: Interestingly, occurrence of several taxonomic level specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Many prokaryotic Ser/Thr kinases exhibit a wide variety of modular organization which indicates a degree of complexity and protein-protein interactions in the signaling pathways in these microbes.

The Electronic Journal of Information Technology in Construction (ITcon): An Open Access Journal Using an Un-paid, Volunteer-Based Organization

Introduction This case study is based on the experiences with the Electronic Journal of Information Technology in Construction (ITcon), founded in 1995. Development This journal is an example of a particular category of open access journals, which use neither author charges nor subscriptions to finance their operations, but rely largely on unpaid voluntary work in the spirit of the open source movement. The journal has, after some initial struggle, survived its first decade and is now established as one of half-a-dozen peer reviewed journals in its field. Operations The journal publishes articles as they become ready, but creates virtual issues through alerting messages to “subscribers”. It has also started to publish special issues, since this helps in attracting submissions, and also helps in sharing the work-load of review management. From the start the journal adopted a rather traditional layout of the articles. After the first few years the HTML version was dropped and papers are only published in PDF format. Performance The journal has recently been benchmarked against the competing journals in its field. Its acceptance rate of 53% is slightly higher and its average turnaround time of seven months almost a year faster compared to those journals in the sample for which data could be obtained. The server log files for the past three years have also been studied. Conclusions Our overall experience demonstrates that it is possible to publish this type of OA journal, with a yearly publishing volume equal to a quarterly journal and involving the processing of some fifty submissions a year, using a networked volunteer-based organization.

Determinants and Consequences of Information Sharing with Key Suppliers

As companies become more efficient with respect to their internal processes, they begin to shift the focus beyond their corporate boundaries. Thus, the recent years have witnessed an increased interest by practitioners and researchers in interorganizational collaboration, which promises better firm performance through more effective supply chain management. It is no coincidence that this interest comes in parallel with the recent advancements in Information and Communication Technologies, which offer many new collaboration possibilities for companies. However, collaboration, or any other type of supply chain integration effort, relies heavily on information sharing. Hence, this study focuses on information sharing, in particular on the factors that determine it and on its value. The empirical evidence from Finnish and Swedish companies suggests that uncertainty (both demand and environmental) and dependency in terms of switching costs and asset specific investments are significant determinants of information sharing. Results also indicate that information sharing improves company performance regarding resource usage, output, and flexibility. However, companies share information more intensely at the operational rather than the strategic level. The use of supply chain practices and technologies is substantial but varies across the two countries. This study sheds light on a common trend in supply chains today. Whereas the results confirm the value of information sharing, the contingent factors help to explain why the intensity of information shared across companies differ. In the future, competitive pressures and uncertainty are likely to intensify. Therefore, companies may want to continue with their integration efforts by focusing on the determinants discussed in this study. However, at the same time, the possibility of opportunistic behavior by the exchange partner cannot be disregarded.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Classification of Protein Kinases on the Basis of Both Kinase and Non-Kinase Regions

Background: Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multidomain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies. Methodology: Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. Conclusions: The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multidomain architecture.

A classification of homogeneous operators in the Cowen-Douglas class

An explicit construction of all the homogeneous holomorphic Hermitian vector bundles over the unit disc D is given. It is shown that every such vector bundle is a direct sum of irreducible ones. Among these irreducible homogeneous holomorphic Hermitian vector bundles over D, the ones corresponding to operators in the Cowen-Douglas class B-n(D) are identified. The classification of homogeneous operators in B-n(D) is completed using an explicit realization of these operators. We also show how the homogeneous operators in B-n(D) split into similarity classes. (C) 2011 Elsevier Inc. All rights reserved.

Two-mode quantum systems: Invariant classification of squeezing transformations and squeezed states

A general analysis of squeezing transformations for two-mode systems is given based on the four-dimensional real symplectic group Sp(4, R). Within the framework of the unitary (metaplectic) representation of this group, a distinction between compact photon-number-conserving and noncompact photon-number-nonconserving squeezing transformations is made. We exploit the U(2) invariant squeezing criterion to divide the set of all squeezing transformations into a two-parameter family of distinct equivalence classes with representative elements chosen for each class. Familiar two-mode squeezing transformations in the literature are recognized in our framework and seen to form a set of measure zero. Examples of squeezed coherent and thermal states are worked out. The need to extend the heterodyne detection scheme to encompass all of U(2) is emphasized, and known experimental situations where all U(2) elements can be reproduced are briefly described.