NeuroTerrain – a client-server system for browsing 3D biomedical image data sets

BACKGROUND: Three dimensional biomedical image sets are becoming ubiquitous, along with the canonical atlases providing the necessary spatial context for analysis. To make full use of these 3D image sets, one must be able to present views for 2D display, either surface renderings or 2D cross-sections through the data. Typical display software is limited to presentations along one of the three orthogonal anatomical axes (coronal, horizontal, or sagittal). However, data sets precisely oriented along the major axes are rare. To make fullest use of these datasets, one must reasonably match the atlas' orientation; this involves resampling the atlas in planes matched to the data set. Traditionally, this requires the atlas and browser reside on the user's desktop; unfortunately, in addition to being monolithic programs, these tools often require substantial local resources. In this article, we describe a network-capable, client-server framework to slice and visualize 3D atlases at off-axis angles, along with an open client architecture and development kit to support integration into complex data analysis environments. RESULTS: Here we describe the basic architecture of a client-server 3D visualization system, consisting of a thin Java client built on a development kit, and a computationally robust, high-performance server written in ANSI C++. The Java client components (NetOStat) support arbitrary-angle viewing and run on readily available desktop computers running Mac OS X, Windows XP, or Linux as a downloadable Java Application. Using the NeuroTerrain Software Development Kit (NT-SDK), sophisticated atlas browsing can be added to any Java-compatible application requiring as little as 50 lines of Java glue code, thus making it eminently re-useable and much more accessible to programmers building more complex, biomedical data analysis tools. The NT-SDK separates the interactive GUI components from the server control and monitoring, so as to support development of non-interactive applications. The server implementation takes full advantage of data center's high-performance hardware, where it can be co-localized with centrally-located, 3D dataset repositories, extending access to the researcher community throughout the Internet. CONCLUSION: The combination of an optimized server and modular, platform-independent client provides an ideal environment for viewing complex 3D biomedical datasets, taking full advantage of high-performance servers to prepare images and subsets of associated meta-data for viewing, as well as the graphical capabilities in Java to actually display the data

A Formal Ontology of Subcellular Neuroanatomy

The complexity of the nervous system requires high-resolution microscopy to resolve the detailed 3D structure of nerve cells and supracellular domains. The analysis of such imaging data to extract cellular surfaces and cell components often requires the combination of expert human knowledge with carefully engineered software tools. In an effort to make better tools to assist humans in this endeavor, create a more accessible and permanent record of their data, and to aid the process of constructing complex and detailed computational models, we have created a core of formalized knowledge about the structure of the nervous system and have integrated that core into several software applications. In this paper, we describe the structure and content of a formal ontology whose scope is the subcellular anatomy of the nervous system (SAO), covering nerve cells, their parts, and interactions between these parts. Many applications of this ontology to image annotation, content-based retrieval of structural data, and integration of shared data across scales and researchers are also described

The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or ‘ontologies’. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium has set in train a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing a process of coordinated reform, and new ontologies being created, on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable, logically well-formed, and to incorporate accurate representations of biological reality. We describe the OBO Foundry initiative, and provide guidelines for those who might wish to become involved in the future

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu

Ruxolitinib for Glucocorticoid-Refractory Chronic Graft-versus-Host Disease

Background: Chronic graft-versus-host disease (GVHD), a major complication of allogeneic stem-cell transplantation, becomes glucocorticoid-refractory or glucocorticoid-dependent in approximately 50% of patients. Robust data from phase 3 randomized studies evaluating second-line therapy for chronic GVHD are lacking. In retrospective surveys, ruxolitinib, a Janus kinase (JAK1-JAK2) inhibitor, showed potential efficacy in patients with glucocorticoid-refractory or -dependent chronic GVHD. Methods: This phase 3 open-label, randomized trial evaluated the efficacy and safety of ruxolitinib at a dose of 10 mg twice daily, as compared with the investigator's choice of therapy from a list of 10 commonly used options considered best available care (control), in patients 12 years of age or older with moderate or severe glucocorticoid-refractory or -dependent chronic GVHD. The primary end point was overall response (complete or partial response) at week 24; key secondary end points were failure-free survival and improved score on the modified Lee Symptom Scale at week 24. Results: A total of 329 patients underwent randomization; 165 patients were assigned to receive ruxolitinib and 164 patients to receive control therapy. Overall response at week 24 was greater in the ruxolitinib group than in the control group (49.7% vs. 25.6%; odds ratio, 2.99; P18.6 months vs. 5.7 months; hazard ratio, 0.37; P<0.001) and higher symptom response (24.2% vs. 11.0%; odds ratio, 2.62; P = 0.001). The most common (occurring in ≥10% patients) adverse events of grade 3 or higher up to week 24 were thrombocytopenia (15.2% in the ruxolitinib group and 10.1% in the control group) and anemia (12.7% and 7.6%, respectively). The incidence of cytomegalovirus infections and reactivations was similar in the two groups. Conclusions: Among patients with glucocorticoid-refractory or -dependent chronic GVHD, ruxolitinib led to significantly greater overall response, failure-free survival, and symptom response. The incidence of thrombocytopenia and anemia was greater with ruxolitinib. (Funded by Novartis and Incyte; REACH3 ClinicalTrials.gov number, NCT03112603.)