Astrocytes with their specialised morphology are essential for brain homeostasis as metabolic mediators between blood vessels and neurons. In neurodegenerative diseases such as Alzheimer's disease (AD), astrocytes adopt reactive profiles with molecular and morphological changes that could lead to the impairment of their metabolic support and impact disease progression. However, the underlying mechanisms of how the metabolic function of human astrocytes is impaired by their morphological changes in AD are still elusive. To address this challenge, we developed and applied a metabolic multiscale modelling approach integrating the dynamics of metabolic energy pathways and physiological astrocyte morphologies acquired in human AD and age-matched control brain samples. The results demonstrate that the complex cell shape and intracellular organisation of energetic pathways determine the metabolic profile and support capacity of astrocytes in health and AD conditions. Thus, our mechanistic approach indicates the importance of spatial orchestration in metabolism and allows for the identification of protective mechanisms against disease-associated metabolic impairments.

The Neuroscience domain stands out from the field of sciences for its dependence on the study and characterization of complex, intertwining structures. Understanding the complexity of the brain has led to widespread advances in the structure of large-scale computing resources and the design of artificially intelligent analysis systems. However, the scale of problems and data generated continues to grow and outpace the standards and practices of neuroscience. In this paper, we present an automated neuroscience reconstruction framework, called NeuroKube, for large-scale processing and labeling of neuroimage volumes. Automated labels are generated through a machine-learning (ML) workflow, with data-intensive steps feeding through multiple GPU stages and distributed data locations leveraging autoscalable cloud-native deployments on a multi-institution Kubernetes system. Leading-edge hardware and storage empower multiple stages of machine-learning, GPU-accelerated solutions. This demonstrates an abstract approach to allocating the resources and algorithms needed to elucidate the highly complex structures of the brain. We summarize an integrated gateway architecture, and a scalable workflow-driven segmentation and reconstruction environment that brings together image big data with state-of-the-art, extensible machine learning methods.

SUMMARY: To expedite the review of semi-automated probability maps of organelles and other features from 3D electron microscopy data we have developed Probability Map Viewer, a Java-based web application that enables the computation and visualization of probability map generation results in near real-time as the data are being collected from the microscope. Probability Map Viewer allows the user to select one or more voxel classifiers, apply them on a sub-region of an active collection, and visualize the results as overlays on the raw data via any web browser using a personal computer or mobile device. Thus, Probability Map Viewer accelerates and informs the image analysis workflow by providing a tool for experimenting with and optimizing dataset-specific segmentation strategies during imaging. AVAILABILITY AND IMPLEMENTATION: https://github.com/crbs/probabilitymapviewer. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Kidney podocytes' function depends on fingerlike projections (foot processes) that interdigitate with those from neighboring cells to form the glomerular filtration barrier. The integrity of the barrier depends on spatial control of dynamics of actin cytoskeleton in the foot processes. We determined how imbalances in regulation of actin cytoskeletal dynamics could result in pathological morphology. We obtained 3-D electron microscopy images of podocytes and used quantitative features to build dynamical models to investigate how regulation of actin dynamics within foot processes controls local morphology. We find that imbalances in regulation of actin bundling lead to chaotic spatial patterns that could impair the foot process morphology. Simulation results are consistent with experimental observations for cytoskeletal reconfiguration through dysregulated RhoA or Rac1, and they predict compensatory mechanisms for biochemical stability. We conclude that podocyte morphology, optimized for filtration, is intrinsically fragile, whereby local transient biochemical imbalances may lead to permanent morphological changes associated with pathophysiology.

Spatio-temporal dynamics of intracellular calcium, [Ca2+]i, regulate the contractile function of cardiac muscle cells. Measuring [Ca2+]i flux is central to the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease. However, current imaging techniques are limited in the spatial resolution to which changes in [Ca2+]i can be detected. Using spatial point process statistics techniques we developed a novel method to simulate the spatial distribution of RyR clusters, which act as the major mediators of contractile Ca2+ release, upon a physiologically-realistic cellular landscape composed of tightly-packed mitochondria and myofibrils. We applied this method to computationally combine confocal-scale (~ 200 nm) data of RyR clusters with 3D electron microscopy data (~ 30 nm) of myofibrils and mitochondria, both collected from adult rat left ventricular myocytes. Using this hybrid-scale spatial model, we simulated reaction-diffusion of [Ca2+]i during the rising phase of the transient (first 30 ms after initiation). At 30 ms, the average peak of the simulated [Ca2+]i transient and of the simulated fluorescence intensity signal, F/F0, reached values similar to that found in the literature ([Ca2+]i ≈1 μM; F/F0≈5.5). However, our model predicted the variation in [Ca2+]i to be between 0.3 and 12.7 μM (~3 to 100 fold from resting value of 0.1 μM) and the corresponding F/F0 signal ranging from 3 to 9.5. We demonstrate in this study that: (i) heterogeneities in the [Ca2+]i transient are due not only to heterogeneous distribution and clustering of mitochondria; (ii) but also to heterogeneous local densities of RyR clusters. Further, we show that: (iii) these structure-induced heterogeneities in [Ca2+]i can appear in line scan data. Finally, using our unique method for generating RyR cluster distributions, we demonstrate the robustness in the [Ca2+]i transient to differences in RyR cluster distributions measured between rat and human cardiomyocytes.

Automated electron microscopy (EM) image analysis techniques can be tremendously helpful for connectomics research. In this paper, we extend our previous work [1] and propose a fully automatic method to utilize inter-section information for intra-section neuron segmentation of EM image stacks. A watershed merge forest is built via the watershed transform with each tree representing the region merging hierarchy of one 2D section in the stack. A section classifier is learned to identify the most likely region correspondence between adjacent sections. The inter-section information from such correspondence is incorporated to update the potentials of tree nodes. We resolve the merge forest using these potentials together with consistency constraints to acquire the final segmentation of the whole stack. We demonstrate that our method leads to notable segmentation accuracy improvement by experimenting with two types of EM image data sets.

SUMMARY: This application note describes a new scalable semi-automatic approach, the Dual Point Decision Process, for segmentation of 3D structures contained in 3D microscopy. The segmentation problem is distributed to many individual workers such that each receives only simple questions regarding whether two points in an image are placed on the same object. A large pool of micro-labor workers available through Amazon's Mechanical Turk system provides the labor in a scalable manner. AVAILABILITY AND IMPLEMENTATION: Python-based code for non-commercial use and test data are available in the source archive at https://sites.google.com/site/imagecrowdseg/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. RESULTS: We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. CONCLUSIONS: We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with other texture identifiers, and we plan to explore this in future work.

Over the last decade, workflows have been established as a mechanism for scientific developers to create simplified views of complex scientific processes. However, there is a need for a comprehensive system architecture to link scientific developers creating workflows with researchers launching workflows in large scale computing environments. We present the architecture for the CAMERA 2.0 Cyber infrastructure platform that provides a scaffold where workflows can be uploaded into the system, and user interface components for launching and viewing results are automatically generated. In CAMERA 2.0, scientific developers and metagenomics researchers seamlessly collaborate to (i) wrap data-analysis software applications and heterogeneous tools as Resource Oriented Architecture (ROA) components integrating them using scientific workflows; (ii) publish and run scientific workflows via dynamically generated uniform portal interfaces; (iii) map heterogeneous workflow products to provenance and CAMERA semantic database through a transformation component, to save output data resulting from workflow runs based on this mapping; (iv) record and visualize the provenance of all workflow run-related data and processes; and (v) conduct queries across multiple workflow executions and link these workflow executions to each other through data and provenance related to these runs. Furthermore, workflows added to CAMERA also have access to a variety of physical resources for computation and data management. Here, we demonstrate the usability of this framework with some of the developed metagenomics workflows.

This paper presents an overview of the data integration mediation system developed as part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A core BIRN goal is the development of a multi-institution information management system to support biomedical research. Each participating institution maintains a database of their experimental or computationally derived data, and the data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This demonstration paper describes architecture, implementation, and capabilities of the semantically based data integration system for BIRN

The Telescience Project/spl trade/ (https://telescience.ucsd.edu) aims to provide a complete, end-to-end, single sign-on solution for biomedical image analysis and structure-function correlation. Telescience merges advanced solutions for remote instrumentation (via Telemicroscopy/spl trade/), distributed data computation and storage, and transparent access to federated databases of cell structure. Here, we describe the Grid-based system architecture that enables the Telescience Project. This Grid service architecture provides a fabric for seamless interoperability among user interfaces (Web portals and applications) and externally addressable Grid resources (instruments and computers). Although many software components and tools provide some capabilities relating to enabling usable scientific grids, few systems offer the required complete interactions with grid infrastructures "out of the box". Significant time and effort, therefore, are needed for software evaluation, testing, and integration. Here we describe an emerging layer of the overall Grid infrastructure that provides a complete solution for application and portal developers to interact with core Grid functionality.

The Cybermedia Center, Osaka University (CMC) is a research institution that offers resource with knowledge and technology of all advanced research in the area of large-scale computation, information and communication, multimedia content and education. Currently, CMC involves in Japanese national grid projects such as JGN II (Japan Gigabit Network) and BioGrid. Not limited to Japan, CMC also takes an active part in international activities such as PRAGMA. In these projects and international collaboration, CMC has developed the Grid system that allows scientists to perform their analysis by remotely controlling the world-largest ultra-high voltage electron microscope located in Osaka University. On the other, CMC has been taking a leading role at BioGrid sharing experience and knowledge on the system development for biology. In this paper, we will describe BioGrid project overview and introduce progress of Telescience group which collaborates with Telescience project lead by National Center for Microscopy and Imaging Research (NCMIR).

For over the last decade, researchers at the National Center for Microscopy and Imaging Research (NCMIR, http://ncrrdr.ucsd.edu) have been developing and implementing novel technologies to propel collaborative research. NCMIR has built flexible high throughput, cyber infrastructure environments which connect researchers to advanced imaging instruments datagrids and computational grids. Through the integration of pioneering research in remote instrumentation research (known as Telemicroscopytrade) and grid based distributed computing and data management, this group demonstrated this vision in the context of The Telescience Project (https://telescience.ucsd.edu). Telescience provides an end-to-end, single sign-on solution for biomedical image analysis and structure-function correlation that integrates users with resources and applications with unified security and without prohibitive complexity. Here, we describe the flattening and generalization of the layers of software that make up the Grid-based system architecture of the project. In particular, we focus on the maturation and generalization of the architecture, including the development of an Application to middleware interaction component (ATOMIC) services fabric that streamlines application integration with core grid middleware. This broadening of the overall grid service architecture is the product of over 6 years of user-developer iterative software refinement cycles which have resulted in a suite of Telescience Tools that provide generalized solutions for increasing the interoperability of user interfaces (Web portals and applications) and externally addressable grid resources (instruments and computers)

Scientific imaging instruments are used in a variety of disciplines to gather vital data for research and study. Specifically, in the biomedical field various types of biological imaging instruments, such as electron microscopes and light microscopes, are used everyday to acquire 2D and 3D datasets for further understanding of biological structures. Remote operation or "teleoperation" of instruments has become a popular solution for research scientists to acquire and share data across research domains separated by geographical barriers. A generalized software architecture solution is presented in this paper to use emerging software technologies to develop a reusable framework to easily integrate instruments for remote-operation in a safe and secure fashion. Web services have emerged as a popular technology to provide software applications with a framework to achieve interoperability and integration with other applications. This generalized software architecture was developed to take advantage of Web service middleware technology and to provide a solution for easily plugging in scientific imaging instruments for teleoperation. The architecture has also incorporated grid technology to achieve a more scalable and robust solution for handling the enormous data sets produced from these instruments. Finally a set of client libraries is presented to demonstrate a useful API for developers to quickly develop a graphical user interface to communicate and acquire data from these instruments