BrainAligner: 3D registration atlases of Drosophila brains

Analyzing Drosophila melanogaster neural expression patterns in thousands of three-dimensional image stacks of individual brains requires registering them into a canonical framework based on a fiducial reference of neuropil morphology. Given a target brain labeled with predefined landmarks, the BrainAligner program automatically finds the corresponding landmarks in a subject brain and maps it to the coordinate system of the target brain via a deformable warp. Using a neuropil marker (the antibody nc82) as a reference of the brain morphology and a target brain that is itself a statistical average of data for 295 brains, we achieved a registration accuracy of 2 μm on average, permitting assessment of stereotypy, potential connectivity and functional mapping of the adult fruit fly brain. We used BrainAligner to generate an image pattern atlas of 2954 registered brains containing 470 different expression patterns that cover all the major compartments of the fly brain.     

A high-level 3D visualization API for Java and ImageJ

Background  

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set.     

FPV: fast protein visualization using Java 3D

MOTIVATION: Many tools have been developed to visualize protein structures. Tools that have been based on Java 3D((TM)) are compatible among different systems and they can be run remotely through web browsers. However, using Java 3D for visualization has some performance issues with it. The primary concerns about molecular visualization tools based on Java 3D are in their being slow in terms of interaction speed and in their inability to load large molecules. This behavior is especially apparent when the number of atoms to be displayed is huge, or when several proteins are to be displayed simultaneously for comparison. RESULTS: In this paper we present techniques for organizing a Java 3D scene graph to tackle these problems. We have developed a protein visualization system based on Java 3D and these techniques. We demonstrate the effectiveness of the proposed method by comparing the visualization component of our system with two other Java 3D based molecular visualization tools. In particular, for van der Waals display mode, with the efficient organization of the scene graph, we could achieve up to eight times improvement in rendering speed and could load molecules three times as large as the previous systems could. AVAILABILITY: EPV is freely available with source code at the following URL: http://www.cs.ucsb.edu/~tcan/fpv/     

Yale Image Finder (YIF): a new search engine for retrieving biomedical images

Yale Image Finder (YIF) is a publicly accessible search engine featuring a new way of retrieving biomedical images and associated papers based on the text carried inside the images. Image queries can also be issued against the image caption, as well as words in the associated paper abstract and title. A typical search scenario using YIF is as follows: a user provides few search keywords and the most relevant images are returned and presented in the form of thumbnails. Users can click on the image of interest to retrieve the high resolution image. In addition, the search engine will provide two types of related images: those that appear in the same paper, and those from other papers with similar image content. Retrieved images link back to their source papers, allowing users to find related papers starting with an image of interest. Currently, YIF has indexed over 140 000 images from over 34 000 open access biomedical journal papers. AVAILABILITY: http://krauthammerlab.med.yale.edu/imagefinder/     

Visualization and analysis of 3D microscopic images

In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.     

High-resolution digital brain atlases: a Hubble telescope for the brain

We describe implementation of a method for digitizing at microscopic resolution brain tissue sections containing normal and experimental data and for making the content readily accessible online. Web-accessible brain atlases and virtual microscopes for online examination can be developed using existing computer and internet technologies. Resulting databases, made up of hierarchically organized, multiresolution images, enable rapid, seamless navigation through the vast image datasets generated by high-resolution scanning. Tools for visualization and annotation of virtual microscope slides enable remote and universal data sharing. Interactive visualization of a complete series of brain sections digitized at subneuronal levels of resolution offers fine grain and large-scale localization and quantification of many aspects of neural organization and structure. The method is straightforward and replicable; it can increase accessibility and facilitate sharing of neuroanatomical data. It provides an opportunity for capturing and preserving irreplaceable, archival neurohistological collections and making them available to all scientists in perpetuity, if resources could be obtained from hitherto uninterested agencies of scientific support.     

Single particle 3D reconstruction for 2D crystal images of membrane proteins

In cases where ultra-flat cryo-preparations of well-ordered two-dimensional (2D) crystals are available, electron crystallography is a powerful method for the determination of the high-resolution structures of membrane and soluble proteins. However, crystal unbending and Fourier-filtering methods in electron crystallography three-dimensional (3D) image processing are generally limited in their performance for 2D crystals that are badly ordered or non-flat. Here we present a single particle image processing approach, which is implemented as an extension of the 2D crystallographic pipeline realized in the 2dx software package, for the determination of high-resolution 3D structures of membrane proteins. The algorithm presented, addresses the low single-to-noise ratio (SNR) of 2D crystal images by exploiting neighborhood correlation between adjacent proteins in the 2D crystal. Compared with conventional single particle processing for randomly oriented particles, the computational costs are greatly reduced due to the crystal-induced limited search space, which allows a much finer search space compared to classical single particle processing. To reduce the considerable computational costs, our software features a hybrid parallelization scheme for multi-CPU clusters and computer with high-end graphic processing units (GPUs). We successfully apply the new refinement method to the structure of the potassium channel MloK1. The calculated 3D reconstruction shows more structural details and contains less noise than the map obtained by conventional Fourier-filtering based processing of the same 2D crystal images.     

RAG-3D: a search tool for RNA 3D substructures

To address many challenges in RNA structure/function prediction, the characterization of RNA''s modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.     

An integrated system for feature evaluation of 3D images of a tissue specimen.

In this article we have proposed an integrated system for measurement of important features from 3D tissue images. We propose a segmentation technique, where we combine several methods to achieve a good degree of automation. Important histological and cytological three-dimensional features and strategies to measure them are described.     

3D reconstruction of dental specimens from 2D histological images and microCT-scans

Direct comparison of experimental and theoretical results in biomechanical studies requires a careful reconstruction of specimen surfaces to achieve a satisfactory congruence for validation. In this paper a semi-automatic approach is described to reconstruct triangular boundary representations from images originating from, either histological sections or microCT-, CT- or MRI-data, respectively. In a user-guided first step, planar 2D contours were extracted for every material of interest, using image segmentation techniques. In a second step, standard 2D triangulation algorithms were used to derive high quality mesh representations of the underlying surfaces. This was accomplished by converting the 2D meshes into 3D meshes by a novel lifting procedure. The meshes can be imported as is into finite element programme packages such as Marc/Mentat or COSMOS/M. Accuracy and feasibility of the algorithm is demonstrated by reconstructing several specimens as examples and comparing simulated results with available measurements performed on the original objects.     

Celestial3D: a novel method for 3D visualization of familial data

Summary: Traditional two-dimensional (2D) software programsfor drawing pedigrees are limited when dealing with extendedpedigrees. In successive generations, the number of individualsgrows exponentially, leading to an unworkable amount of spacerequired in the horizontal direction for 2D displays. In addition,it is not always possible to place closely related individualsnear each other due to the lack of space in 2Ds. To addressthese issues we have developed three-dimensional (3D) pedigreedrawing techniques to enable clearer visualization of extendedpedigrees. Currently no other methods are available for displayingextended pedigrees in 3Ds. We have made freely available a softwaretool—‘Celestial3D’—that implements thesenovel techniques. Availability: Freely available to non-commercial users Contact: celestial3d{at}genepi.org.au Supplementary information: www.genepi.org.au/celestial3d Associate Editor: Martin Bishop ¹A more extensive list of software tools appears in the SupplementaryMaterial.     

Deconvolution of images from 3D printed cells in layers on a chip

Layer‐by‐layer cell printing is useful in mimicking layered tissue structures inside the human body and has great potential for being a promising tool in the field of tissue engineering, regenerative medicine, and drug discovery. However, imaging human cells cultured in multiple hydrogel layers in 3D‐printed tissue constructs is challenging as the cells are not in a single focal plane. Although confocal microscopy could be a potential solution for this issue, it compromises the throughput which is a key factor in rapidly screening drug efficacy and toxicity in pharmaceutical industries. With epifluorescence microscopy, the throughput can be maintained at a cost of blurred cell images from printed tissue constructs. To rapidly acquire in‐focus cell images from bioprinted tissues using an epifluorescence microscope, we created two layers of Hep3B human hepatoma cells by printing green and red fluorescently labeled Hep3B cells encapsulated in two alginate layers in a microwell chip. In‐focus fluorescent cell images were obtained in high throughput using an automated epifluorescence microscopy coupled with image analysis algorithms, including three deconvolution methods in combination with three kernel estimation methods, generating a total of nine deconvolution paths. As a result, a combination of Inter‐Level Intra‐Level Deconvolution (ILILD) algorithm and Richardson‐Lucy (RL) kernel estimation proved to be highly useful in bringing out‐of‐focus cell images into focus, thus rapidly yielding more sensitive and accurate fluorescence reading from the cells in different layers. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:445–454, 2018     

Patterns and trends in coral reef macroalgae browsing: a review of browsing herbivorous fishes of the Indo-Pacific

Browsing fishes have been identified as an important component of coral reef resilience, because in contrast to other herbivorous fishes they are able to feed on established macroalgae. Climate change and local anthropogenic impacts have contributed to phase shifts in many coral reefs from coral to macroalgae dominance, and recent research suggests the potential ability of browsers to reverse such phase shifts. However, there is high variation among studies and some contradicting findings exist. Here, we review the relevant literature to assemble a list of species currently known to contribute to browsing in the Indo-Pacific. Furthermore, we identify spatial and temporal patterns, outline factors influencing browsing, and discuss the probability of phase shift reversal. We formulate research recommendations addressing the identified gaps in knowledge about the interactions of browsing fishes and their environment. To date, 37 species of fishes have been observed consuming macroalgae in the Indo-Pacific. The most important groups are the family Siganidae, the subfamily Scarinae (Labridae), and the subfamily Nasinae (Acanthuridae). Browsing species vary between studies depending on location, season and macroalgae species examined. Several influencing factors, such as structural complexity, palatability of macroalgae and ecosystem connectivity have been suggested to cause these discrepancies. The most promising avenues for future research are the effect of structural complexity, the importance of mobile link species and influences of food availability on the selectivity of browsing species. Increasing our knowledge in these fields will provide a better basis for successful management strategies directed at increasing the resilience of coral reefs.     

Preference for mirror images and video image in Java sparrows (Padda oryzivora)

Java sparrows were exposed to a mirror and a frosted mirror, a mirror and a live bird, a mirror and a live bird with frosted screen, a closed circuit TV monitor and a TV program or the closed circuit monitor and an upside down monitor. The birds showed strong preference for the self-image on the mirror, the live bird and the self-image on the monitor. They preferred almost equally to the mirror and the frosted live bird. These results suggest that the Java sparrows saw the self-image on the mirror as conspecific image.