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Pubmed Article
Automatic target recognition based on cross-plot.
PUBLISHED: 04-09-2011
Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository.
To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is desired. A novel neural-machine interface (NMI) based on neuromuscular-mechanical fusion developed in our previous study has demonstrated a great potential to accurately identify the intended movement of transfemoral amputees. However, this interface has not yet been integrated with a powered prosthetic leg for true neural control. This study aimed to report (1) a flexible platform to implement and optimize neural control of powered lower limb prosthesis and (2) an experimental setup and protocol to evaluate neural prosthesis control on patients with lower limb amputations. First a platform based on a PC and a visual programming environment were developed to implement the prosthesis control algorithms, including NMI training algorithm, NMI online testing algorithm, and intrinsic control algorithm. To demonstrate the function of this platform, in this study the NMI based on neuromuscular-mechanical fusion was hierarchically integrated with intrinsic control of a prototypical transfemoral prosthesis. One patient with a unilateral transfemoral amputation was recruited to evaluate our implemented neural controller when performing activities, such as standing, level-ground walking, ramp ascent, and ramp descent continuously in the laboratory. A novel experimental setup and protocol were developed in order to test the new prosthesis control safely and efficiently. The presented proof-of-concept platform and experimental setup and protocol could aid the future development and application of neurally-controlled powered artificial legs.
23 Related JoVE Articles!
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Electronic Tongue Generating Continuous Recognition Patterns for Protein Analysis
Authors: Yanxia Hou, Maria Genua, Laurie-Amandine Garçon, Arnaud Buhot, Roberto Calemczuk, David Bonnaffé, Hugues Lortat-Jacob, Thierry Livache.
Institutions: Institut Nanosciences et Cryogénie, CEA-Grenoble, Université Paris-Sud, Institut de Biologie Structurale.
In current protocol, a combinatorial approach has been developed to simplify the design and production of sensing materials for the construction of electronic tongues (eT) for protein analysis. By mixing a small number of simple and easily accessible molecules with different physicochemical properties, used as building blocks (BBs), in varying and controlled proportions and allowing the mixtures to self-assemble on the gold surface of a prism, an array of combinatorial surfaces featuring appropriate properties for protein sensing was created. In this way, a great number of cross-reactive receptors can be rapidly and efficiently obtained. By combining such an array of combinatorial cross-reactive receptors (CoCRRs) with an optical detection system such as surface plasmon resonance imaging (SPRi), the obtained eT can monitor the binding events in real-time and generate continuous recognition patterns including 2D continuous evolution profile (CEP) and 3D continuous evolution landscape (CEL) for samples in liquid. Such an eT system is efficient for discrimination of common purified proteins.
Bioengineering, Issue 91, electronic tongue, combinatorial cross-reactive receptor, surface plasmon resonance imaging, pattern recognition, continuous evolution profiles, continuous evolution landscapes, protein analysis
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Patterned Photostimulation with Digital Micromirror Devices to Investigate Dendritic Integration Across Branch Points
Authors: Conrad W. Liang, Michael Mohammadi, M. Daniel Santos, Cha-Min Tang.
Institutions: University of Maryland School of Medicine.
Light is a versatile and precise means to control neuronal excitability. The recent introduction of light sensitive effectors such as channel-rhodopsin and caged neurotransmitters have led to interests in developing better means to control patterns of light in space and time that are useful for experimental neuroscience. One conventional strategy, employed in confocal and 2-photon microscopy, is to focus light to a diffraction limited spot and then scan that single spot sequentially over the region of interest. This approach becomes problematic if large areas have to be stimulated within a brief time window, a problem more applicable to photostimulation than for imaging. An alternate strategy is to project the complete spatial pattern on the target with the aid of a digital micromirror device (DMD). The DMD approach is appealing because the hardware components are relatively inexpensive and is supported by commercial interests. Because such a system is not available for upright microscopes, we will discuss the critical issues in the construction and operations of such a DMD system. Even though we will be primarily describing the construction of the system for UV photolysis, the modifications for building the much simpler visible light system for optogenetic experiments will also be provided. The UV photolysis system was used to carryout experiments to study a fundamental question in neuroscience, how are spatially distributed inputs integrated across distal dendritic branch points. The results suggest that integration can be non-linear across branch points and the supralinearity is largely mediated by NMDA receptors.
Bioengineering, Issue 49, DMD, photolysis, dendrite, photostimulation, DLP, optogenetics
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
Authors: Laura Ekstrand, Nikolaus Karpinsky, Yajun Wang, Song Zhang.
Institutions: Iowa State University.
Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces. Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth. However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras1. The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera’s field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation. Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop. DFP systems can also achieve the same measurement resolution as the camera. For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in1-5). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30 Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame6,7. Binary defocusing DFP methods can achieve even greater speeds8. Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis9, facial animation10, cardiac mechanics studies11, and fluid surface measurements, but many other potential applications exist. This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.
Physics, Issue 82, Structured light, Fringe projection, 3D imaging, 3D scanning, 3D video, binary defocusing, phase-shifting
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Micro 3D Printing Using a Digital Projector and its Application in the Study of Soft Materials Mechanics
Authors: Howon Lee, Nicholas X. Fang.
Institutions: Massachusetts Institute of Technology.
Buckling is a classical topic in mechanics. While buckling has long been studied as one of the major structural failure modes1, it has recently drawn new attention as a unique mechanism for pattern transformation. Nature is full of such examples where a wealth of exotic patterns are formed through mechanical instability2-5. Inspired by this elegant mechanism, many studies have demonstrated creation and transformation of patterns using soft materials such as elastomers and hydrogels6-11. Swelling gels are of particular interest because they can spontaneously trigger mechanical instability to create various patterns without the need of external force6-10. Recently, we have reported demonstration of full control over buckling pattern of micro-scaled tubular gels using projection micro-stereolithography (PμSL), a three-dimensional (3D) manufacturing technology capable of rapidly converting computer generated 3D models into physical objects at high resolution12,13. Here we present a simple method to build up a simplified PμSL system using a commercially available digital data projector to study swelling-induced buckling instability for controlled pattern transformation. A simple desktop 3D printer is built using an off-the-shelf digital data projector and simple optical components such as a convex lens and a mirror14. Cross-sectional images extracted from a 3D solid model is projected on the photosensitive resin surface in sequence, polymerizing liquid resin into a desired 3D solid structure in a layer-by-layer fashion. Even with this simple configuration and easy process, arbitrary 3D objects can be readily fabricated with sub-100 μm resolution. This desktop 3D printer holds potential in the study of soft material mechanics by offering a great opportunity to explore various 3D geometries. We use this system to fabricate tubular shaped hydrogel structure with different dimensions. Fixed on the bottom to the substrate, the tubular gel develops inhomogeneous stress during swelling, which gives rise to buckling instability. Various wavy patterns appear along the circumference of the tube when the gel structures undergo buckling. Experiment shows that circumferential buckling of desired mode can be created in a controlled manner. Pattern transformation of three-dimensionally structured tubular gels has significant implication not only in mechanics and material science, but also in many other emerging fields such as tunable matamaterials.
Mechanical Engineering, Issue 69, Materials Science, Physics, Chemical Engineering, 3D printing, stereo-lithography, photo-polymerization, gel, swelling, elastic instability, buckling, pattern formation
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Preparation and Use of HIV-1 Infected Primary CD4+ T-Cells as Target Cells in Natural Killer Cell Cytotoxic Assays
Authors: Zachary B. Davis, Jeffrey P. Ward, Edward Barker.
Institutions: Rush University Medical Center.
Natural killer (NK) cells are a vital component of the innate immune response to virus-infected cells. It is important to understand the ability of NK cells to recognize and lyse HIV-1 infected cells because identifying any aberrancy in NK cell function against HIV-infected cells could potentially lead to therapies that would enhance their cytolytic activity. There is a need to use HIV-infected primary T-cell blasts as target cells rather then infected-T-cell lines in the cytotoxicity assays. T-cell lines, even without infection, are quite susceptible to NK cell lysis. Furthermore, it is necessary to use autologous primary cells to prevent major histocompatibility complex class I mismatches between the target and effector cell that will result in lysis. Early studies evaluating NK cell cytolytic responses to primary HIV-infected cells failed to show significant killing of the infected cells 1,2. However, using HIV-1 infected primary T-cells as target cells in NK cell functional assays has been difficult due the presence of contaminating uninfected cells 3. This inconsistent infected cell to uninfected cell ratio will result in variation in NK cell killing between samples that may not be due to variability in donor NK cell function. Thus, it would be beneficial to work with a purified infected cell population in order to standardize the effector to target cell ratios between experiments 3,4. Here we demonstrate the isolation of a highly purified population of HIV-1 infected cells by taking advantage of HIV-1's ability to down-modulate CD4 on infected cells and the availability of commercial kits to remove dead or dying cells 3-6. The purified infected primary T-cell blasts can then be used as targets in either a degranulation or cytotoxic assay with purified NK cells as the effector population 5-7. Use of NK cells as effectors in a degranulation assay evaluates the ability of an NK cell to release the lytic contents of specialized lysosomes 8 called "cytolytic granules". By staining with a fluorochrome conjugated antibody against CD107a, a lysosomal membrane protein that becomes expressed on the NK cell surface when the cytolytic granules fuse to the plasma membrane, we can determine what percentage of NK cells degranulate in response to target cell recognition. Alternatively, NK cell lytic activity can be evaluated in a cytotoxic assay that allows for the determination of the percentage of target cells lysed by release of 51Cr from within the target cell in the presence of NK cells.
Immunology, Issue 49, innate immunity, HIV-1, natural killer cell, cytolytic assay, degranulation assay, primary lymphocytes
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Designing a Bio-responsive Robot from DNA Origami
Authors: Eldad Ben-Ishay, Almogit Abu-Horowitz, Ido Bachelet.
Institutions: Bar-Ilan University.
Nucleic acids are astonishingly versatile. In addition to their natural role as storage medium for biological information1, they can be utilized in parallel computing2,3 , recognize and bind molecular or cellular targets4,5 , catalyze chemical reactions6,7 , and generate calculated responses in a biological system8,9. Importantly, nucleic acids can be programmed to self-assemble into 2D and 3D structures10-12, enabling the integration of all these remarkable features in a single robot linking the sensing of biological cues to a preset response in order to exert a desired effect. Creating shapes from nucleic acids was first proposed by Seeman13, and several variations on this theme have since been realized using various techniques11,12,14,15 . However, the most significant is perhaps the one proposed by Rothemund, termed scaffolded DNA origami16. In this technique, the folding of a long (>7,000 bases) single-stranded DNA 'scaffold' is directed to a desired shape by hundreds of short complementary strands termed 'staples'. Folding is carried out by temperature annealing ramp. This technique was successfully demonstrated in the creation of a diverse array of 2D shapes with remarkable precision and robustness. DNA origami was later extended to 3D as well17,18 . The current paper will focus on the caDNAno 2.0 software19 developed by Douglas and colleagues. caDNAno is a robust, user-friendly CAD tool enabling the design of 2D and 3D DNA origami shapes with versatile features. The design process relies on a systematic and accurate abstraction scheme for DNA structures, making it relatively straightforward and efficient. In this paper we demonstrate the design of a DNA origami nanorobot that has been recently described20. This robot is 'robotic' in the sense that it links sensing to actuation, in order to perform a task. We explain how various sensing schemes can be integrated into the structure, and how this can be relayed to a desired effect. Finally we use Cando21 to simulate the mechanical properties of the designed shape. The concept we discuss can be adapted to multiple tasks and settings.
Bioengineering, Issue 77, Genetics, Biomedical Engineering, Molecular Biology, Medicine, Genomics, Nanotechnology, Nanomedicine, DNA origami, nanorobot, caDNAno, DNA, DNA Origami, nucleic acids, DNA structures, CAD, sequencing
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High-throughput Fluorometric Measurement of Potential Soil Extracellular Enzyme Activities
Authors: Colin W. Bell, Barbara E. Fricks, Jennifer D. Rocca, Jessica M. Steinweg, Shawna K. McMahon, Matthew D. Wallenstein.
Institutions: Colorado State University, Oak Ridge National Laboratory, University of Colorado.
Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be assimilated for energy and nutrients. Measuring soil microbial enzyme activity is crucial in understanding soil ecosystem functional dynamics. The general concept of the fluorescence enzyme assay is that synthetic C-, N-, or P-rich substrates bound with a fluorescent dye are added to soil samples. When intact, the labeled substrates do not fluoresce. Enzyme activity is measured as the increase in fluorescence as the fluorescent dyes are cleaved from their substrates, which allows them to fluoresce. Enzyme measurements can be expressed in units of molarity or activity. To perform this assay, soil slurries are prepared by combining soil with a pH buffer. The pH buffer (typically a 50 mM sodium acetate or 50 mM Tris buffer), is chosen for the buffer's particular acid dissociation constant (pKa) to best match the soil sample pH. The soil slurries are inoculated with a nonlimiting amount of fluorescently labeled (i.e. C-, N-, or P-rich) substrate. Using soil slurries in the assay serves to minimize limitations on enzyme and substrate diffusion. Therefore, this assay controls for differences in substrate limitation, diffusion rates, and soil pH conditions; thus detecting potential enzyme activity rates as a function of the difference in enzyme concentrations (per sample). Fluorescence enzyme assays are typically more sensitive than spectrophotometric (i.e. colorimetric) assays, but can suffer from interference caused by impurities and the instability of many fluorescent compounds when exposed to light; so caution is required when handling fluorescent substrates. Likewise, this method only assesses potential enzyme activities under laboratory conditions when substrates are not limiting. Caution should be used when interpreting the data representing cross-site comparisons with differing temperatures or soil types, as in situ soil type and temperature can influence enzyme kinetics.
Environmental Sciences, Issue 81, Ecological and Environmental Phenomena, Environment, Biochemistry, Environmental Microbiology, Soil Microbiology, Ecology, Eukaryota, Archaea, Bacteria, Soil extracellular enzyme activities (EEAs), fluorometric enzyme assays, substrate degradation, 4-methylumbelliferone (MUB), 7-amino-4-methylcoumarin (MUC), enzyme temperature kinetics, soil
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Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
Authors: Jillian Nguyen, Thomas V. Papathomas, Jay H. Ravaliya, Elizabeth B. Torres.
Institutions: Rutgers University, Rutgers University, Rutgers University, Rutgers University, Rutgers University.
Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are deliberately planned, while others spontaneously occur below conscious awareness. The deliberate component of this dichotomy has been studied extensively in several contexts, while the spontaneous component remains largely under-explored. Moreover, how perceptual processes modulate these movement classes is still unclear. In particular, a currently debated issue is whether the visuomotor system is governed by the spatial percept produced by a visual illusion or whether it is not affected by the illusion and is governed instead by the veridical percept. Bistable percepts such as 3D depth inversion illusions (DIIs) provide an excellent context to study such interactions and balance, particularly when used in combination with reach-to-grasp movements. In this study, a methodology is developed that uses a DII to clarify the role of top-down processes on motor action, particularly exploring how reaches toward a target on a DII are affected in both deliberate and spontaneous movement domains.
Behavior, Issue 86, vision for action, vision for perception, motor control, reach, grasp, visuomotor, ventral stream, dorsal stream, illusion, space perception, depth inversion
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Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
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Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics
Authors: Onur Mudanyali, Anthony Erlinger, Sungkyu Seo, Ting-Wei Su, Derek Tseng, Aydogan Ozcan.
Institutions: University of California, Los Angeles, University of California, Los Angeles.
Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as ~18 cm2. Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of ~5 mm without the need for refocusing which corresponds to up to ~9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments.
Cellular Biology, Issue 34, LUCAS, lensfree imaging, on-chip imaging, point-of-care diagnostics, global health, cell-biology, telemedicine, wireless health, microscopy, red blood cells
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Authors: Daniel T. Claiborne, Jessica L. Prince, Eric Hunter.
Institutions: Emory University, Emory University.
The protective effect of many HLA class I alleles on HIV-1 pathogenesis and disease progression is, in part, attributed to their ability to target conserved portions of the HIV-1 genome that escape with difficulty. Sequence changes attributed to cellular immune pressure arise across the genome during infection, and if found within conserved regions of the genome such as Gag, can affect the ability of the virus to replicate in vitro. Transmission of HLA-linked polymorphisms in Gag to HLA-mismatched recipients has been associated with reduced set point viral loads. We hypothesized this may be due to a reduced replication capacity of the virus. Here we present a novel method for assessing the in vitro replication of HIV-1 as influenced by the gag gene isolated from acute time points from subtype C infected Zambians. This method uses restriction enzyme based cloning to insert the gag gene into a common subtype C HIV-1 proviral backbone, MJ4. This makes it more appropriate to the study of subtype C sequences than previous recombination based methods that have assessed the in vitro replication of chronically derived gag-pro sequences. Nevertheless, the protocol could be readily modified for studies of viruses from other subtypes. Moreover, this protocol details a robust and reproducible method for assessing the replication capacity of the Gag-MJ4 chimeric viruses on a CEM-based T cell line. This method was utilized for the study of Gag-MJ4 chimeric viruses derived from 149 subtype C acutely infected Zambians, and has allowed for the identification of residues in Gag that affect replication. More importantly, the implementation of this technique has facilitated a deeper understanding of how viral replication defines parameters of early HIV-1 pathogenesis such as set point viral load and longitudinal CD4+ T cell decline.
Infectious Diseases, Issue 90, HIV-1, Gag, viral replication, replication capacity, viral fitness, MJ4, CEM, GXR25
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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Interview: HIV-1 Proviral DNA Excision Using an Evolved Recombinase
Authors: Joachim Hauber.
Institutions: Heinrich-Pette-Institute for Experimental Virology and Immunology, University of Hamburg.
HIV-1 integrates into the host chromosome of infected cells and persists as a provirus flanked by long terminal repeats. Current treatment strategies primarily target virus enzymes or virus-cell fusion, suppressing the viral life cycle without eradicating the infection. Since the integrated provirus is not targeted by these approaches, new resistant strains of HIV-1 may emerge. Here, we report that the engineered recombinase Tre (see Molecular evolution of the Tre recombinase , Buchholz, F., Max Planck Institute for Cell Biology and Genetics, Dresden) efficiently excises integrated HIV-1 proviral DNA from the genome of infected cells. We produced loxLTR containing viral pseudotypes and infected HeLa cells to examine whether Tre recombinase can excise the provirus from the genome of HIV-1 infected human cells. A virus particle-releasing cell line was cloned and transfected with a plasmid expressing Tre or with a parental control vector. Recombinase activity and virus production were monitored. All assays demonstrated the efficient deletion of the provirus from infected cells without visible cytotoxic effects. These results serve as proof of principle that it is possible to evolve a recombinase to specifically target an HIV-1 LTR and that this recombinase is capable of excising the HIV-1 provirus from the genome of HIV-1-infected human cells. Before an engineered recombinase could enter the therapeutic arena, however, significant obstacles need to be overcome. Among the most critical issues, that we face, are an efficient and safe delivery to targeted cells and the absence of side effects.
Medicine, Issue 16, HIV, Cell Biology, Recombinase, provirus, HeLa Cells
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Cross-Modal Multivariate Pattern Analysis
Authors: Kaspar Meyer, Jonas T. Kaplan.
Institutions: University of Southern California.
Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices.
Neuroscience, Issue 57, perception, sensory, cross-modal, top-down, mental imagery, fMRI, MRI, neuroimaging, multivariate pattern analysis, MVPA
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.