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Pubmed Article
Efficient spatio-temporal local binary patterns for spontaneous facial micro-expression recognition.
PUBLISHED: 05-21-2015
Micro-expression recognition is still in the preliminary stage, owing much to the numerous difficulties faced in the development of datasets. Since micro-expression is an important affective clue for clinical diagnosis and deceit analysis, much effort has gone into the creation of these datasets for research purposes. There are currently two publicly available spontaneous micro-expression datasets--SMIC and CASME II, both with baseline results released using the widely used dynamic texture descriptor LBP-TOP for feature extraction. Although LBP-TOP is popular and widely used, it is still not compact enough. In this paper, we draw further inspiration from the concept of LBP-TOP that considers three orthogonal planes by proposing two efficient approaches for feature extraction. The compact robust form described by the proposed LBP-Six Intersection Points (SIP) and a super-compact LBP-Three Mean Orthogonal Planes (MOP) not only preserves the essential patterns, but also reduces the redundancy that affects the discriminality of the encoded features. Through a comprehensive set of experiments, we demonstrate the strengths of our approaches in terms of recognition accuracy and efficiency.
Authors: Michael Heethoff, Lukas Helfen, Peter Cloetens.
Published: 05-27-2008
Little is known about the internal organization of many micro-arthropods with body sizes below 1 mm. The reasons for that are the small size and the hard cuticle which makes it difficult to use protocols of classical histology. In addition, histological sectioning destroys the sample and can therefore not be used for unique material. Hence, a non-destructive method is desirable which allows to view inside small samples without the need of sectioning. We used synchrotron X-ray tomography at the European Synchrotron Radiation Facility (ESRF) in Grenoble (France) to non-invasively produce 3D tomographic datasets with a pixel-resolution of 0.7µm. Using volume rendering software, this allows us to reconstruct the internal organization in its natural state without the artefacts produced by histological sectioning. These date can be used for quantitative morphology, landmarks, or for the visualization of animated movies to understand the structure of hidden body parts and to follow complete organ systems or tissues through the samples.
26 Related JoVE Articles!
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Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Authors: Zulfi Haneef, Agatha Lenartowicz, Hsiang J. Yeh, Jerome Engel Jr., John M. Stern.
Institutions: Baylor College of Medicine, Michael E. DeBakey VA Medical Center, University of California, Los Angeles, University of California, Los Angeles.
Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal fluctuations over time. Temporal Lobe Epilepsy (TLE) is the most common type of adult epilepsy and involves multiple brain networks. The default mode network (DMN) is involved in conscious, resting state cognition and is thought to be affected in TLE where seizures cause impairment of consciousness. The DMN in epilepsy was examined using seed based fcMRI. The anterior and posterior hubs of the DMN were used as seeds in this analysis. The results show a disconnection between the anterior and posterior hubs of the DMN in TLE during the basal state. In addition, increased DMN connectivity to other brain regions in left TLE along with decreased connectivity in right TLE is revealed. The analysis demonstrates how seed-based fcMRI can be used to probe cerebral networks in brain disorders such as TLE.
Medicine, Issue 90, Default Mode Network (DMN), Temporal Lobe Epilepsy (TLE), fMRI, MRI, functional connectivity MRI (fcMRI), blood oxygenation level dependent (BOLD)
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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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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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Improved In-gel Reductive β-Elimination for Comprehensive O-linked and Sulfo-glycomics by Mass Spectrometry
Authors: David B. Nix, Tadahiro Kumagai, Toshihiko Katoh, Michael Tiemeyer, Kazuhiro Aoki.
Institutions: University of Georgia, University of Georgia, Ishikawa Prefectural University.
Separation of proteins by SDS-PAGE followed by in-gel proteolytic digestion of resolved protein bands has produced high-resolution proteomic analysis of biological samples. Similar approaches, that would allow in-depth analysis of the glycans carried by glycoproteins resolved by SDS-PAGE, require special considerations in order to maximize recovery and sensitivity when using mass spectrometry (MS) as the detection method. A major hurdle to be overcome in achieving high-quality data is the removal of gel-derived contaminants that interfere with MS analysis. The sample workflow presented here is robust, efficient, and eliminates the need for in-line HPLC clean-up prior to MS. Gel pieces containing target proteins are washed in acetonitrile, water, and ethyl acetate to remove contaminants, including polymeric acrylamide fragments. O-linked glycans are released from target proteins by in-gel reductive β-elimination and recovered through robust, simple clean-up procedures. An advantage of this workflow is that it improves sensitivity for detecting and characterizing sulfated glycans. These procedures produce an efficient separation of sulfated permethylated glycans from non-sulfated (sialylated and neutral) permethylated glycans by a rapid phase-partition prior to MS analysis, and thereby enhance glycomic and sulfoglycomic analyses of glycoproteins resolved by SDS-PAGE.
Chemistry, Issue 93, glycoprotein, glycosylation, in-gel reductive β-elimination, O-linked glycan, sulfated glycan, mass spectrometry, protein ID, SDS-PAGE, glycomics, sulfoglycomics
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From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
Authors: Carmine Di Rienzo, Enrico Gratton, Fabio Beltram, Francesco Cardarelli.
Institutions: Scuola Normale Superiore, Instituto Italiano di Tecnologia, University of California, Irvine.
It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn’t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.
Bioengineering, Issue 92, fluorescence, protein dynamics, lipid dynamics, membrane heterogeneity, transient confinement, single molecule, GFP
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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Authors: Noam Nissan, Edna Furman-Haran, Myra Feinberg-Shapiro, Dov Grobgeld, Erez Eyal, Tania Zehavi, Hadassa Degani.
Institutions: Weizmann Institute of Science, Weizmann Institute of Science, Meir Medical Center, Meir Medical Center.
Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.
Medicine, Issue 94, Magnetic Resonance Imaging, breast, breast cancer, diagnosis, water diffusion, diffusion tensor imaging
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Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
Authors: Yan Wei Lim, Matthew Haynes, Mike Furlan, Charles E. Robertson, J. Kirk Harris, Forest Rohwer.
Institutions: San Diego State University, DOE Joint Genome Institute, University of Colorado, University of Colorado.
The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.
Molecular Biology, Issue 94, virome, microbiome, metagenomics, metatranscriptomics, cystic fibrosis, mucosal-surface
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Modeling Mucosal Candidiasis in Larval Zebrafish by Swimbladder Injection
Authors: Remi L. Gratacap, Audrey C. Bergeron, Robert T. Wheeler.
Institutions: University of Maine, University of Maine.
Early defense against mucosal pathogens consists of both an epithelial barrier and innate immune cells. The immunocompetency of both, and their intercommunication, are paramount for the protection against infections. The interactions of epithelial and innate immune cells with a pathogen are best investigated in vivo, where complex behavior unfolds over time and space. However, existing models do not allow for easy spatio-temporal imaging of the battle with pathogens at the mucosal level. The model developed here creates a mucosal infection by direct injection of the fungal pathogen, Candida albicans, into the swimbladder of juvenile zebrafish. The resulting infection enables high-resolution imaging of epithelial and innate immune cell behavior throughout the development of mucosal disease. The versatility of this method allows for interrogation of the host to probe the detailed sequence of immune events leading to phagocyte recruitment and to examine the roles of particular cell types and molecular pathways in protection. In addition, the behavior of the pathogen as a function of immune attack can be imaged simultaneously by using fluorescent protein-expressing C. albicans. Increased spatial resolution of the host-pathogen interaction is also possible using the described rapid swimbladder dissection technique. The mucosal infection model described here is straightforward and highly reproducible, making it a valuable tool for the study of mucosal candidiasis. This system may also be broadly translatable to other mucosal pathogens such as mycobacterial, bacterial or viral microbes that normally infect through epithelial surfaces.
Immunology, Issue 93, Zebrafish, mucosal candidiasis, mucosal infection, epithelial barrier, epithelial cells, innate immunity, swimbladder, Candida albicans, in vivo.
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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Authors: Jacopo Tessadori, Michela Chiappalone.
Institutions: Istituto Italiano di Tecnologia.
Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history. If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed. Here an experimental system is introduced and described in which the activity of a neuronal element (i.e., a network of neurons extracted from embryonic mammalian hippocampi) is given context and used to control the movement of an artificial agent, while environmental information is fed back to the culture as a sequence of electrical stimuli. This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.
Neuroscience, Issue 97, Micro Electrode Arrays (MEA), in vitro cultures, coding, decoding, tetanic stimulation, spike, burst
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Single-stage Dynamic Reanimation of the Smile in Irreversible Facial Paralysis by Free Functional Muscle Transfer
Authors: Jan Thiele, Holger Bannasch, G. Bjoern Stark, Steffen U. Eisenhardt.
Institutions: University of Freiburg Medical Centre.
Unilateral facial paralysis is a common disease that is associated with significant functional, aesthetic and psychological issues. Though idiopathic facial paralysis (Bell’s palsy) is the most common diagnosis, patients can also present with a history of physical trauma, infectious disease, tumor, or iatrogenic facial paralysis. Early repair within one year of injury can be achieved by direct nerve repair, cross-face nerve grafting or regional nerve transfer. It is due to muscle atrophy that in long lasting facial paralysis complex reconstructive methods have to be applied. Instead of one single procedure, different surgical approaches have to be considered to alleviate the various components of the paralysis. The reconstruction of a spontaneous dynamic smile with a symmetric resting tone is a crucial factor to overcome the functional deficits and the social handicap that are associated with facial paralysis. Although numerous surgical techniques have been described, a two-stage approach with an initial cross-facial nerve grafting followed by a free functional muscle transfer is most frequently applied. In selected patients however, a single-stage reconstruction using the motor nerve to the masseter as donor nerve is superior to a two-stage repair. The gracilis muscle is most commonly used for reconstruction, as it presents with a constant anatomy, a simple dissection and minimal donor site morbidity. Here we demonstrate the pre-operative work-up, the post-operative management, and precisely describe the surgical procedure of single-stage microsurgical reconstruction of the smile by free functional gracilis muscle transfer in a step by step protocol. We further illustrate common pitfalls and provide useful tips which should enable the reader to truly comprehend the procedure. We further discuss indications and limitations of the technique and demonstrate representative results.
Medicine, Issue 97, microsurgery, free microvascular tissue transfer, face, head, head and neck surgery, facial paralysis
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Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
Authors: Sandra Zehentmeier, Zoltan Cseresnyes, Juan Escribano Navarro, Raluca A. Niesner, Anja E. Hauser.
Institutions: German Rheumatism Research Center, a Leibniz Institute, German Rheumatism Research Center, a Leibniz Institute, Max-Delbrück Center for Molecular Medicine, Wimasis GmbH, Charité - University of Medicine.
Confocal microscopy is the method of choice for the analysis of localization of multiple cell types within complex tissues such as the bone marrow. However, the analysis and quantification of cellular localization is difficult, as in many cases it relies on manual counting, thus bearing the risk of introducing a rater-dependent bias and reducing interrater reliability. Moreover, it is often difficult to judge whether the co-localization between two cells results from random positioning, especially when cell types differ strongly in the frequency of their occurrence. Here, a method for unbiased quantification of cellular co-localization in the bone marrow is introduced. The protocol describes the sample preparation used to obtain histological sections of whole murine long bones including the bone marrow, as well as the staining protocol and the acquisition of high-resolution images. An analysis workflow spanning from the recognition of hematopoietic and non-hematopoietic cell types in 2-dimensional (2D) bone marrow images to the quantification of the direct contacts between those cells is presented. This also includes a neighborhood analysis, to obtain information about the cellular microenvironment surrounding a certain cell type. In order to evaluate whether co-localization of two cell types is the mere result of random cell positioning or reflects preferential associations between the cells, a simulation tool which is suitable for testing this hypothesis in the case of hematopoietic as well as stromal cells, is used. This approach is not limited to the bone marrow, and can be extended to other tissues to permit reproducible, quantitative analysis of histological data.
Developmental Biology, Issue 98, Image analysis, neighborhood analysis, bone marrow, stromal cells, bone marrow niches, simulation, bone cryosectioning, bone histology
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Sample Drift Correction Following 4D Confocal Time-lapse Imaging
Authors: Adam Parslow, Albert Cardona, Robert J. Bryson-Richardson.
Institutions: Monash University, Howard Hughes Medical Institute.
The generation of four-dimensional (4D) confocal datasets; consisting of 3D image sequences over time; provides an excellent methodology to capture cellular behaviors involved in developmental processes.  The ability to track and follow cell movements is limited by sample movements that occur due to drift of the sample or, in some cases, growth during image acquisition. Tracking cells in datasets affected by drift and/or growth will incorporate these movements into any analysis of cell position. This may result in the apparent movement of static structures within the sample. Therefore prior to cell tracking, any sample drift should be corrected. Using the open source Fiji distribution 1  of ImageJ 2,3 and the incorporated LOCI tools 4, we developed the Correct 3D drift plug-in to remove erroneous sample movement in confocal datasets. This protocol effectively compensates for sample translation or alterations in focal position by utilizing phase correlation to register each time-point of a four-dimensional confocal datasets while maintaining the ability to visualize and measure cell movements over extended time-lapse experiments.
Bioengineering, Issue 86, Image Processing, Computer-Assisted, Zebrafish, Microscopy, Confocal, Time-Lapse Imaging, imaging, zebrafish, Confocal, fiji, three-dimensional, four-dimensional, registration
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Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
Authors: James J. Jun, André Longtin, Leonard Maler.
Institutions: University of Ottawa, University of Ottawa, University of Ottawa.
Long-term behavioral tracking can capture and quantify natural animal behaviors, including those occurring infrequently. Behaviors such as exploration and social interactions can be best studied by observing unrestrained, freely behaving animals. Weakly electric fish (WEF) display readily observable exploratory and social behaviors by emitting electric organ discharge (EOD). Here, we describe three effective techniques to synchronously measure the EOD, body position, and posture of a free-swimming WEF for an extended period of time. First, we describe the construction of an experimental tank inside of an isolation chamber designed to block external sources of sensory stimuli such as light, sound, and vibration. The aquarium was partitioned to accommodate four test specimens, and automated gates remotely control the animals' access to the central arena. Second, we describe a precise and reliable real-time EOD timing measurement method from freely swimming WEF. Signal distortions caused by the animal's body movements are corrected by spatial averaging and temporal processing stages. Third, we describe an underwater near-infrared imaging setup to observe unperturbed nocturnal animal behaviors. Infrared light pulses were used to synchronize the timing between the video and the physiological signal over a long recording duration. Our automated tracking software measures the animal's body position and posture reliably in an aquatic scene. In combination, these techniques enable long term observation of spontaneous behavior of freely swimming weakly electric fish in a reliable and precise manner. We believe our method can be similarly applied to the study of other aquatic animals by relating their physiological signals with exploratory or social behaviors.
Neuroscience, Issue 85, animal tracking, weakly electric fish, electric organ discharge, underwater infrared imaging, automated image tracking, sensory isolation chamber, exploratory behavior
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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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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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Using Learning Outcome Measures to assess Doctoral Nursing Education
Authors: Glenn H. Raup, Jeff King, Romana J. Hughes, Natasha Faidley.
Institutions: Harris College of Nursing and Health Sciences, Texas Christian University.
Education programs at all levels must be able to demonstrate successful program outcomes. Grades alone do not represent a comprehensive measurement methodology for assessing student learning outcomes at either the course or program level. The development and application of assessment rubrics provides an unequivocal measurement methodology to ensure a quality learning experience by providing a foundation for improvement based on qualitative and quantitatively measurable, aggregate course and program outcomes. Learning outcomes are the embodiment of the total learning experience and should incorporate assessment of both qualitative and quantitative program outcomes. The assessment of qualitative measures represents a challenge for educators in any level of a learning program. Nursing provides a unique challenge and opportunity as it is the application of science through the art of caring. Quantification of desired student learning outcomes may be enhanced through the development of assessment rubrics designed to measure quantitative and qualitative aspects of the nursing education and learning process. They provide a mechanism for uniform assessment by nursing faculty of concepts and constructs that are otherwise difficult to describe and measure. A protocol is presented and applied to a doctoral nursing education program with recommendations for application and transformation of the assessment rubric to other education programs. Through application of these specially designed rubrics, all aspects of an education program can be adequately assessed to provide information for program assessment that facilitates the closure of the gap between desired and actual student learning outcomes for any desired educational competency.
Medicine, Issue 40, learning, outcomes, measurement, program, assessment, rubric
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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
Authors: David C. Shih, Kevin C. Ho, Kyle M. Melnick, Ronald A. Rensink, Tobias R. Kollmann, Edgardo S. Fortuno III.
Institutions: University of British Columbia, University of British Columbia, University of British Columbia.
Visual analytics (VA) has emerged as a new way to analyze large dataset through interactive visual display. We demonstrated the utility and the flexibility of a VA approach in the analysis of biological datasets. Examples of these datasets in immunology include flow cytometry, Luminex data, and genotyping (e.g., single nucleotide polymorphism) data. Contrary to the traditional information visualization approach, VA restores the analysis power in the hands of analyst by allowing the analyst to engage in real-time data exploration process. We selected the VA software called Tableau after evaluating several VA tools. Two types of analysis tasks analysis within and between datasets were demonstrated in the video presentation using an approach called paired analysis. Paired analysis, as defined in VA, is an analysis approach in which a VA tool expert works side-by-side with a domain expert during the analysis. The domain expert is the one who understands the significance of the data, and asks the questions that the collected data might address. The tool expert then creates visualizations to help find patterns in the data that might answer these questions. The short lag-time between the hypothesis generation and the rapid visual display of the data is the main advantage of a VA approach.
Immunology, Issue 47, Visual analytics, flow cytometry, Luminex, Tableau, cytokine, innate immunity, single nucleotide polymorphism
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Collecting Variable-concentration Isothermal Titration Calorimetry Datasets in Order to Determine Binding Mechanisms
Authors: Lee A. Freiburger, Anthony K. Mittermaier, Karine Auclair.
Institutions: McGill University.
Isothermal titration calorimetry (ITC) is commonly used to determine the thermodynamic parameters associated with the binding of a ligand to a host macromolecule. ITC has some advantages over common spectroscopic approaches for studying host/ligand interactions. For example, the heat released or absorbed when the two components interact is directly measured and does not require any exogenous reporters. Thus the binding enthalpy and the association constant (Ka) are directly obtained from ITC data, and can be used to compute the entropic contribution. Moreover, the shape of the isotherm is dependent on the c-value and the mechanistic model involved. The c-value is defined as c = n[P]tKa, where [P]t is the protein concentration, and n is the number of ligand binding sites within the host. In many cases, multiple binding sites for a given ligand are non-equivalent and ITC allows the characterization of the thermodynamic binding parameters for each individual binding site. This however requires that the correct binding model be used. This choice can be problematic if different models can fit the same experimental data. We have previously shown that this problem can be circumvented by performing experiments at several c-values. The multiple isotherms obtained at different c-values are fit simultaneously to separate models. The correct model is next identified based on the goodness of fit across the entire variable-c dataset. This process is applied here to the aminoglycoside resistance-causing enzyme aminoglycoside N-6'-acetyltransferase-Ii (AAC(6')-Ii). Although our methodology is applicable to any system, the necessity of this strategy is better demonstrated with a macromolecule-ligand system showing allostery or cooperativity, and when different binding models provide essentially identical fits to the same data. To our knowledge, there are no such systems commercially available. AAC(6')-Ii, is a homo-dimer containing two active sites, showing cooperativity between the two subunits. However ITC data obtained at a single c-value can be fit equally well to at least two different models a two-sets-of-sites independent model and a two-site sequential (cooperative) model. Through varying the c-value as explained above, it was established that the correct binding model for AAC(6')-Ii is a two-site sequential binding model. Herein, we describe the steps that must be taken when performing ITC experiments in order to obtain datasets suitable for variable-c analyses.
Biochemistry, Issue 50, ITC, global fitting, cooperativity, binding model, ligand
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Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures
Authors: Dietmar Plenz, Craig V. Stewart, Woodrow Shew, Hongdian Yang, Andreas Klaus, Tim Bellay.
Institutions: National Institute of Mental Health.
The cortex is spontaneously active, even in the absence of any particular input or motor output. During development, this activity is important for the migration and differentiation of cortex cell types and the formation of neuronal connections1. In the mature animal, ongoing activity reflects the past and the present state of an animal into which sensory stimuli are seamlessly integrated to compute future actions. Thus, a clear understanding of the organization of ongoing i.e. spontaneous activity is a prerequisite to understand cortex function. Numerous recording techniques revealed that ongoing activity in cortex is comprised of many neurons whose individual activities transiently sum to larger events that can be detected in the local field potential (LFP) with extracellular microelectrodes, or in the electroencephalogram (EEG), the magnetoencephalogram (MEG), and the BOLD signal from functional magnetic resonance imaging (fMRI). The LFP is currently the method of choice when studying neuronal population activity with high temporal and spatial resolution at the mesoscopic scale (several thousands of neurons). At the extracellular microelectrode, locally synchronized activities of spatially neighbored neurons result in rapid deflections in the LFP up to several hundreds of microvolts. When using an array of microelectrodes, the organizations of such deflections can be conveniently monitored in space and time. Neuronal avalanches describe the scale-invariant spatiotemporal organization of ongoing neuronal activity in the brain2,3. They are specific to the superficial layers of cortex as established in vitro4,5, in vivo in the anesthetized rat 6, and in the awake monkey7. Importantly, both theoretical and empirical studies2,8-10 suggest that neuronal avalanches indicate an exquisitely balanced critical state dynamics of cortex that optimizes information transfer and information processing. In order to study the mechanisms of neuronal avalanche development, maintenance, and regulation, in vitro preparations are highly beneficial, as they allow for stable recordings of avalanche activity under precisely controlled conditions. The current protocol describes how to study neuronal avalanches in vitro by taking advantage of superficial layer development in organotypic cortex cultures, i.e. slice cultures, grown on planar, integrated microelectrode arrays (MEA; see also 11-14).
Neuroscience, Issue 54, neuronal activity, neuronal avalanches, organotypic culture, slice culture, microelectrode array, electrophysiology, local field potential, extracellular spikes
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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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Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution
Authors: Serhan O. Isikman, Waheb Bishara, Aydogan Ozcan.
Institutions: University of California, Los Angeles , University of California, Los Angeles , University of California, Los Angeles .
Tomographic imaging has been a widely used tool in medicine as it can provide three-dimensional (3D) structural information regarding objects of different size scales. In micrometer and millimeter scales, optical microscopy modalities find increasing use owing to the non-ionizing nature of visible light, and the availability of a rich set of illumination sources (such as lasers and light-emitting-diodes) and detection elements (such as large format CCD and CMOS detector-arrays). Among the recently developed optical tomographic microscopy modalities, one can include optical coherence tomography, optical diffraction tomography, optical projection tomography and light-sheet microscopy. 1-6 These platforms provide sectional imaging of cells, microorganisms and model animals such as C. elegans, zebrafish and mouse embryos. Existing 3D optical imagers generally have relatively bulky and complex architectures, limiting the availability of these equipments to advanced laboratories, and impeding their integration with lab-on-a-chip platforms and microfluidic chips. To provide an alternative tomographic microscope, we recently developed lensfree optical tomography (LOT) as a high-throughput, compact and cost-effective optical tomography modality. 7 LOT discards the use of lenses and bulky optical components, and instead relies on multi-angle illumination and digital computation to achieve depth-resolved imaging of micro-objects over a large imaging volume. LOT can image biological specimen at a spatial resolution of <1 μm x <1 μm x <3 μm in the x, y and z dimensions, respectively, over a large imaging volume of 15-100 mm3, and can be particularly useful for lab-on-a-chip platforms.
Bioengineering, Issue 66, Electrical Engineering, Mechanical Engineering, lensfree imaging, lensless imaging, on-chip microscopy, lensfree tomography, 3D microscopy, pixel super-resolution, C. elegans, optical sectioning, lab-on-a-chip
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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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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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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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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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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Authors: Savannah E. Sanchez, Daniel A. Cuevas, Jason E. Rostron, Tiffany Y. Liang, Cullen G. Pivaroff, Matthew R. Haynes, Jim Nulton, Ben Felts, Barbara A. Bailey, Peter Salamon, Robert A. Edwards, Alex B. Burgin, Anca M. Segall, Forest Rohwer.
Institutions: San Diego State University, San Diego State University, San Diego State University, San Diego State University, San Diego State University, Argonne National Laboratory, Broad Institute.
Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.
Immunology, Issue 100, phenomics, phage, viral metagenome, Multi-phenotype Assay Plates (MAPs), continuous culture, metabolomics
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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.