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Spatial pattern of standing timber value across the Brazilian Amazon.
The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome.
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Published: 11-03-2011
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
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Determination of Microbial Extracellular Enzyme Activity in Waters, Soils, and Sediments using High Throughput Microplate Assays
Authors: Colin R. Jackson, Heather L. Tyler, Justin J. Millar.
Institutions: The University of Mississippi.
Much of the nutrient cycling and carbon processing in natural environments occurs through the activity of extracellular enzymes released by microorganisms. Thus, measurement of the activity of these extracellular enzymes can give insights into the rates of ecosystem level processes, such as organic matter decomposition or nitrogen and phosphorus mineralization. Assays of extracellular enzyme activity in environmental samples typically involve exposing the samples to artificial colorimetric or fluorometric substrates and tracking the rate of substrate hydrolysis. Here we describe microplate based methods for these procedures that allow the analysis of large numbers of samples within a short time frame. Samples are allowed to react with artificial substrates within 96-well microplates or deep well microplate blocks, and enzyme activity is subsequently determined by absorption or fluorescence of the resulting end product using a typical microplate reader or fluorometer. Such high throughput procedures not only facilitate comparisons between spatially separate sites or ecosystems, but also substantially reduce the cost of such assays by reducing overall reagent volumes needed per sample.
Environmental Sciences, Issue 80, Environmental Monitoring, Ecological and Environmental Processes, Environmental Microbiology, Ecology, extracellular enzymes, freshwater microbiology, soil microbiology, microbial activity, enzyme activity
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Trajectory Data Analyses for Pedestrian Space-time Activity Study
Authors: Feng Qi, Fei Du.
Institutions: Kean University, University of Wisconsin-Madison.
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4. Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5 involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6 and density volume rendering7. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.
Environmental Sciences, Issue 72, Computer Science, Behavior, Infectious Diseases, Geography, Cartography, Data Display, Disease Outbreaks, cartography, human behavior, Trajectory data, space-time activity, GPS, GIS, ArcGIS, spatiotemporal analysis, visualization, segmentation, density surface, density volume, exploratory data analysis, modelling
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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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Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis
Authors: Fan Zhang, Ming Liu, Stephen Harper, Michael Lee, He Huang.
Institutions: North Carolina State University & University of North Carolina at Chapel Hill, University of North Carolina School of Medicine, Atlantic Prosthetics & Orthotics, LLC.
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.
Biomedical Engineering, Issue 89, neural control, powered transfemoral prosthesis, electromyography (EMG), neural-machine interface, experimental setup and protocol
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Measuring Material Microstructure Under Flow Using 1-2 Plane Flow-Small Angle Neutron Scattering
Authors: A. Kate Gurnon, P. Douglas Godfrin, Norman J. Wagner, Aaron P. R. Eberle, Paul Butler, Lionel Porcar.
Institutions: University of Delaware, National Institute of Standards and Technology, Institut Laue-Langevin.
A new small-angle neutron scattering (SANS) sample environment optimized for studying the microstructure of complex fluids under simple shear flow is presented. The SANS shear cell consists of a concentric cylinder Couette geometry that is sealed and rotating about a horizontal axis so that the vorticity direction of the flow field is aligned with the neutron beam enabling scattering from the 1-2 plane of shear (velocity-velocity gradient, respectively). This approach is an advance over previous shear cell sample environments as there is a strong coupling between the bulk rheology and microstructural features in the 1-2 plane of shear. Flow-instabilities, such as shear banding, can also be studied by spatially resolved measurements. This is accomplished in this sample environment by using a narrow aperture for the neutron beam and scanning along the velocity gradient direction. Time resolved experiments, such as flow start-ups and large amplitude oscillatory shear flow are also possible by synchronization of the shear motion and time-resolved detection of scattered neutrons. Representative results using the methods outlined here demonstrate the useful nature of spatial resolution for measuring the microstructure of a wormlike micelle solution that exhibits shear banding, a phenomenon that can only be investigated by resolving the structure along the velocity gradient direction. Finally, potential improvements to the current design are discussed along with suggestions for supplementary experiments as motivation for future experiments on a broad range of complex fluids in a variety of shear motions.
Physics, Issue 84, Surfactants, Rheology, Shear Banding, Nanostructure, Neutron Scattering, Complex Fluids, Flow-induced Structure
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Towards Biomimicking Wood: Fabricated Free-standing Films of Nanocellulose, Lignin, and a Synthetic Polycation
Authors: Karthik Pillai, Fernando Navarro Arzate, Wei Zhang, Scott Renneckar.
Institutions: Virginia Tech, Virginia Tech, Illinois Institute of Technology- Moffett Campus, University of Guadalajara, Virginia Tech, Virginia Tech.
Woody materials are comprised of plant cell walls that contain a layered secondary cell wall composed of structural polymers of polysaccharides and lignin. Layer-by-layer (LbL) assembly process which relies on the assembly of oppositely charged molecules from aqueous solutions was used to build a freestanding composite film of isolated wood polymers of lignin and oxidized nanofibril cellulose (NFC). To facilitate the assembly of these negatively charged polymers, a positively charged polyelectrolyte, poly(diallyldimethylammomium chloride) (PDDA), was used as a linking layer to create this simplified model cell wall. The layered adsorption process was studied quantitatively using quartz crystal microbalance with dissipation monitoring (QCM-D) and ellipsometry. The results showed that layer mass/thickness per adsorbed layer increased as a function of total number of layers. The surface coverage of the adsorbed layers was studied with atomic force microscopy (AFM). Complete coverage of the surface with lignin in all the deposition cycles was found for the system, however, surface coverage by NFC increased with the number of layers. The adsorption process was carried out for 250 cycles (500 bilayers) on a cellulose acetate (CA) substrate. Transparent free-standing LBL assembled nanocomposite films were obtained when the CA substrate was later dissolved in acetone. Scanning electron microscopy (SEM) of the fractured cross-sections showed a lamellar structure, and the thickness per adsorption cycle (PDDA-Lignin-PDDA-NC) was estimated to be 17 nm for two different lignin types used in the study. The data indicates a film with highly controlled architecture where nanocellulose and lignin are spatially deposited on the nanoscale (a polymer-polymer nanocomposites), similar to what is observed in the native cell wall.
Plant Biology, Issue 88, nanocellulose, thin films, quartz crystal microbalance, layer-by-layer, LbL
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Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Authors: Thomas C. Bulea, Atilla Kilicarslan, Recep Ozdemir, William H. Paloski, Jose L. Contreras-Vidal.
Institutions: National Institutes of Health, University of Houston, University of Houston, University of Houston, University of Houston.
Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.
Behavior, Issue 77, Neuroscience, Neurobiology, Medicine, Anatomy, Physiology, Biomedical Engineering, Molecular Biology, Electroencephalography, EEG, Electromyography, EMG, electroencephalograph, gait, brain-computer interface, brain machine interface, neural decoding, over-ground walking, robotic gait, brain, imaging, clinical techniques
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A Multi-Modal Approach to Assessing Recovery in Youth Athletes Following Concussion
Authors: Nick Reed, James Murphy, Talia Dick, Katie Mah, Melissa Paniccia, Lee Verweel, Danielle Dobney, Michelle Keightley.
Institutions: Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, University of Toronto.
Concussion is one of the most commonly reported injuries amongst children and youth involved in sport participation. Following a concussion, youth can experience a range of short and long term neurobehavioral symptoms (somatic, cognitive and emotional/behavioral) that can have a significant impact on one’s participation in daily activities and pursuits of interest (e.g., school, sports, work, family/social life, etc.). Despite this, there remains a paucity in clinically driven research aimed specifically at exploring concussion within the youth sport population, and more specifically, multi-modal approaches to measuring recovery. This article provides an overview of a novel and multi-modal approach to measuring recovery amongst youth athletes following concussion. The presented approach involves the use of both pre-injury/baseline testing and post-injury/follow-up testing to assess performance across a wide variety of domains (post-concussion symptoms, cognition, balance, strength, agility/motor skills and resting state heart rate variability). The goal of this research is to gain a more objective and accurate understanding of recovery following concussion in youth athletes (ages 10-18 years). Findings from this research can help to inform the development and use of improved approaches to concussion management and rehabilitation specific to the youth sport community.
Medicine, Issue 91, concussion, children, youth, athletes, assessment, management, rehabilitation
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Preparation of Hydroxy-PAAm Hydrogels for Decoupling the Effects of Mechanotransduction Cues
Authors: Thomas Grevesse, Marie Versaevel, Sylvain Gabriele.
Institutions: Université de Mons.
It is now well established that many cellular functions are regulated by interactions of cells with physicochemical and mechanical cues of their extracellular matrix (ECM) environment. Eukaryotic cells constantly sense their local microenvironment through surface mechanosensors to transduce physical changes of ECM into biochemical signals, and integrate these signals to achieve specific changes in gene expression. Interestingly, physicochemical and mechanical parameters of the ECM can couple with each other to regulate cell fate. Therefore, a key to understanding mechanotransduction is to decouple the relative contribution of ECM cues on cellular functions. Here we present a detailed experimental protocol to rapidly and easily generate biologically relevant hydrogels for the independent tuning of mechanotransduction cues in vitro. We chemically modified polyacrylamide hydrogels (PAAm) to surmount their intrinsically non-adhesive properties by incorporating hydroxyl-functionalized acrylamide monomers during the polymerization. We obtained a novel PAAm hydrogel, called hydroxy-PAAm, which permits immobilization of any desired nature of ECM proteins. The combination of hydroxy-PAAm hydrogels with microcontact printing allows to independently control the morphology of single-cells, the matrix stiffness, the nature and the density of ECM proteins. We provide a simple and rapid method that can be set up in every biology lab to study in vitro cell mechanotransduction processes. We validate this novel two-dimensional platform by conducting experiments on endothelial cells that demonstrate a mechanical coupling between ECM stiffness and the nucleus.
Bioengineering, Issue 90, hydrogels, mechanotransduction, polyacrylamide, microcontact printing, cell shape, stiffness, durotaxis, cell-ligand density
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Methods for the Modulation and Analysis of NF-κB-dependent Adult Neurogenesis
Authors: Darius Widera, Janine Müller, Yvonne Imielski, Peter Heimann, Christian Kaltschmidt, Barbara Kaltschmidt.
Institutions: University of Bielefeld, University of Bielefeld.
The hippocampus plays a pivotal role in the formation and consolidation of episodic memories, and in spatial orientation. Historically, the adult hippocampus has been viewed as a very static anatomical region of the mammalian brain. However, recent findings have demonstrated that the dentate gyrus of the hippocampus is an area of tremendous plasticity in adults, involving not only modifications of existing neuronal circuits, but also adult neurogenesis. This plasticity is regulated by complex transcriptional networks, in which the transcription factor NF-κB plays a prominent role. To study and manipulate adult neurogenesis, a transgenic mouse model for forebrain-specific neuronal inhibition of NF-κB activity can be used. In this study, methods are described for the analysis of NF-κB-dependent neurogenesis, including its structural aspects, neuronal apoptosis and progenitor proliferation, and cognitive significance, which was specifically assessed via a dentate gyrus (DG)-dependent behavioral test, the spatial pattern separation-Barnes maze (SPS-BM). The SPS-BM protocol could be simply adapted for use with other transgenic animal models designed to assess the influence of particular genes on adult hippocampal neurogenesis. Furthermore, SPS-BM could be used in other experimental settings aimed at investigating and manipulating DG-dependent learning, for example, using pharmacological agents.
Neuroscience, Issue 84, NF-κB, hippocampus, Adult neurogenesis, spatial pattern separation-Barnes maze, dentate gyrus, p65 knock-out mice
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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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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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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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Aseptic Laboratory Techniques: Plating Methods
Authors: Erin R. Sanders.
Institutions: University of California, Los Angeles .
Microorganisms are present on all inanimate surfaces creating ubiquitous sources of possible contamination in the laboratory. Experimental success relies on the ability of a scientist to sterilize work surfaces and equipment as well as prevent contact of sterile instruments and solutions with non-sterile surfaces. Here we present the steps for several plating methods routinely used in the laboratory to isolate, propagate, or enumerate microorganisms such as bacteria and phage. All five methods incorporate aseptic technique, or procedures that maintain the sterility of experimental materials. Procedures described include (1) streak-plating bacterial cultures to isolate single colonies, (2) pour-plating and (3) spread-plating to enumerate viable bacterial colonies, (4) soft agar overlays to isolate phage and enumerate plaques, and (5) replica-plating to transfer cells from one plate to another in an identical spatial pattern. These procedures can be performed at the laboratory bench, provided they involve non-pathogenic strains of microorganisms (Biosafety Level 1, BSL-1). If working with BSL-2 organisms, then these manipulations must take place in a biosafety cabinet. Consult the most current edition of the Biosafety in Microbiological and Biomedical Laboratories (BMBL) as well as Material Safety Data Sheets (MSDS) for Infectious Substances to determine the biohazard classification as well as the safety precautions and containment facilities required for the microorganism in question. Bacterial strains and phage stocks can be obtained from research investigators, companies, and collections maintained by particular organizations such as the American Type Culture Collection (ATCC). It is recommended that non-pathogenic strains be used when learning the various plating methods. By following the procedures described in this protocol, students should be able to: ● Perform plating procedures without contaminating media. ● Isolate single bacterial colonies by the streak-plating method. ● Use pour-plating and spread-plating methods to determine the concentration of bacteria. ● Perform soft agar overlays when working with phage. ● Transfer bacterial cells from one plate to another using the replica-plating procedure. ● Given an experimental task, select the appropriate plating method.
Basic Protocols, Issue 63, Streak plates, pour plates, soft agar overlays, spread plates, replica plates, bacteria, colonies, phage, plaques, dilutions
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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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Analyzing Protein Dynamics Using Hydrogen Exchange Mass Spectrometry
Authors: Nikolai Hentze, Matthias P. Mayer.
Institutions: University of Heidelberg.
All cellular processes depend on the functionality of proteins. Although the functionality of a given protein is the direct consequence of its unique amino acid sequence, it is only realized by the folding of the polypeptide chain into a single defined three-dimensional arrangement or more commonly into an ensemble of interconverting conformations. Investigating the connection between protein conformation and its function is therefore essential for a complete understanding of how proteins are able to fulfill their great variety of tasks. One possibility to study conformational changes a protein undergoes while progressing through its functional cycle is hydrogen-1H/2H-exchange in combination with high-resolution mass spectrometry (HX-MS). HX-MS is a versatile and robust method that adds a new dimension to structural information obtained by e.g. crystallography. It is used to study protein folding and unfolding, binding of small molecule ligands, protein-protein interactions, conformational changes linked to enzyme catalysis, and allostery. In addition, HX-MS is often used when the amount of protein is very limited or crystallization of the protein is not feasible. Here we provide a general protocol for studying protein dynamics with HX-MS and describe as an example how to reveal the interaction interface of two proteins in a complex.   
Chemistry, Issue 81, Molecular Chaperones, mass spectrometers, Amino Acids, Peptides, Proteins, Enzymes, Coenzymes, Protein dynamics, conformational changes, allostery, protein folding, secondary structure, mass spectrometry
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
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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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Cryosectioning Yeast Communities for Examining Fluorescence Patterns
Authors: Babak Momeni, Wenying Shou.
Institutions: Fred Hutchinson Cancer Research Center.
Microbes typically live in communities. The spatial organization of cells within a community is believed to impact the survival and function of the community1. Optical sectioning techniques, including confocal and two-photon microscopy, have proven useful for observing spatial organization of bacterial and archaeal communities2,3. A combination of confocal imaging and physical sectioning of yeast colonies has revealed internal organization of cells4. However, direct optical sectioning using confocal or two-photon microscopy has been only able to reach a few cell layers deep into yeast colonies. This limitation is likely because of strong scattering of light from yeast cells4. Here, we present a method based on fixing and cryosectioning to obtain spatial distribution of fluorescent cells within Saccharomyces cerevisiae communities. We use methanol as the fixative agent to preserve the spatial distribution of cells. Fixed communities are infiltrated with OCT compound, frozen, and cryosectioned in a cryostat. Fluorescence imaging of the sections reveals the internal organization of fluorescent cells within the community. Examples of yeast communities consisting of strains expressing red and green fluorescent proteins demonstrate the potentials of the cryosectioning method to reveal the spatial distribution of fluorescent cells as well as that of gene expression within yeast colonies2,3. Even though our focus has been on Saccharomyces cerevisiae communities, the same method can potentially be applied to examine other microbial communities.
Microbiology, Issue 70, Molecular Biology, Cellular Biology, Basic Protocols, Yeasts, Saccharomyces cerevisiae, Clinical Laboratory Techniques, Cytological Techniques, Environmental Microbiology, Investigative Techniques, Life Sciences, cryosectioning, sectioning, cryotome, fixing, microbial community, yeast colonies, Saccharomyces cerevisiae, community interactions
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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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In situ Protocol for Butterfly Pupal Wings Using Riboprobes
Authors: Diane Ramos, Antonia Monteiro.
Institutions: SUNY-University at Buffalo, Yale University.
Here we present, in video format, a protocol for in situ hybridizations in pupal wings of the butterfly Bicyclus anynana using riboprobes. In situ hybridizations, a mainstay of developmental biology, are useful to study the spatial and temporal patterns of gene expression in developing tissues at the level of transcription. If antibodies that target the protein products of gene transcription have not yet been developed, and/or there are multiple gene copies of a particular protein in the genome that cannot be differentiated using available antibodies, in situs can be used instead. While an in situ technique for larval wing discs has been available to the butterfly community for several years, the current protocol has been optimized for the larger and more fragile pupal wings.
Developmental Biology, issue 4, hybridization, wing, staining
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Authors: Sergey Rabotyagov, Todd Campbell, Adriana Valcu, Philip Gassman, Manoj Jha, Keith Schilling, Calvin Wolter, Catherine Kling.
Institutions: University of Washington, Iowa State University, North Carolina A&T University, Iowa Geological and Water Survey.
Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods3,4,9,10,13-15,17-19,22,23,25. In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model7 with a multiobjective evolutionary algorithm SPEA226, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.
Environmental Sciences, Issue 70, Plant Biology, Civil Engineering, Forest Sciences, Water quality, multiobjective optimization, evolutionary algorithms, cost efficiency, agriculture, development
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Yeast Colony Embedding Method
Authors: Sarah Piccirillo, Saul M. Honigberg.
Institutions: University of Missouri - Kansas City.
Patterning of different cell types in embryos is a key mechanism in metazoan development. Communities of microorganisms, such as colonies and biofilms also display patterns of cell types. For example, in the yeast S. cerevisiae, sporulated cells and pseudohyphal cells are not uniformly distributed in colonies. The functional importance of patterning and the molecular mechanisms that underlie these patterns are still poorly understood. One challenge with respect to investigating patterns of cell types in fungal colonies is that unlike metazoan tissue, cells in colonies are relatively weakly attached to one another. In particular, fungal colonies do not contain the same extensive level of extracellular matrix found in most tissues . Here we report on a method for embedding and sectioning yeast colonies that reveals the interior patterns of cell types in these colonies. The method can be used to prepare thick sections (0.5 μ) useful for light microscopy and thin sections (0.1 μ) suitable for transmission electron microscopy. Asci and pseudohyphal cells can easily be distinguished from ovoid yeast cells by light microscopy , while the interior structure of these cells can be visualized by EM. The method is based on surrounding colonies with agar, infiltrating them with Spurr's medium, and then sectioning. Colonies with a diameter in the range of 1-2 mm are suitable for this protocol. In addition to visualizing the interior of colonies, the method allows visualization of the region of the colony that invades the underlying agar.
Cellular Biology, Issue 49, yeast, Saccharomyces cerevisiae, colony, embedding, sporulation, pattern formation, organization
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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Patterning Cells on Optically Transparent Indium Tin Oxide Electrodes
Authors: Sunny Shah, Alexander Revzin.
Institutions: University of California, Davis.
The ability to exercise precise spatial and temporal control over cell-surface interactions is an important prerequisite to the assembly of multi-cellular constructs serving as in vitro mimics of native tissues. In this study, photolithography and wet etching techniques were used to fabricate individually addressable indium tin oxide (ITO) electrodes on glass substrates. The glass substrates containing ITO microelectrodes were modified with poly(ethylene glycol) (PEG) silane to make them protein and cell resistive. Presence of insulating PEG molecules on the electrode surface was verified by cyclic voltammetry employing potassium ferricyanide as a redox reporter molecule. Importantly, the application of reductive potential caused desorption of the PEG layer, resulting in regeneration of the conductive electrode surface and appearance of typical ferricyanide redox peaks. Application of reductive potential also corresponded to switching of ITO electrode properties from cell non-adhesive to cell-adhesive. Electrochemical stripping of PEG-silane layer from ITO microelectrodes allowed for cell adhesion to take place in a spatially defined fashion, with cellular patterns corresponding closely to electrode patterns. Micropatterning of several cell types was demonstrated on these substrates. In the future, the control of the biointerfacial properties afforded by this method will allow to engineer cellular microenvironments through the assembly of three or more cell types into a precise geometric configuration on an optically transparent substrate.
Cellular Biology, Issue 7, indium tin oxide, surface modification, electrochemistry, cell patterning
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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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We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

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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.