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A global and spatially explicit assessment of climate change impacts on crop production and consumptive water use.
PUBLISHED: 01-29-2013
Food security and water scarcity have become two major concerns for future humans sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security.
Authors: Sarah M. Collier, Matthew D. Ruark, Lawrence G. Oates, William E. Jokela, Curtis J. Dell.
Published: 08-03-2014
Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.
23 Related JoVE Articles!
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Optimization and Utilization of Agrobacterium-mediated Transient Protein Production in Nicotiana
Authors: Moneim Shamloul, Jason Trusa, Vadim Mett, Vidadi Yusibov.
Institutions: Fraunhofer USA Center for Molecular Biotechnology.
Agrobacterium-mediated transient protein production in plants is a promising approach to produce vaccine antigens and therapeutic proteins within a short period of time. However, this technology is only just beginning to be applied to large-scale production as many technological obstacles to scale up are now being overcome. Here, we demonstrate a simple and reproducible method for industrial-scale transient protein production based on vacuum infiltration of Nicotiana plants with Agrobacteria carrying launch vectors. Optimization of Agrobacterium cultivation in AB medium allows direct dilution of the bacterial culture in Milli-Q water, simplifying the infiltration process. Among three tested species of Nicotiana, N. excelsiana (N. benthamiana × N. excelsior) was selected as the most promising host due to the ease of infiltration, high level of reporter protein production, and about two-fold higher biomass production under controlled environmental conditions. Induction of Agrobacterium harboring pBID4-GFP (Tobacco mosaic virus-based) using chemicals such as acetosyringone and monosaccharide had no effect on the protein production level. Infiltrating plant under 50 to 100 mbar for 30 or 60 sec resulted in about 95% infiltration of plant leaf tissues. Infiltration with Agrobacterium laboratory strain GV3101 showed the highest protein production compared to Agrobacteria laboratory strains LBA4404 and C58C1 and wild-type Agrobacteria strains at6, at10, at77 and A4. Co-expression of a viral RNA silencing suppressor, p23 or p19, in N. benthamiana resulted in earlier accumulation and increased production (15-25%) of target protein (influenza virus hemagglutinin).
Plant Biology, Issue 86, Agroinfiltration, Nicotiana benthamiana, transient protein production, plant-based expression, viral vector, Agrobacteria
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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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Characterization of Recombination Effects in a Liquid Ionization Chamber Used for the Dosimetry of a Radiosurgical Accelerator
Authors: Antoine Wagner, Frederik Crop, Thomas Lacornerie, Nick Reynaert.
Institutions: Centre Oscar Lambret.
Most modern radiation therapy devices allow the use of very small fields, either through beamlets in Intensity-Modulated Radiation Therapy (IMRT) or via stereotactic radiotherapy where positioning accuracy allows delivering very high doses per fraction in a small volume of the patient. Dosimetric measurements on medical accelerators are conventionally realized using air-filled ionization chambers. However, in small beams these are subject to nonnegligible perturbation effects. This study focuses on liquid ionization chambers, which offer advantages in terms of spatial resolution and low fluence perturbation. Ion recombination effects are investigated for the microLion detector (PTW) used with the Cyberknife system (Accuray). The method consists of performing a series of water tank measurements at different source-surface distances, and applying corrections to the liquid detector readings based on simultaneous gaseous detector measurements. This approach facilitates isolating the recombination effects arising from the high density of the liquid sensitive medium and obtaining correction factors to apply to the detector readings. The main difficulty resides in achieving a sufficient level of accuracy in the setup to be able to detect small changes in the chamber response.
Physics, Issue 87, Radiation therapy, dosimetry, small fields, Cyberknife, liquid ionization, recombination effects
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Assessment of Vascular Function in Patients With Chronic Kidney Disease
Authors: Kristen L. Jablonski, Emily Decker, Loni Perrenoud, Jessica Kendrick, Michel Chonchol, Douglas R. Seals, Diana Jalal.
Institutions: University of Colorado, Denver, University of Colorado, Boulder.
Patients with chronic kidney disease (CKD) have significantly increased risk of cardiovascular disease (CVD) compared to the general population, and this is only partially explained by traditional CVD risk factors. Vascular dysfunction is an important non-traditional risk factor, characterized by vascular endothelial dysfunction (most commonly assessed as impaired endothelium-dependent dilation [EDD]) and stiffening of the large elastic arteries. While various techniques exist to assess EDD and large elastic artery stiffness, the most commonly used are brachial artery flow-mediated dilation (FMDBA) and aortic pulse-wave velocity (aPWV), respectively. Both of these noninvasive measures of vascular dysfunction are independent predictors of future cardiovascular events in patients with and without kidney disease. Patients with CKD demonstrate both impaired FMDBA, and increased aPWV. While the exact mechanisms by which vascular dysfunction develops in CKD are incompletely understood, increased oxidative stress and a subsequent reduction in nitric oxide (NO) bioavailability are important contributors. Cellular changes in oxidative stress can be assessed by collecting vascular endothelial cells from the antecubital vein and measuring protein expression of markers of oxidative stress using immunofluorescence. We provide here a discussion of these methods to measure FMDBA, aPWV, and vascular endothelial cell protein expression.
Medicine, Issue 88, chronic kidney disease, endothelial cells, flow-mediated dilation, immunofluorescence, oxidative stress, pulse-wave velocity
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Design and Construction of an Urban Runoff Research Facility
Authors: Benjamin G. Wherley, Richard H. White, Kevin J. McInnes, Charles H. Fontanier, James C. Thomas, Jacqueline A. Aitkenhead-Peterson, Steven T. Kelly.
Institutions: Texas A&M University, The Scotts Miracle-Gro Company.
As the urban population increases, so does the area of irrigated urban landscape. Summer water use in urban areas can be 2-3x winter base line water use due to increased demand for landscape irrigation. Improper irrigation practices and large rainfall events can result in runoff from urban landscapes which has potential to carry nutrients and sediments into local streams and lakes where they may contribute to eutrophication. A 1,000 m2 facility was constructed which consists of 24 individual 33.6 m2 field plots, each equipped for measuring total runoff volumes with time and collection of runoff subsamples at selected intervals for quantification of chemical constituents in the runoff water from simulated urban landscapes. Runoff volumes from the first and second trials had coefficient of variability (CV) values of 38.2 and 28.7%, respectively. CV values for runoff pH, EC, and Na concentration for both trials were all under 10%. Concentrations of DOC, TDN, DON, PO4-P, K+, Mg2+, and Ca2+ had CV values less than 50% in both trials. Overall, the results of testing performed after sod installation at the facility indicated good uniformity between plots for runoff volumes and chemical constituents. The large plot size is sufficient to include much of the natural variability and therefore provides better simulation of urban landscape ecosystems.
Environmental Sciences, Issue 90, urban runoff, landscapes, home lawns, turfgrass, St. Augustinegrass, carbon, nitrogen, phosphorus, sodium
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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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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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Multimodal Optical Microscopy Methods Reveal Polyp Tissue Morphology and Structure in Caribbean Reef Building Corals
Authors: Mayandi Sivaguru, Glenn A. Fried, Carly A. H. Miller, Bruce W. Fouke.
Institutions: University of Illinois at Urbana-Champaign, University of Illinois at Urbana-Champaign, University of Illinois at Urbana-Champaign.
An integrated suite of imaging techniques has been applied to determine the three-dimensional (3D) morphology and cellular structure of polyp tissues comprising the Caribbean reef building corals Montastraeaannularis and M. faveolata. These approaches include fluorescence microscopy (FM), serial block face imaging (SBFI), and two-photon confocal laser scanning microscopy (TPLSM). SBFI provides deep tissue imaging after physical sectioning; it details the tissue surface texture and 3D visualization to tissue depths of more than 2 mm. Complementary FM and TPLSM yield ultra-high resolution images of tissue cellular structure. Results have: (1) identified previously unreported lobate tissue morphologies on the outer wall of individual coral polyps and (2) created the first surface maps of the 3D distribution and tissue density of chromatophores and algae-like dinoflagellate zooxanthellae endosymbionts. Spectral absorption peaks of 500 nm and 675 nm, respectively, suggest that M. annularis and M. faveolata contain similar types of chlorophyll and chromatophores. However, M. annularis and M. faveolata exhibit significant differences in the tissue density and 3D distribution of these key cellular components. This study focusing on imaging methods indicates that SBFI is extremely useful for analysis of large mm-scale samples of decalcified coral tissues. Complimentary FM and TPLSM reveal subtle submillimeter scale changes in cellular distribution and density in nondecalcified coral tissue samples. The TPLSM technique affords: (1) minimally invasive sample preparation, (2) superior optical sectioning ability, and (3) minimal light absorption and scattering, while still permitting deep tissue imaging.
Environmental Sciences, Issue 91, Serial block face imaging, two-photon fluorescence microscopy, Montastraea annularis, Montastraea faveolata, 3D coral tissue morphology and structure, zooxanthellae, chromatophore, autofluorescence, light harvesting optimization, environmental change
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Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation
Authors: Audrey R. Matteson, Denis J. Mahoney, Travis W. Gannon, Matthew L. Polizzotto.
Institutions: North Carolina State University, North Carolina State University.
Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals is often not well understood. Here we demonstrate an integrated field lysimetry and porewater sampling method for evaluating the mobility of chemicals applied to soils and established vegetation. Lysimeters, open columns made of metal or plastic, are driven into bareground or vegetated soils. Porewater samplers, which are commercially available and use vacuum to collect percolating soil water, are installed at predetermined depths within the lysimeters. At prearranged times following chemical application to experimental plots, porewater is collected, and lysimeters, containing soil and vegetation, are exhumed. By analyzing chemical concentrations in the lysimeter soil, vegetation, and porewater, downward leaching rates, soil retention capacities, and plant uptake for the chemical of interest may be quantified. Because field lysimetry and porewater sampling are conducted under natural environmental conditions and with minimal soil disturbance, derived results project real-case scenarios and provide valuable information for chemical management. As chemicals are increasingly applied to land worldwide, the described techniques may be utilized to determine whether applied chemicals pose adverse effects to human health or the environment.
Environmental Sciences, Issue 89, Lysimetry, porewater, soil, chemical leaching, pesticides, turfgrass, waste
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An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus
Authors: Monica F. Poelchau, Xin Huang, Allison Goff, Julie Reynolds, Peter Armbruster.
Institutions: Georgetown University, The Ohio State University.
Photoperiodic diapause is an important adaptation that allows individuals to escape harsh seasonal environments via a series of physiological changes, most notably developmental arrest and reduced metabolism. Global gene expression profiling via RNA-Seq can provide important insights into the transcriptional mechanisms of photoperiodic diapause. The Asian tiger mosquito, Aedes albopictus, is an outstanding organism for studying the transcriptional bases of diapause due to its ease of rearing, easily induced diapause, and the genomic resources available. This manuscript presents a general experimental workflow for identifying diapause-induced transcriptional differences in A. albopictus. Rearing techniques, conditions necessary to induce diapause and non-diapause development, methods to estimate percent diapause in a population, and RNA extraction and integrity assessment for mosquitoes are documented. A workflow to process RNA-Seq data from Illumina sequencers culminates in a list of differentially expressed genes. The representative results demonstrate that this protocol can be used to effectively identify genes differentially regulated at the transcriptional level in A. albopictus due to photoperiodic differences. With modest adjustments, this workflow can be readily adapted to study the transcriptional bases of diapause or other important life history traits in other mosquitoes.
Genetics, Issue 93, Aedes albopictus Asian tiger mosquito, photoperiodic diapause, RNA-Seq de novo transcriptome assembly, mosquito husbandry
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
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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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An Investigation of the Effects of Sports-related Concussion in Youth Using Functional Magnetic Resonance Imaging and the Head Impact Telemetry System
Authors: Michelle Keightley, Stephanie Green, Nick Reed, Sabrina Agnihotri, Amy Wilkinson, Nancy Lobaugh.
Institutions: University of Toronto, University of Toronto, University of Toronto, Bloorview Kids Rehab, Toronto Rehab, Sunnybrook Health Sciences Centre, University of Toronto.
One of the most commonly reported injuries in children who participate in sports is concussion or mild traumatic brain injury (mTBI)1. Children and youth involved in organized sports such as competitive hockey are nearly six times more likely to suffer a severe concussion compared to children involved in other leisure physical activities2. While the most common cognitive sequelae of mTBI appear similar for children and adults, the recovery profile and breadth of consequences in children remains largely unknown2, as does the influence of pre-injury characteristics (e.g. gender) and injury details (e.g. magnitude and direction of impact) on long-term outcomes. Competitive sports, such as hockey, allow the rare opportunity to utilize a pre-post design to obtain pre-injury data before concussion occurs on youth characteristics and functioning and to relate this to outcome following injury. Our primary goals are to refine pediatric concussion diagnosis and management based on research evidence that is specific to children and youth. To do this we use new, multi-modal and integrative approaches that will: 1.Evaluate the immediate effects of head trauma in youth 2.Monitor the resolution of post-concussion symptoms (PCS) and cognitive performance during recovery 3.Utilize new methods to verify brain injury and recovery To achieve our goals, we have implemented the Head Impact Telemetry (HIT) System. (Simbex; Lebanon, NH, USA). This system equips commercially available Easton S9 hockey helmets (Easton-Bell Sports; Van Nuys, CA, USA) with single-axis accelerometers designed to measure real-time head accelerations during contact sport participation 3 - 5. By using telemetric technology, the magnitude of acceleration and location of all head impacts during sport participation can be objectively detected and recorded. We also use functional magnetic resonance imaging (fMRI) to localize and assess changes in neural activity specifically in the medial temporal and frontal lobes during the performance of cognitive tasks, since those are the cerebral regions most sensitive to concussive head injury 6. Finally, we are acquiring structural imaging data sensitive to damage in brain white matter.
Medicine, Issue 47, Mild traumatic brain injury, concussion, fMRI, youth, Head Impact Telemetry System
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A Protocol for Computer-Based Protein Structure and Function Prediction
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Institutions: University of Michigan , University of Kansas.
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.
Biochemistry, Issue 57, On-line server, I-TASSER, protein structure prediction, function prediction
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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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Mouse Short- and Long-term Locomotor Activity Analyzed by Video Tracking Software
Authors: Jason M. York, Neil A. Blevins, Leslie K. McNeil, Gregory G. Freund.
Institutions: University of Illinois at Urbana-Champaign, University of Illinois at Urbana-Champaign.
Locomotor activity (LMA) is a simple and easily performed measurement of behavior in mice and other rodents. Improvements in video tracking software (VTS) have allowed it to be coupled to LMA testing, dramatically improving specificity and sensitivity when compared to the line crossings method with manual scoring. In addition, VTS enables high-throughput experimentation. While similar to automated video tracking used for the open field test (OFT), LMA testing is unique in that it allows mice to remain in their home cage and does not utilize the anxiogenic stimulus of bright lighting during the active phase of the light-dark cycle. Traditionally, LMA has been used for short periods of time (mins), while longer movement studies (hrs-days) have often used implanted transmitters and biotelemetry. With the option of real-time tracking, long-, like short-term LMA testing, can now be conducted using videography. Long-term LMA testing requires a specialized, but easily constructed, cage so that food and water (which is usually positioned on the cage top) does not obstruct videography. Importantly, videography and VTS allows for the quantification of parameters, such as path of mouse movement, that are difficult or unfeasible to measure with line crossing and/or biotelemetry. In sum, LMA testing coupled to VTS affords a more complete description of mouse movement and the ability to examine locomotion over an extended period of time.
Neuroscience, Issue 76, Behavior, Neurobiology, Anatomy, Physiology, Psychology, Animal, Exploratory Behavior, Behavioral Research, Psychoneuroimmunology, Locomotion, Neuroimmune, high throughput, sickness behavior, noninvasive, video recording, imaging, animal model
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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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Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Authors: Evan D. Morris, Su Jin Kim, Jenna M. Sullivan, Shuo Wang, Marc D. Normandin, Cristian C. Constantinescu, Kelly P. Cosgrove.
Institutions: Yale University, Yale University, Yale University, Yale University, Massachusetts General Hospital, University of California, Irvine.
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized. We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8 that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7 to a conventional model 9. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
Behavior, Issue 78, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Medicine, Anatomy, Physiology, Image Processing, Computer-Assisted, Receptors, Dopamine, Dopamine, Functional Neuroimaging, Binding, Competitive, mathematical modeling (systems analysis), Neurotransmission, transient, dopamine release, PET, modeling, linear, time-invariant, smoking, F-test, ventral-striatum, clinical techniques
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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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Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model
Authors: Denise Lawrie, George Janossy, Maarten Roos, Deborah K. Glencross.
Institutions: National Health Laboratory Services (NHLS-SA), University of Witwatersrand, Lightcurve Films.
We present the video about assisting anti-retroviral therapy (ART) by an apt laboratory service - representing a South-African role model for economical large scale diagnostic testing. In the low-income countries inexpensive ART has transformed the prospects for the survival of HIV seropositive patients but there are doubts whether there is a need for the laboratory monitoring of ART and at what costs - in situations when the overall quality of pathology services can still be very low. The appropriate answer is to establish economically sound services with better coordination and stricter internal quality assessment than seen in western countries. This video, photographed at location in the National Health Laboratory Services (NHLS-SA) at the Witwatersrand University, Johannesburg, South Africa, provides such a coordinated scheme expanding the original 2-color CD4-CD45 PanLeucoGating strategy (PLG). Thus the six modules of the video presentation reveal the simplicity of a 4-color flow cytometric assay to combine haematological, immunological and virology-related tests in a single tube. These video modules are: (i) the set-up of instruments; (ii) sample preparations; (iii) testing absolute counts and monitoring quality for each sample by bead-count-rate; (iv) the heamatological CD45 test for white cell counts and differentials; (v) the CD4 counts, and (vi) the activation of CD8+ T cells measured by CD38 display, a viral load related parameter. The potential cost-savings are remarkable. This arrangement is a prime example for the feasibility of performing > 800-1000 tests per day with a stricter quality control than that applied in western laboratories, and also with a transfer of technology to other laboratories within a NHLS-SA network. Expert advisors, laboratory managers and policy makers who carry the duty of making decisions about introducing modern medical technology are frequently not in a position to see the latest technical details as carried out in the large regional laboratories with huge burdens of workload. Hence this video shows details of these new developments.
Immunology, Issue 44, Human Immunodeficiency virus (HIV); CD4 lymphocyte count, white cell count, CD45, panleucogating, lymphocyte activation, CD38, HIV viral load, antiretroviral therapy (ART), internal quality control
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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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High Density Event-related Potential Data Acquisition in Cognitive Neuroscience
Authors: Scott D. Slotnick.
Institutions: Boston College.
Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.
Neuroscience, Issue 38, ERP, electrodes, methods, setup
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Gibberella zeae Ascospore Production and Collection for Microarray Experiments.
Authors: Matias Pasquali, Corby Kistler.
Institutions: USDA, University of Minnesota/ Agroinnova, University of Torino, University of Minnesota.
Fusarium graminearum Schwabe (teleomorph Gibberella zeae) is a plant pathogen causing scab disease on wheat and barley that reduces crop yield and grain quality. F. graminearum also causes stalk and ear rots of maize and is a producer of mycotoxins such as the trichothecenes that contaminate grain and are harmful to humans and livestock (Goswami and Kistler, 2004). The fungus produces two types of spores. Ascospores, the propagules resulting from sexual reproduction, are the main source of primary infection. These spores are forcibly discharged from mature perithecia and dispersed by wind (Francl et al 1999). Secondary infections are mainly caused by macroconidia which are produced by asexual means on the plant surface. To study the developmental processes of ascospores in this fungus, a procedure for their collection in large quantity under sterile conditions was required. Our protocol was filmed in order to generate the highest level of information for understanding and reproducibility; crucial aspects when full genome gene expression profiles are generated and interpreted. In particular, the variability of ascospore germination and biological activity are dependent on the prior manipulation of the material. The use of video for documenting every step in ascospore production is proposed in order to increase standardization, complying with the increasingly stringent requirements for microarray analysis. The procedure requires only standard laboratory equipment. Steps are shown to prevent contamination and favor time synchronization of ascospores.
Plant Biology, Issue 1, sexual cross, spore separation, MIAME standards
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What is Visualize?

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.