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Pubmed Article
Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using QuickBird Images.
PUBLISHED: 05-18-2015
This paper proposes a supervised classification scheme to identify 40 tree species (2 coniferous, 38 broadleaf) belonging to 22 families and 36 genera in high spatial resolution QuickBird multispectral images (HMS). Overall kappa coefficient (OKC) and species conditional kappa coefficients (SCKC) were used to evaluate classification performance in training samples and estimate accuracy and uncertainty in test samples. Baseline classification performance using HMS images and vegetation index (VI) images were evaluated with an OKC value of 0.58 and 0.48 respectively, but performance improved significantly (up to 0.99) when used in combination with an HMS spectral-spatial texture image (SpecTex). One of the 40 species had very high conditional kappa coefficient performance (SCKC ? 0.95) using 4-band HMS and 5-band VIs images, but, only five species had lower performance (0.68 ? SCKC ? 0.94) using the SpecTex images. When SpecTex images were combined with a Visible Atmospherically Resistant Index (VARI), there was a significant improvement in performance in the training samples. The same level of improvement could not be replicated in the test samples indicating that a high degree of uncertainty exists in species classification accuracy which may be due to individual tree crown density, leaf greenness (inter-canopy gaps), and noise in the background environment (intra-canopy gaps). These factors increase uncertainty in the spectral texture features and therefore represent potential problems when using pixel-based classification techniques for multi-species classification.
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Published: 10-15-2014
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
24 Related JoVE Articles!
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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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Long-term Imaging Mammalian Cells using Wide-Field Microscopy
Authors: Meg Bentley, Randy King.
Institutions: Harvard Medical School.
Cellular Biology, Issue 1, imaging, tissue culture, screen
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Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling
Authors: Jennifer L Soong, Dan Reuss, Colin Pinney, Ty Boyack, Michelle L Haddix, Catherine E Stewart, M. Francesca Cotrufo.
Institutions: Colorado State University, USDA-ARS, Colorado State University.
Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes and soil organic matter formation to small-scale stable-isotope biomarker probing. Coupling multiple stable isotopes such as 13C with 15N, 18O or 2H has the potential to reveal even more information about complex stoichiometric relationships during biogeochemical transformations. Isotope labeled plant material has been used in various studies of litter decomposition and soil organic matter formation1-4. From these and other studies, however, it has become apparent that structural components of plant material behave differently than metabolic components (i.e. leachable low molecular weight compounds) in terms of microbial utilization and long-term carbon storage5-7. The ability to study structural and metabolic components separately provides a powerful new tool for advancing the forefront of ecosystem biogeochemical studies. Here we describe a method for producing 13C and 15N labeled plant material that is either uniformly labeled throughout the plant or differentially labeled in structural and metabolic plant components. Here, we present the construction and operation of a continuous 13C and 15N labeling chamber that can be modified to meet various research needs. Uniformly labeled plant material is produced by continuous labeling from seedling to harvest, while differential labeling is achieved by removing the growing plants from the chamber weeks prior to harvest. Representative results from growing Andropogon gerardii Kaw demonstrate the system's ability to efficiently label plant material at the targeted levels. Through this method we have produced plant material with a 4.4 atom%13C and 6.7 atom%15N uniform plant label, or material that is differentially labeled by up to 1.29 atom%13C and 0.56 atom%15N in its metabolic and structural components (hot water extractable and hot water residual components, respectively). Challenges lie in maintaining proper temperature, humidity, CO2 concentration, and light levels in an airtight 13C-CO2 atmosphere for successful plant production. This chamber description represents a useful research tool to effectively produce uniformly or differentially multi-isotope labeled plant material for use in experiments on ecosystem biogeochemical cycling.
Environmental Sciences, Issue 83, 13C, 15N, plant, stable isotope labeling, Andropogon gerardii, metabolic compounds, structural compounds, hot water extraction
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A Venturi Effect Can Help Cure Our Trees
Authors: Lucio Montecchio.
Institutions: Unversity of Padova.
In woody plants, xylem sap moves upwards through the vessels due to a decreasing gradient of water potential from the groundwater to the foliage. According to these factors and their dynamics, small amounts of sap-compatible liquids (i.e. pesticides) can be injected into the xylem system, reaching their target from inside. This endotherapic method, called "trunk injection" or "trunk infusion" (depending on whether the user supplies an external pressure or not), confines the applied chemicals only within the target tree, thereby making it particularly useful in urban situations. The main factors limiting wider use of the traditional drilling methods are related to negative side effects of the holes that must be drilled around the trunk circumference in order to gain access to the xylem vessels beneath the bark. The University of Padova (Italy) recently developed a manual, drill-free instrument with a small, perforated blade that enters the trunk by separating the woody fibers with minimal friction. Furthermore, the lenticular shaped blade reduces the vessels' cross section, increasing sap velocity and allowing the natural uptake of an external liquid up to the leaves, when transpiration rate is substantial. Ports partially close soon after the removal of the blade due to the natural elasticity and turgidity of the plant tissues, and the cambial activity completes the healing process in few weeks.
Environmental Sciences, Issue 80, Trunk injection, systemic injection, xylematic injection, endotherapy, sap flow, Bernoulli principle, plant diseases, pesticides, desiccants
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Transcript and Metabolite Profiling for the Evaluation of Tobacco Tree and Poplar as Feedstock for the Bio-based Industry
Authors: Colin Ruprecht, Takayuki Tohge, Alisdair Fernie, Cara L. Mortimer, Amanda Kozlo, Paul D. Fraser, Norma Funke, Igor Cesarino, Ruben Vanholme, Wout Boerjan, Kris Morreel, Ingo Burgert, Notburga Gierlinger, Vincent Bulone, Vera Schneider, Andrea Stockero, Juan Navarro-Aviñó, Frank Pudel, Bart Tambuyser, James Hygate, Jon Bumstead, Louis Notley, Staffan Persson.
Institutions: Max Planck Institute for Molecular Plant Physiology, Royal Holloway, University of London, VIB, UGhent, ETH Zurich, EMPA, Royal Institute of Technology (KTH), European Research and Project Office GmbH, ABBA Gaia S.L., Pflanzenöltechnologie, Capax Environmental Services, Green Fuels, Neutral Consulting Ltd, University of Melbourne.
The global demand for food, feed, energy, and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.
Environmental Sciences, Issue 87, botany, plants, Biorefining, Poplar, Tobacco tree, Arabidopsis, suberin, lignin, cell walls, biomass, long-chain hydrocarbons, isoprenoids, Nicotiana glauca, systems biology
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A Technique to Screen American Beech for Resistance to the Beech Scale Insect (Cryptococcus fagisuga Lind.)
Authors: Jennifer L. Koch, David W. Carey.
Institutions: US Forest Service.
Beech bark disease (BBD) results in high levels of initial mortality, leaving behind survivor trees that are greatly weakened and deformed. The disease is initiated by feeding activities of the invasive beech scale insect, Cryptococcus fagisuga, which creates entry points for infection by one of the Neonectria species of fungus. Without scale infestation, there is little opportunity for fungal infection. Using scale eggs to artificially infest healthy trees in heavily BBD impacted stands demonstrated that these trees were resistant to the scale insect portion of the disease complex1. Here we present a protocol that we have developed, based on the artificial infestation technique by Houston2, which can be used to screen for scale-resistant trees in the field and in smaller potted seedlings and grafts. The identification of scale-resistant trees is an important component of management of BBD through tree improvement programs and silvicultural manipulation.
Environmental Sciences, Issue 87, Forestry, Insects, Disease Resistance, American beech, Fagus grandifolia, beech scale, Cryptococcus fagisuga, resistance, screen, bioassay
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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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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
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High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
Authors: Hari Sreedhar, Vishal K. Varma, Peter L. Nguyen, Bennett Davidson, Sanjeev Akkina, Grace Guzman, Suman Setty, Andre Kajdacsy-Balla, Michael J. Walsh.
Institutions: University of Illinois at Chicago, University of Illinois at Chicago, University of Illinois at Chicago, University of Illinois at Chicago, University of Illinois at Chicago.
High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis.
Medicine, Issue 95, Spectroscopy, Imaging, Fourier Transform, Pathology, Cancer, Liver, Kidney, Hyperspectral, Biopsy, Infrared, Optics, Tissue
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A Technical Perspective in Modern Tree-ring Research - How to Overcome Dendroecological and Wood Anatomical Challenges
Authors: Holger Gärtner, Paolo Cherubini, Patrick Fonti, Georg von Arx, Loïc Schneider, Daniel Nievergelt, Anne Verstege, Alexander Bast, Fritz H. Schweingruber, Ulf Büntgen.
Institutions: Swiss Federal Research Institute WSL.
Dendroecological research uses information stored in tree rings to understand how single trees and even entire forest ecosystems responded to environmental changes and to finally reconstruct such changes. This is done by analyzing growth variations back in time and correlating various plant-specific parameters to (for example) temperature records. Integrating wood anatomical parameters in these analyses would strengthen reconstructions, even down to intra-annual resolution. We therefore present a protocol on how to sample, prepare, and analyze wooden specimen for common macroscopic analyses, but also for subsequent microscopic analyses. Furthermore we introduce a potential solution for analyzing digital images generated from common small and large specimens to support time-series analyses. The protocol presents the basic steps as they currently can be used. Beyond this, there is an ongoing need for the improvement of existing techniques, and development of new techniques, to record and quantify past and ongoing environmental processes. Traditional wood anatomical research needs to be expanded to include ecological information to this field of research. This would support dendro-scientists who intend to analyze new parameters and develop new methodologies to understand the short and long term effects of specific environmental factors on the anatomy of woody plants.
Environmental Sciences, Issue 97, Cell parameters, dendroecology, image analysis, micro sectioning, microtomes, sample preparation, wood anatomy
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The Use of High-resolution Infrared Thermography (HRIT) for the Study of Ice Nucleation and Ice Propagation in Plants
Authors: Michael Wisniewski, Gilbert Neuner, Lawrence V. Gusta.
Institutions: Agricultural Research Service (USDA-ARS), Kearneysville, WV, University of Innsbruck, University of Saskatechewan.
Freezing events that occur when plants are actively growing can be a lethal event, particularly if the plant has no freezing tolerance. Such frost events often have devastating effects on agricultural production and can also play an important role in shaping community structure in natural populations of plants, especially in alpine, sub-arctic, and arctic ecosystems. Therefore, a better understanding of the freezing process in plants can play an important role in the development of methods of frost protection and understanding mechanisms of freeze avoidance. Here, we describe a protocol to visualize the freezing process in plants using high-resolution infrared thermography (HRIT). The use of this technology allows one to determine the primary sites of ice formation in plants, how ice propagates, and the presence of ice barriers. Furthermore, it allows one to examine the role of extrinsic and intrinsic nucleators in determining the temperature at which plants freeze and evaluate the ability of various compounds to either affect the freezing process or increase freezing tolerance. The use of HRIT allows one to visualize the many adaptations that have evolved in plants, which directly or indirectly impact the freezing process and ultimately enables plants to survive frost events.
Environmental Sciences, Issue 99, Freeze avoidance, supercooling, ice nucleation active bacteria, frost tolerance, ice crystallization, antifreeze proteins, intrinsic nucleation, extrinsic nucleation, heterogeneous nucleation, homogeneous nucleation, differential thermal analysis
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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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Technique for Studying Arthropod and Microbial Communities within Tree Tissues
Authors: Nicholas C Aflitto, Richard W Hofstetter, Reagan McGuire, David D Dunn, Kristen A Potter.
Institutions: Northern Arizona University, Acoustic Ecology Institute.
Phloem tissues of pine are habitats for many thousands of organisms. Arthropods and microbes use phloem and cambium tissues to seek mates, lay eggs, rear young, feed, or hide from natural enemies or harsh environmental conditions outside of the tree. Organisms that persist within the phloem habitat are difficult to observe given their location under bark. We provide a technique to preserve intact phloem and prepare it for experimentation with invertebrates and microorganisms. The apparatus is called a ‘phloem sandwich’ and allows for the introduction and observation of arthropods, microbes, and other organisms. This technique has resulted in a better understanding of the feeding behaviors, life-history traits, reproduction, development, and interactions of organisms within tree phloem. The strengths of this technique include the use of inexpensive materials, variability in sandwich size, flexibility to re-open the sandwich or introduce multiple organisms through drilled holes, and the preservation and maintenance of phloem integrity. The phloem sandwich is an excellent educational tool for scientific discovery in both K-12 science courses and university research laboratories.
Environmental Sciences, Issue 93, phloem sandwich, pine, bark beetles, mites, acoustics, phloem
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PDMS Device Fabrication and Surface Modification
Authors: Kenneth Kotz, Xuanhong Cheng, Mehmet Toner.
Institutions: MGH - Massachusetts General Hospital.
Cellular Biology, Issue 8, microfluidics, diagnostics, Bioengineering
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Cell Capture Using a Microfluidic Device
Authors: Kenneth Kotz, Xuanhong Cheng, Mehmet Toner.
Institutions: MGH - Massachusetts General Hospital.
Cellular Biology, Issue 8, microfluidics, cell isolation, diagnostics, Bioengineering
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Development of New Therapeutic Applications Using Microfluidics
Authors: Mehmet Toner.
Institutions: MGH - Massachusetts General Hospital.
Cellular Biology, Issue 8, Microfluidics, Translational Research, Diagnostics, Bioengineering
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Non-radioactive in situ Hybridization Protocol Applicable for Norway Spruce and a Range of Plant Species
Authors: Anna Karlgren, Jenny Carlsson, Niclas Gyllenstrand, Ulf Lagercrantz, Jens F. Sundström.
Institutions: Uppsala University, Swedish University of Agricultural Sciences.
The high-throughput expression analysis technologies available today give scientists an overflow of expression profiles but their resolution in terms of tissue specific expression is limited because of problems in dissecting individual tissues. Expression data needs to be confirmed and complemented with expression patterns using e.g. in situ hybridization, a technique used to localize cell specific mRNA expression. The in situ hybridization method is laborious, time-consuming and often requires extensive optimization depending on species and tissue. In situ experiments are relatively more difficult to perform in woody species such as the conifer Norway spruce (Picea abies). Here we present a modified DIG in situ hybridization protocol, which is fast and applicable on a wide range of plant species including P. abies. With just a few adjustments, including altered RNase treatment and proteinase K concentration, we could use the protocol to study tissue specific expression of homologous genes in male reproductive organs of one gymnosperm and two angiosperm species; P. abies, Arabidopsis thaliana and Brassica napus. The protocol worked equally well for the species and genes studied. AtAP3 and BnAP3 were observed in second and third whorl floral organs in A. thaliana and B. napus and DAL13 in microsporophylls of male cones from P. abies. For P. abies the proteinase K concentration, used to permeablize the tissues, had to be increased to 3 g/ml instead of 1 g/ml, possibly due to more compact tissues and higher levels of phenolics and polysaccharides. For all species the RNase treatment was removed due to reduced signal strength without a corresponding increase in specificity. By comparing tissue specific expression patterns of homologous genes from both flowering plants and a coniferous tree we demonstrate that the DIG in situ protocol presented here, with only minute adjustments, can be applied to a wide range of plant species. Hence, the protocol avoids both extensive species specific optimization and the laborious use of radioactively labeled probes in favor of DIG labeled probes. We have chosen to illustrate the technically demanding steps of the protocol in our film. Anna Karlgren and Jenny Carlsson contributed equally to this study. Corresponding authors: Anna Karlgren at and Jens F. Sundström at
Plant Biology, Issue 26, RNA, expression analysis, Norway spruce, Arabidopsis, rapeseed, conifers
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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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Multiplexed Fluorometric ImmunoAssay Testing Methodology and Troubleshooting
Authors: Michelle L. Wunderlich, Megan E. Dodge, Rajeev K. Dhawan, William R. Shek.
Institutions: Charles River .
To ensure the quality of animal models used in biomedical research we have developed a number of diagnostic testing strategies and methods to determine if animals have been exposed to adventitious infectious agents (viruses, mycoplasma, and other fastidious microorganisms). Infections of immunocompetent animals are generally transient, yet serum antibody responses to infection often can be detected within days to weeks and persist throughout the life of the host. Serology is the primary diagnostic methodology by which laboratory animals are monitored. Historically the indirect enzyme-linked immunosorbent assay (ELISA) has been the main screening method for serosurveillance. The ELISA is performed as a singleplex, in which one microbial antigen-antibody reaction is measured per well. In comparison the MFIA is performed as a multiplexed assay. Since the microspheres come in 100 distinct color sets, as many as 100 different assays can be performed simultaneously in a single microplate well. This innovation decreases the amount of serum, reagents and disposables required for routine testing while increasing the amount of information obtained from a single test well. In addition, we are able to incorporate multiple internal control beads to verify sample and system suitability and thereby assure the accuracy of results. These include tissue control and IgG anti-test serum species immunoglobulin (αIg) coated bead sets to evaluate sample suitability. As in the ELISA and IFA, the tissue control detects non-specific binding of serum immunoglobulin. The αIg control (Serum control) confirms that serum has been added and contains a sufficient immunoglobulin concentration while the IgG control bead (System Suitability control), coated with serum species immunoglobulin, demonstrates that the labeled reagents and Luminex reader are functioning properly.
Basic Protocols, Issue 58, Multiplexed Fluorometric ImmunoAssay, MFIA, bead, serum, BAG, SPE, aggregate, microarray
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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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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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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Morris Water Maze Test: Optimization for Mouse Strain and Testing Environment
Authors: Daniel S. Weitzner, Elizabeth B. Engler-Chiurazzi, Linda A. Kotilinek, Karen Hsiao Ashe, Miranda Nicole Reed.
Institutions: West Virginia University, West Virginia University, N. Bud Grossman Center for Memory Research and Care, University of Minnesota, N. Bud Grossman Center for Memory Research and Care, University of Minnesota, GRECC, VA Medical Center, West Virginia University.
The Morris water maze (MWM) is a commonly used task to assess hippocampal-dependent spatial learning and memory in transgenic mouse models of disease, including neurocognitive disorders such as Alzheimer’s disease. However, the background strain of the mouse model used can have a substantial effect on the observed behavioral phenotype, with some strains exhibiting superior learning ability relative to others. To ensure differences between transgene negative and transgene positive mice can be detected, identification of a training procedure sensitive to the background strain is essential. Failure to tailor the MWM protocol to the background strain of the mouse model may lead to under- or over- training, thereby masking group differences in probe trials. Here, a MWM protocol tailored for use with the F1 FVB/N x 129S6 background is described. This is a frequently used background strain to study the age-dependent effects of mutant P301L tau (rTg(TauP301L)4510 mice) on the memory deficits associated with Alzheimer’s disease. Also described is a strategy to re-optimize, as dictated by the particular testing environment utilized.
Behavior, Issue 100, Spatial learning, spatial reference memory, Morris water maze, Alzheimer’s disease, behavior, tau, hippocampal-dependent learning, rTg4510, Tg2576, strain background, transgenic mouse models
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