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Pubmed Article
The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures.
PUBLISHED: 07-11-2011
Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statistical viewpoint, but surprisingly few studies have investigated the relative strengths and weaknesses of the plethora of existing feature selection methods. In this study we compare 32 feature selection methods on 4 public gene expression datasets for breast cancer prognosis, in terms of predictive performance, stability and functional interpretability of the signatures they produce. We observe that the feature selection method has a significant influence on the accuracy, stability and interpretability of signatures. Surprisingly, complex wrapper and embedded methods generally do not outperform simple univariate feature selection methods, and ensemble feature selection has generally no positive effect. Overall a simple Students t-test seems to provide the best results.
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Published: 08-13-2014
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.
25 Related JoVE Articles!
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Irrelevant Stimuli and Action Control: Analyzing the Influence of Ignored Stimuli via the Distractor-Response Binding Paradigm
Authors: Birte Moeller, Hartmut Schächinger, Christian Frings.
Institutions: Trier University, Trier University.
Selection tasks in which simple stimuli (e.g. letters) are presented and a target stimulus has to be selected against one or more distractor stimuli are frequently used in the research on human action control. One important question in these settings is how distractor stimuli, competing with the target stimulus for a response, influence actions. The distractor-response binding paradigm can be used to investigate this influence. It is particular useful to separately analyze response retrieval and distractor inhibition effects. Computer-based experiments are used to collect the data (reaction times and error rates). In a number of sequentially presented pairs of stimulus arrays (prime-probe design), participants respond to targets while ignoring distractor stimuli. Importantly, the factors response relation in the arrays of each pair (repetition vs. change) and distractor relation (repetition vs. change) are varied orthogonally. The repetition of the same distractor then has a different effect depending on response relation (repetition vs. change) between arrays. This result pattern can be explained by response retrieval due to distractor repetition. In addition, distractor inhibition effects are indicated by a general advantage due to distractor repetition. The described paradigm has proven useful to determine relevant parameters for response retrieval effects on human action.
Behavior, Issue 87, stimulus-response binding, distractor-response binding, response retrieval, distractor inhibition, event file, action control, selection task
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Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Authors: Dana Faratian, Jason Christiansen, Mark Gustavson, Christine Jones, Christopher Scott, InHwa Um, David J. Harrison.
Institutions: University of Edinburgh, HistoRx Inc..
Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ. We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7. To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.
Medicine, Issue 56, quantitative immunofluorescence, heterogeneity, cancer, biomarker, targeted therapy, immunohistochemistry, proteomics, histopathology
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Development of a Negative Selectable Marker for Entamoeba histolytica
Authors: Mayuresh M Abhyankar, Sarah M Haviland, Carol A Gilchrist, William A Petri, Jr..
Institutions: University of Virginia Health System.
Entamoeba histolytica is the causative agent of amebiasis and infects up to 10% of the world's population. The molecular techniques that have enabled the up- and down-regulation of gene expression rely on the transfection of stably maintained plasmids. While these have increased our understanding of Entamoeba virulence factors, the capacity to integrate exogenous DNA into genome, which would allow reverse genetics experiments, would be a significant advantage in the study of this parasite. The challenges presented by this organism include inability to select for homologous recombination events and difficulty to cure episomal plasmid DNA from transfected trophozoites. The later results in a high background of exogenous DNA, a major problem in the identification of trophozoites in which a bona fide genomic integration event has occurred. We report the development of a negative selection system based upon transgenic expression of a yeast cytosine deaminase and uracil phosphoribosyl transferase chimera (FCU1) and selection with prodrug 5-fluorocytosine (5-FC). The FCU1 enzyme converts non-toxic 5-FC into toxic 5-fluorouracil and 5-fluorouridine-5'-monophosphate. E. histolytica lines expressing FCU1 were found to be 30 fold more sensitive to the prodrug compared to the control strain.
Infectious Disease, Issue 46, Entamoeba, negative selectable marker, 5-fluorocytosine, gene knockout, Cytosine deaminase, UPRT CMFDA.
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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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Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
Authors: Andreas Ender, Albert Mehl.
Institutions: University of Zürich.
Reference scanners are used in dental medicine to verify a lot of procedures. The main interest is to verify impression methods as they serve as a base for dental restorations. The current limitation of many reference scanners is the lack of accuracy scanning large objects like full dental arches, or the limited possibility to assess detailed tooth surfaces. A new reference scanner, based on focus variation scanning technique, was evaluated with regards to highest local and general accuracy. A specific scanning protocol was tested to scan original tooth surface from dental impressions. Also, different model materials were verified. The results showed a high scanning accuracy of the reference scanner with a mean deviation of 5.3 ± 1.1 µm for trueness and 1.6 ± 0.6 µm for precision in case of full arch scans. Current dental impression methods showed much higher deviations (trueness: 20.4 ± 2.2 µm, precision: 12.5 ± 2.5 µm) than the internal scanning accuracy of the reference scanner. Smaller objects like single tooth surface can be scanned with an even higher accuracy, enabling the system to assess erosive and abrasive tooth surface loss. The reference scanner can be used to measure differences for a lot of dental research fields. The different magnification levels combined with a high local and general accuracy can be used to assess changes of single teeth or restorations up to full arch changes.
Medicine, Issue 86, Laboratories, Dental, Calibration, Technology, Dental impression, Accuracy, Trueness, Precision, Full arch scan, Abrasion
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Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
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In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions
Authors: Grant E. Johnson, K. Don Dasitha Gunaratne, Julia Laskin.
Institutions: Pacific Northwest National Laboratory.
Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+ (bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.
Chemistry, Issue 88, soft landing, mass selected ions, electrospray, secondary ion mass spectrometry, infrared spectroscopy, organometallic, catalysis
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Analysis of Targeted Viral Protein Nanoparticles Delivered to HER2+ Tumors
Authors: Jae Youn Hwang, Daniel L. Farkas, Lali K. Medina-Kauwe.
Institutions: University of Southern California, Cedars-Sinai Medical Center, University of California, Los Angeles.
The HER2+ tumor-targeted nanoparticle, HerDox, exhibits tumor-preferential accumulation and tumor-growth ablation in an animal model of HER2+ cancer. HerDox is formed by non-covalent self-assembly of a tumor targeted cell penetration protein with the chemotherapy agent, doxorubicin, via a small nucleic acid linker. A combination of electrophilic, intercalation, and oligomerization interactions facilitate self-assembly into round 10-20 nm particles. HerDox exhibits stability in blood as well as in extended storage at different temperatures. Systemic delivery of HerDox in tumor-bearing mice results in tumor-cell death with no detectable adverse effects to non-tumor tissue, including the heart and liver (which undergo marked damage by untargeted doxorubicin). HER2 elevation facilitates targeting to cells expressing the human epidermal growth factor receptor, hence tumors displaying elevated HER2 levels exhibit greater accumulation of HerDox compared to cells expressing lower levels, both in vitro and in vivo. Fluorescence intensity imaging combined with in situ confocal and spectral analysis has allowed us to verify in vivo tumor targeting and tumor cell penetration of HerDox after systemic delivery. Here we detail our methods for assessing tumor targeting via multimode imaging after systemic delivery.
Biomedical Engineering, Issue 76, Cancer Biology, Medicine, Bioengineering, Molecular Biology, Cellular Biology, Biochemistry, Nanotechnology, Nanomedicine, Drug Delivery Systems, Molecular Imaging, optical imaging devices (design and techniques), HerDox, Nanoparticle, Tumor, Targeting, Self-Assembly, Doxorubicin, Human Epidermal Growth Factor, HER, HER2+, Receptor, mice, animal model, tumors, imaging
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SIVQ-LCM Protocol for the ArcturusXT Instrument
Authors: Jason D. Hipp, Jerome Cheng, Jeffrey C. Hanson, Avi Z. Rosenberg, Michael R. Emmert-Buck, Michael A. Tangrea, Ulysses J. Balis.
Institutions: National Institutes of Health, University of Michigan.
SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process. It aims to create an advanced, rapidly customizable laser dissection platform technology. In this report, we describe the integration of the image analysis software Spatially Invariant Vector Quantization (SIVQ) onto the ArcturusXT instrument. The ArcturusXT system contains both an infrared (IR) and ultraviolet (UV) laser, allowing for specific cell or large area dissections. The principal goal is to improve the speed, accuracy, and reproducibility of the laser dissection to increase sample throughput. This novel approach facilitates microdissection of both animal and human tissues in research and clinical workflows.
Bioengineering, Issue 89, SIVQ, LCM, personalized medicine, digital pathology, image analysis, ArcturusXT
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Aseptic Laboratory Techniques: Plating Methods
Authors: Erin R. Sanders.
Institutions: University of California, Los Angeles .
Microorganisms are present on all inanimate surfaces creating ubiquitous sources of possible contamination in the laboratory. Experimental success relies on the ability of a scientist to sterilize work surfaces and equipment as well as prevent contact of sterile instruments and solutions with non-sterile surfaces. Here we present the steps for several plating methods routinely used in the laboratory to isolate, propagate, or enumerate microorganisms such as bacteria and phage. All five methods incorporate aseptic technique, or procedures that maintain the sterility of experimental materials. Procedures described include (1) streak-plating bacterial cultures to isolate single colonies, (2) pour-plating and (3) spread-plating to enumerate viable bacterial colonies, (4) soft agar overlays to isolate phage and enumerate plaques, and (5) replica-plating to transfer cells from one plate to another in an identical spatial pattern. These procedures can be performed at the laboratory bench, provided they involve non-pathogenic strains of microorganisms (Biosafety Level 1, BSL-1). If working with BSL-2 organisms, then these manipulations must take place in a biosafety cabinet. Consult the most current edition of the Biosafety in Microbiological and Biomedical Laboratories (BMBL) as well as Material Safety Data Sheets (MSDS) for Infectious Substances to determine the biohazard classification as well as the safety precautions and containment facilities required for the microorganism in question. Bacterial strains and phage stocks can be obtained from research investigators, companies, and collections maintained by particular organizations such as the American Type Culture Collection (ATCC). It is recommended that non-pathogenic strains be used when learning the various plating methods. By following the procedures described in this protocol, students should be able to: ● Perform plating procedures without contaminating media. ● Isolate single bacterial colonies by the streak-plating method. ● Use pour-plating and spread-plating methods to determine the concentration of bacteria. ● Perform soft agar overlays when working with phage. ● Transfer bacterial cells from one plate to another using the replica-plating procedure. ● Given an experimental task, select the appropriate plating method.
Basic Protocols, Issue 63, Streak plates, pour plates, soft agar overlays, spread plates, replica plates, bacteria, colonies, phage, plaques, dilutions
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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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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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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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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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Test Samples for Optimizing STORM Super-Resolution Microscopy
Authors: Daniel J. Metcalf, Rebecca Edwards, Neelam Kumarswami, Alex E. Knight.
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
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Rapid and Low-cost Prototyping of Medical Devices Using 3D Printed Molds for Liquid Injection Molding
Authors: Philip Chung, J. Alex Heller, Mozziyar Etemadi, Paige E. Ottoson, Jonathan A. Liu, Larry Rand, Shuvo Roy.
Institutions: University of California, San Francisco, University of California, San Francisco, University of Southern California.
Biologically inert elastomers such as silicone are favorable materials for medical device fabrication, but forming and curing these elastomers using traditional liquid injection molding processes can be an expensive process due to tooling and equipment costs. As a result, it has traditionally been impractical to use liquid injection molding for low-cost, rapid prototyping applications. We have devised a method for rapid and low-cost production of liquid elastomer injection molded devices that utilizes fused deposition modeling 3D printers for mold design and a modified desiccator as an injection system. Low costs and rapid turnaround time in this technique lower the barrier to iteratively designing and prototyping complex elastomer devices. Furthermore, CAD models developed in this process can be later adapted for metal mold tooling design, enabling an easy transition to a traditional injection molding process. We have used this technique to manufacture intravaginal probes involving complex geometries, as well as overmolding over metal parts, using tools commonly available within an academic research laboratory. However, this technique can be easily adapted to create liquid injection molded devices for many other applications.
Bioengineering, Issue 88, liquid injection molding, reaction injection molding, molds, 3D printing, fused deposition modeling, rapid prototyping, medical devices, low cost, low volume, rapid turnaround time.
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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Setting Limits on Supersymmetry Using Simplified Models
Authors: Christian Gütschow, Zachary Marshall.
Institutions: University College London, CERN, Lawrence Berkeley National Laboratories.
Experimental limits on supersymmetry and similar theories are difficult to set because of the enormous available parameter space and difficult to generalize because of the complexity of single points. Therefore, more phenomenological, simplified models are becoming popular for setting experimental limits, as they have clearer physical interpretations. The use of these simplified model limits to set a real limit on a concrete theory has not, however, been demonstrated. This paper recasts simplified model limits into limits on a specific and complete supersymmetry model, minimal supergravity. Limits obtained under various physical assumptions are comparable to those produced by directed searches. A prescription is provided for calculating conservative and aggressive limits on additional theories. Using acceptance and efficiency tables along with the expected and observed numbers of events in various signal regions, LHC experimental results can be recast in this manner into almost any theoretical framework, including nonsupersymmetric theories with supersymmetry-like signatures.
Physics, Issue 81, high energy physics, particle physics, Supersymmetry, LHC, ATLAS, CMS, New Physics Limits, Simplified Models
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Isolation of CD4+ T cells from Mouse Lymph Nodes Using Miltenyi MACS Purification
Authors: Melanie P. Matheu, Michael D. Cahalan.
Institutions: University of California, Irvine (UCI).
Isolation of cells from the primary source is a necessary step in many more complex protocols. Miltenyi offers kits to isolate cells from several organisms including humans, non-human primates, rat and, as we describe here, mice. Magnetic bead-based cell separation allows for either positive selection (or cell depletion) as well as negative selection. Here, we demonstrate negative selection of untouched or na ve CD4+ helper T cells. Using this standard protocol we typically purify cells that are ≥ 96% pure CD4+/CD3+. This protocol is used in conjunction with the protocol Dissection and 2-Photon Imaging of Peripheral Lymph Nodes in Mice published in issue 7 of JoVE, for purification of T cells and other cell types to adoptively transfer for imaging purposes. Although we did not demonstrate FACS analysis in this protocol video, it is highly recommended to check the overall purity of isolated cells using the appropriate antibodies via FACS. In addition, we demonstrate the non-sterile method of T cell isolation. If sterile cells are needed for your particular end-user application, be sure to do all of the demonstrated procedures in the tissue culture hood under standard sterile conditions. Thank you for watching and good luck with your own experiments!
Immunology, Issue 9, Cell isolation, Cell separation, T cells, Purification, Mouse, Lymphocyte, Purification, Miltenyi, MACS kit,
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Preparation of 2-dGuo-Treated Thymus Organ Cultures
Authors: William Jenkinson, Eric Jenkinson, Graham Anderson.
Institutions: University of Birmingham .
In the thymus, interactions between developing T-cell precursors and stromal cells that include cortical and medullary epithelial cells are known to play a key role in the development of a functionally competent T-cell pool. However, the complexity of T-cell development in the thymus in vivo can limit analysis of individual cellular components and particular stages of development. In vitro culture systems provide a readily accessible means to study multiple complex cellular processes. Thymus organ culture systems represent a widely used approach to study intrathymic development of T-cells under defined conditions in vitro. Here we describe a system in which mouse embryonic thymus lobes can be depleted of endogenous haemopoeitic elements by prior organ culture in 2-deoxyguanosine, a compound that is selectively toxic to haemopoeitic cells. As well as providing a readily accessible source of thymic stromal cells to investigate the role of thymic microenvironments in the development and selection of T-cells, this technique also underpins further experimental approaches that include the reconstitution of alymphoid thymus lobes in vitro with defined haemopoietic elements, the transplantation of alymphoid thymuses into recipient mice, and the formation of reaggregate thymus organ cultures. (This article is based on work first reported Methods in Molecular Biology 2007, Vol. 380 pages 185-196).
Immunology, Issue 18, Springer Protocols, Thymus, 2-dGuo, Thymus Organ Cultures, Immune Tolerance, Positive and Negative Selection, Lymphoid Development
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Reaggregate Thymus Cultures
Authors: Andrea White, Eric Jenkinson, Graham Anderson.
Institutions: University of Birmingham .
Stromal cells within lymphoid tissues are organized into three-dimensional structures that provide a scaffold that is thought to control the migration and development of haemopoeitic cells. Importantly, the maintenance of this three-dimensional organization appears to be critical for normal stromal cell function, with two-dimensional monolayer cultures often being shown to be capable of supporting only individual fragments of lymphoid tissue function. In the thymus, complex networks of cortical and medullary epithelial cells act as a framework that controls the recruitment, proliferation, differentiation and survival of lymphoid progenitors as they undergo the multi-stage process of intrathymic T-cell development. Understanding the functional role of individual stromal compartments in the thymus is essential in determining how the thymus imposes self/non-self discrimination. Here we describe a technique in which we exploit the plasticity of fetal tissues to re-associate into intact three-dimensional structures in vitro, following their enzymatic disaggregation. The dissociation of fetal thymus lobes into heterogeneous cellular mixtures, followed by their separation into individual cellular components, is then combined with the in vitro re-association of these desired cell types into three-dimensional reaggregate structures at defined ratios, thereby providing an opportunity to investigate particular aspects of T-cell development under defined cellular conditions. (This article is based on work first reported Methods in Molecular Biology 2007, Vol. 380 pages 185-196).
Immunology, Issue 18, Springer Protocols, Thymus, 2-dGuo, Thymus Organ Cultures, Immune Tolerance, Positive and Negative Selection, Lymphoid Development
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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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Enrichment of NK Cells from Human Blood with the RosetteSep Kit from StemCell Technologies
Authors: Christine Beeton, K. George Chandy.
Institutions: University of California, Irvine (UCI).
Natural killer (NK) cells are large granular cytotoxic lymphocytes that belong to the innate immune system and play major roles in fighting against cancer and infections, but are also implicated in the early stages of pregnancy and transplant rejection. These cells are present in peripheral blood, from which they can be isolated. Cells can be isolated using either positive or negative selection. For positive selection we use antibodies directed to a surface marker present only on the cells of interest whereas for negative selection we use cocktails of antibodies targeted to surface markers present on all cells but the cells of interest. This latter technique presents the advantage of leaving the cells of interest free of antibodies, thereby reducing the risk of unwanted cell activation or differenciation. In this video-protocol we demonstrate how to separate NK cells from human blood by negative selection, using the RosetteSep kit from StemCell technologies. The procedure involves obtaining human peripheral blood (under an institutional review board-approved protocol to protect the human subjects) and mixing it with a cocktail of antibodies that will bind to markers absent on NK cells, but present on all other mononuclear cells present in peripheral blood (e.g., T lymphocytes, monocytes...). The antibodies present in the cocktail are conjugated to antibodies directed to glycophorin A on erythrocytes. All unwanted cells and red blood cells will therefore be trapped in complexes. The mix of blood and antibody cocktail is then diluted, overlayed on a Histopaque gradient, and centrifuged. NK cells (>80% pure) can be collected at the interface between the Histopaque and the diluted plasma. Similar cocktails are available for enrichment of other cell populations, such as human T lymphocytes.
Immunology, issue 8, blood, cell isolation, natural killer, lymphocyte, primary cells, negative selection, PBMC, Ficoll gradient, cell separation
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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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Concentration Determination of Nucleic Acids and Proteins Using the Micro-volume Bio-spec Nano Spectrophotometer
Authors: Suja Sukumaran.
Institutions: Scientific Instruments.
Nucleic Acid quantitation procedures have advanced significantly in the last three decades. More and more, molecular biologists require consistent small-volume analysis of nucleic acid samples for their experiments. The BioSpec-nano provides a potential solution to the problems of inaccurate, non-reproducible results, inherent in current DNA quantitation methods, via specialized optics and a sensitive PDA detector. The BioSpec-nano also has automated functionality such that mounting, measurement, and cleaning are done by the instrument, thereby eliminating tedious, repetitive, and inconsistent placement of the fiber optic element and manual cleaning. In this study, data is presented on the quantification of DNA and protein, as well as on measurement reproducibility and accuracy. Automated sample contact and rapid scanning allows measurement in three seconds, resulting in excellent throughput. Data analysis is carried out using the built-in features of the software. The formula used for calculating DNA concentration is: Sample Concentration = DF · (OD260-OD320)· NACF (1) Where DF = sample dilution factor and NACF = nucleic acid concentration factor. The Nucleic Acid concentration factor is set in accordance with the analyte selected1. Protein concentration results can be expressed as μg/ mL or as moles/L by entering e280 and molecular weight values respectively. When residue values for Tyr, Trp and Cysteine (S-S bond) are entered in the e280Calc tab, the extinction coefficient values are calculated as e280 = 5500 x (Trp residues) + 1490 x (Tyr residues) + 125 x (cysteine S-S bond). The e280 value is used by the software for concentration calculation. In addition to concentration determination of nucleic acids and protein, the BioSpec-nano can be used as an ultra micro-volume spectrophotometer for many other analytes or as a standard spectrophotometer using 5 mm pathlength cells.
Molecular Biology, Issue 48, Nucleic acid quantitation, protein quantitation, micro-volume analysis, label quantitation
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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