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Pubmed Article
The spatial limitations of current neutral models of biodiversity.
PLoS ONE
PUBLISHED: 02-01-2011
The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional) to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a fat-tailed distribution). Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit models simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.
Authors: Nicholas L. Balderston, Douglas H. Schultz, Sylvain Baillet, Fred J. Helmstetter.
Published: 06-03-2013
ABSTRACT
In trace fear conditioning a conditional stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS), which is presented after a brief stimulus free period (trace interval)1. Because the CS and UCS do not co-occur temporally, the subject must maintain a representation of that CS during the trace interval. In humans, this type of learning requires awareness of the stimulus contingencies in order to bridge the trace interval2-4. However when a face is used as a CS, subjects can implicitly learn to fear the face even in the absence of explicit awareness*. This suggests that there may be additional neural mechanisms capable of maintaining certain types of "biologically-relevant" stimuli during a brief trace interval. Given that the amygdala is involved in trace conditioning, and is sensitive to faces, it is possible that this structure can maintain a representation of a face CS during a brief trace interval. It is challenging to understand how the brain can associate an unperceived face with an aversive outcome, even though the two stimuli are separated in time. Furthermore investigations of this phenomenon are made difficult by two specific challenges. First, it is difficult to manipulate the subject's awareness of the visual stimuli. One common way to manipulate visual awareness is to use backward masking. In backward masking, a target stimulus is briefly presented (< 30 msec) and immediately followed by a presentation of an overlapping masking stimulus5. The presentation of the mask renders the target invisible6-8. Second, masking requires very rapid and precise timing making it difficult to investigate neural responses evoked by masked stimuli using many common approaches. Blood-oxygenation level dependent (BOLD) responses resolve at a timescale too slow for this type of methodology, and real time recording techniques like electroencephalography (EEG) and magnetoencephalography (MEG) have difficulties recovering signal from deep sources. However, there have been recent advances in the methods used to localize the neural sources of the MEG signal9-11. By collecting high-resolution MRI images of the subject's brain, it is possible to create a source model based on individual neural anatomy. Using this model to "image" the sources of the MEG signal, it is possible to recover signal from deep subcortical structures, like the amygdala and the hippocampus*.
27 Related JoVE Articles!
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Micro-Mechanical Characterization of Lung Tissue Using Atomic Force Microscopy
Authors: Fei Liu, Daniel J. Tschumperlin.
Institutions: Harvard School of Public Health.
Matrix stiffness strongly influences growth, differentiation and function of adherent cells1-3. On the macro scale the stiffness of tissues and organs within the human body span several orders of magnitude4. Much less is known about how stiffness varies spatially within tissues, and what the scope and spatial scale of stiffness changes are in disease processes that result in tissue remodeling. To better understand how changes in matrix stiffness contribute to cellular physiology in health and disease, measurements of tissue stiffness obtained at a spatial scale relevant to resident cells are needed. This is particularly true for the lung, a highly compliant and elastic tissue in which matrix remodeling is a prominent feature in diseases such as asthma, emphysema, hypertension and fibrosis. To characterize the local mechanical environment of lung parenchyma at a spatial scale relevant to resident cells, we have developed methods to directly measure the local elastic properties of fresh murine lung tissue using atomic force microscopy (AFM) microindentation. With appropriate choice of AFM indentor, cantilever, and indentation depth, these methods allow measurements of local tissue shear modulus in parallel with phase contrast and fluorescence imaging of the region of interest. Systematic sampling of tissue strips provides maps of tissue mechanical properties that reveal local spatial variations in shear modulus. Correlations between mechanical properties and underlying anatomical and pathological features illustrate how stiffness varies with matrix deposition in fibrosis. These methods can be extended to other soft tissues and disease processes to reveal how local tissue mechanical properties vary across space and disease progression.
Biophysics, Issue 54, Atomic force microscopy, indentation, stiffness, fibrosis, extracellular matrix
2911
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A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Authors: Bianca DeBenedictis, J. Bruce Morton.
Institutions: University of Western Ontario.
The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.
Behavior, Issue 87, Neurosciences, fMRI, Cognitive Control, Development, Functional Connectivity
51003
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Characterization Of Multi-layered Fish Scales (Atractosteus spatula) Using Nanoindentation, X-ray CT, FTIR, and SEM
Authors: Paul G. Allison, Rogie I. Rodriguez, Robert D. Moser, Brett A. Williams, Aimee R. Poda, Jennifer M. Seiter, Brandon J. Lafferty, Alan J. Kennedy, Mei Q. Chandler.
Institutions: U.S. Army Engineer Research and Development Center, University of Alabama, U.S. Army Engineer Research and Development Center.
The hierarchical architecture of protective biological materials such as mineralized fish scales, gastropod shells, ram’s horn, antlers, and turtle shells provides unique design principles with potentials for guiding the design of protective materials and systems in the future. Understanding the structure-property relationships for these material systems at the microscale and nanoscale where failure initiates is essential. Currently, experimental techniques such as nanoindentation, X-ray CT, and SEM provide researchers with a way to correlate the mechanical behavior with hierarchical microstructures of these material systems1-6. However, a well-defined standard procedure for specimen preparation of mineralized biomaterials is not currently available. In this study, the methods for probing spatially correlated chemical, structural, and mechanical properties of the multilayered scale of A. spatula using nanoindentation, FTIR, SEM, with energy-dispersive X-ray (EDX) microanalysis, and X-ray CT are presented.
Bioengineering, Issue 89, Atractosteus spatula, structure-property relation, nanoindentation, scan electron microscopy, X-ray computed tomography, Fourier transform infrared (FTIR) spectroscopy
51535
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
51705
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Spatial Separation of Molecular Conformers and Clusters
Authors: Daniel Horke, Sebastian Trippel, Yuan-Pin Chang, Stephan Stern, Terry Mullins, Thomas Kierspel, Jochen Küpper.
Institutions: CFEL, DESY, University of Hamburg, University of Hamburg.
Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold molecular beams. However, these beams often contain multiple conformers and clusters, even at low rotational temperatures. We present an experimental methodology that allows the spatial separation of these constituent parts of a molecular beam expansion. Using an electric deflector the beam is separated by its mass-to-dipole moment ratio, analogous to a bender or an electric sector mass spectrometer spatially dispersing charged molecules on the basis of their mass-to-charge ratio. This deflector exploits the Stark effect in an inhomogeneous electric field and allows the separation of individual species of polar neutral molecules and clusters. It furthermore allows the selection of the coldest part of a molecular beam, as low-energy rotational quantum states generally experience the largest deflection. Different structural isomers (conformers) of a species can be separated due to the different arrangement of functional groups, which leads to distinct dipole moments. These are exploited by the electrostatic deflector for the production of a conformationally pure sample from a molecular beam. Similarly, specific cluster stoichiometries can be selected, as the mass and dipole moment of a given cluster depends on the degree of solvation around the parent molecule. This allows experiments on specific cluster sizes and structures, enabling the systematic study of solvation of neutral molecules.
Physics, Issue 83, Chemical Physics, Physical Chemistry, Molecular Physics, Molecular beams, Laser Spectroscopy, Clusters
51137
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Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology
Authors: Andreas Florian Haas, Ben Knowles, Yan Wei Lim, Tracey McDole Somera, Linda Wegley Kelly, Mark Hatay, Forest Rohwer.
Institutions: San Diego State University, University of California San Diego.
Here we introduce a series of thoroughly tested and well standardized research protocols adapted for use in remote marine environments. The sampling protocols include the assessment of resources available to the microbial community (dissolved organic carbon, particulate organic matter, inorganic nutrients), and a comprehensive description of the viral and bacterial communities (via direct viral and microbial counts, enumeration of autofluorescent microbes, and construction of viral and microbial metagenomes). We use a combination of methods, which represent a dispersed field of scientific disciplines comprising already established protocols and some of the most recent techniques developed. Especially metagenomic sequencing techniques used for viral and bacterial community characterization, have been established only in recent years, and are thus still subjected to constant improvement. This has led to a variety of sampling and sample processing procedures currently in use. The set of methods presented here provides an up to date approach to collect and process environmental samples. Parameters addressed with these protocols yield the minimum on information essential to characterize and understand the underlying mechanisms of viral and microbial community dynamics. It gives easy to follow guidelines to conduct comprehensive surveys and discusses critical steps and potential caveats pertinent to each technique.
Environmental Sciences, Issue 93, dissolved organic carbon, particulate organic matter, nutrients, DAPI, SYBR, microbial metagenomics, viral metagenomics, marine environment
52131
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Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro
Authors: Aya D. Pusic, Yelena Y. Grinberg, Heidi M. Mitchell, Richard P. Kraig.
Institutions: The University of Chicago Medical Center, The University of Chicago Medical Center.
Migraine and its transformation to chronic migraine are healthcare burdens in need of improved treatment options. We seek to define how neural immune signaling modulates the susceptibility to migraine, modeled in vitro using spreading depression (SD), as a means to develop novel therapeutic targets for episodic and chronic migraine. SD is the likely cause of migraine aura and migraine pain. It is a paroxysmal loss of neuronal function triggered by initially increased neuronal activity, which slowly propagates within susceptible brain regions. Normal brain function is exquisitely sensitive to, and relies on, coincident low-level immune signaling. Thus, neural immune signaling likely affects electrical activity of SD, and therefore migraine. Pain perception studies of SD in whole animals are fraught with difficulties, but whole animals are well suited to examine systems biology aspects of migraine since SD activates trigeminal nociceptive pathways. However, whole animal studies alone cannot be used to decipher the cellular and neural circuit mechanisms of SD. Instead, in vitro preparations where environmental conditions can be controlled are necessary. Here, it is important to recognize limitations of acute slices and distinct advantages of hippocampal slice cultures. Acute brain slices cannot reveal subtle changes in immune signaling since preparing the slices alone triggers: pro-inflammatory changes that last days, epileptiform behavior due to high levels of oxygen tension needed to vitalize the slices, and irreversible cell injury at anoxic slice centers. In contrast, we examine immune signaling in mature hippocampal slice cultures since the cultures closely parallel their in vivo counterpart with mature trisynaptic function; show quiescent astrocytes, microglia, and cytokine levels; and SD is easily induced in an unanesthetized preparation. Furthermore, the slices are long-lived and SD can be induced on consecutive days without injury, making this preparation the sole means to-date capable of modeling the neuroimmune consequences of chronic SD, and thus perhaps chronic migraine. We use electrophysiological techniques and non-invasive imaging to measure neuronal cell and circuit functions coincident with SD. Neural immune gene expression variables are measured with qPCR screening, qPCR arrays, and, importantly, use of cDNA preamplification for detection of ultra-low level targets such as interferon-gamma using whole, regional, or specific cell enhanced (via laser dissection microscopy) sampling. Cytokine cascade signaling is further assessed with multiplexed phosphoprotein related targets with gene expression and phosphoprotein changes confirmed via cell-specific immunostaining. Pharmacological and siRNA strategies are used to mimic and modulate SD immune signaling.
Neuroscience, Issue 52, innate immunity, hormesis, microglia, T-cells, hippocampus, slice culture, gene expression, laser dissection microscopy, real-time qPCR, interferon-gamma
2910
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CometChip: A High-throughput 96-Well Platform for Measuring DNA Damage in Microarrayed Human Cells
Authors: Jing Ge, Somsak Prasongtanakij, David K. Wood, David M. Weingeist, Jessica Fessler, Panida Navasummrit, Mathuros Ruchirawat, Bevin P. Engelward.
Institutions: Massachusetts Institute of Technology, Chulabhorn Graduate Institute, University of Minnesota.
DNA damaging agents can promote aging, disease and cancer and they are ubiquitous in the environment and produced within human cells as normal cellular metabolites. Ironically, at high doses DNA damaging agents are also used to treat cancer. The ability to quantify DNA damage responses is thus critical in the public health, pharmaceutical and clinical domains. Here, we describe a novel platform that exploits microfabrication techniques to pattern cells in a fixed microarray. The ‘CometChip’ is based upon the well-established single cell gel electrophoresis assay (a.k.a. the comet assay), which estimates the level of DNA damage by evaluating the extent of DNA migration through a matrix in an electrical field. The type of damage measured by this assay includes abasic sites, crosslinks, and strand breaks. Instead of being randomly dispersed in agarose in the traditional assay, cells are captured into an agarose microwell array by gravity. The platform also expands from the size of a standard microscope slide to a 96-well format, enabling parallel processing. Here we describe the protocols of using the chip to evaluate DNA damage caused by known genotoxic agents and the cellular repair response followed after exposure. Through the integration of biological and engineering principles, this method potentiates robust and sensitive measurements of DNA damage in human cells and provides the necessary throughput for genotoxicity testing, drug development, epidemiological studies and clinical assays.
Bioengineering, Issue 92, comet assay, electrophoresis, microarray, DNA damage, DNA repair
50607
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Quantitative Analysis and Characterization of Atherosclerotic Lesions in the Murine Aortic Sinus
Authors: Daniel E. Venegas-Pino, Nicole Banko, Mohammed I. Khan, Yuanyuan Shi, Geoff H. Werstuck.
Institutions: McMaster University, McMaster University.
Atherosclerosis is a disease of the large arteries and a major underlying cause of myocardial infarction and stroke. Several different mouse models have been developed to facilitate the study of the molecular and cellular pathophysiology of this disease. In this manuscript we describe specific techniques for the quantification and characterization of atherosclerotic lesions in the murine aortic sinus and ascending aorta. The advantage of this procedure is that it provides an accurate measurement of the cross-sectional area and total volume of the lesion, which can be used to compare atherosclerotic progression across different treatment groups. This is possible through the use of the valve leaflets as an anatomical landmark, together with careful adjustment of the sectioning angle. We also describe basic staining methods that can be used to begin to characterize atherosclerotic progression. These can be further modified to investigate antigens of specific interest to the researcher. The described techniques are generally applicable to a wide variety of existing and newly created dietary and genetically-induced models of atherogenesis.
Medicine, Issue 82, atherosclerosis, atherosclerotic lesion, Mouse Model, aortic sinus, tissue preparation and sectioning, Immunohistochemistry
50933
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Authors: Fijoy Vadakkumpadan, Hermenegild Arevalo, Natalia A. Trayanova.
Institutions: Johns Hopkins University.
Patient-specific simulations of heart (dys)function aimed at personalizing cardiac therapy are hampered by the absence of in vivo imaging technology for clinically acquiring myocardial fiber orientations. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4 °. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.The new insights obtained from the project will pave the way for the development of patient-specific models of the heart that can aid physicians in personalized diagnosis and decisions regarding electrophysiological interventions.
Bioengineering, Issue 71, Biomedical Engineering, Medicine, Anatomy, Physiology, Cardiology, Myocytes, Cardiac, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, MRI, Diffusion Magnetic Resonance Imaging, Cardiac Electrophysiology, computerized simulation (general), mathematical modeling (systems analysis), Cardiomyocyte, biomedical image processing, patient-specific modeling, Electrophysiology, simulation
50125
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Discovery of New Intracellular Pathogens by Amoebal Coculture and Amoebal Enrichment Approaches
Authors: Nicolas Jacquier, Sébastien Aeby, Julia Lienard, Gilbert Greub.
Institutions: University Hospital Center and University of Lausanne.
Intracellular pathogens such as legionella, mycobacteria and Chlamydia-like organisms are difficult to isolate because they often grow poorly or not at all on selective media that are usually used to cultivate bacteria. For this reason, many of these pathogens were discovered only recently or following important outbreaks. These pathogens are often associated with amoebae, which serve as host-cell and allow the survival and growth of the bacteria. We intend here to provide a demonstration of two techniques that allow isolation and characterization of intracellular pathogens present in clinical or environmental samples: the amoebal coculture and the amoebal enrichment. Amoebal coculture allows recovery of intracellular bacteria by inoculating the investigated sample onto an amoebal lawn that can be infected and lysed by the intracellular bacteria present in the sample. Amoebal enrichment allows recovery of amoebae present in a clinical or environmental sample. This can lead to discovery of new amoebal species but also of new intracellular bacteria growing specifically in these amoebae. Together, these two techniques help to discover new intracellular bacteria able to grow in amoebae. Because of their ability to infect amoebae and resist phagocytosis, these intracellular bacteria might also escape phagocytosis by macrophages and thus, be pathogenic for higher eukaryotes.
Immunology, Issue 80, Environmental Microbiology, Soil Microbiology, Water Microbiology, Amoebae, microorganisms, coculture, obligate intracellular bacteria
51055
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Eye Movement Monitoring of Memory
Authors: Jennifer D. Ryan, Lily Riggs, Douglas A. McQuiggan.
Institutions: Rotman Research Institute, University of Toronto, University of Toronto.
Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank yesterday."), however such reports can often be unreliable or sensitive to response bias 1, and may be unobtainable in some participant populations. Furthermore, explicit reports only reveal when information has reached consciousness and cannot comment on when memories were accessed during processing, regardless of whether the information is subsequently accessed in a conscious manner. Eye movement monitoring (eye tracking) provides a tool by which memory can be probed without asking participants to comment on the contents of their memories, and access of such memories can be revealed on-line 2,3. Video-based eye trackers (either head-mounted or remote) use a system of cameras and infrared markers to examine the pupil and corneal reflection in each eye as the participant views a display monitor. For head-mounted eye trackers, infrared markers are also used to determine head position to allow for head movement and more precise localization of eye position. Here, we demonstrate the use of a head-mounted eye tracking system to investigate memory performance in neurologically-intact and neurologically-impaired adults. Eye movement monitoring procedures begin with the placement of the eye tracker on the participant, and setup of the head and eye cameras. Calibration and validation procedures are conducted to ensure accuracy of eye position recording. Real-time recordings of X,Y-coordinate positions on the display monitor are then converted and used to describe periods of time in which the eye is static (i.e. fixations) versus in motion (i.e., saccades). Fixations and saccades are time-locked with respect to the onset/offset of a visual display or another external event (e.g. button press). Experimental manipulations are constructed to examine how and when patterns of fixations and saccades are altered through different types of prior experience. The influence of memory is revealed in the extent to which scanning patterns to new images differ from scanning patterns to images that have been previously studied 2, 4-5. Memory can also be interrogated for its specificity; for instance, eye movement patterns that differ between an identical and an altered version of a previously studied image reveal the storage of the altered detail in memory 2-3, 6-8. These indices of memory can be compared across participant populations, thereby providing a powerful tool by which to examine the organization of memory in healthy individuals, and the specific changes that occur to memory with neurological insult or decline 2-3, 8-10.
Neuroscience, Issue 42, eye movement monitoring, eye tracking, memory, aging, amnesia, visual processing
2108
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
4273
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Use of an Eight-arm Radial Water Maze to Assess Working and Reference Memory Following Neonatal Brain Injury
Authors: Stephanie C. Penley, Cynthia M. Gaudet, Steven W. Threlkeld.
Institutions: Rhode Island College, Rhode Island College.
Working and reference memory are commonly assessed using the land based radial arm maze. However, this paradigm requires pretraining, food deprivation, and may introduce scent cue confounds. The eight-arm radial water maze is designed to evaluate reference and working memory performance simultaneously by requiring subjects to use extra-maze cues to locate escape platforms and remedies the limitations observed in land based radial arm maze designs. Specifically, subjects are required to avoid the arms previously used for escape during each testing day (working memory) as well as avoid the fixed arms, which never contain escape platforms (reference memory). Re-entries into arms that have already been used for escape during a testing session (and thus the escape platform has been removed) and re-entries into reference memory arms are indicative of working memory deficits. Alternatively, first entries into reference memory arms are indicative of reference memory deficits. We used this maze to compare performance of rats with neonatal brain injury and sham controls following induction of hypoxia-ischemia and show significant deficits in both working and reference memory after eleven days of testing. This protocol could be easily modified to examine many other models of learning impairment.
Behavior, Issue 82, working memory, reference memory, hypoxia-ischemia, radial arm maze, water maze
50940
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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
50680
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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
4375
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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
50579
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
50319
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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
51047
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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
51673
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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
50893
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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
51216
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From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
Authors: Carmine Di Rienzo, Enrico Gratton, Fabio Beltram, Francesco Cardarelli.
Institutions: Scuola Normale Superiore, Instituto Italiano di Tecnologia, University of California, Irvine.
It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn’t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.
Bioengineering, Issue 92, fluorescence, protein dynamics, lipid dynamics, membrane heterogeneity, transient confinement, single molecule, GFP
51994
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Brain Imaging Investigation of the Neural Correlates of Emotion Regulation
Authors: Sanda Dolcos, Keen Sung, Ekaterina Denkova, Roger A. Dixon, Florin Dolcos.
Institutions: University of Illinois, Urbana-Champaign, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Illinois, Urbana-Champaign, University of Illinois, Urbana-Champaign.
The ability to control/regulate emotions is an important coping mechanism in the face of emotionally stressful situations. Although significant progress has been made in understanding conscious/deliberate emotion regulation (ER), less is known about non-conscious/automatic ER and the associated neural correlates. This is in part due to the problems inherent in the unitary concepts of automatic and conscious processing1. Here, we present a protocol that allows investigation of the neural correlates of both deliberate and automatic ER using functional magnetic resonance imaging (fMRI). This protocol allows new avenues of inquiry into various aspects of ER. For instance, the experimental design allows manipulation of the goal to regulate emotion (conscious vs. non-conscious), as well as the intensity of the emotional challenge (high vs. low). Moreover, it allows investigation of both immediate (emotion perception) and long-term effects (emotional memory) of ER strategies on emotion processing. Therefore, this protocol may contribute to better understanding of the neural mechanisms of emotion regulation in healthy behaviour, and to gaining insight into possible causes of deficits in depression and anxiety disorders in which emotion dysregulation is often among the core debilitating features.
Neuroscience, Issue 54, Emotion Suppression, Automatic Emotion Control, Deliberate Emotion Control, Goal Induction, Neuroimaging
2430
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Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells
Authors: Robert DeRose, Christopher Pohlmeyer, Nobuhiro Umeda, Tasuku Ueno, Tetsuo Nagano, Scot Kuo, Takanari Inoue.
Institutions: Johns Hopkins University, University of Tokyo, Johns Hopkins University.
Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular functions and events1, 2. Their spatiotemporally dynamic nature has been revealed by visualization of their activity and localization in real time3. In order to gain deeper understanding of their roles in diverse cellular functions at the molecular level, the next step should be perturbation of protein activities at a precise subcellular location and timing. To achieve this goal, we have developed a method for light-induced, spatio-temporally controlled activation of small GTPases by combining two techniques: (1) rapamycin-induced FKBP-FRB heterodimerization and (2) a photo-caging method of rapamycin. With the use of rapamycin-mediated FKBP-FRB heterodimerization, we have developed a method for rapidly inducible activation or inactivation of small GTPases including Rac4, Cdc424, RhoA4 and Ras5, in which rapamycin induces translocation of FKBP-fused GTPases, or their activators, to the plasma membrane where FRB is anchored. For coupling with this heterodimerization system, we have also developed a photo-caging system of rapamycin analogs. A photo-caged compound is a small molecule whose activity is suppressed with a photocleavable protecting group known as a caging group. To suppress heterodimerization activity completely, we designed a caged rapamycin that is tethered to a macromolecule such that the resulting large complex cannot cross the plasma membrane, leading to virtually no background activity as a chemical dimerizer inside cells6. Figure 1 illustrates a scheme of our system. With the combination of these two systems, we locally recruited a Rac activator to the plasma membrane on a timescale of seconds and achieved light-induced Rac activation at the subcellular level6.
Bioengineering, Issue 61, Small GTPase, rapamycin, caged compound, spatiotemporal control, heterodimerization, FKBP, FRB, light irradiation
3794
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Patterning Cells on Optically Transparent Indium Tin Oxide Electrodes
Authors: Sunny Shah, Alexander Revzin.
Institutions: University of California, Davis.
The ability to exercise precise spatial and temporal control over cell-surface interactions is an important prerequisite to the assembly of multi-cellular constructs serving as in vitro mimics of native tissues. In this study, photolithography and wet etching techniques were used to fabricate individually addressable indium tin oxide (ITO) electrodes on glass substrates. The glass substrates containing ITO microelectrodes were modified with poly(ethylene glycol) (PEG) silane to make them protein and cell resistive. Presence of insulating PEG molecules on the electrode surface was verified by cyclic voltammetry employing potassium ferricyanide as a redox reporter molecule. Importantly, the application of reductive potential caused desorption of the PEG layer, resulting in regeneration of the conductive electrode surface and appearance of typical ferricyanide redox peaks. Application of reductive potential also corresponded to switching of ITO electrode properties from cell non-adhesive to cell-adhesive. Electrochemical stripping of PEG-silane layer from ITO microelectrodes allowed for cell adhesion to take place in a spatially defined fashion, with cellular patterns corresponding closely to electrode patterns. Micropatterning of several cell types was demonstrated on these substrates. In the future, the control of the biointerfacial properties afforded by this method will allow to engineer cellular microenvironments through the assembly of three or more cell types into a precise geometric configuration on an optically transparent substrate.
Cellular Biology, Issue 7, indium tin oxide, surface modification, electrochemistry, cell patterning
259
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Growth Factor-Coated Bead Placement on Dorsal Forebrain Explants
Authors: D. Spencer Currle, Aaron Kolski-Andreaco, Edwin S. Monuki.
Institutions: University of California, Irvine (UCI), University of California, Irvine (UCI), University of California, Irvine (UCI).
Developmental Biology, Issue 2, Growth Factor, Neuroscience, mouse, Affi-Gel Beads
134
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