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Pubmed Article
Boosted beta regression.
PUBLISHED: 01-01-2013
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1). Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.
Authors: Jeremy D. Smith, Abbie E. Ferris, Gary D. Heise, Richard N. Hinrichs, Philip E. Martin.
Published: 05-08-2014
The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.
22 Related JoVE Articles!
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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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Viability Assays for Cells in Culture
Authors: Jessica M. Posimo, Ajay S. Unnithan, Amanda M. Gleixner, Hailey J. Choi, Yiran Jiang, Sree H. Pulugulla, Rehana K. Leak.
Institutions: Duquesne University.
Manual cell counts on a microscope are a sensitive means of assessing cellular viability but are time-consuming and therefore expensive. Computerized viability assays are expensive in terms of equipment but can be faster and more objective than manual cell counts. The present report describes the use of three such viability assays. Two of these assays are infrared and one is luminescent. Both infrared assays rely on a 16 bit Odyssey Imager. One infrared assay uses the DRAQ5 stain for nuclei combined with the Sapphire stain for cytosol and is visualized in the 700 nm channel. The other infrared assay, an In-Cell Western, uses antibodies against cytoskeletal proteins (α-tubulin or microtubule associated protein 2) and labels them in the 800 nm channel. The third viability assay is a commonly used luminescent assay for ATP, but we use a quarter of the recommended volume to save on cost. These measurements are all linear and correlate with the number of cells plated, but vary in sensitivity. All three assays circumvent time-consuming microscopy and sample the entire well, thereby reducing sampling error. Finally, all of the assays can easily be completed within one day of the end of the experiment, allowing greater numbers of experiments to be performed within short timeframes. However, they all rely on the assumption that cell numbers remain in proportion to signal strength after treatments, an assumption that is sometimes not met, especially for cellular ATP. Furthermore, if cells increase or decrease in size after treatment, this might affect signal strength without affecting cell number. We conclude that all viability assays, including manual counts, suffer from a number of caveats, but that computerized viability assays are well worth the initial investment. Using all three assays together yields a comprehensive view of cellular structure and function.
Cellular Biology, Issue 83, In-cell Western, DRAQ5, Sapphire, Cell Titer Glo, ATP, primary cortical neurons, toxicity, protection, N-acetyl cysteine, hormesis
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Polymalic Acid-based Nano Biopolymers for Targeting of Multiple Tumor Markers: An Opportunity for Personalized Medicine?
Authors: Julia Y. Ljubimova, Hui Ding, Jose Portilla-Arias, Rameshwar Patil, Pallavi R. Gangalum, Alexandra Chesnokova, Satoshi Inoue, Arthur Rekechenetskiy, Tala Nassoura, Keith L. Black, Eggehard Holler.
Institutions: Cedars-Sinai Medical Center.
Tumors with similar grade and morphology often respond differently to the same treatment because of variations in molecular profiling. To account for this diversity, personalized medicine is developed for silencing malignancy associated genes. Nano drugs fit these needs by targeting tumor and delivering antisense oligonucleotides for silencing of genes. As drugs for the treatment are often administered repeatedly, absence of toxicity and negligible immune response are desirable. In the example presented here, a nano medicine is synthesized from the biodegradable, non-toxic and non-immunogenic platform polymalic acid by controlled chemical ligation of antisense oligonucleotides and tumor targeting molecules. The synthesis and treatment is exemplified for human Her2-positive breast cancer using an experimental mouse model. The case can be translated towards synthesis and treatment of other tumors.
Chemistry, Issue 88, Cancer treatment, personalized medicine, polymalic acid, nanodrug, biopolymer, targeting, host compatibility, biodegradability
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Anticancer Metal Complexes: Synthesis and Cytotoxicity Evaluation by the MTT Assay
Authors: Nitzan Ganot, Sigalit Meker, Lilia Reytman, Avia Tzubery, Edit Y. Tshuva.
Institutions: The Hebrew University of Jerusalem.
Titanium (IV) and vanadium (V) complexes are highly potent anticancer agents. A challenge in their synthesis refers to their hydrolytic instability; therefore their preparation should be conducted under an inert atmosphere. Evaluation of the anticancer activity of these complexes can be achieved by the MTT assay. The MTT assay is a colorimetric viability assay based on enzymatic reduction of the MTT molecule to formazan when it is exposed to viable cells. The outcome of the reduction is a color change of the MTT molecule. Absorbance measurements relative to a control determine the percentage of remaining viable cancer cells following their treatment with varying concentrations of a tested compound, which is translated to the compound anticancer activity and its IC50 values. The MTT assay is widely common in cytotoxicity studies due to its accuracy, rapidity, and relative simplicity. Herein we present a detailed protocol for the synthesis of air sensitive metal based drugs and cell viability measurements, including preparation of the cell plates, incubation of the compounds with the cells, viability measurements using the MTT assay, and determination of IC50 values.
Medicine, Issue 81, Inorganic Chemicals, Therapeutics, Metals and Metallic Materials, anticancer drugs, cell viability, cisplatin, metal complex, cytotoxicity, HT-29, metal-based drugs, MTT assay, titanium (IV), vanadium (V)
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Experimental Metastasis and CTL Adoptive Transfer Immunotherapy Mouse Model
Authors: Mary Zimmerman, Xiaolin Hu, Kebin Liu.
Institutions: Medical College of Georgia.
Experimental metastasis mouse model is a simple and yet physiologically relevant metastasis model. The tumor cells are injected intravenously (i.v) into mouse tail veins and colonize in the lungs, thereby, resembling the last steps of tumor cell spontaneous metastasis: survival in the circulation, extravasation and colonization in the distal organs. From a therapeutic point of view, the experimental metastasis model is the simplest and ideal model since the target of therapies is often the end point of metastasis: established metastatic tumor in the distal organ. In this model, tumor cells are injected i.v into mouse tail veins and allowed to colonize and grow in the lungs. Tumor-specific CTLs are then injected i.v into the metastases-bearing mouse. The number and size of the lung metastases can be controlled by the number of tumor cells to be injected and the time of tumor growth. Therefore, various stages of metastasis, from minimal metastasis to extensive metastasis, can be modeled. Lung metastases are analyzed by inflation with ink, thus allowing easier visual observation and quantification.
Immunology, Issue 45, Metastasis, CTL adoptive transfer, Lung, Tumor Immunology
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
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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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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
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Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers
Authors: Sarah M. Collier, Matthew D. Ruark, Lawrence G. Oates, William E. Jokela, Curtis J. Dell.
Institutions: University of Wisconsin-Madison, University of Wisconsin-Madison, University of Wisconsin-Madison, University of Wisconsin-Madison, USDA-ARS Dairy Forage Research Center, USDA-ARS Pasture Systems Watershed Management Research Unit.
Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.
Environmental Sciences, Issue 90, greenhouse gas, trace gas, gas flux, static chamber, soil, field, agriculture, climate
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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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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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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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Ex vivo Expansion of Tumor-reactive T Cells by Means of Bryostatin 1/Ionomycin and the Common Gamma Chain Cytokines Formulation
Authors: Maciej Kmieciak, Amir Toor, Laura Graham, Harry D. Bear, Masoud H. Manjili.
Institutions: Virginia Commonwealth University- Massey Cancer Center, Virginia Commonwealth University- Massey Cancer Center, Virginia Commonwealth University- Massey Cancer Center.
It was reported that breast cancer patients have pre-existing immune responses against their tumors1,2. However, such immune responses fail to provide complete protection against the development or recurrence of breast cancer. To overcome this problem by increasing the frequency of tumor-reactive T cells, adoptive immunotherapy has been employed. A variety of protocols have been used for the expansion of tumor-specific T cells. These protocols, however, are restricted to the use of tumor antigens ex vivo for the activation of antigen-specific T cells. Very recently, common gamma chain cytokines such as IL-2, IL-7, IL-15, and IL-21 have been used alone or in combination for the enhancement of anti-tumor immune responses3. However, it is not clear what formulation would work best for the expansion of tumor-reactive T cells. Here we present a protocol for the selective activation and expansion of tumor-reactive T cells from the FVBN202 transgenic mouse model of HER-2/neu positive breast carcinoma for use in adoptive T cell therapy of breast cancer. The protocol includes activation of T cells with bryostatin-1/ionomycin (B/I) and IL-2 in the absence of tumor antigens for 16 hours. B/I activation mimics intracellular signals that result in T cell activation by increasing protein kinase C activity and intracellular calcium, respectively4. This protocol specifically activates tumor-specific T cells while killing irrelevant T cells. The B/I-activated T cells are cultured with IL-7 and IL-15 for 24 hours and then pulsed with IL-2. After 24 hours, T cells are washed, split, and cultured with IL-7 + IL-15 for additional 4 days. Tumor-specificity and anti-tumor efficacy of the ex vivo expanded T cells is determined.
Immunology, Issue 47, Adoptive T cell therapy, Breast Cancer, HER-2/neu, common gamma chain cytokines, Bryostatin 1, Ionomycin
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Measuring Circadian and Acute Light Responses in Mice using Wheel Running Activity
Authors: Tara A. LeGates, Cara M. Altimus.
Institutions: John Hopkins University.
Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2. They are responsible for timing our sleep/wake cycles and hormone secretion. Since this timing is not precisely 24-hours, it is synchronized to the solar day by light input. This is accomplished via photic input from the retina to the suprachiasmatic nucleus (SCN) which serves as the master pacemaker synchronizing peripheral clocks in other regions of the brain and peripheral tissues to the environmental light dark cycle3-7. The alignment of rhythms to this environmental light dark cycle organizes particular physiological events to the correct temporal niche, which is crucial for survival8. For example, mice sleep during the day and are active at night. This ability to consolidate activity to either the light or dark portion of the day is referred to as circadian photoentrainment and requires light input to the circadian clock9. Activity of mice at night is robust particularly in the presence of a running wheel. Measuring this behavior is a minimally invasive method that can be used to evaluate the functionality of the circadian system as well as light input to this system. Methods that will covered here are used to examine the circadian clock, light input to this system, as well as the direct influence of light on wheel running behavior.
Neuroscience, Issue 48, mouse, circadian, behavior, wheel running
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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
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Experimental Manipulation of Body Size to Estimate Morphological Scaling Relationships in Drosophila
Authors: R. Craig Stillwell, Ian Dworkin, Alexander W. Shingleton, W. Anthony Frankino.
Institutions: University of Houston, Michigan State University.
The scaling of body parts is a central feature of animal morphology1-7. Within species, morphological traits need to be correctly proportioned to the body for the organism to function; larger individuals typically have larger body parts and smaller individuals generally have smaller body parts, such that overall body shape is maintained across a range of adult body sizes. The requirement for correct proportions means that individuals within species usually exhibit low variation in relative trait size. In contrast, relative trait size can vary dramatically among species and is a primary mechanism by which morphological diversity is produced. Over a century of comparative work has established these intra- and interspecific patterns3,4. Perhaps the most widely used approach to describe this variation is to calculate the scaling relationship between the size of two morphological traits using the allometric equation y=bxα, where x and y are the size of the two traits, such as organ and body size8,9. This equation describes the within-group (e.g., species, population) scaling relationship between two traits as both vary in size. Log-transformation of this equation produces a simple linear equation, log(y) = log(b) + αlog(x) and log-log plots of the size of different traits among individuals of the same species typically reveal linear scaling with an intercept of log(b) and a slope of α, called the 'allometric coefficient'9,10. Morphological variation among groups is described by differences in scaling relationship intercepts or slopes for a given trait pair. Consequently, variation in the parameters of the allometric equation (b and α) elegantly describes the shape variation captured in the relationship between organ and body size within and among biological groups (see 11,12). Not all traits scale linearly with each other or with body size (e.g., 13,14) Hence, morphological scaling relationships are most informative when the data are taken from the full range of trait sizes. Here we describe how simple experimental manipulation of diet can be used to produce the full range of body size in insects. This permits an estimation of the full scaling relationship for any given pair of traits, allowing a complete description of how shape covaries with size and a robust comparison of scaling relationship parameters among biological groups. Although we focus on Drosophila, our methodology should be applicable to nearly any fully metamorphic insect.
Developmental Biology, Issue 56, Drosophila, allometry, morphology, body size, scaling, insect
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Simultaneous Quantification of T-Cell Receptor Excision Circles (TRECs) and K-Deleting Recombination Excision Circles (KRECs) by Real-time PCR
Authors: Alessandra Sottini, Federico Serana, Diego Bertoli, Marco Chiarini, Monica Valotti, Marion Vaglio Tessitore, Luisa Imberti.
Institutions: Spedali Civili di Brescia.
T-cell receptor excision circles (TRECs) and K-deleting recombination excision circles (KRECs) are circularized DNA elements formed during recombination process that creates T- and B-cell receptors. Because TRECs and KRECs are unable to replicate, they are diluted after each cell division, and therefore persist in the cell. Their quantity in peripheral blood can be considered as an estimation of thymic and bone marrow output. By combining well established and commonly used TREC assay with a modified version of KREC assay, we have developed a duplex quantitative real-time PCR that allows quantification of both newly-produced T and B lymphocytes in a single assay. The number of TRECs and KRECs are obtained using a standard curve prepared by serially diluting TREC and KREC signal joints cloned in a bacterial plasmid, together with a fragment of T-cell receptor alpha constant gene that serves as reference gene. Results are reported as number of TRECs and KRECs/106 cells or per ml of blood. The quantification of these DNA fragments have been proven useful for monitoring immune reconstitution following bone marrow transplantation in both children and adults, for improved characterization of immune deficiencies, or for better understanding of certain immunomodulating drug activity.
Immunology, Issue 94, B lymphocytes, primary immunodeficiency, real-time PCR, immune recovery, T-cell homeostasis, T lymphocytes, thymic output, bone marrow output
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Authors: Ifat Levy, Lior Rosenberg Belmaker, Kirk Manson, Agnieszka Tymula, Paul W. Glimcher.
Institutions: Yale School of Medicine, Yale School of Medicine, New York University , New York University , New York University .
Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity1,2, the degree of those aversions vary substantially across individuals, such that the subjective value of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3 to assess the neural representation of the subjective values of risky and ambiguous options4. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations. In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.
Neuroscience, Issue 67, Medicine, Molecular Biology, fMRI, magnetic resonance imaging, decision-making, value, uncertainty, risk, ambiguity
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The α-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva
Authors: Cynthia L. Bristow, Mariya A. Babayeva, Rozbeh Modarresi, Carole P. McArthur, Santosh Kumar, Charles Awasom, Leo Ayuk, Annette Njinda, Paul Achu, Ronald Winston.
Institutions: Weill Cornell Medical College , University of Missouri-Kansas City-School of Dentistry, University of Missouri Kansas City- School of Pharmacy, Bamenda, NWP, Cameroon, Mezam Polyclinic HIV/AIDS Treatment Center, Cameroon, Institute for Human Genetics and Biochemistry.
There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time and temperature restrictions, technical sophistication, and cost of reagents, in particular monoclonal antibodies to measure CD4 on blood cells, the only currently acceptable method. A commonly used cost-saving and time-saving laboratory strategy is to calculate, rather than measure certain blood values. For example, LDL levels are calculated using the measured levels of total cholesterol, HDL, and triglycerides1. Thus, identification of cell-free correlates that directly regulate the number of CD4+ T cells could provide an accurate method for calculating CD4 counts due to the physiological relevance of the correlates. The number of stem cells that enter blood and are destined to become circulating CD4+ T cells is determined by the chemokine CXCL12 and its receptor CXCR4 due to their influence on locomotion2. The process of stem cell locomotion into blood is additionally regulated by cell surface human leukocyte elastase (HLECS) and the HLECS-reactive active α1proteinase inhibitor (α1PI, α1antitrypsin, SerpinA1)3. In HIV-1 disease, α1PI is inactivated due to disease processes 4. In the early asymptomatic categories of HIV-1 disease, active α1PI was found to be below normal in 100% of untreated HIV-1 patients (median=12 μM, and to achieve normal levels during the symptomatic categories4, 5. This pattern has been attributed to immune inactivation, not to insufficient synthesis, proteolytic inactivation, or oxygenation. We observed that in HIV-1 subjects with >220 CD4 cells/μl, CD4 counts were correlated with serum levels of active α1PI (r2=0.93, p<0.0001, n=26) and inactive α1PI (r2=0.91, p<0.0001, n=26) 5. Administration of α1PI to HIV-1 infected and uninfected subjects resulted in dramatic increases in CD4 counts suggesting α1PI participates in regulating the number of CD4+ T cells in blood 3. With stimulation, whole saliva contains sufficient serous exudate (plasma containing proteinaceous material that passes through blood vessel walls into saliva) to allow measurement of active α1PI and the correlation of this measurement is evidence that it is an accurate method for calculating CD4 counts. Briefly, sialogogues such as chewing gum or citric acid stimulate the exudation of serum into whole mouth saliva. After stimulating serum exudation, the activity of serum α1PI in saliva is measured by its capacity to inhibit elastase activity. Porcine pancreatic elastase (PPE) is a readily available inexpensive source of elastase. PPE binds to α1PI forming a one-to-one complex that prevents PPE from cleaving its specific substrates, one of which is the colorimetric peptide, succinyl-L-Ala-L-Ala-L-Ala-p-nitroanilide (SA3NA). Incubating saliva with a saturating concentration of PPE for 10 min at room temperature allows the binding of PPE to all the active α1PI in saliva. The resulting inhibition of PPE by active α1PI can be measured by adding the PPE substrate SA3NA. (Figure 1). Although CD4 counts are measured in terms of blood volume (CD4 cells/μl), the concentration of α1PI in saliva is related to the concentration of serum in saliva, not to volume of saliva since volume can vary considerably during the day and person to person6. However, virtually all the protein in saliva is due to serum content, and the protein content of saliva is measurable7. Thus, active α1PI in saliva is calculated as a ratio to saliva protein content and is termed the α1PI Index. Results presented herein demonstrate that the α1PI Index provides an accurate and precise physiologic method for calculating CD4 counts.
Medicine, Issue 63, CD4 count, saliva, antitrypsin, hematopoiesis, T cells, HIV/AIDS, clinical
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Customization of Aspergillus niger Morphology Through Addition of Talc Micro Particles
Authors: Thomas Wucherpfennig, Antonia Lakowitz, Habib Driouch, Rainer Krull, Christoph Wittmann.
Institutions: Technische Universität Braunschweig.
The filamentous fungus A. niger is a widely used strain in a broad range of industrial processes from food to pharmaceutical industry. One of the most intriguing and often uncontrollable characteristics of this filamentous organism is its complex morphology. It ranges from dense spherical pellets to viscous mycelia (Figure 1). Various process parameters and ingredients are known to influence fungal morphology 1. Since optimal productivity correlates strongly with a specific morphological form, the fungal morphology often represents the bottleneck of productivity in industrial production. A straight forward and elegant approach to precisely control morphological shape is the addition of inorganic insoluble micro particles (like hydrous magnesium silicate, aluminum oxide or titanium silicate oxide) to the culture medium contributing to increased enzyme production 2-6. Since there is an obvious correlation between micro particle dependent morphology and enzyme production it is desirable to mathematically link productivity and morphological appearance. Therefore a quantitative precise and holistic morphological description is targeted. Thus, we present a method to generate and characterize micro particle dependent morphological structures and to correlate fungal morphology with productivity (Figure 1) which possibly contributes to a better understanding of the morphogenesis of filamentous microorganisms. The recombinant strain A. niger SKAn1015 is cultivated for 72 h in a 3 L stirred tank bioreactor. By addition of talc micro particles in concentrations of 1 g/L, 3 g/L and 10 g/L prior to inoculation a variety of morphological structures is reproducibly generated. Sterile samples are taken after 24, 48 and 72 hours for determination of growth progress and activity of the produced enzyme. The formed product is the high-value enzyme β-fructofuranosidase, an important biocatalyst for neo-sugar formation in food or pharmaceutical industry, which catalyzes among others the reaction of sucrose to glucose 7-9. Therefore, the quantification of glucose after adding sucrose implies the amount of produced β-fructofuranosidase. Glucose quantification is made by a GOD/POD-Assay 10, which is modified for high-throughput analysis in 96-well micro titer plates. Fungal morphology after 72 hours is examined by microscope and characterized by digital image analysis. In doing so, particle shape factors for fungal macro morphology like Feret's diameter, projected area, perimeter, circularity, aspect ratio, roundness und solidity are calculated with the open source image processing program ImageJ. Relevant parameters are combined to a dimensionless Morphology number (Mn) 11, which enables a comprehensive characterization of fungal morphology. The close correlation of the Morphology number and productivity are highlighted by mathematical regression.
Immunology, Issue 61, morphology engineering, Morphology number (Mn), filamentous fungi, fructofuranosidase, micro particles, image analysis
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Determination of the Gas-phase Acidities of Oligopeptides
Authors: Jianhua Ren, Ashish Sawhney, Yuan Tian, Bhupinder Padda, Patrick Batoon.
Institutions: University of the Pacific.
Amino acid residues located at different positions in folded proteins often exhibit different degrees of acidities. For example, a cysteine residue located at or near the N-terminus of a helix is often more acidic than that at or near the C-terminus 1-6. Although extensive experimental studies on the acid-base properties of peptides have been carried out in the condensed phase, in particular in aqueous solutions 6-8, the results are often complicated by solvent effects 7. In fact, most of the active sites in proteins are located near the interior region where solvent effects have been minimized 9,10. In order to understand intrinsic acid-base properties of peptides and proteins, it is important to perform the studies in a solvent-free environment. We present a method to measure the acidities of oligopeptides in the gas-phase. We use a cysteine-containing oligopeptide, Ala3CysNH2 (A3CH), as the model compound. The measurements are based on the well-established extended Cooks kinetic method (Figure 1) 11-16. The experiments are carried out using a triple-quadrupole mass spectrometer interfaced with an electrospray ionization (ESI) ion source (Figure 2). For each peptide sample, several reference acids are selected. The reference acids are structurally similar organic compounds with known gas-phase acidities. A solution of the mixture of the peptide and a reference acid is introduced into the mass spectrometer, and a gas-phase proton-bound anionic cluster of peptide-reference acid is formed. The proton-bound cluster is mass isolated and subsequently fragmented via collision-induced dissociation (CID) experiments. The resulting fragment ion abundances are analyzed using a relationship between the acidities and the cluster ion dissociation kinetics. The gas-phase acidity of the peptide is then obtained by linear regression of the thermo-kinetic plots 17,18. The method can be applied to a variety of molecular systems, including organic compounds, amino acids and their derivatives, oligonucleotides, and oligopeptides. By comparing the gas-phase acidities measured experimentally with those values calculated for different conformers, conformational effects on the acidities can be evaluated.
Chemistry, Issue 76, Biochemistry, Molecular Biology, Oligopeptide, gas-phase acidity, kinetic method, collision-induced dissociation, triple-quadrupole mass spectrometry, oligopeptides, peptides, mass spectrometry, MS
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Quantifying Agonist Activity at G Protein-coupled Receptors
Authors: Frederick J. Ehlert, Hinako Suga, Michael T. Griffin.
Institutions: University of California, Irvine, University of California, Chapman University.
When an agonist activates a population of G protein-coupled receptors (GPCRs), it elicits a signaling pathway that culminates in the response of the cell or tissue. This process can be analyzed at the level of a single receptor, a population of receptors, or a downstream response. Here we describe how to analyze the downstream response to obtain an estimate of the agonist affinity constant for the active state of single receptors. Receptors behave as quantal switches that alternate between active and inactive states (Figure 1). The active state interacts with specific G proteins or other signaling partners. In the absence of ligands, the inactive state predominates. The binding of agonist increases the probability that the receptor will switch into the active state because its affinity constant for the active state (Kb) is much greater than that for the inactive state (Ka). The summation of the random outputs of all of the receptors in the population yields a constant level of receptor activation in time. The reciprocal of the concentration of agonist eliciting half-maximal receptor activation is equivalent to the observed affinity constant (Kobs), and the fraction of agonist-receptor complexes in the active state is defined as efficacy (ε) (Figure 2). Methods for analyzing the downstream responses of GPCRs have been developed that enable the estimation of the Kobs and relative efficacy of an agonist 1,2. In this report, we show how to modify this analysis to estimate the agonist Kb value relative to that of another agonist. For assays that exhibit constitutive activity, we show how to estimate Kb in absolute units of M-1. Our method of analyzing agonist concentration-response curves 3,4 consists of global nonlinear regression using the operational model 5. We describe a procedure using the software application, Prism (GraphPad Software, Inc., San Diego, CA). The analysis yields an estimate of the product of Kobs and a parameter proportional to efficacy (τ). The estimate of τKobs of one agonist, divided by that of another, is a relative measure of Kb (RAi) 6. For any receptor exhibiting constitutive activity, it is possible to estimate a parameter proportional to the efficacy of the free receptor complex (τsys). In this case, the Kb value of an agonist is equivalent to τKobssys 3. Our method is useful for determining the selectivity of an agonist for receptor subtypes and for quantifying agonist-receptor signaling through different G proteins.
Molecular Biology, Issue 58, agonist activity, active state, ligand bias, constitutive activity, G protein-coupled receptor
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