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Ensemble positive unlabeled learning for disease gene identification.
PUBLISHED: 01-01-2014
An increasing number of genes have been experimentally confirmed in recent years as causative genes to various human diseases. The newly available knowledge can be exploited by machine learning methods to discover additional unknown genes that are likely to be associated with diseases. In particular, positive unlabeled learning (PU learning) methods, which require only a positive training set P (confirmed disease genes) and an unlabeled set U (the unknown candidate genes) instead of a negative training set N, have been shown to be effective in uncovering new disease genes in the current scenario. Using only a single source of data for prediction can be susceptible to bias due to incompleteness and noise in the genomic data and a single machine learning predictor prone to bias caused by inherent limitations of individual methods. In this paper, we propose an effective PU learning framework that integrates multiple biological data sources and an ensemble of powerful machine learning classifiers for disease gene identification. Our proposed method integrates data from multiple biological sources for training PU learning classifiers. A novel ensemble-based PU learning method EPU is then used to integrate multiple PU learning classifiers to achieve accurate and robust disease gene predictions. Our evaluation experiments across six disease groups showed that EPU achieved significantly better results compared with various state-of-the-art prediction methods as well as ensemble learning classifiers. Through integrating multiple biological data sources for training and the outputs of an ensemble of PU learning classifiers for prediction, we are able to minimize the potential bias and errors in individual data sources and machine learning algorithms to achieve more accurate and robust disease gene predictions. In the future, our EPU method provides an effective framework to integrate the additional biological and computational resources for better disease gene predictions.
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Published: 07-25-2013
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.
26 Related JoVE Articles!
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Low-stress Route Learning Using the Lashley III Maze in Mice
Authors: Amanda Bressler, David Blizard, Anne Andrews.
Institutions: Pennsylvania State University, Pennsylvania State University, Pennsylvania State University, Pennsylvania State University, University of California, Los Angeles, University of California, Los Angeles.
Many behavior tests designed to assess learning and memory in rodents, particularly mice, rely on visual cues, food and/or water deprivation, or other aversive stimuli to motivate task acquisition. As animals age, sensory modalities deteriorate. For example, many strains of mice develop hearing deficits or cataracts. Changes in the sensory systems required to guide mice during task acquisition present potential confounds in interpreting learning changes in aging animals. Moreover, the use of aversive stimuli to motivate animals to learn tasks is potentially confounding when comparing mice with differential sensitivities to stress. To minimize these types of confounding effects, we have implemented a modified version of the Lashley III maze. This maze relies on route learning, whereby mice learn to navigate a maze via repeated exposure under low stress conditions, e.g. dark phase, no food/water deprivation, until they navigate a path from the start location to a pseudo-home cage with 0 or 1 error(s) on two consecutive trials. We classify this as a low-stress behavior test because it does not rely on aversive stimuli to encourage exploration of the maze and learning of the task. The apparatus consists of a modular start box, a 4-arm maze body, and a goal box. At the end of the goal box is a pseudo-home cage that contains bedding similar to that found in the animal’s home cage and is specific to each animal for the duration of maze testing. It has been demonstrated previously that this pseudo-home cage provides sufficient reward to motivate mice to learn to navigate the maze1. Here, we present the visualization of the Lashley III maze procedure in the context of evaluating age-related differences in learning and memory in mice along with a comparison of learning behavior in two different background strains of mice. We hope that other investigators interested in evaluating the effects of aging or stress vulnerability in mice will consider this maze an attractive alternative to behavioral tests that involve more stressful learning tasks and/or visual cues.
Neuroscience, Issue 39, mouse, behavior testing, learning, memory, neuroscience, phenotyping, aging
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Movement Retraining using Real-time Feedback of Performance
Authors: Michael Anthony Hunt.
Institutions: University of British Columbia .
Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular patterns responsible for governing the movement performance. This motor learning can be enhanced through a number of methods that are utilized in research and clinical settings alike. In general, verbal feedback of performance in real-time or knowledge of results following movement is commonly used clinically as a preliminary means of instilling motor learning. Depending on patient preference and learning style, visual feedback (e.g. through use of a mirror or different types of video) or proprioceptive guidance utilizing therapist touch, are used to supplement verbal instructions from the therapist. Indeed, a combination of these forms of feedback is commonplace in the clinical setting to facilitate motor learning and optimize outcomes. Laboratory-based, quantitative motion analysis has been a mainstay in research settings to provide accurate and objective analysis of a variety of movements in healthy and injured populations. While the actual mechanisms of capturing the movements may differ, all current motion analysis systems rely on the ability to track the movement of body segments and joints and to use established equations of motion to quantify key movement patterns. Due to limitations in acquisition and processing speed, analysis and description of the movements has traditionally occurred offline after completion of a given testing session. This paper will highlight a new supplement to standard motion analysis techniques that relies on the near instantaneous assessment and quantification of movement patterns and the display of specific movement characteristics to the patient during a movement analysis session. As a result, this novel technique can provide a new method of feedback delivery that has advantages over currently used feedback methods.
Medicine, Issue 71, Biophysics, Anatomy, Physiology, Physics, Biomedical Engineering, Behavior, Psychology, Kinesiology, Physical Therapy, Musculoskeletal System, Biofeedback, biomechanics, gait, movement, walking, rehabilitation, clinical, training
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Drosophila Adult Olfactory Shock Learning
Authors: Bilal R. Malik, James J.L. Hodge.
Institutions: University of Bristol.
Drosophila have been used in classical conditioning experiments for over 40 years, thus greatly facilitating our understanding of memory, including the elucidation of the molecular mechanisms involved in cognitive diseases1-7. Learning and memory can be assayed in larvae to study the effect of neurodevelopmental genes8-10 and in flies to measure the contribution of adult plasticity genes1-7. Furthermore, the short lifespan of Drosophila facilitates the analysis of genes mediating age-related memory impairment5,11-13. The availability of many inducible promoters that subdivide the Drosophila nervous system makes it possible to determine when and where a gene of interest is required for normal memory as well as relay of different aspects of the reinforcement signal3,4,14,16. Studying memory in adult Drosophila allows for a detailed analysis of the behavior and circuitry involved and a measurement of long-term memory15-17. The length of the adult stage accommodates longer-term genetic, behavioral, dietary and pharmacological manipulations of memory, in addition to determining the effect of aging and neurodegenerative disease on memory3-6,11-13,15-21. Classical conditioning is induced by the simultaneous presentation of a neutral odor cue (conditioned stimulus, CS+) and a reinforcement stimulus, e.g., an electric shock or sucrose, (unconditioned stimulus, US), that become associated with one another by the animal1,16. A second conditioned stimulus (CS-) is subsequently presented without the US. During the testing phase, Drosophila are simultaneously presented with CS+ and CS- odors. After the Drosophila are provided time to choose between the odors, the distribution of the animals is recorded. This procedure allows associative aversive or appetitive conditioning to be reliably measured without a bias introduced by the innate preference for either of the conditioned stimuli. Various control experiments are also performed to test whether all genotypes respond normally to odor and reinforcement alone.
Neuroscience, Issue 90, Drosophila, Pavlovian learning, classical conditioning, learning, memory, olfactory, electric shock, associative memory
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The Dig Task: A Simple Scent Discrimination Reveals Deficits Following Frontal Brain Damage
Authors: Kris M. Martens, Cole Vonder Haar, Blake A. Hutsell, Michael R. Hoane.
Institutions: Southern Illinois University at Carbondale.
Cognitive impairment is the most frequent cause of disability in humans following brain damage, yet the behavioral tasks used to assess cognition in rodent models of brain injury is lacking. Borrowing from the operant literature our laboratory utilized a basic scent discrimination paradigm1-4 in order to assess deficits in frontally-injured rats. Previously we have briefly described the Dig task and demonstrated that rats with frontal brain damage show severe deficits across multiple tests within the task5. Here we present a more detailed protocol for this task. Rats are placed into a chamber and allowed to discriminate between two scented sands, one of which contains a reinforcer. The trial ends after the rat either correctly discriminates (defined as digging in the correct scented sand), incorrectly discriminates, or 30 sec elapses. Rats that correctly discriminate are allowed to recover and consume the reinforcer. Rats that discriminate incorrectly are immediately removed from the chamber. This can continue through a variety of reversals and novel scents. The primary analysis is the accuracy for each scent pairing (cumulative proportion correct for each scent). The general findings from the Dig task suggest that it is a simple experimental preparation that can assess deficits in rats with bilateral frontal cortical damage compared to rats with unilateral parietal damage. The Dig task can also be easily incorporated into an existing cognitive test battery. The use of more tasks such as this one can lead to more accurate testing of frontal function following injury, which may lead to therapeutic options for treatment. All animal use was conducted in accordance with protocols approved by the Institutional Animal Care and Use Committee.
Neuroscience, Issue 71, Medicine, Neurobiology, Anatomy, Physiology, Psychology, Behavior, cognitive assessment, dig task, scent discrimination, olfactory, brain injury, traumatic brain injury, TBI, brain damage, rats, animal model
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Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
Authors: Michal S. Shoshan, Edit Y. Tshuva, Deborah E. Shalev.
Institutions: The Hebrew University of Jerusalem, The Hebrew University of Jerusalem.
Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox reactions. The Cu (I) complex of the peptide model of a Cu (I) binding metallochaperone protein, which includes the sequence MTCSGCSRPG (underlined is conserved), was determined in solution under inert conditions by NMR spectroscopy. NMR is a widely accepted technique for the determination of solution structures of proteins and peptides. Due to difficulty in crystallization to provide single crystals suitable for X-ray crystallography, the NMR technique is extremely valuable, especially as it provides information on the solution state rather than the solid state. Herein we describe all steps that are required for full three-dimensional structure determinations by NMR. The protocol includes sample preparation in an NMR tube, 1D and 2D data collection and processing, peak assignment and integration, molecular mechanics calculations, and structure analysis. Importantly, the analysis was first conducted without any preset metal-ligand bonds, to assure a reliable structure determination in an unbiased manner.
Chemistry, Issue 82, solution structure determination, NMR, peptide models, copper-binding proteins, copper complexes
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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees
Authors: Martin Fritz Brill, Maren Reuter, Wolfgang Rössler, Martin Fritz Strube-Bloss.
Institutions: University of Würzburg.
In both mammals and insects neuronal information is processed in different higher and lower order brain centers. These centers are coupled via convergent and divergent anatomical connections including feed forward and feedback wiring. Furthermore, information of the same origin is partially sent via parallel pathways to different and sometimes into the same brain areas. To understand the evolutionary benefits as well as the computational advantages of these wiring strategies and especially their temporal dependencies on each other, it is necessary to have simultaneous access to single neurons of different tracts or neuropiles in the same preparation at high temporal resolution. Here we concentrate on honeybees by demonstrating a unique extracellular long term access to record multi unit activity at two subsequent neuropiles1, the antennal lobe (AL), the first olfactory processing stage and the mushroom body (MB), a higher order integration center involved in learning and memory formation, or two parallel neuronal tracts2 connecting the AL with the MB. The latter was chosen as an example and will be described in full. In the supporting video the construction and permanent insertion of flexible multi channel wire electrodes is demonstrated. Pairwise differential amplification of the micro wire electrode channels drastically reduces the noise and verifies that the source of the signal is closely related to the position of the electrode tip. The mechanical flexibility of the used wire electrodes allows stable invasive long term recordings over many hours up to days, which is a clear advantage compared to conventional extra and intracellular in vivo recording techniques.
Neuroscience, Issue 89, honeybee brain, olfaction, extracellular long term recordings, double recordings, differential wire electrodes, single unit, multi-unit recordings
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Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
Authors: Bernd Rädle, Andrzej J. Rutkowski, Zsolt Ruzsics, Caroline C. Friedel, Ulrich H. Koszinowski, Lars Dölken.
Institutions: Max von Pettenkofer Institute, University of Cambridge, Ludwig-Maximilians-University Munich.
The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated. We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.
Genetics, Issue 78, Cellular Biology, Molecular Biology, Microbiology, Biochemistry, Eukaryota, Investigative Techniques, Biological Phenomena, Gene expression profiling, RNA synthesis, RNA processing, RNA decay, 4-thiouridine, 4sU-tagging, microarray analysis, RNA-seq, RNA, DNA, PCR, sequencing
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Cell Surface Marker Mediated Purification of iPS Cell Intermediates from a Reprogrammable Mouse Model
Authors: Christian M. Nefzger, Sara Alaei, Anja S. Knaupp, Melissa L. Holmes, Jose M. Polo.
Institutions: Monash University, Monash University.
Mature cells can be reprogrammed to a pluripotent state. These so called induced pluripotent stem (iPS) cells are able to give rise to all cell types of the body and consequently have vast potential for regenerative medicine applications. Traditionally iPS cells are generated by viral introduction of transcription factors Oct-4, Klf-4, Sox-2, and c-Myc (OKSM) into fibroblasts. However, reprogramming is an inefficient process with only 0.1-1% of cells reverting towards a pluripotent state, making it difficult to study the reprogramming mechanism. A proven methodology that has allowed the study of the reprogramming process is to separate the rare intermediates of the reaction from the refractory bulk population. In the case of mouse embryonic fibroblasts (MEFs), we and others have previously shown that reprogramming cells undergo a distinct series of changes in the expression profile of cell surface markers which can be used for the separation of these cells. During the early stages of OKSM expression successfully reprogramming cells lose fibroblast identity marker Thy-1.2 and up-regulate pluripotency associated marker Ssea-1. The final transition of a subset of Ssea-1 positive cells towards the pluripotent state is marked by the expression of Epcam during the late stages of reprogramming. Here we provide a detailed description of the methodology used to isolate reprogramming intermediates from cultures of reprogramming MEFs. In order to increase experimental reproducibility we use a reprogrammable mouse strain that has been engineered to express a transcriptional transactivator (m2rtTA) under control of the Rosa26 locus and OKSM under control of a doxycycline responsive promoter. Cells isolated from these mice are isogenic and express OKSM homogenously upon addition of doxycycline. We describe in detail the establishment of the reprogrammable mice, the derivation of MEFs, and the subsequent isolation of intermediates during reprogramming into iPS cells via fluorescent activated cells sorting (FACS).
Stem Cell Biology, Issue 91, Induced pluripotent stem cells; reprogramming; intermediates; fluorescent activated cells sorting; cell surface marker; reprogrammable mouse model; derivation of mouse embryonic fibroblasts
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Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures
Authors: Witold G. Szymanski, Sylwia Kierszniowska, Waltraud X. Schulze.
Institutions: Max Plank Institute of Molecular Plant Physiology, University of Hohenheim.
Plasma membrane microdomains are features based on the physical properties of the lipid and sterol environment and have particular roles in signaling processes. Extracting sterol-enriched membrane microdomains from plant cells for proteomic analysis is a difficult task mainly due to multiple preparation steps and sources for contaminations from other cellular compartments. The plasma membrane constitutes only about 5-20% of all the membranes in a plant cell, and therefore isolation of highly purified plasma membrane fraction is challenging. A frequently used method involves aqueous two-phase partitioning in polyethylene glycol and dextran, which yields plasma membrane vesicles with a purity of 95% 1. Sterol-rich membrane microdomains within the plasma membrane are insoluble upon treatment with cold nonionic detergents at alkaline pH. This detergent-resistant membrane fraction can be separated from the bulk plasma membrane by ultracentrifugation in a sucrose gradient 2. Subsequently, proteins can be extracted from the low density band of the sucrose gradient by methanol/chloroform precipitation. Extracted protein will then be trypsin digested, desalted and finally analyzed by LC-MS/MS. Our extraction protocol for sterol-rich microdomains is optimized for the preparation of clean detergent-resistant membrane fractions from Arabidopsis thaliana cell cultures. We use full metabolic labeling of Arabidopsis thaliana suspension cell cultures with K15NO3 as the only nitrogen source for quantitative comparative proteomic studies following biological treatment of interest 3. By mixing equal ratios of labeled and unlabeled cell cultures for joint protein extraction the influence of preparation steps on final quantitative result is kept at a minimum. Also loss of material during extraction will affect both control and treatment samples in the same way, and therefore the ratio of light and heave peptide will remain constant. In the proposed method either labeled or unlabeled cell culture undergoes a biological treatment, while the other serves as control 4.
Empty Value, Issue 79, Cellular Structures, Plants, Genetically Modified, Arabidopsis, Membrane Lipids, Intracellular Signaling Peptides and Proteins, Membrane Proteins, Isotope Labeling, Proteomics, plants, Arabidopsis thaliana, metabolic labeling, stable isotope labeling, suspension cell cultures, plasma membrane fractionation, two phase system, detergent resistant membranes (DRM), mass spectrometry, membrane microdomains, quantitative proteomics
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Identification of Olfactory Volatiles using Gas Chromatography-Multi-unit Recordings (GCMR) in the Insect Antennal Lobe
Authors: Kelsey J. R. P. Byers, Elischa Sanders, Jeffrey A. Riffell.
Institutions: University of Washington.
All organisms inhabit a world full of sensory stimuli that determine their behavioral and physiological response to their environment. Olfaction is especially important in insects, which use their olfactory systems to respond to, and discriminate amongst, complex odor stimuli. These odors elicit behaviors that mediate processes such as reproduction and habitat selection1-3. Additionally, chemical sensing by insects mediates behaviors that are highly significant for agriculture and human health, including pollination4-6, herbivory of food crops7, and transmission of disease8,9. Identification of olfactory signals and their role in insect behavior is thus important for understanding both ecological processes and human food resources and well-being. To date, the identification of volatiles that drive insect behavior has been difficult and often tedious. Current techniques include gas chromatography-coupled electroantennogram recording (GC-EAG), and gas chromatography-coupled single sensillum recordings (GC-SSR)10-12. These techniques proved to be vital in the identification of bioactive compounds. We have developed a method that uses gas chromatography coupled to multi-channel electrophysiological recordings (termed 'GCMR') from neurons in the antennal lobe (AL; the insect's primary olfactory center)13,14. This state-of-the-art technique allows us to probe how odor information is represented in the insect brain. Moreover, because neural responses to odors at this level of olfactory processing are highly sensitive owing to the degree of convergence of the antenna's receptor neurons into AL neurons, AL recordings will allow the detection of active constituents of natural odors efficiently and with high sensitivity. Here we describe GCMR and give an example of its use. Several general steps are involved in the detection of bioactive volatiles and insect response. Volatiles first need to be collected from sources of interest (in this example we use flowers from the genus Mimulus (Phyrmaceae)) and characterized as needed using standard GC-MS techniques14-16. Insects are prepared for study using minimal dissection, after which a recording electrode is inserted into the antennal lobe and multi-channel neural recording begins. Post-processing of the neural data then reveals which particular odorants cause significant neural responses by the insect nervous system. Although the example we present here is specific to pollination studies, GCMR can be expanded to a wide range of study organisms and volatile sources. For instance, this method can be used in the identification of odorants attracting or repelling vector insects and crop pests. Moreover, GCMR can also be used to identify attractants for beneficial insects, such as pollinators. The technique may be expanded to non-insect subjects as well.
Neuroscience, Issue 72, Neurobiology, Physiology, Biochemistry, Chemistry, Entomlogy, Behavior, electrophysiology, olfaction, olfactory system, insect, multi-channel recording, gas chromatography, pollination, bees, Bombus impatiens, antennae, brain, animal model
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Generation of Human Alloantigen-specific T Cells from Peripheral Blood
Authors: Burhan P Jama, Gerald P Morris.
Institutions: University of California, San Diego.
The study of human T lymphocyte biology often involves examination of responses to activating ligands. T cells recognize and respond to processed peptide antigens presented by MHC (human ortholog HLA) molecules through the T cell receptor (TCR) in a highly sensitive and specific manner. While the primary function of T cells is to mediate protective immune responses to foreign antigens presented by self-MHC, T cells respond robustly to antigenic differences in allogeneic tissues. T cell responses to alloantigens can be described as either direct or indirect alloreactivity. In alloreactivity, the T cell responds through highly specific recognition of both the presented peptide and the MHC molecule. The robust oligoclonal response of T cells to allogeneic stimulation reflects the large number of potentially stimulatory alloantigens present in allogeneic tissues. While the breadth of alloreactive T cell responses is an important factor in initiating and mediating the pathology associated with biologically-relevant alloreactive responses such as graft versus host disease and allograft rejection, it can preclude analysis of T cell responses to allogeneic ligands. To this end, this protocol describes a method for generating alloreactive T cells from naive human peripheral blood leukocytes (PBL) that respond to known peptide-MHC (pMHC) alloantigens. The protocol applies pMHC multimer labeling, magnetic bead enrichment and flow cytometry to single cell in vitro culture methods for the generation of alloantigen-specific T cell clones. This enables studies of the biochemistry and function of T cells responding to allogeneic stimulation.
Immunology, Issue 93, T cell, immunology, human cell culture, transplantation, flow cytometry, alloreactivity
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Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration
Authors: Yousuf O. Ali, Wilfredo Escala, Kai Ruan, R. Grace Zhai.
Institutions: University of Miami, Miller School of Medicine.
Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of these diseases, including Alzheimer's, Parkinson's and Huntington's disease are characterized by age-dependent deterioration in learning and memory functions and movement coordination2. Here we use behavioral assays, including the negative geotaxis assay3 and the aversive phototaxic suppression assay (APS assay)4,5, to show that some of the behavior characteristics associated with human neurodegeneration can be recapitulated in flies. In the negative geotaxis assay, the natural tendency of flies to move against gravity when agitated is utilized to study genes or conditions that may hinder locomotor capacities. In the APS assay, the learning and memory functions are tested in positively-phototactic flies trained to associate light with aversive bitter taste and hence avoid this otherwise natural tendency to move toward light. Testing these trained flies 6 hours post-training is used to assess memory functions. Using these assays, the contribution of any genetic or environmental factors toward developing neurodegeneration can be easily studied in flies.
Neuroscience, Issue 49, Geotaxis, phototaxis, behavior, Tau
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Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
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A Proboscis Extension Response Protocol for Investigating Behavioral Plasticity in Insects: Application to Basic, Biomedical, and Agricultural Research
Authors: Brian H. Smith, Christina M. Burden.
Institutions: Arizona State University.
Insects modify their responses to stimuli through experience of associating those stimuli with events important for survival (e.g., food, mates, threats). There are several behavioral mechanisms through which an insect learns salient associations and relates them to these events. It is important to understand this behavioral plasticity for programs aimed toward assisting insects that are beneficial for agriculture. This understanding can also be used for discovering solutions to biomedical and agricultural problems created by insects that act as disease vectors and pests. The Proboscis Extension Response (PER) conditioning protocol was developed for honey bees (Apis mellifera) over 50 years ago to study how they perceive and learn about floral odors, which signal the nectar and pollen resources a colony needs for survival. The PER procedure provides a robust and easy-to-employ framework for studying several different ecologically relevant mechanisms of behavioral plasticity. It is easily adaptable for use with several other insect species and other behavioral reflexes. These protocols can be readily employed in conjunction with various means for monitoring neural activity in the CNS via electrophysiology or bioimaging, or for manipulating targeted neuromodulatory pathways. It is a robust assay for rapidly detecting sub-lethal effects on behavior caused by environmental stressors, toxins or pesticides. We show how the PER protocol is straightforward to implement using two procedures. One is suitable as a laboratory exercise for students or for quick assays of the effect of an experimental treatment. The other provides more thorough control of variables, which is important for studies of behavioral conditioning. We show how several measures for the behavioral response ranging from binary yes/no to more continuous variable like latency and duration of proboscis extension can be used to test hypotheses. And, we discuss some pitfalls that researchers commonly encounter when they use the procedure for the first time.
Neuroscience, Issue 91, PER, conditioning, honey bee, olfaction, olfactory processing, learning, memory, toxin assay
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Barnes Maze Testing Strategies with Small and Large Rodent Models
Authors: Cheryl S. Rosenfeld, Sherry A. Ferguson.
Institutions: University of Missouri, Food and Drug Administration.
Spatial learning and memory of laboratory rodents is often assessed via navigational ability in mazes, most popular of which are the water and dry-land (Barnes) mazes. Improved performance over sessions or trials is thought to reflect learning and memory of the escape cage/platform location. Considered less stressful than water mazes, the Barnes maze is a relatively simple design of a circular platform top with several holes equally spaced around the perimeter edge. All but one of the holes are false-bottomed or blind-ending, while one leads to an escape cage. Mildly aversive stimuli (e.g. bright overhead lights) provide motivation to locate the escape cage. Latency to locate the escape cage can be measured during the session; however, additional endpoints typically require video recording. From those video recordings, use of automated tracking software can generate a variety of endpoints that are similar to those produced in water mazes (e.g. distance traveled, velocity/speed, time spent in the correct quadrant, time spent moving/resting, and confirmation of latency). Type of search strategy (i.e. random, serial, or direct) can be categorized as well. Barnes maze construction and testing methodologies can differ for small rodents, such as mice, and large rodents, such as rats. For example, while extra-maze cues are effective for rats, smaller wild rodents may require intra-maze cues with a visual barrier around the maze. Appropriate stimuli must be identified which motivate the rodent to locate the escape cage. Both Barnes and water mazes can be time consuming as 4-7 test trials are typically required to detect improved learning and memory performance (e.g. shorter latencies or path lengths to locate the escape platform or cage) and/or differences between experimental groups. Even so, the Barnes maze is a widely employed behavioral assessment measuring spatial navigational abilities and their potential disruption by genetic, neurobehavioral manipulations, or drug/ toxicant exposure.
Behavior, Issue 84, spatial navigation, rats, Peromyscus, mice, intra- and extra-maze cues, learning, memory, latency, search strategy, escape motivation
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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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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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Appetitive Associative Olfactory Learning in Drosophila Larvae
Authors: Anthi A. Apostolopoulou, Annekathrin Widmann, Astrid Rohwedder, Johanna E. Pfitzenmaier, Andreas S. Thum.
Institutions: University of Konstanz, University of Fribourg.
In the following we describe the methodological details of appetitive associative olfactory learning in Drosophila larvae. The setup, in combination with genetic interference, provides a handle to analyze the neuronal and molecular fundamentals of specifically associative learning in a simple larval brain. Organisms can use past experience to adjust present behavior. Such acquisition of behavioral potential can be defined as learning, and the physical bases of these potentials as memory traces1-4. Neuroscientists try to understand how these processes are organized in terms of molecular and neuronal changes in the brain by using a variety of methods in model organisms ranging from insects to vertebrates5,6. For such endeavors it is helpful to use model systems that are simple and experimentally accessible. The Drosophila larva has turned out to satisfy these demands based on the availability of robust behavioral assays, the existence of a variety of transgenic techniques and the elementary organization of the nervous system comprising only about 10,000 neurons (albeit with some concessions: cognitive limitations, few behavioral options, and richness of experience questionable)7-10. Drosophila larvae can form associations between odors and appetitive gustatory reinforcement like sugar11-14. In a standard assay, established in the lab of B. Gerber, animals receive a two-odor reciprocal training: A first group of larvae is exposed to an odor A together with a gustatory reinforcer (sugar reward) and is subsequently exposed to an odor B without reinforcement 9. Meanwhile a second group of larvae receives reciprocal training while experiencing odor A without reinforcement and subsequently being exposed to odor B with reinforcement (sugar reward). In the following both groups are tested for their preference between the two odors. Relatively higher preferences for the rewarded odor reflect associative learning - presented as a performance index (PI). The conclusion regarding the associative nature of the performance index is compelling, because apart from the contingency between odors and tastants, other parameters, such as odor and reward exposure, passage of time and handling do not differ between the two groups9.
Neuroscience, Issue 72, Developmental Biology, Neurobiology, Biochemistry, Molecular Biology, Physiology, Behavior, Drosophila, fruit fly, larvae, instar, olfaction, olfactory system, odor, 1-octanol, OCT, learning, reward, sugar, feeding, animal model
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
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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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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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Using Learning Outcome Measures to assess Doctoral Nursing Education
Authors: Glenn H. Raup, Jeff King, Romana J. Hughes, Natasha Faidley.
Institutions: Harris College of Nursing and Health Sciences, Texas Christian University.
Education programs at all levels must be able to demonstrate successful program outcomes. Grades alone do not represent a comprehensive measurement methodology for assessing student learning outcomes at either the course or program level. The development and application of assessment rubrics provides an unequivocal measurement methodology to ensure a quality learning experience by providing a foundation for improvement based on qualitative and quantitatively measurable, aggregate course and program outcomes. Learning outcomes are the embodiment of the total learning experience and should incorporate assessment of both qualitative and quantitative program outcomes. The assessment of qualitative measures represents a challenge for educators in any level of a learning program. Nursing provides a unique challenge and opportunity as it is the application of science through the art of caring. Quantification of desired student learning outcomes may be enhanced through the development of assessment rubrics designed to measure quantitative and qualitative aspects of the nursing education and learning process. They provide a mechanism for uniform assessment by nursing faculty of concepts and constructs that are otherwise difficult to describe and measure. A protocol is presented and applied to a doctoral nursing education program with recommendations for application and transformation of the assessment rubric to other education programs. Through application of these specially designed rubrics, all aspects of an education program can be adequately assessed to provide information for program assessment that facilitates the closure of the gap between desired and actual student learning outcomes for any desired educational competency.
Medicine, Issue 40, learning, outcomes, measurement, program, assessment, rubric
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
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Morris Water Maze Experiment
Authors: Joseph Nunez.
Institutions: Michigan State University (MSU).
The Morris water maze is widely used to study spatial memory and learning. Animals are placed in a pool of water that is colored opaque with powdered non-fat milk or non-toxic tempera paint, where they must swim to a hidden escape platform. Because they are in opaque water, the animals cannot see the platform, and cannot rely on scent to find the escape route. Instead, they must rely on external/extra-maze cues. As the animals become more familiar with the task, they are able to find the platform more quickly. Developed by Richard G. Morris in 1984, this paradigm has become one of the "gold standards" of behavioral neuroscience.
Behavior, Issue 19, Declarative, Hippocampus, Memory, Procedural, Rodent, Spatial Learning
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Operant Learning of Drosophila at the Torque Meter
Authors: Bjoern Brembs.
Institutions: Free University of Berlin.
For experiments at the torque meter, flies are kept on standard fly medium at 25°C and 60% humidity with a 12hr light/12hr dark regime. A standardized breeding regime assures proper larval density and age-matched cohorts. Cold-anesthetized flies are glued with head and thorax to a triangle-shaped hook the day before the experiment. Attached to the torque meter via a clamp, the fly's intended flight maneuvers are measured as the angular momentum around its vertical body axis. The fly is placed in the center of a cylindrical panorama to accomplish stationary flight. An analog to digital converter card feeds the yaw torque signal into a computer which stores the trace for later analysis. The computer also controls a variety of stimuli which can be brought under the fly's control by closing the feedback loop between these stimuli and the yaw torque trace. Punishment is achieved by applying heat from an adjustable infrared laser.
Neuroscience, Issue 16, operant, learning, Drosophila, fruit fly, insect, invertebrate, neuroscience, neurobiology, fly, conditioning
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Authors: Viktor Martyanov, Robert H. Gross.
Institutions: Dartmouth College.
SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference1. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data1. In this article, we utilize a web version of SCOPE2 to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs3,4 and has been used in other studies5-8. The three algorithms that comprise SCOPE are BEAM9, which finds non-degenerate motifs (ACCGGT), PRISM10, which finds degenerate motifs (ASCGWT), and SPACER11, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail1,2,9-11.
Genetics, Issue 51, gene regulation, computational biology, algorithm, promoter sequence motif
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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