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An evaluation framework and comparative analysis of the widely used first programming languages.
PUBLISHED: 01-01-2014
Computer programming is the core of computer science curriculum. Several programming languages have been used to teach the first course in computer programming, and such languages are referred to as first programming language (FPL). The pool of programming languages has been evolving with the development of new languages, and from this pool different languages have been used as FPL at different times. Though the selection of an appropriate FPL is very important, yet it has been a controversial issue in the presence of many choices. Many efforts have been made for designing a good FPL, however, there is no ample way to evaluate and compare the existing languages so as to find the most suitable FPL. In this article, we have proposed a framework to evaluate the existing imperative, and object oriented languages for their suitability as an appropriate FPL. Furthermore, based on the proposed framework we have devised a customizable scoring function to compute a quantitative suitability score for a language, which reflects its conformance to the proposed framework. Lastly, we have also evaluated the conformance of the widely used FPLs to the proposed framework, and have also computed their suitability scores.
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Published: 02-26-2014
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.
23 Related JoVE Articles!
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Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism
Authors: Letitia R. Naigles, Andrea T. Tovar.
Institutions: University of Connecticut.
One of the defining characteristics of autism spectrum disorder (ASD) is difficulty with language and communication.1 Children with ASD's onset of speaking is usually delayed, and many children with ASD consistently produce language less frequently and of lower lexical and grammatical complexity than their typically developing (TD) peers.6,8,12,23 However, children with ASD also exhibit a significant social deficit, and researchers and clinicians continue to debate the extent to which the deficits in social interaction account for or contribute to the deficits in language production.5,14,19,25 Standardized assessments of language in children with ASD usually do include a comprehension component; however, many such comprehension tasks assess just one aspect of language (e.g., vocabulary),5 or include a significant motor component (e.g., pointing, act-out), and/or require children to deliberately choose between a number of alternatives. These last two behaviors are known to also be challenging to children with ASD.7,12,13,16 We present a method which can assess the language comprehension of young typically developing children (9-36 months) and children with autism.2,4,9,11,22 This method, Portable Intermodal Preferential Looking (P-IPL), projects side-by-side video images from a laptop onto a portable screen. The video images are paired first with a 'baseline' (nondirecting) audio, and then presented again paired with a 'test' linguistic audio that matches only one of the video images. Children's eye movements while watching the video are filmed and later coded. Children who understand the linguistic audio will look more quickly to, and longer at, the video that matches the linguistic audio.2,4,11,18,22,26 This paradigm includes a number of components that have recently been miniaturized (projector, camcorder, digitizer) to enable portability and easy setup in children's homes. This is a crucial point for assessing young children with ASD, who are frequently uncomfortable in new (e.g., laboratory) settings. Videos can be created to assess a wide range of specific components of linguistic knowledge, such as Subject-Verb-Object word order, wh-questions, and tense/aspect suffixes on verbs; videos can also assess principles of word learning such as a noun bias, a shape bias, and syntactic bootstrapping.10,14,17,21,24 Videos include characters and speech that are visually and acoustically salient and well tolerated by children with ASD.
Medicine, Issue 70, Neuroscience, Psychology, Behavior, Intermodal preferential looking, language comprehension, children with autism, child development, autism
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One Dimensional Turing-Like Handshake Test for Motor Intelligence
Authors: Amir Karniel, Guy Avraham, Bat-Chen Peles, Shelly Levy-Tzedek, Ilana Nisky.
Institutions: Ben-Gurion University.
In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. However, this test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, and the movement of the human hand is a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human or artificial). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a two-alternative forced choice method and ask which of two systems is more human-like. We extract a quantitative grade for each model according to its resemblance to the human handshake motion and name it "Model Human-Likeness Grade" (MHLG). We present three methods to estimate the MHLG. (i) By calculating the proportion of subjects' answers that the model is more human-like than the human; (ii) By comparing two weighted sums of human and model handshakes we fit a psychometric curve and extract the point of subjective equality (PSE); (iii) By comparing a given model with a weighted sum of human and random signal, we fit a psychometric curve to the answers of the interrogator and extract the PSE for the weight of the human in the weighted sum. Altogether, we provide a protocol to test computational models of the human handshake. We believe that building a model is a necessary step in understanding any phenomenon and, in this case, in understanding the neural mechanisms responsible for the generation of the human handshake.
Neuroscience, Issue 46, Turing test, Human Machine Interface, Haptics, Teleoperation, Motor Control, Motor Behavior, Diagnostics, Perception, handshake, telepresence
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
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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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Quantitative Autonomic Testing
Authors: Peter Novak.
Institutions: University of Massachusetts Medical School.
Disorders associated with dysfunction of autonomic nervous system are quite common yet frequently unrecognized. Quantitative autonomic testing can be invaluable tool for evaluation of these disorders, both in clinic and research. There are number of autonomic tests, however, only few were validated clinically or are quantitative. Here, fully quantitative and clinically validated protocol for testing of autonomic functions is presented. As a bare minimum the clinical autonomic laboratory should have a tilt table, ECG monitor, continuous noninvasive blood pressure monitor, respiratory monitor and a mean for evaluation of sudomotor domain. The software for recording and evaluation of autonomic tests is critical for correct evaluation of data. The presented protocol evaluates 3 major autonomic domains: cardiovagal, adrenergic and sudomotor. The tests include deep breathing, Valsalva maneuver, head-up tilt, and quantitative sudomotor axon test (QSART). The severity and distribution of dysautonomia is quantitated using Composite Autonomic Severity Scores (CASS). Detailed protocol is provided highlighting essential aspects of testing with emphasis on proper data acquisition, obtaining the relevant parameters and unbiased evaluation of autonomic signals. The normative data and CASS algorithm for interpretation of results are provided as well.
Medicine, Issue 53, Deep breathing, Valsalva maneuver, tilt test, sudomotor testing, Composite Autonomic Severity Score, CASS
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Synthesis and Characterization of Functionalized Metal-organic Frameworks
Authors: Olga Karagiaridi, Wojciech Bury, Amy A. Sarjeant, Joseph T. Hupp, Omar K. Farha.
Institutions: Northwestern University, Warsaw University of Technology, King Abdulaziz University.
Metal-organic frameworks have attracted extraordinary amounts of research attention, as they are attractive candidates for numerous industrial and technological applications. Their signature property is their ultrahigh porosity, which however imparts a series of challenges when it comes to both constructing them and working with them. Securing desired MOF chemical and physical functionality by linker/node assembly into a highly porous framework of choice can pose difficulties, as less porous and more thermodynamically stable congeners (e.g., other crystalline polymorphs, catenated analogues) are often preferentially obtained by conventional synthesis methods. Once the desired product is obtained, its characterization often requires specialized techniques that address complications potentially arising from, for example, guest-molecule loss or preferential orientation of microcrystallites. Finally, accessing the large voids inside the MOFs for use in applications that involve gases can be problematic, as frameworks may be subject to collapse during removal of solvent molecules (remnants of solvothermal synthesis). In this paper, we describe synthesis and characterization methods routinely utilized in our lab either to solve or circumvent these issues. The methods include solvent-assisted linker exchange, powder X-ray diffraction in capillaries, and materials activation (cavity evacuation) by supercritical CO2 drying. Finally, we provide a protocol for determining a suitable pressure region for applying the Brunauer-Emmett-Teller analysis to nitrogen isotherms, so as to estimate surface area of MOFs with good accuracy.
Chemistry, Issue 91, Metal-organic frameworks, porous coordination polymers, supercritical CO2 activation, crystallography, solvothermal, sorption, solvent-assisted linker exchange
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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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Directed Differentiation of Induced Pluripotent Stem Cells towards T Lymphocytes
Authors: Fengyang Lei, Rizwanul Haque, Xiaofang Xiong, Jianxun Song.
Institutions: Pennsylvania State University College of Medicine.
Adoptive cell transfer (ACT) of antigen-specific CD8+ cytotoxic T lymphocytes (CTLs) is a promising treatment for a variety of malignancies 1. CTLs can recognize malignant cells by interacting tumor antigens with the T cell receptors (TCR), and release cytotoxins as well as cytokines to kill malignant cells. It is known that less-differentiated and central-memory-like (termed highly reactive) CTLs are the optimal population for ACT-based immunotherapy, because these CTLs have a high proliferative potential, are less prone to apoptosis than more differentiated cells and have a higher ability to respond to homeostatic cytokines 2-7. However, due to difficulties in obtaining a high number of such CTLs from patients, there is an urgent need to find a new approach to generate highly reactive Ag-specific CTLs for successful ACT-based therapies. TCR transduction of the self-renewable stem cells for immune reconstitution has a therapeutic potential for the treatment of diseases 8-10. However, the approach to obtain embryonic stem cells (ESCs) from patients is not feasible. Although the use of hematopoietic stem cells (HSCs) for therapeutic purposes has been widely applied in clinic 11-13, HSCs have reduced differentiation and proliferative capacities, and HSCs are difficult to expand in in vitro cell culture 14-16. Recent iPS cell technology and the development of an in vitro system for gene delivery are capable of generating iPS cells from patients without any surgical approach. In addition, like ESCs, iPS cells possess indefinite proliferative capacity in vitro, and have been shown to differentiate into hematopoietic cells. Thus, iPS cells have greater potential to be used in ACT-based immunotherapy compared to ESCs or HSCs. Here, we present methods for the generation of T lymphocytes from iPS cells in vitro, and in vivo programming of antigen-specific CTLs from iPS cells for promoting cancer immune surveillance. Stimulation in vitro with a Notch ligand drives T cell differentiation from iPS cells, and TCR gene transduction results in iPS cells differentiating into antigen-specific T cells in vivo, which prevents tumor growth. Thus, we demonstrate antigen-specific T cell differentiation from iPS cells. Our studies provide a potentially more efficient approach for generating antigen-specific CTLs for ACT-based therapies and facilitate the development of therapeutic strategies for diseases.
Stem Cell Biology, Issue 63, Immunology, T cells, induced pluripotent stem cells, differentiation, Notch signaling, T cell receptor, adoptive cell transfer
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A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry
Authors: Kerstin Trompelt, Janina Steinbeck, Mia Terashima, Michael Hippler.
Institutions: University of Münster, Carnegie Institution for Science.
The introduced protocol provides a tool for the analysis of multiprotein complexes in the thylakoid membrane, by revealing insights into complex composition under different conditions. In this protocol the approach is demonstrated by comparing the composition of the protein complex responsible for cyclic electron flow (CEF) in Chlamydomonas reinhardtii, isolated from genetically different strains. The procedure comprises the isolation of thylakoid membranes, followed by their separation into multiprotein complexes by sucrose density gradient centrifugation, SDS-PAGE, immunodetection and comparative, quantitative mass spectrometry (MS) based on differential metabolic labeling (14N/15N) of the analyzed strains. Detergent solubilized thylakoid membranes are loaded on sucrose density gradients at equal chlorophyll concentration. After ultracentrifugation, the gradients are separated into fractions, which are analyzed by mass-spectrometry based on equal volume. This approach allows the investigation of the composition within the gradient fractions and moreover to analyze the migration behavior of different proteins, especially focusing on ANR1, CAS, and PGRL1. Furthermore, this method is demonstrated by confirming the results with immunoblotting and additionally by supporting the findings from previous studies (the identification and PSI-dependent migration of proteins that were previously described to be part of the CEF-supercomplex such as PGRL1, FNR, and cyt f). Notably, this approach is applicable to address a broad range of questions for which this protocol can be adopted and e.g. used for comparative analyses of multiprotein complex composition isolated from distinct environmental conditions.
Microbiology, Issue 85, Sucrose density gradients, Chlamydomonas, multiprotein complexes, 15N metabolic labeling, thylakoids
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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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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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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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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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Designing a Bio-responsive Robot from DNA Origami
Authors: Eldad Ben-Ishay, Almogit Abu-Horowitz, Ido Bachelet.
Institutions: Bar-Ilan University.
Nucleic acids are astonishingly versatile. In addition to their natural role as storage medium for biological information1, they can be utilized in parallel computing2,3 , recognize and bind molecular or cellular targets4,5 , catalyze chemical reactions6,7 , and generate calculated responses in a biological system8,9. Importantly, nucleic acids can be programmed to self-assemble into 2D and 3D structures10-12, enabling the integration of all these remarkable features in a single robot linking the sensing of biological cues to a preset response in order to exert a desired effect. Creating shapes from nucleic acids was first proposed by Seeman13, and several variations on this theme have since been realized using various techniques11,12,14,15 . However, the most significant is perhaps the one proposed by Rothemund, termed scaffolded DNA origami16. In this technique, the folding of a long (>7,000 bases) single-stranded DNA 'scaffold' is directed to a desired shape by hundreds of short complementary strands termed 'staples'. Folding is carried out by temperature annealing ramp. This technique was successfully demonstrated in the creation of a diverse array of 2D shapes with remarkable precision and robustness. DNA origami was later extended to 3D as well17,18 . The current paper will focus on the caDNAno 2.0 software19 developed by Douglas and colleagues. caDNAno is a robust, user-friendly CAD tool enabling the design of 2D and 3D DNA origami shapes with versatile features. The design process relies on a systematic and accurate abstraction scheme for DNA structures, making it relatively straightforward and efficient. In this paper we demonstrate the design of a DNA origami nanorobot that has been recently described20. This robot is 'robotic' in the sense that it links sensing to actuation, in order to perform a task. We explain how various sensing schemes can be integrated into the structure, and how this can be relayed to a desired effect. Finally we use Cando21 to simulate the mechanical properties of the designed shape. The concept we discuss can be adapted to multiple tasks and settings.
Bioengineering, Issue 77, Genetics, Biomedical Engineering, Molecular Biology, Medicine, Genomics, Nanotechnology, Nanomedicine, DNA origami, nanorobot, caDNAno, DNA, DNA Origami, nucleic acids, DNA structures, CAD, sequencing
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Flying Insect Detection and Classification with Inexpensive Sensors
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Institutions: University of California, Riverside, University of California, Riverside, University of São Paulo - USP, ISCA Technologies.
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
Bioengineering, Issue 92, flying insect detection, automatic insect classification, pseudo-acoustic optical sensors, Bayesian classification framework, flight sound, circadian rhythm
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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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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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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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Long-term Lethal Toxicity Test with the Crustacean Artemia franciscana
Authors: Loredana Manfra, Federica Savorelli, Marco Pisapia, Erika Magaletti, Anna Maria Cicero.
Institutions: Institute for Environmental Protection and Research, Regional Agency for Environmental Protection in Emilia-Romagna.
Our research activities target the use of biological methods for the evaluation of environmental quality, with particular reference to saltwater/brackish water and sediment. The choice of biological indicators must be based on reliable scientific knowledge and, possibly, on the availability of standardized procedures. In this article, we present a standardized protocol that used the marine crustacean Artemia to evaluate the toxicity of chemicals and/or of marine environmental matrices. Scientists propose that the brine shrimp (Artemia) is a suitable candidate for the development of a standard bioassay for worldwide utilization. A number of papers have been published on the toxic effects of various chemicals and toxicants on brine shrimp (Artemia). The major advantage of this crustacean for toxicity studies is the overall availability of the dry cysts; these can be immediately used in testing and difficult cultivation is not demanded1,2. Cyst-based toxicity assays are cheap, continuously available, simple and reliable and are thus an important answer to routine needs of toxicity screening, for industrial monitoring requirements or for regulatory purposes3. The proposed method involves the mortality as an endpoint. The numbers of survivors were counted and percentage of deaths were calculated. Larvae were considered dead if they did not exhibit any internal or external movement during several seconds of observation4. This procedure was standardized testing a reference substance (Sodium Dodecyl Sulfate); some results are reported in this work. This article accompanies a video that describes the performance of procedural toxicity testing, showing all the steps related to the protocol.
Chemistry, Issue 62, Artemia franciscana, bioassays, chemical substances, crustaceans, marine environment
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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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Reaggregate Thymus Cultures
Authors: Andrea White, Eric Jenkinson, Graham Anderson.
Institutions: University of Birmingham .
Stromal cells within lymphoid tissues are organized into three-dimensional structures that provide a scaffold that is thought to control the migration and development of haemopoeitic cells. Importantly, the maintenance of this three-dimensional organization appears to be critical for normal stromal cell function, with two-dimensional monolayer cultures often being shown to be capable of supporting only individual fragments of lymphoid tissue function. In the thymus, complex networks of cortical and medullary epithelial cells act as a framework that controls the recruitment, proliferation, differentiation and survival of lymphoid progenitors as they undergo the multi-stage process of intrathymic T-cell development. Understanding the functional role of individual stromal compartments in the thymus is essential in determining how the thymus imposes self/non-self discrimination. Here we describe a technique in which we exploit the plasticity of fetal tissues to re-associate into intact three-dimensional structures in vitro, following their enzymatic disaggregation. The dissociation of fetal thymus lobes into heterogeneous cellular mixtures, followed by their separation into individual cellular components, is then combined with the in vitro re-association of these desired cell types into three-dimensional reaggregate structures at defined ratios, thereby providing an opportunity to investigate particular aspects of T-cell development under defined cellular conditions. (This article is based on work first reported Methods in Molecular Biology 2007, Vol. 380 pages 185-196).
Immunology, Issue 18, Springer Protocols, Thymus, 2-dGuo, Thymus Organ Cultures, Immune Tolerance, Positive and Negative Selection, Lymphoid Development
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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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Designing and Implementing Nervous System Simulations on LEGO Robots
Authors: Daniel Blustein, Nikolai Rosenthal, Joseph Ayers.
Institutions: Northeastern University, Bremen University of Applied Sciences.
We present a method to use the commercially available LEGO Mindstorms NXT robotics platform to test systems level neuroscience hypotheses. The first step of the method is to develop a nervous system simulation of specific reflexive behaviors of an appropriate model organism; here we use the American Lobster. Exteroceptive reflexes mediated by decussating (crossing) neural connections can explain an animal's taxis towards or away from a stimulus as described by Braitenberg and are particularly well suited for investigation using the NXT platform.1 The nervous system simulation is programmed using LabVIEW software on the LEGO Mindstorms platform. Once the nervous system is tuned properly, behavioral experiments are run on the robot and on the animal under identical environmental conditions. By controlling the sensory milieu experienced by the specimens, differences in behavioral outputs can be observed. These differences may point to specific deficiencies in the nervous system model and serve to inform the iteration of the model for the particular behavior under study. This method allows for the experimental manipulation of electronic nervous systems and serves as a way to explore neuroscience hypotheses specifically regarding the neurophysiological basis of simple innate reflexive behaviors. The LEGO Mindstorms NXT kit provides an affordable and efficient platform on which to test preliminary biomimetic robot control schemes. The approach is also well suited for the high school classroom to serve as the foundation for a hands-on inquiry-based biorobotics curriculum.
Neuroscience, Issue 75, Neurobiology, Bioengineering, Behavior, Mechanical Engineering, Computer Science, Marine Biology, Biomimetics, Marine Science, Neurosciences, Synthetic Biology, Robotics, robots, Modeling, models, Sensory Fusion, nervous system, Educational Tools, programming, software, lobster, Homarus americanus, animal model
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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.