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Pubmed Article
Leukemia prediction using sparse logistic regression.
PUBLISHED: 01-01-2013
We describe a supervised prediction method for diagnosis of acute myeloid leukemia (AML) from patient samples based on flow cytometry measurements. We use a data driven approach with machine learning methods to train a computational model that takes in flow cytometry measurements from a single patient and gives a confidence score of the patient being AML-positive. Our solution is based on an [Formula: see text] regularized logistic regression model that aggregates AML test statistics calculated from individual test tubes with different cell populations and fluorescent markers. The model construction is entirely data driven and no prior biological knowledge is used. The described solution scored a 100% classification accuracy in the DREAM6/FlowCAP2 Molecular Classification of Acute Myeloid Leukaemia Challenge against a golden standard consisting of 20 AML-positive and 160 healthy patients. Here we perform a more extensive validation of the prediction model performance and further improve and simplify our original method showing that statistically equal results can be obtained by using simple average marker intensities as features in the logistic regression model. In addition to the logistic regression based model, we also present other classification models and compare their performance quantitatively. The key benefit in our prediction method compared to other solutions with similar performance is that our model only uses a small fraction of the flow cytometry measurements making our solution highly economical.
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Published: 06-26-2013
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
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A Protocol for Computer-Based Protein Structure and Function Prediction
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Institutions: University of Michigan , University of Kansas.
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
Biochemistry, Issue 57, On-line server, I-TASSER, protein structure prediction, function prediction
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Identifying DNA Mutations in Purified Hematopoietic Stem/Progenitor Cells
Authors: Ziming Cheng, Ting Zhou, Azhar Merchant, Thomas J. Prihoda, Brian L. Wickes, Guogang Xu, Christi A. Walter, Vivienne I. Rebel.
Institutions: UT Health Science Center at San Antonio, UT Health Science Center at San Antonio, UT Health Science Center at San Antonio, UT Health Science Center at San Antonio, UT Health Science Center at San Antonio.
In recent years, it has become apparent that genomic instability is tightly related to many developmental disorders, cancers, and aging. Given that stem cells are responsible for ensuring tissue homeostasis and repair throughout life, it is reasonable to hypothesize that the stem cell population is critical for preserving genomic integrity of tissues. Therefore, significant interest has arisen in assessing the impact of endogenous and environmental factors on genomic integrity in stem cells and their progeny, aiming to understand the etiology of stem-cell based diseases. LacI transgenic mice carry a recoverable λ phage vector encoding the LacI reporter system, in which the LacI gene serves as the mutation reporter. The result of a mutated LacI gene is the production of β-galactosidase that cleaves a chromogenic substrate, turning it blue. The LacI reporter system is carried in all cells, including stem/progenitor cells and can easily be recovered and used to subsequently infect E. coli. After incubating infected E. coli on agarose that contains the correct substrate, plaques can be scored; blue plaques indicate a mutant LacI gene, while clear plaques harbor wild-type. The frequency of blue (among clear) plaques indicates the mutant frequency in the original cell population the DNA was extracted from. Sequencing the mutant LacI gene will show the location of the mutations in the gene and the type of mutation. The LacI transgenic mouse model is well-established as an in vivo mutagenesis assay. Moreover, the mice and the reagents for the assay are commercially available. Here we describe in detail how this model can be adapted to measure the frequency of spontaneously occurring DNA mutants in stem cell-enriched Lin-IL7R-Sca-1+cKit++(LSK) cells and other subpopulations of the hematopoietic system.
Infection, Issue 84, In vivo mutagenesis, hematopoietic stem/progenitor cells, LacI mouse model, DNA mutations, E. coli
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Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
Authors: Jeremy D. Smith, Abbie E. Ferris, Gary D. Heise, Richard N. Hinrichs, Philip E. Martin.
Institutions: University of Northern Colorado, Arizona State University, Iowa State University.
The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.
Bioengineering, Issue 87, prosthesis inertia, amputee locomotion, below-knee prosthesis, transtibial amputee
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Dynamic Visual Tests to Identify and Quantify Visual Damage and Repair Following Demyelination in Optic Neuritis Patients
Authors: Noa Raz, Michal Hallak, Tamir Ben-Hur, Netta Levin.
Institutions: Hadassah Hebrew-University Medical Center.
In order to follow optic neuritis patients and evaluate the effectiveness of their treatment, a handy, accurate and quantifiable tool is required to assess changes in myelination at the central nervous system (CNS). However, standard measurements, including routine visual tests and MRI scans, are not sensitive enough for this purpose. We present two visual tests addressing dynamic monocular and binocular functions which may closely associate with the extent of myelination along visual pathways. These include Object From Motion (OFM) extraction and Time-constrained stereo protocols. In the OFM test, an array of dots compose an object, by moving the dots within the image rightward while moving the dots outside the image leftward or vice versa. The dot pattern generates a camouflaged object that cannot be detected when the dots are stationary or moving as a whole. Importantly, object recognition is critically dependent on motion perception. In the Time-constrained Stereo protocol, spatially disparate images are presented for a limited length of time, challenging binocular 3-dimensional integration in time. Both tests are appropriate for clinical usage and provide a simple, yet powerful, way to identify and quantify processes of demyelination and remyelination along visual pathways. These protocols may be efficient to diagnose and follow optic neuritis and multiple sclerosis patients. In the diagnostic process, these protocols may reveal visual deficits that cannot be identified via current standard visual measurements. Moreover, these protocols sensitively identify the basis of the currently unexplained continued visual complaints of patients following recovery of visual acuity. In the longitudinal follow up course, the protocols can be used as a sensitive marker of demyelinating and remyelinating processes along time. These protocols may therefore be used to evaluate the efficacy of current and evolving therapeutic strategies, targeting myelination of the CNS.
Medicine, Issue 86, Optic neuritis, visual impairment, dynamic visual functions, motion perception, stereopsis, demyelination, remyelination
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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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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Authors: Marc N. Coutanche, Sharon L. Thompson-Schill.
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
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Detection of Invasive Pulmonary Aspergillosis in Haematological Malignancy Patients by using Lateral-flow Technology
Authors: Christopher Thornton, Gemma Johnson, Samir Agrawal.
Institutions: University of Exeter, Queen Mary University of London, St. Bartholomew's Hospital and The London NHS Trust.
Invasive pulmonary aspergillosis (IPA) is a leading cause of morbidity and mortality in haematological malignancy patients and hematopoietic stem cell transplant recipients1. Detection of IPA represents a formidable diagnostic challenge and, in the absence of a 'gold standard', relies on a combination of clinical data and microbiology and histopathology where feasible. Diagnosis of IPA must conform to the European Organization for Research and Treatment of Cancer and the National Institute of Allergy and Infectious Diseases Mycology Study Group (EORTC/MSG) consensus defining "proven", "probable", and "possible" invasive fungal diseases2. Currently, no nucleic acid-based tests have been externally validated for IPA detection and so polymerase chain reaction (PCR) is not included in current EORTC/MSG diagnostic criteria. Identification of Aspergillus in histological sections is problematic because of similarities in hyphal morphologies with other invasive fungal pathogens3, and proven identification requires isolation of the etiologic agent in pure culture. Culture-based approaches rely on the availability of biopsy samples, but these are not always accessible in sick patients, and do not always yield viable propagules for culture when obtained. An important feature in the pathogenesis of Aspergillus is angio-invasion, a trait that provides opportunities to track the fungus immunologically using tests that detect characteristic antigenic signatures molecules in serum and bronchoalveolar lavage (BAL) fluids. This has led to the development of the Platelia enzyme immunoassay (GM-EIA) that detects Aspergillus galactomannan and a 'pan-fungal' assay (Fungitell test) that detects the conserved fungal cell wall component (1 →3)-β-D-glucan, but not in the mucorales that lack this component in their cell walls1,4. Issues surrounding the accuracy of these tests1,4-6 has led to the recent development of next-generation monoclonal antibody (MAb)-based assays that detect surrogate markers of infection1,5. Thornton5 recently described the generation of an Aspergillus-specific MAb (JF5) using hybridoma technology and its use to develop an immuno-chromatographic lateral-flow device (LFD) for the point-of-care (POC) diagnosis of IPA. A major advantage of the LFD is its ability to detect activity since MAb JF5 binds to an extracellular glycoprotein antigen that is secreted during active growth of the fungus only5. This is an important consideration when using fluids such as lung BAL for diagnosing IPA since Aspergillus spores are a common component of inhaled air. The utility of the device in diagnosing IPA has been demonstrated using an animal model of infection, where the LFD displayed improved sensitivity and specificity compared to the Platelia GM and Fungitell (1 → 3)-β-D-glucan assays7. Here, we present a simple LFD procedure to detect Aspergillus antigen in human serum and BAL fluids. Its speed and accuracy provides a novel adjunct point-of-care test for diagnosis of IPA in haematological malignancy patients.
Immunology, Issue 61, Invasive pulmonary aspergillosis, acute myeloid leukemia, bone marrow transplant, diagnosis, monoclonal antibody, lateral-flow technology
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A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Authors: Daniel T. Claiborne, Jessica L. Prince, Eric Hunter.
Institutions: Emory University, Emory University.
The protective effect of many HLA class I alleles on HIV-1 pathogenesis and disease progression is, in part, attributed to their ability to target conserved portions of the HIV-1 genome that escape with difficulty. Sequence changes attributed to cellular immune pressure arise across the genome during infection, and if found within conserved regions of the genome such as Gag, can affect the ability of the virus to replicate in vitro. Transmission of HLA-linked polymorphisms in Gag to HLA-mismatched recipients has been associated with reduced set point viral loads. We hypothesized this may be due to a reduced replication capacity of the virus. Here we present a novel method for assessing the in vitro replication of HIV-1 as influenced by the gag gene isolated from acute time points from subtype C infected Zambians. This method uses restriction enzyme based cloning to insert the gag gene into a common subtype C HIV-1 proviral backbone, MJ4. This makes it more appropriate to the study of subtype C sequences than previous recombination based methods that have assessed the in vitro replication of chronically derived gag-pro sequences. Nevertheless, the protocol could be readily modified for studies of viruses from other subtypes. Moreover, this protocol details a robust and reproducible method for assessing the replication capacity of the Gag-MJ4 chimeric viruses on a CEM-based T cell line. This method was utilized for the study of Gag-MJ4 chimeric viruses derived from 149 subtype C acutely infected Zambians, and has allowed for the identification of residues in Gag that affect replication. More importantly, the implementation of this technique has facilitated a deeper understanding of how viral replication defines parameters of early HIV-1 pathogenesis such as set point viral load and longitudinal CD4+ T cell decline.
Infectious Diseases, Issue 90, HIV-1, Gag, viral replication, replication capacity, viral fitness, MJ4, CEM, GXR25
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Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
Authors: Lori E. Lowes, Benjamin D. Hedley, Michael Keeney, Alison L. Allan.
Institutions: London Health Sciences Centre, Western University, London Health Sciences Centre, Lawson Health Research Institute, Western University.
The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.
Medicine, Issue 84, Metastasis, circulating tumor cells (CTCs), CellSearch system, user defined marker characterization, in vivo, preclinical mouse model, clinical research
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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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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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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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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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Pre-clinical Evaluation of Tyrosine Kinase Inhibitors for Treatment of Acute Leukemia
Authors: Sandra Christoph, Alisa B. Lee-Sherick, Susan Sather, Deborah DeRyckere, Douglas K. Graham.
Institutions: University of Colorado Anschutz Medical Campus, University Hospital of Essen.
Receptor tyrosine kinases have been implicated in the development and progression of many cancers, including both leukemia and solid tumors, and are attractive druggable therapeutic targets. Here we describe an efficient four-step strategy for pre-clinical evaluation of tyrosine kinase inhibitors (TKIs) in the treatment of acute leukemia. Initially, western blot analysis is used to confirm target inhibition in cultured leukemia cells. Functional activity is then evaluated using clonogenic assays in methylcellulose or soft agar cultures. Experimental compounds that demonstrate activity in cell culture assays are evaluated in vivo using NOD-SCID-gamma (NSG) mice transplanted orthotopically with human leukemia cell lines. Initial in vivo pharmacodynamic studies evaluate target inhibition in leukemic blasts isolated from the bone marrow. This approach is used to determine the dose and schedule of administration required for effective target inhibition. Subsequent studies evaluate the efficacy of the TKIs in vivo using luciferase expressing leukemia cells, thereby allowing for non-invasive bioluminescent monitoring of leukemia burden and assessment of therapeutic response using an in vivo bioluminescence imaging system. This strategy has been effective for evaluation of TKIs in vitro and in vivo and can be applied for identification of molecularly-targeted agents with therapeutic potential or for direct comparison and prioritization of multiple compounds.
Medicine, Issue 79, Leukemia, Receptor Protein-Tyrosine Kinases, Molecular Targeted Therapy, Therapeutics, novel small molecule inhibitor, receptor tyrosine kinase, leukemia
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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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The α-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva
Authors: Cynthia L. Bristow, Mariya A. Babayeva, Rozbeh Modarresi, Carole P. McArthur, Santosh Kumar, Charles Awasom, Leo Ayuk, Annette Njinda, Paul Achu, Ronald Winston.
Institutions: Weill Cornell Medical College , University of Missouri-Kansas City-School of Dentistry, University of Missouri Kansas City- School of Pharmacy, Bamenda, NWP, Cameroon, Mezam Polyclinic HIV/AIDS Treatment Center, Cameroon, Institute for Human Genetics and Biochemistry.
There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time and temperature restrictions, technical sophistication, and cost of reagents, in particular monoclonal antibodies to measure CD4 on blood cells, the only currently acceptable method. A commonly used cost-saving and time-saving laboratory strategy is to calculate, rather than measure certain blood values. For example, LDL levels are calculated using the measured levels of total cholesterol, HDL, and triglycerides1. Thus, identification of cell-free correlates that directly regulate the number of CD4+ T cells could provide an accurate method for calculating CD4 counts due to the physiological relevance of the correlates. The number of stem cells that enter blood and are destined to become circulating CD4+ T cells is determined by the chemokine CXCL12 and its receptor CXCR4 due to their influence on locomotion2. The process of stem cell locomotion into blood is additionally regulated by cell surface human leukocyte elastase (HLECS) and the HLECS-reactive active α1proteinase inhibitor (α1PI, α1antitrypsin, SerpinA1)3. In HIV-1 disease, α1PI is inactivated due to disease processes 4. In the early asymptomatic categories of HIV-1 disease, active α1PI was found to be below normal in 100% of untreated HIV-1 patients (median=12 μM, and to achieve normal levels during the symptomatic categories4, 5. This pattern has been attributed to immune inactivation, not to insufficient synthesis, proteolytic inactivation, or oxygenation. We observed that in HIV-1 subjects with >220 CD4 cells/μl, CD4 counts were correlated with serum levels of active α1PI (r2=0.93, p<0.0001, n=26) and inactive α1PI (r2=0.91, p<0.0001, n=26) 5. Administration of α1PI to HIV-1 infected and uninfected subjects resulted in dramatic increases in CD4 counts suggesting α1PI participates in regulating the number of CD4+ T cells in blood 3. With stimulation, whole saliva contains sufficient serous exudate (plasma containing proteinaceous material that passes through blood vessel walls into saliva) to allow measurement of active α1PI and the correlation of this measurement is evidence that it is an accurate method for calculating CD4 counts. Briefly, sialogogues such as chewing gum or citric acid stimulate the exudation of serum into whole mouth saliva. After stimulating serum exudation, the activity of serum α1PI in saliva is measured by its capacity to inhibit elastase activity. Porcine pancreatic elastase (PPE) is a readily available inexpensive source of elastase. PPE binds to α1PI forming a one-to-one complex that prevents PPE from cleaving its specific substrates, one of which is the colorimetric peptide, succinyl-L-Ala-L-Ala-L-Ala-p-nitroanilide (SA3NA). Incubating saliva with a saturating concentration of PPE for 10 min at room temperature allows the binding of PPE to all the active α1PI in saliva. The resulting inhibition of PPE by active α1PI can be measured by adding the PPE substrate SA3NA. (Figure 1). Although CD4 counts are measured in terms of blood volume (CD4 cells/μl), the concentration of α1PI in saliva is related to the concentration of serum in saliva, not to volume of saliva since volume can vary considerably during the day and person to person6. However, virtually all the protein in saliva is due to serum content, and the protein content of saliva is measurable7. Thus, active α1PI in saliva is calculated as a ratio to saliva protein content and is termed the α1PI Index. Results presented herein demonstrate that the α1PI Index provides an accurate and precise physiologic method for calculating CD4 counts.
Medicine, Issue 63, CD4 count, saliva, antitrypsin, hematopoiesis, T cells, HIV/AIDS, clinical
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A Quantitative Fitness Analysis Workflow
Authors: A.P. Banks, C. Lawless, D.A. Lydall.
Institutions: Newcastle University Medical School.
Quantitative Fitness Analysis (QFA) is an experimental and computational workflow for comparing fitnesses of microbial cultures grown in parallel1,2,3,4. QFA can be applied to focused observations of single cultures but is most useful for genome-wide genetic interaction or drug screens investigating up to thousands of independent cultures. The central experimental method is the inoculation of independent, dilute liquid microbial cultures onto solid agar plates which are incubated and regularly photographed. Photographs from each time-point are analyzed, producing quantitative cell density estimates, which are used to construct growth curves, allowing quantitative fitness measures to be derived. Culture fitnesses can be compared to quantify and rank genetic interaction strengths or drug sensitivities. The effect on culture fitness of any treatments added into substrate agar (e.g. small molecules, antibiotics or nutrients) or applied to plates externally (e.g. UV irradiation, temperature) can be quantified by QFA. The QFA workflow produces growth rate estimates analogous to those obtained by spectrophotometric measurement of parallel liquid cultures in 96-well or 200-well plate readers. Importantly, QFA has significantly higher throughput compared with such methods. QFA cultures grow on a solid agar surface and are therefore well aerated during growth without the need for stirring or shaking. QFA throughput is not as high as that of some Synthetic Genetic Array (SGA) screening methods5,6. However, since QFA cultures are heavily diluted before being inoculated onto agar, QFA can capture more complete growth curves, including exponential and saturation phases3. For example, growth curve observations allow culture doubling times to be estimated directly with high precision, as discussed previously1. Here we present a specific QFA protocol applied to thousands of S. cerevisiae cultures which are automatically handled by robots during inoculation, incubation and imaging. Any of these automated steps can be replaced by an equivalent, manual procedure, with an associated reduction in throughput, and we also present a lower throughput manual protocol. The same QFA software tools can be applied to images captured in either workflow. We have extensive experience applying QFA to cultures of the budding yeast S. cerevisiae but we expect that QFA will prove equally useful for examining cultures of the fission yeast S. pombe and bacterial cultures.
Physiology, Issue 66, Medicine, Robotic, microbial, culture, yeast, array, library, high-throughput, analysis, fitness, growth rate, quantitative, solid agar
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Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model
Authors: Denise Lawrie, George Janossy, Maarten Roos, Deborah K. Glencross.
Institutions: National Health Laboratory Services (NHLS-SA), University of Witwatersrand, Lightcurve Films.
We present the video about assisting anti-retroviral therapy (ART) by an apt laboratory service - representing a South-African role model for economical large scale diagnostic testing. In the low-income countries inexpensive ART has transformed the prospects for the survival of HIV seropositive patients but there are doubts whether there is a need for the laboratory monitoring of ART and at what costs - in situations when the overall quality of pathology services can still be very low. The appropriate answer is to establish economically sound services with better coordination and stricter internal quality assessment than seen in western countries. This video, photographed at location in the National Health Laboratory Services (NHLS-SA) at the Witwatersrand University, Johannesburg, South Africa, provides such a coordinated scheme expanding the original 2-color CD4-CD45 PanLeucoGating strategy (PLG). Thus the six modules of the video presentation reveal the simplicity of a 4-color flow cytometric assay to combine haematological, immunological and virology-related tests in a single tube. These video modules are: (i) the set-up of instruments; (ii) sample preparations; (iii) testing absolute counts and monitoring quality for each sample by bead-count-rate; (iv) the heamatological CD45 test for white cell counts and differentials; (v) the CD4 counts, and (vi) the activation of CD8+ T cells measured by CD38 display, a viral load related parameter. The potential cost-savings are remarkable. This arrangement is a prime example for the feasibility of performing > 800-1000 tests per day with a stricter quality control than that applied in western laboratories, and also with a transfer of technology to other laboratories within a NHLS-SA network. Expert advisors, laboratory managers and policy makers who carry the duty of making decisions about introducing modern medical technology are frequently not in a position to see the latest technical details as carried out in the large regional laboratories with huge burdens of workload. Hence this video shows details of these new developments.
Immunology, Issue 44, Human Immunodeficiency virus (HIV); CD4 lymphocyte count, white cell count, CD45, panleucogating, lymphocyte activation, CD38, HIV viral load, antiretroviral therapy (ART), internal quality control
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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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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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