Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction.
The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries.
We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1–BRCA2 samples with RBF kernel of SVM.
We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance.
The SVM Classifier is available at .
The lateral mobility of individual, incoming human papillomavirus type 16 pseudoviruses (PsV) bound to live HeLa cells was studied by single particle tracking using fluorescence video microscopy. The trajectories were computationally analyzed in terms of diffusion rate and mode of motion as described by the moment scaling spectrum. Four distinct modes of mobility were seen: confined movement in small zones (30–60 nm in diameter), confined movement with a slow drift, fast random motion with transient confinement, and linear, directed movement for long distances. The directed movement was most prominent on actin-rich cell protrusions such as filopodia or retraction fibres, where the rate was similar to that measured for actin retrograde flow. It was, moreover, sensitive to perturbants of actin retrograde flow such as cytochalasin D, jasplakinolide, and blebbistatin. We found that transport along actin protrusions significantly enhanced HPV-16 infection in sparse tissue culture, cells suggesting a role for in vivo infection of basal keratinocytes during wound healing.
To replicate, viruses have to enter into host cells. Since they have no means of locomotion, they rely entirely on cellular transport systems to access the cellular compartments where replication occurs. Following individual virus particles by video microscopy, we found that human papillomavirus type 16, the main causative agent of cervical cancer, bound to long finger-like protrusions of cells. There, they were transported from the periphery to the cell body. The transport was mediated by a process termed actin retrograde flow, where viruses bound to cell surface molecules hooked up to filamentuos actin and were dragged along with the actin-like items on a transport belt. Entry into the cell occured at the cell body. The results raised the interesting possibility that viruses use retrograde flow when they infect wounded epidermal keratinocytes, where finger-like protrusions of cells are abundant.
Gastrointestinal contractions are controlled by an underlying bioelectrical activity. High-resolution spatiotemporal electrical mapping has become an important advance for investigating gastrointestinal electrical behaviors in health and motility disorders. However, research progress has been constrained by the low efficiency of the data analysis tasks. This work introduces a new efficient software package: GEMS (Gastrointestinal Electrical Mapping Suite), for analyzing and visualizing high-resolution multi-electrode gastrointestinal mapping data in spatiotemporal detail.
GEMS incorporates a number of new and previously validated automated analytical and visualization methods into a coherent framework coupled to an intuitive and user-friendly graphical user interface. GEMS is implemented using MATLAB®, which combines sophisticated mathematical operations and GUI compatibility. Recorded slow wave data can be filtered via a range of inbuilt techniques, efficiently analyzed via automated event-detection and cycle clustering algorithms, and high quality isochronal activation maps, velocity field maps, amplitude maps, frequency (time interval) maps and data animations can be rapidly generated. Normal and dysrhythmic activities can be analyzed, including initiation and conduction abnormalities. The software is distributed free to academics via a community user website and forum (http://sites.google.com/site/gimappingsuite).
This software allows for the rapid analysis and generation of critical results from gastrointestinal high-resolution electrical mapping data, including quantitative analysis and graphical outputs for qualitative analysis. The software is designed to be used by non-experts in data and signal processing, and is intended to be used by clinical researchers as well as physiologists and bioengineers. The use and distribution of this software package will greatly accelerate efforts to improve the understanding of the causes and clinical consequences of gastrointestinal electrical disorders, through high-resolution electrical mapping.
Slow wave; Spike; Signal processing; Electrophysiology; Motility; Tachygastria
Graphic User Interface (GUI) is commonly considered to be superior to Text-based User Interface (TUI). This study compares GUI and TUI in an electronic dental record system. Several usability analysis techniques compared the relative effectiveness of a GUI and a TUI. Expert users and novice users were evaluated in time required and steps needed to complete the task. A within-subject design was used to evaluate if the experience with either interface will affect task performance. The results show that the GUI interface was not better than the TUI for expert users. GUI interface was better for novice users. For novice users there was a learning transfer effect from TUI to GUI. This means a user interface is user-friendly or not depending on the mapping between the user interface and tasks. GUI by itself may or may not be better than TUI.
Graphic User Interface (GUI); Text-based User Interface (TUI); electronic dental record
Time-lapsed films of particle motion on the leading lamella of chick
heart fibroblasts and mouse peritoneal macrophages were analyzed. The
particles were composed of powdered glass or powdered aminated polystyrene
and were 0.5-1.0 micrometer in radius. Particle motions were described by
steps in position from one frame to the time-lapse movies to the next. The
statistics of the step-size distribution of the particles were consistent
with a particle in Brownian motion subject to a constant force. From the
Brownian movement, we have calculated the two-dimensional diffusion
coefficient of different particles. These vary by more than an order of
magnitude (10(-11)-10(-10) cm2/s) even for particles composed of the same
material and located very close to each other on the surface of the cell.
This variation was not correlated with particle size but is interpretable
as a result of different numbers of adhesive bonds holding the particles to
the cells. The constant component of particle movement can be interpreted
as a result of a constant force acting on each particle (0.1-1.0 x 10(-8)
dyn). Variations in the fractional coefficient for particles close to each
other on the cell surface do not yield corresponding differences in
velocity, suggesting that the frictional coefficient and the driving force
vary together. This is consistent with the hypothesis that the particles
are carried by flow of the membrane as a whole or by flow of some
submembrane material. The utility of our methods for monitoring cell motile
behavior in biologically interesting situations, such as a chemotactic
gradient, is discussed.
We present an Anti-Brownian Electrokinetic trap (ABEL trap) capable of trapping individual fluorescently labeled protein molecules in aqueous buffer. The ABEL trap operates by tracking the Brownian motion of a single fluorescent particle in solution, and applying a time-dependent electric field designed to induce an electrokinetic drift that cancels the Brownian motion. The trapping strength of the ABEL trap is limited by the latency of the feedback loop. In previous versions of the trap, this latency was set by the finite frame rate of the camera used for video-tracking. In the present system, the motion of the particle is tracked entirely in hardware (without a camera or image-processing software) using a rapidly rotating laser focus and lock-in detection. The feedback latency is set by the finite rate of arrival of photons. We demonstrate trapping of individual molecules of the protein GroEL in buffer, and we show confinement of single fluorophores of the dye Cy3 in water.
This Technical Note describes a novel modular framework for development and interlaboratory distribution and validation of 3D tractography algorithms based on in vivo diffusion tensor imaging (DTI) measurements. The proposed framework allows individual MRI research centers to benefit from new tractography algorithms developed at other independent centers by “plugging” new tractography modules directly into their own custom DTI software tools, such as existing graphical user interfaces (GUI) for visualizing brain white matter pathways. The proposed framework is based on the Java 3D programming platform, which provides an object-oriented programming (OOP) model and independence of computer hardware configuration and operating system. To demonstrate the utility of the proposed approach, a complete GUI for interactive DTI tractography was developed, along with two separate and interchangeable modules that implement two different tractography algorithms. Although the application discussed here relates to DTI tractography, the programming concepts presented here should be of interest to anyone who wishes to develop platform-independent GUI applications for interactive 3D visualization.
Diffusion tensor imaging; white matter; tractography
Good statistical models for analyzing and simulating multilocus recombination data exist but are not accessible to many biologists because their use requires reasonably sophisticated mathematical and computational implementation. While some labs have direct access to statisticians or programmers competent to carry out such analyses, many labs do not. We have created a platform independent application with an easy-to-use graphical user interface that will carry out such analyses including the simulations needed to bootstrap confidence intervals for the parameters of interest. This software should make multi-locus techniques accessible to labs that previously relied on less powerful and potentially statistically confounded single interval or double interval techniques.
We introduce InterferenceAnalyzer, an implementation with a user-friendly graphical interface incorporating previously developed algorithms for the analysis and simulation of multilocus recombination data. We demonstrate the use and features of the program with an example of multilocus tetrad data from the mustard plant, Arabidopsis thaliana, and the yeast, Saccharomyces cerevisiae.
InterferenceAnalyzer provides easy access to the powerful and appropriate statistical tools for the multi-locus analysis of genetic data.
Neurofilaments are long flexible cytoplasmic protein polymers that are transported rapidly but intermittently along the axonal processes of nerve cells. Current methods for studying this movement involve manual tracking of fluorescently tagged neurofilament polymers in videos acquired by time-lapse fluorescence microscopy. Here, we describe an automated tracking method that uses particle filtering to implement a recursive Bayesian estimation of the filament location in successive frames of video sequences. To increase the efficiency of this approach, we take advantage of the fact that neurofilament movement is confined within the boundaries of the axon. We use piecewise cubic spline interpolation to model the path of the axon and then we use this model to limit both the orientation and location of the neurofilament in the particle tracking algorithm. Based on these two spatial constraints, we develop a prior dynamic state model that generates significantly fewer particles than generic particle filtering, and we select an adequate observation model to produce a robust tracking method. We demonstrate the efficacy and efficiency of our method by performing tracking experiments on real time-lapse image sequences of neurofilament movement, and we show that the method performs well compared to manual tracking by an experienced user. This spatially constrained particle filtering approach should also be applicable to the movement of other axonally transported cargoes.
Axonal transport; Bayesian estimation; fluorescence microscopy; neurofilament; object tracking; particle filtering; spatial constraint
Brownian dynamics (BD) in a suitably constructed potential of mean force is an efficient and accurate method for simulating ion transport through wide ion channels. Here, a web-based graphical user interface (GUI) is presented for grand canonical Monte Carlo (GCMC) BD simulations of channel proteins: http://www.charmm-gui.org/input/gcmcbd. The webserver is designed to help users avoid most of the technical difficulties and issues encountered in setting up and simulating complex pore systems. GCMC/BD simulation results for three proteins, the voltage dependent anion channel (VDAC), α-Hemolysin, and the protective antigen pore of the anthrax toxin (PA), are presented to illustrate system setup, input preparation, and typical output (conductance, ion density profile, ion selectivity, and ion asymmetry). Two models for the input diffusion constants for potassium and chloride ions in the pore are compared: scaling of the bulk diffusion constants by 0.5, as deduced from previous all-atom molecular dynamics simulations of VDAC; and a hydrodynamics based model (HD) of diffusion through a tube. The HD model yields excellent agreement with experimental conductances for VDAC and α-Hemolysin, while scaling bulk diffusion constants by 0.5 leads to underestimates of 10–20%. For PA, simulated ion conduction values overestimate experimental values by a factor of 1.5 to 7 (depending on His protonation state and the transmembrane potential), implying that the currently available computational model of this protein requires further structural refinement.
GCMC/BD; Channel conductance; Ion selectivity; VDAC; α-Hemolysin; anthrax toxin protective antigen pore
Construction of a cone-beam computed tomography (CBCT) system for laboratory research usually requires integration of different software and hardware components. As a result, building and operating such a complex system require the expertise of researchers with significantly different backgrounds. Additionally, writing flexible code to control the hardware components of a CBCT system combined with designing a friendly graphical user interface (GUI) can be cumbersome and time consuming. An intuitive and flexible program structure, as well as the program GUI for CBCT acquisition, is presented in this note. The program was developed in National Instrument’s Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) graphical language and is designed to control a custom-built CBCT system but has been also used in a standard angiographic suite. The hardware components are commercially available to researchers and are in general provided with software drivers which are Lab-VIEW compatible. The program structure was designed as a sequential chain. Each step in the chain takes care of one or two hardware commands at a time; the execution of the sequence can be modified according to the CBCT system design. We have scanned and reconstructed over 200 specimens using this interface and present three examples which cover different areas of interest encountered in laboratory research. The resulting 3D data are rendered using a commercial workstation. The program described in this paper is available for use or improvement by other researchers.
Cone-beam micro-CT; graphical user interface; software design; LabVIEW
Construction of a cone-beam computed tomography (CBCT) system for laboratory research usually requires integration of different software and hardware components. As a result, building and operating such a complex system require the expertise of researchers with significantly different backgrounds. Additionally, writing flexible code to control the hardware components of a CBCT system combined with designing a friendly graphical user interface (GUI) can be cumbersome and time consuming. An intuitive and flexible program structure, as well as the program GUI for CBCT acquisition, is presented in this note. The program was developed in National Instrument’s Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) graphical language and is designed to control a custom-built CBCT system but has been also used in a standard angiographic suite. The hardware components are commercially available to researchers and are in general provided with software drivers which are LabVIEW compatible. The program structure was designed as a sequential chain. Each step in the chain takes care of one or two hardware commands at a time; the execution of the sequence can be modified according to the CBCT system design. We have scanned and reconstructed over 200 specimens using this interface and present three examples which cover different areas of interest encountered in laboratory research. The resulting 3D data are rendered using a commercial workstation. The program described in this paper is available for use or improvement by other researchers.
Cone-beam micro-CT; graphical user interface; software design, LabVIEW
Biophysicists use single particle tracking (SPT) methods to probe the dynamic behavior of individual proteins and lipids in cell membranes. The mean squared displacement (MSD) has proven to be a powerful tool for analyzing the data and drawing conclusions about membrane organization, including features like lipid rafts, protein islands, and confinement zones defined by cytoskeletal barriers. Here, we implement time series analysis as a new analytic tool to analyze further the motion of membrane proteins. The experimental data track the motion of 40 nm gold particles bound to Class I major histocompatibility complex (MHCI) molecules on the membranes of mouse hepatoma cells.
Our first novel result is that the tracks are significantly autocorrelated. Because of this, we developed linear autoregressive models to elucidate the autocorrelations. Estimates of the signal to noise ratio for the models show that the autocorrelated part of the motion is significant. Next, we fit the probability distributions of jump sizes with four different models. The first model is a general Weibull distribution that shows that the motion is characterized by an excess of short jumps as compared to a normal random walk. We also fit the data with a chi distribution which provides a natural estimate of the dimension d of the space in which a random walk is occurring. For the biological data, the estimates satisfy 1 < d < 2, implying that particle motion is not confined to a line, but also does not occur freely in the plane. The dimension gives a quantitative estimate of the amount of nanometer scale obstruction met by a diffusing molecule. We introduce a new distribution and use the generalized extreme value distribution to show that the biological data also have an excess of long jumps as compared to normal diffusion. These fits provide novel estimates of the microscopic diffusion constant.
Previous MSD analyses of SPT data have provided evidence for nanometer-scale confinement zones that restrict lateral diffusion, supporting the notion that plasma membrane organization is highly structured. Our demonstration that membrane protein motion is autocorrelated and is characterized by an excess of both short and long jumps reinforces the concept that the membrane environment is heterogeneous and dynamic. Autocorrelation analysis and modeling of the jump distributions are powerful new techniques for the analysis of SPT data and the development of more refined models of membrane organization.
The time series analysis also provides several methods of estimating the diffusion constant in addition to the constant provided by the mean squared displacement. The mean squared displacement for most of the biological data shows a power law behavior rather the linear behavior of Brownian motion. In this case, we introduce the notion of an instantaneous diffusion constant. All of the diffusion constants show a strong consistency for most of the biological data.
Time series analysis; Single particle tracking; Cell membrane; Mean squared displacement
Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli.
Localization of proteins to specific positions inside bacteria is crucial to several physiological processes, including chromosome organization, chemotaxis or cell division. Since bacterial cells do not possess internal sub-compartments (e.g., cell organelles) nor vesicle-based sorting systems, protein localization in bacteria must rely on alternative mechanisms. In many instances, the nature of these mechanisms remains to be elucidated. In Escherichia coli, the localization of aggregates of misfolded proteins at the poles or the center of the cell has recently been linked to aging. However, the molecular mechanisms governing this localization of the protein aggregates remain controversial. To identify these mechanisms, we have devised an integrated strategy combining innovative experimental and modeling approaches. Our results show the importance of the increased macromolecular crowding in the nucleoids, the regions within the cell where the bacterial chromosome preferentially condensates. They indicate that a purely diffusive pattern of aggregates mobility combined with nucleoid occlusion underlies their accumulation in polar and mid-cell positions.
For nanotoxicology investigations of air-borne particles to provide relevant results it is ever so important that the particle exposure of, for example cells, closely resembles the “real” exposure situation, that the dosimetry is well defined, and that the characteristics of the deposited nanoparticles are known in detail. By synthesizing the particles in the gas-phase and directly depositing them on lung cells the particle deposition conditions in the lung is closely mimicked. In this work we present a setup for generation of gas-borne nanoparticles of a variety of different materials with highly controlled and tunable particle characteristics, and demonstrate the method by generation of gold particles. Particle size, number concentration and mass of individual particles of the population are measured on-line by means of differential mobility analyzers (DMA) and an aerosol particle mass analyzer (APM), whereas primary particle size and internal structure are investigated by transmission electron microscopy. A method for estimating the surface area dose from the DMA-APM measurements is applied and we further demonstrate that for the setup used, a deposition time of around 1 h is needed for deposition onto cells in an air–liquid interface chamber, using electrostatic deposition, to reach a toxicological relevant surface area dose.
APM, aerosol particle; in vitro; nanoparticles; surface area; air–liquid interface; nanotoxicology
In the present study, a portable system based on a microcontroller has been developed to classify different kinds of honeys. In order to do this classification, a Simplified Fuzzy ARTMAP network (SFA) implemented in a microcontroller has been used. Due to memory limits when working with microcontrollers, it is necessary to optimize the use of both program and data memory. Thus, a Graphical User Interface (GUI) for MATLAB® has been developed in order to optimize the necessary parameters to programme the SFA in a microcontroller. The measures have been carried out by potentiometric techniques using a multielectrode made of seven different metals. Next, the neural network has been trained on a PC by means of the GUI in Matlab using the data obtained in the experimental phase. The microcontroller has been programmed with the obtained parameters and then, new samples have been analysed using the portable system in order to test the model. Results are very promising, as an 87.5% recognition rate has been achieved in the training phase, which suggests that this kind of procedures can be successfully used not only for honey classification, but also for many other kinds of food.
honey classification; neural networks; fuzzy ARTMAP; microcontroller
Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the nontechnical end-user in mind. By developing a toolkit that makes these analyses accessible to end users without significant programming experience, we hope to promote the more widespread use of wavelet analysis.
We have developed the WAVOS toolkit for wavelet analysis and visualization of oscillatory systems. WAVOS features both the continuous (Morlet) and discrete (Daubechies) wavelet transforms, with a simple, user-friendly graphical user interface within MATLAB. The interface allows for data to be imported from a number of standard file formats, visualized, processed and analyzed, and exported without use of the command line. Our work has been motivated by the challenges of circadian data, thus default settings appropriate to the analysis of such data have been pre-selected in order to minimize the need for fine-tuning. The toolkit is flexible enough to deal with a wide range of oscillatory signals, however, and may be used in more general contexts.
We have presented WAVOS: a comprehensive wavelet-based MATLAB toolkit that allows for easy visualization, exploration, and analysis of oscillatory data. WAVOS includes both the Morlet continuous wavelet transform and the Daubechies discrete wavelet transform. We have illustrated the use of WAVOS, and demonstrated its utility for the analysis of circadian data on both bioluminesence and wheel-running data. WAVOS is freely available at http://sourceforge.net/projects/wavos/files/
How viruses are transmitted across the mucosal epithelia of the respiratory, digestive, or excretory tracts, and how they spread from cell to cell and cause systemic infections, is incompletely understood. Recent advances from single virus tracking experiments have revealed conserved patterns of virus movements on the plasma membrane, including diffusive motions, drifting motions depending on retrograde flow of actin filaments or actin tail formation by polymerization, and confinement to submicrometer areas. Here, we discuss how viruses take advantage of cellular mechanisms that normally drive the movements of proteins and lipids on the cell surface. A concept emerges where short periods of fast diffusive motions allow viruses to rapidly move over several micrometers. Coupling to actin flow supports directional transport of virus particles during entry and cell-cell transmission, and local confinement coincides with either nonproductive stalling or infectious endocytic uptake. These conserved features of virus–host interactions upstream of infectious entry offer new perspectives for anti-viral interference.
We have developed a Matlab/C toolbox, Brain-SMART (System for Multivariate AutoRegressive Time series, or BSMART), for spectral analysis of continuous neural time series data recorded simultaneously from multiple sensors. Available functions include time series data importing/exporting, preprocessing (normalization and trend removal), AutoRegressive (AR) modeling (multivariate/bivariate model estimation and validation), spectral quantity estimation (auto power, coherence and Granger causality spectra), network analysis (including coherence and causality networks) and visualization (including data, power, coherence and causality views). The tools for investigating causal network structures are unique functions provided by this toolbox. All functionality has been integrated into a simple and user-friendly graphical user interface (GUI) environment designed for easy accessibility. Although we have tested the toolbox only on Windows and Linux operating systems, BSMART itself is system independent. This toolbox is freely available (http://www.sahs.uth.tmc.edu/hliang/software.htm) under the GNU public license for open source development.
Open source toolbox; Neural time series; Multivariate signal analysis; Network analysis; Granger causality
The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI) application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions.
DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations.
DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management.
The biological effects of acute particulate air pollution exposure in host innate immunity remain obscure and have relied largely on in vitro models. We hypothesized that single acute exposure to ambient or engineered particulate matter (PM) in the absence of other secondary stimuli would activate lung dendritic cells (DC) in vivo and provide information on the early immunological events of PM exposure and DC activation in a mouse model naïve to prior PM exposure. Activation of purified lung DC was studied following oropharyngeal instillation of ambient particulate matter (APM). We compared the effects of APM exposure with that of diesel-enriched PM (DEP), carbon black particles (CBP) and silver nanoparticles (AgP). We found that PM species induced variable cellular infiltration in the lungs and only APM exposure induced eosinophilic infiltration. Both APM and DEP activated pulmonary DC and promoted a Th2-type cytokine response from naïve CD4+ T cells ex vivo. Cultures of primary peribronchial lymph node cells from mice exposed to APM and DEP also displayed a Th2-type immune response ex vivo. We conclude that exposure of the lower airway to various PM species induces differential immunological responses and immunomodulation of DC subsets. Environmental APM and DEP activated DC in vivo and provoked a Th2 response ex vivo. By contrast, CBP and AgP induced altered lung tissue barrier integrity but failed to stimulate CD4+ T cells as effectively. Our work suggests that respirable pollutants activate the innate immune response with enhanced DC activation, pulmonary inflammation and Th2-immune responsiveness.
Innate immunity; Allergic immunity; Dendritic cell; Lung; Inflammation; Immunotoxicology; Toxicology; Particulate matter; Nanoparticles
In this paper we present a high-fidelity method for 2D and 3D image boundary segmentation. The algorithm is a novel combination of graph-cuts and initial image segmentation. The pre-segmentation using anisotropic vector diffusion and the fast marching method is employed so that the size of the graph being considered is significantly reduced. To further improve the segmentation accuracy, some user guidance is taken into account in finding the minimal graph cut. To this end, a user-friendly graphical user interface (GUI) is developed not only for visualization purposes but for user input and editing as well. The approaches and tools developed are validated on a number of 2D/3D biomedical imaging data, showing the high efficiency and effectiveness of our method.
Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool.
We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress.
SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.
Movements of transferrin and alpha 2-macroglobulin receptor molecules in the plasma membrane of cultured normal rat kidney (NRK) fibroblastic cells were investigated by video-enhanced contrast optical microscopy with 1.8 nm spatial precision and 33 ms temporal resolution by labeling the receptors with the ligand-coated nanometer-sized colloidal gold particles. For both receptor species, most of the movement trajectories are of the confined diffusion type, within domains of approximately 0.25 microns2 (500-700 nm in diagonal length). Movement within the domains is random with a diffusion coefficient approximately 10(-9) cm2/s, which is consistent with that expected for free Brownian diffusion of proteins in the plasma membrane. The receptor molecules move from one domain to one of the adjacent domains at an average frequency of 0.034 s-1 (the residence time within a domain approximately 29 s), indicating that the plasma membrane is compartmentalized for diffusion of membrane receptors and that long- range diffusion is the result of successive intercompartmental jumps. The macroscopic diffusion coefficients for these two receptor molecules calculated on the basis of the compartment size and the intercompartmental jump rate are approximately 2.4 x 10(-11) cm2/s, which is consistent with those determined by averaging the long-term movements of many particles. Partial destruction of the cytoskeleton decreased the confined diffusion mode, increased the simple diffusion mode, and induced the directed diffusion (transport) mode. These results suggest that the boundaries between compartments are made of dynamically fluctuating membrane skeletons (membrane-skeleton fence model).
Summary: Microbial communities have an important role in natural ecosystems and have an impact on animal and human health. Intuitive graphic and analytical tools that can facilitate the study of these communities are in short supply. This article introduces Microbial Community Analysis GUI, a graphical user interface (GUI) for the R-programming language (R Development Core Team, 2010). With this application, researchers can input aligned and clustered sequence data to create custom abundance tables and perform analyses specific to their needs. This GUI provides a flexible modular platform, expandable to include other statistical tools for microbial community analysis in the future.
Availability: The mcaGUI package and source are freely available as part of Bionconductor at http://www.bioconductor.org/packages/release/bioc/html/mcaGUI.html
Supplementary data and figures are available at Bioinformatics online.