Context-free spheres: A new method for rapid CPK image generation

A new algorithm for rendering CPK images of molecules is presented. The algorithm is based on the observation that (given certain assumptions) the appearance of a sphere representing an atom is independent of the atom's position or orientation. For example, the size of a sphere's projection on the viewing plane is independent of its distance from the viewing plane. The shading of a sphere is dependent only on lighting parameters that are identical for each atom type. This algorithm takes advantage of this observation by precomputing a template for each unique atom type and stamping these into the image with appropriate offsets in X, Y and Z. The implementation described herein enables generation of CPK images an order of magnitude faster than previous methods, with little sacrifice in image quality.     

Conic: A fast renderer for spacefilling molecules with shadows

We present an algorithm for generating images of molecules represented as a set of intersecting opaque spheres. Both perspective and shadows are computed to provide realistic visual cues. Compared to existing programs for generating similar images, our algorithm is both more accurate and several times faster. We present in detail the mathematics used in picture generation, along with examples of the computed images.     

Characterization of receptors with a new negative image: Use in molecular docking and lead optimization

The characterization of receptor binding sites is an important aspect of molecular docking, molecular recognition, and the structure-based design process. This characterization can take several forms: the receptor surface itself can be delineated or described, the space adjacent to the surface can be chemically mapped, or a negative image of the protein binding region can be generated. In this report, we describe a new method of constructing a negative image through generation of a set of spheres. These spheres lie along the receptor surface, and their centers represent possible ligand atom positions. By the method in which they are constructed, these spheres carry a limited amount of energetic and chemical information in addition to their primary geometric information. We test the accuracy of the image by comparing sphere positions to the positions of bound ligand atoms and propose a figure of merit for such tests. Then, we use the spheres to orient ligands in enzyme active sites and show how they can be used to generate low scoring configurations more efficiently than other approaches that search orientation space. In addition, two novel applications of these spheres are described: they are used to help identify structural differences among families of enzymes and to suggest points for ligand modification in analog design. Proteins 30:321–336, 1998. © 1998 Wiley-Liss, Inc.     

Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis

The accurate measurement of bacterial and protistan cell biomass is necessary for understanding their population and trophic dynamics in nature. Direct measurement of fluorescently stained cells is often the method of choice. The tedium of making such measurements visually on the large numbers of cells required has prompted the use of automatic image analysis for this purpose. Accurate measurements by image analysis require an accurate, reliable method of segmenting the image, that is, distinguishing the brightly fluorescing cells from a dark background. This is commonly done by visually choosing a threshold intensity value which most closely coincides with the outline of the cells as perceived by the operator. Ideally, an automated method based on the cell image characteristics should be used. Since the optical nature of edges in images of light-emitting, microscopic fluorescent objects is different from that of images generated by transmitted or reflected light, it seemed that automatic segmentation of such images may require special considerations. We tested nine automated threshold selection methods using standard fluorescent microspheres ranging in size and fluorescence intensity and fluorochrome-stained samples of cells from cultures of cyanobacteria, flagellates, and ciliates. The methods included several variations based on the maximum intensity gradient of the sphere profile (first derivative), the minimum in the second derivative of the sphere profile, the minimum of the image histogram, and the midpoint intensity. Our results indicated that thresholds determined visually and by first-derivative methods tended to overestimate the threshold, causing an underestimation of microsphere size. The method based on the minimum of the second derivative of the profile yielded the most accurate area estimates for spheres of different sizes and brightnesses and for four of the five cell types tested. A simple model of the optical properties of fluorescing objects and the video acquisition system is described which explains how the second derivative best approximates the position of the edge.     

Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis.

The accurate measurement of bacterial and protistan cell biomass is necessary for understanding their population and trophic dynamics in nature. Direct measurement of fluorescently stained cells is often the method of choice. The tedium of making such measurements visually on the large numbers of cells required has prompted the use of automatic image analysis for this purpose. Accurate measurements by image analysis require an accurate, reliable method of segmenting the image, that is, distinguishing the brightly fluorescing cells from a dark background. This is commonly done by visually choosing a threshold intensity value which most closely coincides with the outline of the cells as perceived by the operator. Ideally, an automated method based on the cell image characteristics should be used. Since the optical nature of edges in images of light-emitting, microscopic fluorescent objects is different from that of images generated by transmitted or reflected light, it seemed that automatic segmentation of such images may require special considerations. We tested nine automated threshold selection methods using standard fluorescent microspheres ranging in size and fluorescence intensity and fluorochrome-stained samples of cells from cultures of cyanobacteria, flagellates, and ciliates. The methods included several variations based on the maximum intensity gradient of the sphere profile (first derivative), the minimum in the second derivative of the sphere profile, the minimum of the image histogram, and the midpoint intensity. Our results indicated that thresholds determined visually and by first-derivative methods tended to overestimate the threshold, causing an underestimation of microsphere size. The method based on the minimum of the second derivative of the profile yielded the most accurate area estimates for spheres of different sizes and brightnesses and for four of the five cell types tested. A simple model of the optical properties of fluorescing objects and the video acquisition system is described which explains how the second derivative best approximates the position of the edge.     

Characterization of sphere-propagating cells with stem-like properties from DU145 prostate cancer cells

While accumulating evidence demonstrates the existence of prostate cancer stem cells (PCSCs), PCSCs have not been isolated and thoroughly characterized. We report here the enrichment and characterization of sphere-propagating cells with stem-like properties from DU145 PC cells in a defined serum-free medium (SFM). Approximately 1.25% of monolayer DU145 cells formed spheres in SFM and 26% of sphere cells formed secondary spheres. Spheres are enriched for cells expressing prostate basal and luminal cytokeratins (34βE12 and CK18) and for cancer stem cell markers, including CD44, CD24, and integrin α2β1. Upon culturing spheres under differentiating media conditions in the presence of 10% serum, cells positive for CD44 and CD24 were substantially reduced. Furthermore, spheres could be generated from the sphere-derived adherent cell cultures and xenograft tumors, demonstrating the stemness of DU145 spheres. We have maintained spheres for more than 30 passages within 1.5 years without noticeable loss of their “stemness”. Sphere cells possess self-renewal capacity, display significant increases in proliferation potential, and initiate xenograft tumors with enhanced capacity compared to monolayer DU145 cells. While EGF promoted the generation and maintenance of these stem-like cells, bFGF inhibited these events. Sphere cells proliferate slowly with a significant reduction in the activation of the PI3K-AKT pathway compared to monolayer DU145 cells. While knockdown of PTEN enhanced AKT activation, this did not affect the generation of primary spheres and the propagation of secondary spheres. Consistent with this observation, we were able to demonstrate the generation and propagation of spheres without the addition of external growth factors. This article is part of a Special Issue entitled: 11th European Symposium on Calcium.     

A microcomputer-based algorithm for digitized image simplification and information extraction

Spatial analysis of objects often requires significant image simplification prior to information extraction and application of a decision-making algorithm. Much decision making based on images (e.g., histologic diagnoses) requires identifying patterns in complex backgrounds (image simplification) and comparison of those patterns to other patterns (decision making). Automated extraction of information from images commonly requires the extraction system to recognize edges (contours) of structures and their internal discontinuities (such as gradations in density) and to selectively suppress irrelevant data in order to conserve memory and speed computation; data from homogeneous image areas occupy memory, but are noncontributory or redundant. This paper describes the development of a microcomputer-based algorithm that deletes all homogeneous information from overlaid digitized images, generating contours in the place of nonhomogeneities. Contours corresponding to different areas or objects depend on color differences between an object and its surroundings. Any set of contours can be deleted almost instantaneously, leaving only those of interest. Contours can be highlighted by an operator-driven interactive process if desired and can be deleted and retrieved until an appropriate image is obtained. This contour-generating and image-simplification algorithm facilitates three-dimensional reconstruction of an object from serial images by reducing the number of calculations required and yielding a cleaner final image.     

Multiplexed-Replica Exchange Molecular Dynamics Method for Protein Folding Simulation

Simulating protein folding thermodynamics starting purely from a protein sequence is a grand challenge of computational biology. Here, we present an algorithm to calculate a canonical distribution from molecular dynamics simulation of protein folding. This algorithm is based on the replica exchange method where the kinetic trapping problem is overcome by exchanging noninteracting replicas simulated at different temperatures. Our algorithm uses multiplexed-replicas with a number of independent molecular dynamics runs at each temperature. Exchanges of configurations between these multiplexed-replicas are also tried, rendering the algorithm applicable to large-scale distributed computing (i.e., highly heterogeneous parallel computers with processors having different computational power). We demonstrate the enhanced sampling of this algorithm by simulating the folding thermodynamics of a 23 amino acid miniprotein. We show that better convergence is achieved compared to constant temperature molecular dynamics simulation, with an efficient scaling to large number of computer processors. Indeed, this enhanced sampling results in (to our knowledge) the first example of a replica exchange algorithm that samples a folded structure starting from a completely unfolded state.     

McVol - A program for calculating protein volumes and identifying cavities by a Monte Carlo algorithm

In this paper, we describe a Monte Carlo method for determining the volume of a molecule. A molecule is considered to consist of hard, overlapping spheres. The surface of the molecule is defined by rolling a probe sphere over the surface of the spheres. To determine the volume of the molecule, random points are placed in a three-dimensional box, which encloses the whole molecule. The volume of the molecule in relation to the volume of the box is estimated by calculating the ratio of the random points placed inside the molecule and the total number of random points that were placed. For computational efficiency, we use a grid-cell based neighbor list to determine whether a random point is placed inside the molecule or not. This method in combination with a graph-theoretical algorithm is used to detect internal cavities and surface clefts of molecules. Since cavities and clefts are potential water binding sites, we place water molecules in the cavities. The potential water positions can be used in molecular dynamics calculations as well as in other molecular calculations. We apply this method to several proteins and demonstrate the usefulness of the program. The described methods are all implemented in the program McVol, which is available free of charge from our website at .     

Adaptive spatio-temporal denoising of fluoroscopic X-ray sequences

Lowering the cumulative radiation dose to a patient undergoing fluoroscopic examination requires efficient denoising algorithms. We propose a method, which extensively utilizes temporal dimension in order to maximize denoising efficiency. A set of subsequent images is processed and two estimates of denoised images are calculated. One is based on a special implementation of an adaptive edge preserving wavelet transform, while the other is based on the statistical method intersection of confidence intervals (ICI) rule. Wavelet transform is thought to produce high quality denoised images and ICI estimate can be used to further improve denoising performance about object edges. The estimates are fused to produce the final denoised image. We show that the proposed method performs very well and do not suffer from blurring in clinically important parts of images. As a result, its application could allow for significant lowering of the fluoroscope single frame dose.     

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review

Various methods and specialized software programs are available for processing twodimensional gel electrophoresis(2-DGE)images.However,due to the anomalies present in these images,a reliable,automated,and highly reproducible system for 2-DGE image analysis has still not been achieved.The most common anomalies found in 2-DGE images include vertical and horizontal streaking,fuzzy spots,and background noise,which greatly complicate computational analysis.In this paper,we review the preprocessing techniques applied to 2-DGE images for noise reduction,intensity normalization,and background correction.We also present a quantitative comparison of non-linear?ltering techniques applied to synthetic gel images,through analyzing the performance of the?lters under speci?c conditions.Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size,intensity,and degradation.Three types of noise were added to the images:Gaussian,Rayleigh,and exponential,with signal-to-noise ratios(SNRs)ranging 8–20 decibels(d B).We compared the performanceof wavelet,contourlet,total variation(TV),and wavelet-total variation(WTTV)techniques using parameters SNR and spot ef?ciency.In terms of spot ef?ciency,contourlet and TV were more sensitive to noise than wavelet and WTTV.Wavelet worked the best for images with SNR ranging 10–20 d B,whereas WTTV performed better with high noise levels.Wavelet also presented the best performance with any level of Gaussian noise and low levels(20–14 d B)of Rayleigh and exponential noise in terms of SNR.Finally,the performance of the non-linear?ltering techniques was evaluated using a real 2-DGE image with previously identi?ed proteins marked.Wavelet achieved the best detection rate for the real image.     

Single-scan stereotactic tumor biopsy and brachytherapy

Stereotactic tumor biopsy and brachytherapy catheter implantation can be accomplished with targets derived from computed axial tomography and magnetic resonance scans. Computer manipulation of image data allows both diagnostic and therapeutic procedures to be carried out from a single set of scan slices. This eliminates the need for repeat scanning as part of the surgical procedure. Microcomputer technology is sufficiently advanced to handle the images and graphics necessary for stereotactic neurosurgery. A system based on the IBM PC/AT designed for this purpose uses readily available graphics software and custom-designed imaging programs. Direct loading of computed axial or magnetic resonance scan images from magnetic tape can be accomplished. Determination of points, contours and volumes in three-dimensional space allows intraoperative alignment of image data and patient landmarks within the stereotactic head frame using pattern recognition overlays. Three-axis scaling for magnification correction along with rotational and linear data transformations provide the basis for single-scan stereotaxis. Interactive computer graphics integrate image, patient and frame coordinates for target determination. This method eliminates the need to design and fabricate nonmagnetic or radiolucent scanner-compatible devices.     

CX,an algorithm that identifies protruding atoms in proteins

MOTIVATION: A simple and fast algorithm is described that calculates a measure of protrusion (cx) for atoms in protein structures, directly useable with the common molecular graphics programs. RESULTS: A sphere of predetermined radius is centered around each non-hydrogen atom, and the volume occupied by the protein and the free volume within the sphere (internal and external volumes, respectively) are calculated. Atoms in protruding regions have a high ratio (cx) between the external and the internal volume. The program reads a PDB file, and writes the output in the same format, with cx values in the B factor field. Output structure files can be directly displayed with standard molecular graphics programs like RASMOL, MOLMOL, Swiss-PDB Viewer and colored according to cx values. We show the potential use of this program in the analysis of two protein-protein complexes and in the prediction of limited proteolysis sites in native proteins. AVAILABILITY: The algorithm is implemented in a standalone program written in C and its source is freely available at ftp.icgeb.trieste.it/pub/CX or on request from the authors.     

Visualization of sphere packs using a dataflow toolkit

We describe the construction of a simple application for the visualization of sphere packs, with applications to molecular graphics. Our development environment is IRIS Explorer, one of the new generation of so-called dataflow toolkits. We emphasize particularly the way in which working in such an environment facilitates the design and construction process, paying special attention to tools which aid the importing of data into the application, the design of the user interface, and the extension or modification of existing tools. Some examples of the use of the application in the field of molecular modeling are presented.     

The Fip35 WW Domain Folds with Structural and Mechanistic Heterogeneity in Molecular Dynamics Simulations

We describe molecular dynamics simulations resulting in the folding the Fip35 Hpin1 WW domain. The simulations were run on a distributed set of graphics processors, which are capable of providing up to two orders of magnitude faster computation than conventional processors. Using the Folding@home distributed computing system, we generated thousands of independent trajectories in an implicit solvent model, totaling over 2.73 ms of simulations. A small number of these trajectories folded; the folding proceeded along several distinct routes and the system folded into two distinct three-stranded β-sheet conformations, showing that the folding mechanism of this system is distinctly heterogeneous.     

Bayesian penalized-likelihood reconstruction algorithm suppresses edge artifacts in PET reconstruction based on point-spread-function

PurposeThe Bayesian penalized-likelihood reconstruction algorithm (BPL), Q.Clear, uses relative difference penalty as a regularization function to control image noise and the degree of edge-preservation in PET images. The present study aimed to determine the effects of suppression on edge artifacts due to point-spread-function (PSF) correction using a Q.Clear.MethodsSpheres of a cylindrical phantom contained a background of 5.3 kBq/mL of [¹⁸F]FDG and sphere-to-background ratios (SBR) of 16, 8, 4 and 2. The background also contained water and spheres containing 21.2 kBq/mL of [¹⁸F]FDG as non-background. All data were acquired using a Discovery PET/CT 710 and were reconstructed using three-dimensional ordered-subset expectation maximization with time-of-flight (TOF) and PSF correction (3D-OSEM), and Q.Clear with TOF (BPL). We investigated β-values of 200–800 using BPL. The PET images were analyzed using visual assessment and profile curves, edge variability and contrast recovery coefficients were measured.ResultsThe 38- and 27-mm spheres were surrounded by higher radioactivity concentration when reconstructed with 3D-OSEM as opposed to BPL, which suppressed edge artifacts. Images of 10-mm spheres had sharper overshoot at high SBR and non-background when reconstructed with BPL. Although contrast recovery coefficients of 10-mm spheres in BPL decreased as a function of increasing β, higher penalty parameter decreased the overshoot.ConclusionsBPL is a feasible method for the suppression of edge artifacts of PSF correction, although this depends on SBR and sphere size. Overshoot associated with BPL caused overestimation in small spheres at high SBR. Higher penalty parameter in BPL can suppress overshoot more effectively.     

录象机在生物组织连续切片的计算机三维重建系统中的应用

录象机(Video Tape Recorder)作为输入、输出设备,应用于“生物组织连续切片的计算机三维重建系统”中,其效果是令人满意的.由于研制的“同步再生”单元(Sync RecoveryUnit)有效地消除了静放噪声,从而使Cromemco微型计算机的图象输入接口SDD(Super DazzlerDigitizer)能够稳定地逐帧采集录象机输出的静止图象.录制并编辑计算机三维重建后的生物组织显微结构的空间旋转视图,使其在录象机的监视器上显示得更生动、逼真,更有体视感;还可脱离主机在任何场合演示重建结果.本文还就录象机在生物医学序列图象分析中的应用前景进行了讨论.     

Use of techniques derived from graph theory to compare secondary structure motifs in proteins

A substructure matching algorithm is described that can be used for the automatic identification of secondary structural motifs in three-dimensional protein structures from the Protein Data Bank. The proteins and motifs are stored for searching as labelled graphs, with the nodes of a graph corresponding to linear representations of helices and strands and the edges to the inter-line angles and distances. A modification of Ullman's subgraph isomorphism algorithm is described that can be used to search these graph representations. Tests with patterns from the protein structure literature demonstrate both the efficiency and the effectiveness of the search procedure, which has been implemented in FORTRAN 77 on a MicroVAX-II system, coupled to the molecular fitting program FRODO on an Evans and Sutherland PS300 graphics system.     

CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing

Estimating taxonomic content constitutes a key problem in metagenomic sequencing data analysis. However, extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available software. Here, we present CloudLCA, a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data analysis. Results show that CloudLCA (1) has a running time nearly linear with the increase of dataset magnitude, (2) displays linear speedup as the number of processors grows, especially for large datasets, and (3) reaches a speed of nearly 215 million reads each minute on a cluster with ten thin nodes. In comparison with MEGAN, a well-known metagenome analyzer, the speed of CloudLCA is up to 5 more times faster, and its peak memory usage is approximately 18.5% that of MEGAN, running on a fat node. CloudLCA can be run on one multiprocessor node or a cluster. It is expected to be part of MEGAN to accelerate analyzing reads, with the same output generated as MEGAN, which can be import into MEGAN in a direct way to finish the following analysis. Moreover, CloudLCA is a universal solution for finding the lowest common ancestor, and it can be applied in other fields requiring an LCA algorithm.     

Refinement of herpesvirus B-capsid structure on parallel supercomputers.

Electron cryomicroscopy and icosahedral reconstruction are used to obtain the three-dimensional structure of the 1250-A-diameter herpesvirus B-capsid. The centers and orientations of particles in focal pairs of 400-kV, spot-scan micrographs are determined and iteratively refined by common-lines-based local and global refinement procedures. We describe the rationale behind choosing shared-memory multiprocessor computers for executing the global refinement, which is the most computationally intensive step in the reconstruction procedure. This refinement has been implemented on three different shared-memory supercomputers. The speedup and efficiency are evaluated by using test data sets with different numbers of particles and processors. Using this parallel refinement program, we refine the herpesvirus B-capsid from 355-particle images to 13-A resolution. The map shows new structural features and interactions of the protein subunits in the three distinct morphological units: penton, hexon, and triplex of this T = 16 icosahedral particle.