SEARCH · Search PubMed
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Experimental and computational studies indicate that the formation of a series of zinc 4-cyclohexene-1,2-dicarboxylates takes place under thermodynamic rather than kinetic control.
With the increasing availability of surface extraction techniques for magnetic resonance and x-ray computed tomography images, realistic head models can be readily generated as forward models in the analysis of electroencephalography (EEG) and magnetoencephalography (MEG) data. Inverse analysis of this data, however, requires that the forward model be computationally efficient. We propose two methods for approximating the EEG forward model using realistic head shapes. The 'sensor-fitted sphere' approach fits a multilayer sphere individually to each sensor, and the 'three-dimensional interpolation' scheme interpolates using a grid on which a numerical boundary element method (BEM) solution has been precomputed. We have characterized the performance of each method in terms of magnitude and subspace error metrics, as well as computational and memory requirements. We have also made direct performance comparisons with traditional spherical models. The approximation provided by the interpolative scheme had an accuracy nearly identical to full BEM, even within 3 mm of the inner skull surface. Forward model computation during inverse procedures was approximately 30 times faster than for a traditional three-shell spherical model. Cast in this framework, high-fidelity numerical solutions currently viewed as computationally prohibitive for solving the inverse problem (e.g. linear Galerkin BEM) can be rapidly recomputed in a highly efficient manner. The sensor-fitting method has a similar one-time cost to the BEM method, and while it produces some improvement over a standard three-shell sphere, its performance does not approach that of the interpolation method. In both methods, there is a one-time cost associated with precomputing the forward solution over a set of grid points.
PURPOSE: This study evaluated the precision of fit between an implant framework and a patient simulation model that consisted of five implant abutments located in the mandibular symphysis area. One-piece cast frameworks were compared with Procera machined and laser-welded frameworks with laser videography. MATERIAL AND METHODS: Five frameworks of each type were measured with a laser digitizer and a graphics computer program to determine a single point represented as the "Centroid" for each framework component and each implant abutment. Differences between the paired centroids for each framework/abutment interface are reported as x- and y-axis displacements, and z-axis gaps. The direction of the x- and y-axis displacements was determined. RESULTS: There were significant differences (p < 0.05) in the precision of fit between both the one-piece cast frameworks and the Procera frameworks, when compared with the abutments in the patient simulation model. The laser-welded framework exhibited a more precise fit than the one-piece casting, with significant differences at four of the five prosthodontic interfaces, when evaluated by the mean z-axis gap at the centroid points.
The concept of graph symmetry is explained in terms of the vertex automorphism group, which is a subgroup of the complete vertex permutation group. The automorphism group can be deduced from the automorphism partition of graph vertices. An algorithm is described which constructs the automorphism group of a graph from the automorphism vertex partitioning. The algorithm is useful especially for graphs which contain more than one vertex-partition set. Several well-known topological symmetry perception algorithms that yield automorphism partitions are compared. The comparison is favorable to the Shelley-Munk algorithm, developed in the framework of the SESAMI system for computer-enhanced structure elucidation.
This paper describes a semi-parametric Bayesian approach for estimating receiver operating characteristic (ROC) curves based on mixtures of Dirichlet process priors (MDP). We address difficulties in modelling the underlying distribution of screening scores due to non-normality that may lead to incorrect choices of diagnostic cut-offs and unreliable estimates of prevalence of the disease. MDP is a robust tool for modelling non-standard diagnostic distributions associated with imperfect classification of an underlying diseased population, for example, when a diagnostic test is not a gold standard. For posterior computations, we propose an efficient Gibbs sampling framework based on a finite-dimensional approximation to MDP. We show, using both simulated and real data sets, that MDP modelling for ROC curve estimation closely parallels the frequentist kernel density estimation (KDE) approach.
C4G1, a murine mAb reactive with the platelet gpIIb/IIIa integrin, was humanized for potential treatment of thrombosis-related disorders. The variable regions of light- and heavy-chain cDNAs from the C4G1 hybridoma were first cloned and sequenced. Humanized C4G1 Ab of the IgG1 isotype was constructed by combining the complementarity-determining regions of C4G1 with human framework and constant regions. The human framework was chosen to maximize homology with the C4G1 variable region sequence, and a computer model of C4G1 was used to aid design of the final framework sequence. Genetic constructs were also developed to produce Fab and F(ab')2 fragments of the humanized C4G1 Ab. The humanized IgG1 Ab as well as the Fab and F(ab')2 fragments showed equivalent binding affinities to their murine counterparts, indicating no loss in binding affinity during the humanization process. The humanized Ab and its fragments were also shown to inhibit platelet aggregation and to inhibit binding of fibrinogen to gpIIb/IIIa in vitro.
An overview of computer models developed since the late seventies, which enable the simulation of the primary effects of spinal cord stimulation (SCS) on nerve fibres, is presented. These models consist of a 3-dimensional volume conductor model, representing anatomical structures and their electrical conductivities, and cable models representing the electrical behaviour of nerve fibres. The characteristics of these models and their relation to anatomy and physiology, as well as the calculation of stimulation-induced electrical fields and their effect on nerve fibre models, are reviewed. It is shown that most characteristics of SCS as predicted by computer modelling correspond well with empirical data. Accordingly, a theoretical framework describing the relations between relevant parameters in SCS is presented. Finally, it is shown how theory and computer modeling are applied to improve the efficacy of SCS by the optimization of its technique, primarily by the design of new epidural electrodes.
The gibbon karyotype is known to be extensively rearranged when compared to the human and to the ancestral primate karyotype. By combining a bioinformatics (paired-end sequence analysis) approach and a molecular cytogenetics approach, we have refined the synteny block arrangement of the white-cheeked gibbon (Nomascus leucogenys, NLE) with respect to the human genome. We provide the first detailed clone framework map of the gibbon genome and refine the location of 86 evolutionary breakpoints to <1 Mb resolution. An additional 12 breakpoints, mapping primarily to centromeric and telomeric regions, were mapped to approximately 5 Mb resolution. Our combined FISH and BES analysis indicates that we have effectively subcloned 49 of these breakpoints within NLE gibbon BAC clones, mapped to a median resolution of 79.7 kb. Interestingly, many of the intervals associated with translocations were gene-rich, including some genes associated with normal skeletal development. Comparisons of NLE breakpoints with those of other gibbon species reveal variability in the position, suggesting that chromosomal rearrangement has been a longstanding property of this particular ape lineage. Our data emphasize the synergistic effect of combining computational genomics and cytogenetics and provide a framework for ultimate sequence and assembly of the gibbon genome.
MOTIVATION: Large-scale bioinformatics analyses increasingly require collaboration across multiple cohorts and institutions, yet existing workflows often rely on data co-localization, which is slow, difficult to scale, and raises privacy concerns. We present a privacy-preserving federated analytics framework that enables secure statistical analysis across distributed datasets without transferring raw data, by performing all computations on encrypted data via cryptographic methods. RESULTS: We evaluate the framework by validating polygenic risk scores and conducting meta-analyses on two real-world cohorts. The proposed solution achieves over 99.9% accuracy relative to plaintext analyses, while maintaining scalable runtime performance with increasing data size and number of participating sites. These results demonstrate the feasibility of secure federated analytics for practical bioinformatics applications involving sensitive data.
This article shows that the interpretation of the random-effects models used in meta-analysis to summarize heterogeneous treatment effects can have a marked effect on the results from decision models. Sources of variation in meta-analysis include the following: random variation in outcome definition (amounting to a form of measurement error), variation between the patient groups in different trials, variation between protocols, and variation in the way a given protocol is implemented. Each of these alternatives leads to a different model for how the heterogeneity in the effect sizes previously observed might relate to the effect size(s) in a future implementation. Furthermore, these alternative models require different computations and, when the net benefits are nonlinear in the efficacy parameters, result in different expected net benefits. The authors' analysis suggests that the mean treatment effect from a random-effects meta-analysis will only seldom be an appropriate representation of the efficacy expected in a future implementation. Instead, modelers should consider either the predictive distribution of a future treatment effect, or they should assume that the future implementation will result in a distribution of treatment effects. A worked example, in a probabilistic, Bayesian posterior framework, is used to illustrate the alternative computations and to show how parameter uncertainty can be combined with variation between individuals and heterogeneity in meta-analysis.
A new phenomenon of strain relaxation will be presented. In a series of InxGa1-xAs graded composition buffer layers grown on well cut (001) GaAs substrates, a curvature of the epilayer lattice has been found, i.e. a tilt of the epilayer lattice orientation with respect to the substrate which varies coherently along the sample surface on the scale of several mm. The most recent data analysis performed on a buffer layer compositionally graded with a six-step profile shows also a thickness functional dependence of the curvature. The epilayer lattice curvature has been attributed to a coherent lateral distribution of the Burgers' vectors. An analytical model has been developed in the framework of the continuum elasticity theory to compute the related strain field. The results show small but unexpected contributions to the parallel strain.
A two-stage process is proposed for evaluating computer aiding in cognitive work domains. The first stage relies on a taxonomic framework that facilitates assessments regarding the relative strengths and weaknesses of humans and computers for different computer-aiding schemes. The second stage introduces the construct of tension, which addresses the potential implications of the interplay between computer aiding constraints and human tendencies. This approach is intended to provide designers, analysts and managers with greater insight into the nature of computer aiding and ultimately to enhance their ability to predict its effectiveness as well as its prospects for being used.
MOTIVATION: A comprehensive gene expression database is essential for computer modeling and simulation of biological phenomena, including development. Development is a four-dimensional (4D; 3D structure and time course) phenomenon. We are constructing a 4D database of gene expression for the early embryogenesis of the nematode Caenorhabditis elegans. As a framework of the 4D database, we have constructed computer graphics (CG), into which we will incorporate the expression data of a number of genes at the subcellular level. However, the assignment of 3D distribution of gene products (protein, mRNA), of embryos at various developmental stages, is both difficult and tedious. We need to automate this process. For this purpose, we developed a new system, named SPI after superimposing fluorescent confocal microscopic data onto a CG framework. RESULTS: The scheme of this system comprises the following: (1) acquirement of serial sections (40 slices) of fluorescent confocal images of three colors (4',6'-diamino-2-phenylindole (DAPI) for nuclei, indodicarbocyanine (Cy-3) for the internal marker, which is a germline-specific protein POS-1 and indocarbocyanine (Cy-5) for the gene product to be examined); (2) identification of several features of the stained embryos, such as contour, developmental stage and position of the internal marker; (3) selection of CG images of the corresponding stage for template matching; (4) superimposition of serial sections onto the CG; (5) assignment of the position of superimposed gene products. The Snakes algorithm identified the embryo contour. The detection accuracy of embryo contours was 92.1% when applied to 2- to 28-cell-stage embryos. The accuracy of the developmental stage prediction method was 81.2% for 2- to 8-cell-stage embryos. We manually judged only the later stage embryos because the accuracy for embryos at the later stages was unsatisfactory due to experimental noise effects. Finally, our system chose the optimal CG and performed the superposition and assignment of gene product distribution. We established an initial 4D gene expression database with 56 maternal gene products. AVAILABILITY: This system is available at http://anti.lab.nig.ac.jp/spi/ and http://anti.lab.nig.ac.jp/4ddb/
This paper uses the conceptual framework of Feldman-Stewart et al. to organize and review the types of research methodologies used to investigate various aspects of patient-health care professional communication in the context of cancer. Research methods employed are classified as either non-experimental or experimental. Non-experimental designs include naturalistic observational studies (e.g. participant observation, audio- or videotaping of interactions) and retrospective introspective descriptions (e.g. self-report questionnaires, qualitative interview methods). Experimental designs often involve interventions aimed at improving communication, such as physician or patient training, and the use of technology to enhance communication (e.g. audiotapes, computers). Using the conceptualization of the communication framework description, we argue that the outcome measures used in these studies address either primary goals, enabling goals, or secondary communication outcomes. Outcomes that are related to primary goals of the communication exchange include assessing the level of understanding of information conveyed, aspects of decision making, planning around treatments, or general provision of care. Outcomes related to enabling goals focus on elements that affect the ability to achieve primary goals. Outcomes secondary to the communication do not relate directly to what the communication is attempting to achieve. We conclude by identifying priority areas for further research, such as identifying the goals of both participants, understanding how particular aspects of the communication process affect their ability to achieve their goals, and examining the external environment in which communication takes place.
A computational study of the role of all ionizable groups of the C-peptide in its helix-coil transition is performed within the framework of continuum electrostatics. The method employed in our computations involves a numeric solution of the Poisson equation with the Boundary Element Method. Our calculations correctly predict the experimentally observed trends in the helix-coil equilibrium of the C-peptide, and suggest that the mechanisms involved are more complex than usually presumed in the literature. Our results suggest that electrostatic interactions in the unfolded conformation are often more important than in the helix, total electrostatic contribution to the helix-coil transition due to the side chains of the C-peptide destabilizes the helix, changes in the helix stability produced by the changes in the ionization state of the side chains are dominated by side chain effects, the effect of the helix dipole on the energetics of the helix-coil transition of the C-peptide is either minor or similar to other contributions in magnitude; while the formation of a salt bridge is electrostatically favorable, formation of the hydrogen bond between a charged and a polar side chains is not. Factors limiting the accuracy of the computations are discussed.
Human modelling is an interdisciplinary research field. The topic, emotion-affected decision making, was originally a cognitive psychology issue, but is now recognized as an important research direction for both computer science and biomedical modelling. The main aim of this paper is to attempt to bridge the gap between psychology and bioengineering in emotion-affected decision making. The work is based on Ortony's theory of emotions and bounded rationality theory, and attempts to connect the emotion process with decision making. A computational emotion model is proposed, and the initial framework of this model in virtual human simulation within the platform of Virtools is presented.
UNLABELLED: Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. AVAILABILITY: The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.
A framework is presented that captures the discrete and probabilistic nature of molecular transport and reaction kinetics found in a living cell as well as formally representing the spatial distribution of these phenomena. This particle or agent-based approach is computationally robust and complements established methods. Namely it provides a higher level of spatial resolution than formulations based on ordinary differential equations (ODE) while offering significant advantages in computational efficiency over molecular dynamics (MD). Using this framework, a model cell membrane has been constructed with discrete particle agents that respond to local component interactions that resemble flocking or herding behavioural cues in animals. Results from simulation experiments are presented where this model cell exhibits many of the characteristic behaviours associated with its biological counterpart such as lateral diffusion, response to osmotic pressure gradients, membrane growth and cell division. Lateral diffusion rates and estimates for the membrane modulus of elasticity derived from these simple experiments fall well within a biologically relevant range of values. More importantly, these estimates were obtained by applying a simple qualitative tuning of the model membrane. Membrane growth was simulated by injecting precursor molecules into the proto-cell at different rates and produced a variety of morphologies ranging from a single large cell to a cluster of cells. The computational scalability of this methodology has been tested and results from benchmarking experiments indicate that real-time simulation of a complete bacterial cell will be possible within 10 years.