[ADP support of biopsy processing and findings in the framework of a general hospital's information system].
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Austria↗
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Intelligent diagnostic monitoring using trend templates.
In previous work we have defined our trend template epistemology for clinically significant trends and we have illustrated and tested a program TrenDx that monitors time-ordered process data by matching the data to trend templates. Our initial application domain was pediatric growth monitoring. In continuing work we have explored monitoring hemodynamic and respiratory parameters of intensive care unit patients. This application has highlighted the needs for advances in our representation and monitoring algorithms. In particular, we have added reasoning with uncertainty to the trend template epistemology, and a new control structure allowing numerical ranking of competing trend templates. Furthermore, intelligent monitoring in any medical domain requires a coherent framework for diagnostic monitoring. In this paper we show how TrenDx can be extended to a framework including sending alarms, changing clinical context, and filtering data streams.
Diagnosis, Computer-Assisted↗
Computational study of the conformational preferences of the (R)-8-amino-pentacyclo[5.4.0.0(2,6).0(3,10).0(5,9)]undecane-8-carboxylic acid monopeptide.
alpha-Amino acids are important building blocks for the synthesis of a large number of bioactive compounds and pharmaceutical drugs. However, a literature survey revealed that no theoretical conformational study of alpha-amino acids with cage carbon frameworks has been performed to date. This paper reports the results of a conformational study on the (R)-8-amino-pentacyclo[5.4.0.0(2,6).0(3,10).0(5,9)]undecane-8-carboxylic acid monopeptide (cage monopeptide), using molecular mechanics and ab initio methods. The in vacuo Ramachandran maps computed using the different parameterizations of the AMBER force field show the C7eq structure as the most favourable conformation, in contrast to the C7ax structure, that is the lowest energy conformation at the ab initio level. Analysis of these maps reveals the helical preference for the monopeptide and provides the potential for the cage residue to be incorporated into constrained peptide analogues.
Adamantane↗
Three-dimensional analysis of left ventricular ejection using computational fluid dynamics.
We present in this study a method for constructing computational fluid mechanical models in order to study the effects of time-varying left ventricular ejection. A spherical left ventricular model was implemented in which three dimensional flow fields were obtained. The time course of the ventricular wall changes were assumed to have a trigonometrically varying nature. The wall grid was reformed 25 times during the calculation since the left ventricular wall motion was assumed to follow the blood flow, and the ventricle wall radius was reduced by 60 percent in 0.25 seconds. Centerline and cross-sectional velocity vectors greatly increased in magnitude at the aortic outlet, and pressure dropped from 1.17 x 10(4) dynes/cm2 (8.8 mmHg) to zero in the top 10 percent of the heart. The modeling framework will be used with left ventricular cast data coordinates in future studies. There is presently a lack of three-dimensional data based on a realistic model, and the computational method should make it possible to compare simulation results with important measurement techniques such as echocardiography and magnetic resonance imaging.
Blood Flow Velocity↗
Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges.
During fast oscillations in the local field potential (40-100 Hz gamma, 100-200 Hz sharp-wave ripples) single cortical neurons typically fire irregularly at rates that are much lower than the oscillation frequency. Recent computational studies have provided a mathematical description of such fast oscillations, using the leaky integrate-and-fire (LIF) neuron model. Here, we extend this theoretical framework to populations of more realistic Hodgkin-Huxley-type conductance-based neurons. In a noisy network of GABAergic neurons that are connected randomly and sparsely by chemical synapses, coherent oscillations emerge with a frequency that depends sensitively on the single cell's membrane dynamics. The population frequency can be predicted analytically from the synaptic time constants and the preferred phase of discharge during the oscillatory cycle of a single cell subjected to noisy sinusoidal input. The latter depends significantly on the single cell's membrane properties and can be understood in the context of the simplified exponential integrate-and-fire (EIF) neuron. We find that 200-Hz oscillations can be generated, provided the effective input conductance of single cells is large, so that the single neuron's phase shift is sufficiently small. In a two-population network of excitatory pyramidal cells and inhibitory neurons, recurrent excitation can either decrease or increase the population rhythmic frequency, depending on whether in a neuron the excitatory synaptic current follows or precedes the inhibitory synaptic current in an oscillatory cycle. Detailed single-cell properties have a substantial impact on population oscillations, even though rhythmicity does not originate from pacemaker neurons and is an emergent network phenomenon.
Action Potentials↗
BALLView: an object-oriented molecular visualization and modeling framework.
We present BALLView, an extensible tool for visualizing and modeling bio-molecular structures. It provides a variety of different models for bio-molecular visualization, e.g. ball-and-stick models, molecular surfaces, or ribbon models. In contrast to most existing visualization tools, BALLView also offers rich functionality for molecular modeling and simulation, including molecular mechanics methods (AMBER and CHARMM force fields), continuum electrostatics methods employing a Finite-Difference Poisson Boltzmann solver, and secondary structure calculation. Results of these computations can be exported as publication quality images or as movies. Even unexperienced users have direct access to this functionality through an intuitive graphical user interface, which makes BALLView particularly useful for teaching. For more advanced users, BALLView is extensible in different ways. Owing to its framework design, extension on the level of C per thousand+ per thousand per thousand+ code is very convenient. In addition, an interface to the scripting language Python allows the interactive rapid prototyping of new methods. BALLView is portable and runs on all major platforms (Windows, MacOS X, Linux, most Unix flavors). It is available free of charge under the GNU Public License (GPL) from our website http://www.ballview.org.
Computer Graphics↗
Functional and structural models of pontine modulation of mechanoreceptor and chemoreceptor reflexes.
The dorsolateral and ventrolateral pons (dl-pons, vl-pons) are critical brainstem structures mediating the plasticity of the Hering-Breuer mechanoreflex (HBR) and carotid chemoreflex (CCR). Review of anatomical evidence indicates that dl-pons and vl-pons are connected reciprocally with one another and with medullary nucleus tractus solitarius (NTS) and ventral respiratory group (VRG). With this structural map, functional models of HBR and CCR are proposed in which the respiratory rhythm is modulated by short-term depression (STD) or potentiation (STP) of corresponding primary NTS-VRG and auxiliary pons-VRG excitatory or inhibitory pathways. Behaviorally, STD and STP of respiratory reflexes are akin to non-associative learning such as habituation, sensitization or desensitization to afferent inputs. Computationally, the STD and STP effects amount to signal differentiation and integration in the time domain, or high-pass and low-pass filtering in the frequency domain, respectively. These functional and structural models of pontomedullary signal processing provide a novel conceptual framework that unifies a wealth of experimental observations regarding mechanoreceptor and chemoreceptor reflex control of breathing.
Animals↗
Linking animal models of psychosis to computational models of dopamine function.
Psychosis is linked to dysregulation of the neuromodulator dopamine and antipsychotic drugs (APDs) work by blocking dopamine receptors. Dopamine-modulated disruption of latent inhibition (LI) and conditioned avoidance response (CAR) have served as standard animal models of psychosis and antipsychotic action, respectively. Meanwhile, the 'temporal difference' algorithm (TD) has emerged as the leading computational model of dopamine neuron firing. In this report TD is extended to include action at the level of dopamine receptors in order to explain a number of behavioral phenomena including the dose-dependent disruption of CAR by APDs, the temporal dissociation of the effects of APDs on receptors vs behavior, the facilitation of LI by APDs, and the disruption of LI by amphetamine. The model also predicts an APD-induced change to the latency profile of CAR--a novel prediction that is verified experimentally. The model's primary contribution is to link dopamine neuron firing, receptor manipulation, and behavior within a common formal framework that may offer insights into clinical observations.
Action Potentials↗
Diet modulates cardiac metabolic stress during anthracycline treatment.
Diet is a modifiable determinant of cardiovascular risk and may influence tolerance to cancer therapies. The mechanisms by which specific dietary components affect cardiac metabolism during anthracycline treatment remain poorly defined, limiting the incorporation of dietary recommendations into treatment guidelines. Here, we integrated heart proteomics data from patients treated with or without anthracyclines with a genome-scale reconstruction of human cardiac metabolism (CardioNet). Using constraint-based flux analysis, we conducted >30,000 in silico simulations of diet scenarios generated from chemical profiles of ∼500 foods curated in the Periodic Table of Food Initiative. These simulations revealed that diets enriched in rapidly absorbable sugars and depleted of essential fatty acids impair cardiac metabolic efficiency, increasing reactive oxygen species production and the demand for purine salvage fluxes. These predicted metabolic patterns were consistent with plasma metabolomics from patients treated with anthracyclines, validating our findings. Computational modeling of 39 recipes across six cuisines revealed cardiometabolic effects of omnivorous versus vegan diets in patients. Modeling of a healthy vegan diet increased cardiometabolic efficiency compared with a healthy omnivorous diet in patients treated with anthracyclines, independent of the culinary background. Our approach demonstrates that integrating the molecular composition of food with genome-scale metabolic models enables systematic analysis of diet patterns for translational testing. Ultimately, these in silico studies provide a framework for trials and may inform dietary recommendations for improving cardiometabolic health.NEW & NOTEWORTHY We developed a systems biology framework to predict how diet influences cardiac metabolism during cancer therapy. Across >30,000 in silico diet simulations, we identified nutrient patterns that either exacerbate or mitigate anthracycline-induced metabolic stress. These findings demonstrate how computational modeling can uncover diet-metabolism interactions driving cardiotoxicity and guide dietary interventions.
Humans↗
Identification of relative protein bands in polyacrylamide gel electrophoresis (PAGE) using a multi-resolution snake algorithm.
In polyacrylamide gel electrophoresis (PAGE) image analysis, it is important to determine the percentage of the protein of interest of a protein mixture. This study presents reliable computer software to determine this percentage. The region of interest containing the protein band is detected using the snake algorithm. The iterative snake algorithm is implemented in a multi-resolutional framework. The snake is initialized on a low-resolution image. Then, the final position of the snake at the low resolution is used as the initial position in the higher-resolution image. Finally, the area of the protein is estimated as the area enclosed by the final position of the snake.
Algorithms↗
[Computer-assisted selection of therapeutic measures in ischemic heart disease and arterial hypertension during mass screening of a rural population].
Expert assessments of 537 case histories of patients with various coronary heart diseases made it possible to derive an algorithm for automatic choice of therapeutic and prophylactic measures. This approach was tested within the framework of the automatic system "Cardioscreening". It was shown that there was a good correlation between the automatic choice of therapeutic and prophylactic actions and the strategy of a skilled cardiologist.
Algorithms↗
Computer reconstruction of a human lung boundary model from magnetic resonance images.
A mathematical description of the morphology of the lung is necessary for modeling and analyzing the deposition of inhaled aerosols A model of the lung boundary was generated from magnetic resonance images, with the goal of creating a framework for anatomically realistic morphological models of the human airway network. We used data visualization and analysis software to reconstruct the lung volume from a series of transverse magnetic resonance images collected at many vertical locations in the lung, ranging from apex to base. The lung model was then built using isosurface extraction techniques. These modeling methods may facilitate the creation of customized morphological models for individual subjects, resulting in improved interpretation of aerosol distribution data from single-photon-emission computed tomography (SPECT). Such customized models could be developed for children and for patients with respiratory diseases, thus aiding in the study of inhaled medications and environmental aerosols in these populations.
Anatomy, Cross-Sectional↗
Integrative neurocomputational perspectives on cognitive aging, neuromodulation, and representation.
Besides neuroanatomical changes, neuromodulatory mechanisms are also compromised during aging. Neural network models are suitable tools for exploring the relatively broad and homogenous neuromodulatory influences on cortical function. Computational approaches for understanding neuromodulation of the dynamic properties of cortical function and recent neurocomputational theories relating different aspects of cognitive aging with declines in neuromodulation are reviewed. Considered within an integrative cross-level neurocomputational framework, aging-related decline in dopaminergic neuromodulation reduces the fidelity of neural information and gives rise to less distinctive neural pattern representations that may underlie various facets of aging cognitive and, possibly also, sensorimotor phenomena.
Aging↗
A stochastic method for Bayesian estimation of hidden Markov random field models with application to a color model.
We propose a new stochastic algorithm for computing useful Bayesian estimators of hidden Markov random field (HMRF) models that we call exploration/selection/estimation (ESE) procedure. The algorithm is based on an optimization algorithm of O. François, called the exploration/selection (E/S) algorithm. The novelty consists of using the a posteriori distribution of the HMRF, as exploration distribution in the E/S algorithm. The ESE procedure computes the estimation of the likelihood parameters and the optimal number of region classes, according to global constraints, as well as the segmentation of the image. In our formulation, the total number of region classes is fixed, but classes are allowed or disallowed dynamically. This framework replaces the mechanism of the split-and-merge of regions that can be used in the context of image segmentation. The procedure is applied to the estimation of a HMRF color model for images, whose likelihood is based on multivariate distributions, with each component following a Beta distribution. Meanwhile, a method for computing the maximum likelihood estimators of Beta distributions is presented. Experimental results performed on 100 natural images are reported. We also include a proof of convergence of the E/S algorithm in the case of nonsymmetric exploration graphs.
Algorithms↗
Biomolecular visualization using AVS.
Dataflow systems for scientific visualization are becoming increasingly sophisticated in their architecture and functionality. AVS, from Advanced Visual Systems Inc., is a powerful dataflow environment that has been applied to many computation and visualization tasks. An important, yet complex, application area is molecular modeling and biomolecular visualization. Problems in biomolecular visualization tax the capability of dataflow systems because of the diversity of operations that are required and because many operations do not fit neatly into the dataflow paradigm. Here we describe visualization strategies and auxiliary programs developed to enhance the applicability of AVS for molecular modelling. Our visualization strategy is to use general-purpose AVS modules and a small number of chemistry-specific modules. We have developed methods to control AVS using AVS-tool, a programmable interface to the AVS Command Line Interpreter (CLI), and have also developed NAB, a C-like language for writing AVS modules that has extensions for operating on proteins and nucleic acids. This strategy provides a flexible and extensible framework for a wide variety of molecular modeling tasks.
Artificial Intelligence↗
Using full probability models to compute probabilities of actual interest to decision makers.
The objective of this paper is to illustrate the advantages of the Bayesian approach in quantifying, presenting, and reporting scientific evidence and in assisting decision making. Three basic components in the Bayesian framework are the prior distribution, likelihood function, and posterior distribution. The prior distribution describes analysts' belief a priori, the likelihood function captures how data modify the prior knowledge; and the posterior distribution synthesizes both prior and likelihood information. The Bayesian approach treats the parameters of interest as random variables, uses the entire posterior distribution to quantify the evidence, and reports evidence in a "probabilistic" manner. Two clinical examples are used to demonstrate the value of the Bayesian approach to decision makers. Using either an uninformative or a skeptical prior distribution, these examples show that the Bayesian methods allow calculations of probabilities that are usually of more interest to decision makers, e.g., the probability that treatment A is similar to treatment B, the probability that treatment A is at least 5% better than treatment B, and the probability that treatment A is not within the "similarity region" of treatment B, etc. In addition, the Bayesian approach can deal with multiple endpoints more easily than the classic approach. For example, if decision makers wish to examine mortality and cost jointly, the Bayesian method can report the probability that a treatment achieves at least 2% mortality reduction and less than $20,000 increase in costs. In conclusion, probabilities computed from the Bayesian approach provide more relevant information to decision makers and are easier to interpret.
Arterial Occlusive Diseases↗
Mechanisms of Neural Architecture for Visual Contrast and Brightness Perception.
A neural architecture is proposed that serves as a framework for further empirical as well as theoretical investigations for a unified theory for contrast and brightness perception. The work further extends the brightness perception model developed by Grossberg and Todorovic. The proposed new computational architecture utilizes a (retinal) preprocessing stage with center-surround antagonisms of both polarities. The preprocessed data are shown to multiplex contrast as well as luminance information that can be de-multiplexed subsequently using a scheme of cross-channel interaction. Based on a hypothesized luminance-related channel, a three-stage process is suggested for brightness reconstruction. The separate channel for the representation of luminance-related information provides a key mechanism to assign the reconstructed brightness to an absolute reference level. The architecture provides a framework for the analysis of processes in brightness perception. Copyright 1996 Elsevier Science Ltd.
Journal Article↗
Sample size recalculation using conditional power.
The sample size required to achieve a given power at a prespecified absolute difference in mean response may depend on one or more nuisance parameters, which are usually unknown. Proposed methods for using an internal pilot to recalculate the sample size using estimates of these parameters have been well studied. Most of these methods ignore the fact that data on the parameter of interest from within this internal pilot will contribute towards the value of the final test statistic. We propose a method which involves recalculating the target sample size by computing the number of further observations required to maintain the probability of rejecting the null hypothesis at the end of the study under the prespecified absolute difference in mean response conditional on the data observed so far. We do this within the framework of a two-group error-spending sequential test, modified so as to prevent inflation of the type I error rate.
Breast Neoplasms↗