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At least 523 records · Page 29Linked to original sources
PubMed2001

Reinventing patient-centered computing for the twenty-first century.

Despite evidence over the past decade that patients like and will use patient-centered computing systems in managing their health, patients have remained forgotten stakeholders in advances in clinical computing systems. We present a framework for patient empowerment and the technical realization of that framework in an architecture called CareLink. In an evaluation of the initial deployment of CareLink in the support of neonatal intensive care, we have demonstrated a reduction in the length of stay for very-low birthweight infants, and an improvement in family satisfaction with care delivery. With the ubiquitous adoption of the Internet into the general culture, patient-centered computing provides the opportunity to mend broken health care relationships and reconnect patients to the care delivery process. CareLink itself provides functionality to support both clinical care and research, and provides a living laboratory for the further study of patient-centered computing.

Humans↗
PubMed2004

Medical privacy protection based on granular computing.

Based on granular computing methodology, we propose two criteria to quantitatively measure privacy invasion. The total cost criterion measures the effort needed for a data recipient to find private information. The average benefit criterion measures the benefit a data recipient obtains when he received the released data. These two criteria remedy the inadequacy of the deterministic privacy formulation proposed in Proceedings of Asia Pacific Medical Informatics Conference, 2000; Int J Med Inform 2003;71:17-23. Granular computing methodology provides a unified framework for these quantitative measurements and previous bin size and logical approaches. These two new criteria are implemented in a prototype system Cellsecu 2.0. Preliminary system performance evaluation is conducted and reviewed.

Computing Methodologies↗
PubMed1998

A proposed bioactive conformation of peptide T.

The conformational profiles of Peptide T, (5-8)Peptide T, [Abu5](4-8)Peptide T and (4-8)Peptide T were computed independently to assess the geometrical characteristics of the bioactive conformation of Peptide T. The conformational profiles of the peptides were computed within the molecular mechanics framework using an effective dielectric constant of 80. The conformational space was thoroughly sampled using an iterative simulated annealing protocol. The bioactive conformation was assessed by pairwise cross comparisons of each of the unique low energy conformations found for each of the different analogs studied. After a putative bioactive conformation was selected, in order to further validate our hypothesis the conformational profile of the potent compound cyclo(Thr-Thr-Asn-Tyr-Thr-Asp) was computed and the putative bioactive conformation was found. The conformation exhibits a pseudo beta-turn involving the side chain of Thr5 and the carbonyl oxygen of Tyr7 forming a C12 ring.

Amino Acid Sequence↗
PubMed2004

A computational model of auditory selective attention.

The human auditory system is able to separate acoustic mixtures in order to create a perceptual description of each sound source. It has been proposed that this is achieved by an auditory scene analysis (ASA) in which a mixture of sounds is parsed to give a number of perceptual streams, each of which describes a single sound source. It is widely assumed that ASA is a precursor of attentional mechanisms, which select a stream for attentional focus. However, recent studies suggest that attention plays a key role in the formation of auditory streams. Motivated by these findings, this paper presents a conceptual framework for auditory selective attention in which the formation of groups and streams is heavily influenced by conscious and subconscious attention. This framework is implemented as a computational model comprising a network of neural oscillators, which perform stream segregation on the basis of oscillatory correlation. Within the network, attentional interest is modeled as a Gaussian distribution in frequency. This determines the connection weights between oscillators and the attentional process, which is modeled as an attentional leaky integrator (ALI). Acoustic features are held to be the subject of attention if their oscillatory activity coincides temporally with a peak in the ALI activity. The output of the model is an "attentional stream," which encodes the frequency bands in the attentional focus at each epoch. The model successfully simulates a range of psychophysical phenomena.

Action Potentials↗
PubMed2003

BioSPICE: access to the most current computational tools for biologists.

The goal of the BioSPICE program is to create a framework that provides biologists access to the most current computational tools. At the program midpoint, the BioSPICE member community has produced a software system that comprises contributions from approximately 20 participating laboratories integrated under the BioSPICE Dashboard and a methodology for continued software integration. These contributed software modules are the BioSPICE Dashboard, a graphical environment that combines Open Agent Architecture and NetBeans software technologies in a coherent, biologist-friendly user interface. The current Dashboard permits data sources, models, simulation engines, and output displays provided by different investigators and running on different machines to work together across a distributed, heterogeneous network. Among several other features, the Dashboard enables users to create graphical workflows by configuring and connecting available BioSPICE components. Anticipated future enhancements to BioSPICE include a notebook capability that will permit researchers to browse and compile data to support model building, a biological model repository, and tools to support the development, control, and data reduction of wet-lab experiments. In addition to the BioSPICE software products, a project website supports information exchange and community building.

Computational Biology↗
PubMed2006

Log-Euclidean metrics for fast and simple calculus on diffusion tensors.

Diffusion tensor imaging (DT-MRI or DTI) is an emerging imaging modality whose importance has been growing considerably. However, the processing of this type of data (i.e., symmetric positive-definite matrices), called "tensors" here, has proved difficult in recent years. Usual Euclidean operations on matrices suffer from many defects on tensors, which have led to the use of many ad hoc methods. Recently, affine-invariant Riemannian metrics have been proposed as a rigorous and general framework in which these defects are corrected. These metrics have excellent theoretical properties and provide powerful processing tools, but also lead in practice to complex and slow algorithms. To remedy this limitation, a new family of Riemannian metrics called Log-Euclidean is proposed in this article. They also have excellent theoretical properties and yield similar results in practice, but with much simpler and faster computations. This new approach is based on a novel vector space structure for tensors. In this framework, Riemannian computations can be converted into Euclidean ones once tensors have been transformed into their matrix logarithms. Theoretical aspects are presented and the Euclidean, affine-invariant, and Log-Euclidean frameworks are compared experimentally. The comparison is carried out on interpolation and regularization tasks on synthetic and clinical 3D DTI data.

Algorithms↗
PubMed2005

Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique.

The simulation of blood flow past endovascular devices such as coils and stents is a challenging problem due to the complex geometry of the devices. Traditional unstructured grid computational fluid dynamics relies on the generation of finite element grids that conform to the boundary of the computational domain. However, the generation of such grids for patient-specific modeling of cerebral aneurysm treatment with coils or stents is extremely difficult and time consuming. This paper describes the application of an adaptive grid embedding technique previously developed for complex fluid structure interaction problems to the simulation of endovascular devices. A hybrid approach is used: the vessel walls are treated with body conforming grids and the endovascular devices with an adaptive mesh embedding technique. This methodology fits naturally in the framework of image-based computational fluid dynamics and opens the door for exploration of different therapeutic options and personalization of endovascular procedures.

Algorithms↗
PubMedDate not supplied

A neurocomputational approach to delusions.

Neuronal networks process information in parallel. The cortex can be viewed as a computational surface that creates and maintains dynamic maps of representations of important sensorimotor and higher-level aspects of the environment and the organism. Its functions can be modeled by a particular type of neural network, the self-organizing feature map. Most importantly, representations of information in the cortex and in these maps have been demonstrated to change dynamically according to the salience and frequency of the input. This feature is referred to as neuroplasticity. The fact that general operational characteristics of computational maps in the cortex can be fine-tuned according to specific processing needs is referred to as neuromodulation. Within this framework of cortical maps and their computational models, acute and chronic delusions are discussed in terms of neuromodulation and neuroplasticity. This neurocomputational approach provides new insights into the phenomena in question, is detailed enough to allow empirical testing, and has therapeutic implications.

Brain↗
PubMed1981

A computer model for epidermal cellular interactions.

A model has been constructed of an assembly of mammalian epidermal cells. The model, simulated by computer, has served as a framework by which experiments can be performed "in machina". Relationships between the various parameters considered have been established. Hypotheses referring to the time at which cells leave the basal layer, and to the simultaneous occurrence of folded basal layer and of a significant number of vertical mitosis in some hyperplastic conditions have been implemented and examined.

Animals↗
PubMed2006

Integrating multi-attribute similarity networks for robust representation of the protein space.

MOTIVATION: A global view of the protein space is essential for functional and evolutionary analysis of proteins. In order to achieve this, a similarity network can be built using pairwise relationships among proteins. However, existing similarity networks employ a single similarity measure and therefore their utility depends highly on the quality of the selected measure. A more robust representation of the protein space can be realized if multiple sources of information are used. RESULTS: We propose a novel approach for analyzing multi-attribute similarity networks by combining random walks on graphs with Bayesian theory. A multi-attribute network is created by combining sequence and structure based similarity measures. For each attribute of the similarity network, one can compute a measure of affinity from a given protein to every other protein in the network using random walks. This process makes use of the implicit clustering information of the similarity network, and we show that it is superior to naive, local ranking methods. We then combine the computed affinities using a Bayesian framework. In particular, when we train a Bayesian model for automated classification of a novel protein, we achieve high classification accuracy and outperform single attribute networks. In addition, we demonstrate the effectiveness of our technique by comparison with a competing kernel-based information integration approach.

Algorithms↗
PubMed2005

Efficient decoding algorithms for generalized hidden Markov model gene finders.

BACKGROUND: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility and probabilistic underpinnings. As the focus of the gene finding community shifts toward the use of homology information to improve prediction accuracy, extensions to the basic GHMM model are being explored as possible ways to integrate this homology information into the prediction process. Particularly prominent among these extensions are those techniques which call for the simultaneous prediction of genes in two or more genomes at once, thereby increasing significantly the computational cost of prediction and highlighting the importance of speed and memory efficiency in the implementation of the underlying GHMM algorithms. Unfortunately, the task of implementing an efficient GHMM-based gene finder is already a nontrivial one, and it can be expected that this task will only grow more onerous as our models increase in complexity. RESULTS: As a first step toward addressing the implementation challenges of these next-generation systems, we describe in detail two software architectures for GHMM-based gene finders, one comprising the common array-based approach, and the other a highly optimized algorithm which requires significantly less memory while achieving virtually identical speed. We then show how both of these architectures can be accelerated by a factor of two by optimizing their content sensors. We finish with a brief illustration of the impact these optimizations have had on the feasibility of our new homology-based gene finder, TWAIN. CONCLUSIONS: In describing a number of optimizations for GHMM-based gene finders and making available two complete open-source software systems embodying these methods, it is our hope that others will be more enabled to explore promising extensions to the GHMM framework, thereby improving the state-of-the-art in gene prediction techniques.

Algorithms↗
PubMed2006

Roles of nuclear cardiology, cardiac computed tomography, and cardiac magnetic resonance: Noninvasive risk stratification and a conceptual framework for the selection of noninvasive imaging tests in patients with known or suspected coronary artery disease.

This review deals with noninvasive imaging for risk stratification and with a conceptual approach to the selection of noninvasive tests in patients with suspected or known chronic coronary artery disease (CAD). Already widely acknowledged with SPECT, there is an increasing body of literature data demonstrating that CT coronary calcium assessment is also of prognostic value. The amount of coronary atherosclerosis, as can be extrapolated from CT coronary calcium score, has been shown to be highly predictive of cardiac events. The principal difference between myocardial perfusion SPECT (MPS) and CT coronary calcium for prognostic application appears to be that the former is an excellent tool for assessing short-term risk, thus effectively guiding decisions regarding revascularization. In contrast, the atherosclerosis imaging methods are likely to provide greater long-term risk assessment and, thus, are more useful in determination of the need for aggressive medical prevention measures. Although the more recent development of CT coronary angiography is promising for diagnosis, there has been no information to date regarding the prognostic value of the CT angiographic data. Similarly, cardiac MRI has not yet been adequately studied for its prognostic content. The selection of the most appropriate test for a given patient depends on the specific question being asked. In patients with a very low likelihood of CAD, no imaging test may be required. In screening the remaining asymptomatic patients, atherosclerosis imaging may be beneficial. In symptomatic patients, MPS, CT coronary angiography, and cardiac MRI play important roles. We consider it likely that, with an increased emphasis on prevention and a concomitant aging of the population, many forms of noninvasive cardiac imaging will continue to grow, with nuclear cardiology continuing to grow.

Atherosclerosis↗
PubMed2006

Hydrogen tunnelling in enzyme-catalysed H-transfer reactions: flavoprotein and quinoprotein systems.

It is now widely accepted that enzyme-catalysed C-H bond breakage occurs by quantum mechanical tunnelling. This paradigm shift in the conceptual framework for these reactions away from semi-classical transition state theory (TST, i.e. including zero-point energy, but with no tunnelling correction) has been driven over the recent years by experimental studies of the temperature dependence of kinetic isotope effects (KIEs) for these reactions in a range of enzymes, including the tryptophan tryptophylquinone-dependent enzymes such as methylamine dehydrogenase and aromatic amine dehydrogenase, and the flavoenzymes such as morphinone reductase and pentaerythritol tetranitrate reductase, which produced observations that are also inconsistent with the simple Bell-correction model of tunnelling. However, these data-especially, the strong temperature dependence of reaction rates and the variable temperature dependence of KIEs-are consistent with other tunnelling models (termed full tunnelling models), in which protein and/or substrate fluctuations generate a configuration compatible with tunnelling. These models accommodate substrate/protein (environment) fluctuations required to attain a configuration with degenerate nuclear quantum states and, when necessary, motion required to increase the probability of tunnelling in these states. Furthermore, tunnelling mechanisms in enzymes are supported by atomistic computational studies performed within the framework of modern TST, which incorporates quantum nuclear effects.

Computer Simulation↗
PubMed1993

Virtual trajectory and stiffness ellipse during multijoint arm movement predicted by neural inverse models.

We predict the virtual trajectories and stiffness ellipses during multijoint arm movements by computer simulations. A two-link manipulator with four single-joint muscles and two double-joint muscles is used as a model of the human arm. Physical parameters of the model are derived from several experimental data. Among them, special emphasis is put on low values of the dynamic hand stiffness recently measured during single-joint and multijoint movements. The feedback-error-learning scheme to acquire the inverse dynamics model and the inverse statics model is utilized for this prediction. The virtual trajectories are much more complex than the actual trajectories. This indicates that planning the virtual trajectory is as difficult as solving the inverse dynamics problem for medium and fast movements, and simply falsifies the advocated computational advantage of the virtual trajectory control hypothesis. Thus, we conclude that learning inverse models is essential even in the virtual trajectory control framework. Finally, we propose a new computational model to learn the complicated shape of the virtual trajectories by integrating the virtual trajectory control and the feedback-error-learning scheme.

Arm↗
PubMed2003

A software tool for specifying voxel models for dosimetry estimation.

Many dose estimation problems can be conveniently formulated in terms of finding the energy emitted and absorbed by a set of homogeneous volume elements (voxels) arranged in a rectilinear grid. The solution of these problems requires an accurate model of the source and target geometry to be established, whereupon conventional Monte Carlo simulation of radiation transport can be employed to determine energy deposition. A software application ("MrVoxel") has been developed to assist in the specification of the source and target models. This application includes tools for image segmentation and image registration (2D and 3D, intra- and inter-modality, interactive, and automatic). It employs a plug-in architecture to facilitate customization and future expansion: plug-ins can be written to perform image import and export as well as to implement specialized image processing routines. Using plug-ins, the package can, for example, import DICOM 3.10 files and export input files for a voxel-based Monte Carlo package. Standard dosimetric tools such as the geometric mean method, transmission based attenuation correction, and MIRD-style voxel dose kernel convolution are also implemented as plug-ins. MrVoxel was implemented on a Macintosh computer using a commercial software framework to produce a conventional document-centric application. Hence it includes useful features such as the ability to undo an operation or to save a processed image set at any point. This latter feature enables the production of a processing trail, to allow post-hoc auditing of the analysis process. This paper describes the MrVoxel application and its role in the analysis of a particular dosimetry problem.

Algorithms↗
PubMedDate not supplied

Attitudes of Australian nurses toward the implementation of a clinical information system.

A computerized clinical information system (CIS) used for the majority of patient charting and medical records was installed in six of 15 beds in the intensive care unit (ICU) of a large Australian hospital in November 1993. Staff acceptance was identified as integral to the success of the system. A survey was issued to all nursing staff of the ICU to identify factors that affected attitude toward computers in the critical care environment. Factors resulting in negative attitudes then could be targeted through training and support for users. The factors considered that potentially could influence attitudes were age, nursing experience, intensive care nursing experience, and education. The study showed that nursing experience had a statistically significant effect on motivation to use computers. A strong relation was evident between the concepts of beliefs, attitudes, and motivation. A less apparent association was present between knowledge and the other concepts. Orientation and in-service education programs should provide appropriate and applied information to optimize the motivation, beliefs, and computer literacy of nurses using CIS frameworks.

Adult↗
PubMed2026

Endothelial cell-specific DNA methylation alterations in breast cancer.

DNA methylation alterations are well-established contributors to carcinogenesis, yet, in the tumor microenvironment (TME), patterns of lineage and cell-specific methylation alterations are not well understood. Single-cell DNA methylation profiling in the TME is limited by technical challenges and high costs. Here, we use bulk DNA methylation, cell type deconvolution (HiTIMED), and an interaction testing framework (CellDMC) to identify reproducible, computationally inferred lineage-specific epigenetic alterations in the TME supported by orthogonal data sources. Tumor endothelial cells (TECs), critical regulators of angiogenesis, vascular permeability, and immune cell trafficking, acquire structural and functional abnormalities that promote tumor growth. We hypothesize that TECs have altered DNA methylation compared with endothelial cells in non-tumor tissues. In genome-scale methylation data from discovery and validation datasets (tumor n = 1071; non-tumor n = 415), we identify and validate >4500 TEC-specific CpGs with altered methylation, many mapping to genes involved in angiogenesis and endothelial function. Integration with gene expression data indicates that TEC-specific methylation alterations may reprogram transcriptional networks controlling angiogenesis. High-resolution, cell lineage-specific epigenetic landscapes can be inferred from bulk methylation data, implicating TEC-specific DNA methylation alterations as potential drivers of cancer angiogenesis and vascular dysfunction and providing a framework for future mechanistic and translational studies of the tumor vasculature.

DNA Methylation↗
PubMed2006

Spectroscopic and computational studies of reduction of the metal versus the tetrapyrrole ring of coenzyme F430 from methyl-coenzyme M reductase.

Methyl-coenzyme M reductase (MCR) catalyzes the final step in methane biosynthesis by methanogenic archaea and contains a redox-active nickel tetrahydrocorphin, coenzyme F430, at its active site. Spectroscopic and computational methods have been used to study a novel form of the coenzyme, called F330, which is obtained by reducing F430 with sodium borohydride (NaBH4). F330 exhibits a prominent absorption peak at 330 nm, which is blue shifted by 100 nm relative to F430. Mass spectrometric studies demonstrate that the tetrapyrrole ring in F330 has undergone reduction, on the basis of the incorporation of protium (or deuterium), upon treatment of F430 with NaBH4 (or NaBD4). One- and two-dimensional NMR studies show that the site of reduction is the exocyclic ketone group of the tetrahydrocorphin. Resonance Raman studies indicate that elimination of this pi-bond increases the overall pi-bond order in the conjugative framework. X-ray absorption, magnetic circular dichroism, and computational results show that F330 contains low-spin Ni(II). Thus, conversion of F430 to F330 reduces the hydrocorphin ring but not the metal. Conversely, reduction of F430 with Ti(III) citrate to generate F380 (corresponding to the active MCR(red1) state) reduces the Ni(II) to Ni(I) but does not reduce the tetrapyrrole ring system, which is consistent with other studies [Piskorski, R., and Jaun, B. (2003) J. Am. Chem. Soc. 125, 13120-13125; Craft, J. L., et al. (2004) J. Biol. Inorg. Chem. 9, 77-89]. The distinct origins of the absorption band shifts associated with the formation of F330 and F380 are discussed within the framework of our computational results. These studies on the nature of the product(s) of reduction of F430 are of interest in the context of the mechanism of methane formation by MCR and in relation to the chemistry of hydroporphinoid systems in general. The spectroscopic and time-dependent DFT calculations add important insight into the electronic structure of the nickel hydrocorphinate in its Ni(II) and Ni(I) valence states.

Archaeal Proteins↗