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Structural and optical properties of highly hydroxylated fullerenes: stability of molecular domains on the C60 surface.

The excitation spectra and the structural properties of highly hydroxylated C(60)(OH)(x) fullerenes (so-called fullerenols) are analyzed by comparing optical absorption experiments on dilute fullerenol-water solutions with semiempirical and density functional theory electronic structure calculations. The optical spectrum of fullerenol molecules with 24-28 OH attached to the carbon surface is characterized by the existence of broad bands with reduced intensities near the ultraviolet region (below approximately 500 nm) together with a complete absence of optical transitions in the visible part of the spectra, contrasting with the intense absorption observed in C(60) solutions. Our theoretical calculations of the absorption spectra, performed within the framework of the semiempirical Zerner intermediate neglect of diatomic differential overlap method [Reviews in Computational Chemistry II, edited by K. B. Lipkowitz and D. B. Boyd (VCH, Weinheim, 1991), Chap. 8, pp. 313-316] for various gas-phase-like C(60)(OH)(26) isomers, reveal that the excitation spectra of fullerenol molecules strongly depend on the degree of surface functionalization, the precise distribution of the OH groups on the carbon structure, and the presence of impurities in the samples. Interestingly, we have surprisingly found that low energy atomic configurations are obtained when the OH groups segregate on the C(60) surface forming molecular domains of different sizes. This patchy behavior for the hydroxyl molecules on the carbon surface leads in general to the formation of fullerene compounds with closed electronic shells, large highest occupied molecular orbital-lowest unoccupied molecular orbital energy gaps, and existence of an excitation spectrum that accounts for the main qualitative features observed in the experimental data.

Journal Article↗

GENESIS, a knowledge-based genetic engineering simulation system for representation of genetic data and experiment planning.

We have built a knowledge-based genetic engineering simulation system-- GENESIS-- capable of representing both domain-specific and general knowledge. Information is stored within a hierarchically-organized framework composed of structures called units. A series of sophisticated editors enables no-computer specialist molecular geneticists to construct a knowledge base through direct interaction with the computer. Three types of knowledge specific to the domain of molecular genetics, MAPS, sequences and RULES are discussed in detail with examples.

Animals↗

Accurate calculation of three-body depletion interactions.

We compute three-body depletion interactions in a hard-sphere mixture within the framework of density-functional theory and by considering the infinite dilution limit of the functional. The results look very accurate and show three-body interactions much smaller than the pair depletion ones, revealing that these are strongly influenced by correlations and have a decay length similar to the two-body depletion potential. The results are compared with the predictions of the Asakura-Oosawa model for the triplet interactions.

Journal Article↗

Self-consistency requirement in high-energy nuclear scattering.

Practically all serious calculations of exclusive particle production in ultrarelativistic nuclear or hadronic interactions are performed in the framework of Gribov-Regge theory or the eikonalized parton model scheme. It is the purpose of this paper to point out serious inconsistencies in the above-mentioned approaches. We demonstrate that requiring theoretical self-consistency reduces the freedom in modeling high-energy nuclear scattering enormously, and we introduce a fully self-consistent formulation of the multiple-scattering scheme in the framework of a Gribov-Regge--type effective theory. In addition, we develop new computational techniques which allow for the first time a satisfactory solution of the problem in the sense that calculations of observable quantities can be done strictly within a self-consistent formalism.

Journal Article↗

Topological protection and quantum noiseless subsystems.

Encoding and manipulation of quantum information by means of topological degrees of freedom provides a promising way to achieve natural fault tolerance that is built in at the physical level. We show that this topological approach to quantum information processing is a particular instance of the notion of computation in a noiseless quantum subsystem. The latter then provides the most general conceptual framework for stabilizing quantum information and for preserving quantum coherence in topological and geometric systems.

Journal Article↗

The use of visual search for knowledge gathering in image decision support.

This paper presents a new method of knowledge gathering for decision support in image understanding based on information extracted from the dynamics of saccadic eye movements. The framework involves the construction of a generic image feature extraction library, from which the feature extractors that are most relevant to the visual assessment by domain experts are determined automatically through factor analysis. The dynamics of the visual search are analyzed by using the Markov model for providing training information to novices on how and where to look for image features. The validity of the framework has been evaluated in a clinical scenario whereby the pulmonary vascular distribution on Computed Tomography images was assessed by experienced radiologists as a potential indicator of heart failure. The performance of the system has been demonstrated by training four novices to follow the visual assessment behavior of two experienced observers. In all cases, the accuracy of the students improved from near random decision making (33%) to accuracies ranging from 50% to 68%.

Algorithms↗

Modeling neuronal assemblies: theory and implementation.

Models that describe qualitatively and quantitatively the activity of entire groups of spiking neurons are becoming increasingly important for biologically realistic large-scale network simulations. At the systems and areas modeling level, it is necessary to switch the basic descriptional level from single spiking neurons to neuronal assemblies. In this article, we present and review work that allows a macroscopic description of the assembly activity. We show that such macroscopic models can be used to reproduce in a quantitatively exact manner the joint activity of groups of spike-response or integrate-and-fire neurons. We also show that integral as well as differential equation models of neuronal assemblies can be understood within a single framework, which allows a comparison with the commonly used assembly-averaged graded-response type of models. The presented framework thus enables the large-scale neural network modeler to implement networks using computational units beyond the single spiking neuron without losing much biological accuracy. This article explains the theoretical background as well as the capabilities and the implementation details of the assembly approach.

Computer Simulation↗

Genomic mapping of diabetic kidney disease biomarkers and identification of potential inhibitors through virtual screening.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus, marked by a multifactorial pathogenesis and the absence of sensitive diagnostic biomarkers. Identifying novel molecular targets and therapeutic options is essential to improve early diagnosis and treatment outcomes. METHODS: To uncover potential biomarkers and therapeutic candidates, we performed an integrated genomic analysis using microarray and RNA-seq datasets from the Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) databases. Differentially expressed genes (DEGs) were identified and subjected to protein-protein interaction (PPI) network analysis. Key genes were further explored through virtual screening of an FDA-approved compound library using molecular docking techniques. Drug-likeness was assessed via Lipinski's rule of five. RESULTS: A total of 40 DEGs were identified, among which ISCU (downregulated; involved in iron-sulfur cluster biogenesis) and AP1S2 (upregulated; associated with vesicular trafficking) emerged as potential biomarkers. PPI analysis revealed their involvement in critical DKD-related pathways, such as extracellular matrix remodeling and oxidative stress. Virtual screening identified six FDA-approved compounds with high binding affinity (≤-7.96 kcal/mol) to ISCU, notably ZINC000001576020, all of which complied with Lipinski's rule. CONCLUSIONS: This in-silico study nominates ISCU and AP1S2 as candidate diagnostic biomarkers for DKD and identifies computationally prioritized inhibitors targeting ISCU. These findings require experimental validation but provide a molecular framework for precision diagnosis and therapeutic development. These findings offer new molecular insights that could inform precision diagnosis and personalized treatment strategies for diabetic kidney disease.

Diabetic Nephropathies↗

On ontologies for biologists: the Gene Ontology--untangling the web.

The mantra of the 'post-genomic' era is 'gene function'. Yet surprisingly little attention has been given to how functional and other information concerning genes is to be captured, made accessible to biologists or structured in a computable form. The aim of the Gene Ontology (GO) Consortium is to provide a framework for both the description and the organisation of such information. The GO Consortium is presently concerned with three structured controlled vocabularies which can be used to describe three discrete biological domains, building structured vocabularies which can be used to describe the molecular function, biological roles and cellular locations of gene products.

Animals↗

[Results and experiences with automatic data processing of caries epidemiological data].

The authors report of further results from and experience with the automated processing of caries-epidemiological data by means of the R 300 computer. The extension of result documentation to qualitative characteristics of caries incidence in the framework of scientific problems is described and critically evaluated, taking a caries-protective collective action for an example.

DMF Index↗

The preconstructed vocabulary: a Procrustean bed.

The mechanization of bibliographic services has imposed a change from the retrospective to the prospective approach to vocabulary development. This results in vocabularies rigidly structured to serve a variety of purposes which are not always mutually compatible. The user suffers from the inflexibility of the basic framework, the dearth of cross-references, and the overspecificity of many subject headings. Computer technology and our knowledge of its application have advanced to the point that we should begin to reclaim some of the bibliographic conveniences which no longer have to be sacrificed.

Information Systems↗

[Characteristics of interrelations of external respiration, gas exchange and hemodynamics in patients with bronchopulmonary diseases].

In 60 patients with stage II-III bronchogenic carcinoma of the lung the following procedures were included in the complex of preoperative functional examination: spiro-body-plethysmography, catheterization of the right heart, and simultaneous examination of gas exchange using a DELTATRAC MBM-100 metabolic monitor. To evaluate the lung diffusion capacity and the dimensions of the arteriovenous shunt, oxygen mixtures differing in O2 concentration were used. The results were interpreted within the framework of a homogeneous model of lung gas exchange realized on a PC/AT personal computer. The interrelationship of ventilation disorders with hemodynamic and lung gas--exchange function was studied. Arterial hypoxemia was mainly observed in obstructive and mixed disorders of ventilation function and was more marked in the latter. Primary disturbance of the lung diffusion capacity was found to be the leading link in the development of acute respiratory insufficiency after the operation.

Aged↗

[Evaluation of estimated blood concentration of propofol on wake-up using "ConGrase", a software to control the syringe pump for propofol infusion].

We developed a software to control a Graseby 3500 syringe pump for propofol infusion through the serial port of Apple Macintosh/Power-Macintosh computer. This software, "ConGrase", was developed with Metrowerks CodeWarrior Professional (CWP 1) and PowerPlant framework using C++. ConGrase communicates with the syringe pump at least every three seconds, and calculates the estimated blood concentration (EBC) of propofol based on the amount of propofol actually infused by applying either the Euler or Runge-Kutta method using the three-compartment pharmacokinetic model. The parameter sets reported by Gepts et al. are used. ConGrase was released at the 44 th Annual Meeting of the Japan Society of Anesthesiology, and is distributed freely. The mean and S.D. of the emergence EBC calculated by ConGrase were 1.22 micrograms.ml-1 and 0.16 microgram.ml-1, respectively. These values are almost the same as values already reported outside Japan. The necessary wake-up time can be calculated with this estimated concentration. With this system, anesthetists can control the EBC at the required level and avoid long delays before the patients wake up after anesthesia.

Adolescent↗

Integrated electronic health records management system.

Computer systems and communication technologies are making a strong and influential presence in the different fields of medicine. The cornerstone of a functional medical information system represents the electronic health records management system. Due to a very sensitive nature of medical information, such systems are faced with a number of stringent requirements, like security and confidentiality of patients' related data, different media type's management, diversity of medical data that need to be processed etc. At present most clinical software systems are closed with little or no operability between them, and the medical information are locked in a variety of different incompatible databases. As the result of these facts, it is very hard for the developers to provide the solution for an integrated health computing environment, which would considerably improve the quality of medical care in general. This paper presents the framework for a functional EHR management system that meets these demands, but also follows the initiative taken by the Next Generation Network (NGN) approach, which includes user mobility, service transparency and common communication platform for transferring and serving different types of information, services and media.

Computer Communication Networks↗

Nonrigid registration of 3D tensor medical data.

New medical imaging modalities offering multi-valued data, such as phase contrast MRA and diffusion tensor MRI, require general representations for the development of automated algorithms. In this paper we propose a unified framework for the registration of medical volumetric multi-valued data using local matching. The paper extends the usual concept of similarity between two pieces of data to be matched, commonly used with scalar (intensity) data, to the general tensor case. Our approach to registration is based on a multiresolution scheme, where the deformation field estimated in a coarser level is propagated to provide an initial deformation in the next finer one. In each level, local matching of areas with a high degree of local structure and subsequent interpolation are performed. Consequently, we provide an algorithm to assess the amount of structure in generic multi-valued data by means of gradient and correlation computations. The interpolation step is carried out by means of the Kriging estimator, which provides a novel framework for the interpolation of sparse vector fields in medical applications. The feasibility of the approach is illustrated by results on synthetic and clinical data.

Algorithms↗

A hybrid framework for 3D medical image segmentation.

In this paper we propose a novel hybrid 3D segmentation framework which combines Gibbs models, marching cubes and deformable models. In the framework, first we construct a new Gibbs model whose energy function is defined on a high order clique system. The new model includes both region and boundary information during segmentation. Next we improve the original marching cubes method to construct 3D meshes from Gibbs models' output. The 3D mesh serves as the initial geometry of the deformable model. Then we deform the deformable model using external image forces so that the model converges to the object surface. We run the Gibbs model and the deformable model recursively by updating the Gibbs model's parameters using the region and boundary information in the deformable model segmentation result. In our approach, the hybrid combination of region-based methods and boundary-based methods results in improved segmentations of complex structures. The benefit of the methodology is that it produces high quality segmentations of 3D structures using little prior information and minimal user intervention. The modules in this segmentation methodology are developed within the context of the Insight ToolKit (ITK). We present experimental segmentation results of brain tumors and evaluate our method by comparing experimental results with expert manual segmentations. The evaluation results show that the methodology achieves high quality segmentation results with computational efficiency. We also present segmentation results of other clinical objects to illustrate the strength of the methodology as a generic segmentation framework.

Algorithms↗

Methodological aspects of the genetic dissection of gene expression.

MOTIVATION: Dissection of the genetics underlying gene expression utilizes techniques from microarray analyses as well as quantitative trait loci (QTL) mapping. Available QLT mapping methods are not tailored for the highly automated analyses required to deal with the thousand of gene transcripts encountered in the mapping of QTL affecting gene expression (sometimes referred to as eQTL). This report focuses on the adaptation of QTL mapping methodology to perform automated mapping of QTL affecting gene expression. RESULTS: The analyses of expression data on > 12,000 gene transcripts in BXD recombinant inbred mice found, on average, 629 QTL exceeding the genome-wide 5% threshold. Using additional information on trait repeatabilities and QTL location, 168 of these were classified as 'high confidence' QTL. Current sample sizes of genetical genomics studies make it possible to detect a reasonable number of QTL using simple genetic models, but considerably larger studies are needed to evaluate more complex genetic models. After extensive analyses of real data and additional simulated data (altogether > 300,000 genome scans) we make the following recommendations for detection of QTL for gene expression: (1) For populations with an unbalanced number of replicates on each genotype, weighted least squares should be preferred above ordinary least squares. Weights can be based on repeatability of the trait and the number of replicates. (2) A genome scan based on multiple marker information but analysing only at marker locations is a good approximation to a full interval mapping procedure. (3) Significance testing should be based on empirical genome-wide significance thresholds that are derived for each trait separately. (4) The significant QTL can be separated into high and low confidence QTL using a false discovery rate that incorporates prior information such as transcript repeatabilities and co-localization of gene-transcripts and QTL. (5) Including observations on the founder lines in the QTL analysis should be avoided as it inflates the test statistic and increases the Type I error. (6) To increase the computational efficiency of the study, use of parallel computing is advised. These recommendations are summarized in a possible strategy for mapping of QTL in a least squares framework. AVAILABILITY: The software used for this study is available on request from the authors.

Algorithms↗

Medical expert systems based on causal probabilistic networks.

Causal probabilistic networks (CPNs) offer new methods by which you can build medical expert systems that can handle all types of medical reasoning within a uniform conceptual framework. Based on the experience from a commercially available system and a couple of large prototype systems, it appears that CPNs are now an attractive alternative to other methods. A CPN is an intensional model of a domain, and it is therefore conceptually much closer to qualitative reasoning systems and to simulation systems than to rule-based or logic-based systems. Recent progress in Bayesian inference in networks has yielded computationally efficient methods. The inference method used follows the fundamental axioms of probability theory, and gives a sound framework for causal and diagnostic (deductive and abductive) reasoning under uncertainty. Experience with the prototypes indicates that it may be possible to use decision theory as a rational approach to test planning and therapy planning. The way in which knowledge is acquired and represented in CPNs makes it easy to express 'deep knowledge' for example in the form of physiological models, and the facilities for learning make it possible to make a smooth transition from expert opinion to statistics based on empirical data.

Artificial Intelligence↗