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PubMedDate not supplied

Beam characteristics of a new model of 6-MV linear accelerator.

This paper describes the beam characteristics and dosimetry measurements performed on the 6-MV photon beam of a new model of linear accelerator, three of which were recently introduced and installed in our institution. Percent depth dose and tissue maximum ratio tables for a variety of field sizes and depths, as well as other parameters used for treatment planning are presented. These accelerators are the first of their kind using both hardware and software tools to control interlocks. Checking procedures for these interlocks are available from the authors upon request. Comparison of characteristic parameters between these three new 6-MV linear accelerators and with the 6-MV beams of two other accelerators is also made.

Calibration↗
PubMed1999

A pattern classification approach to characterizing solitary pulmonary nodules imaged on high resolution CT: preliminary results.

The purpose of this research is to characterize solitary pulmonary nodules as benign or malignant based on quantitative measures extracted from high resolution CT (HRCT) images. High resolution CT images of 31 patients with solitary pulmonary nodules and definitive diagnoses were obtained. The diagnoses of these 31 cases (14 benign and 17 malignant) were determined from either radiologic follow-up or pathological specimens. Software tools were developed to perform the classification task. On the HRCT images, solitary nodules were identified using semiautomated contouring techniques. From the resulting contours, several quantitative measures were extracted related to each nodule's size, shape, attenuation, distribution of attenuation, and texture. A stepwise discriminant analysis was performed to determine which combination of measures were best able to discriminate between the benign and malignant nodules. A linear discriminant analysis was then performed using selected features to evaluate the ability of these features to predict the classification for each nodule. A jackknifed procedure was performed to provide a less biased estimate of the linear discriminator's performance. The preliminary discriminant analysis identified two different texture measures--correlation and difference entropy--as the top features in discriminating between benign and malignant nodules. The linear discriminant analysis using these features correctly classified 28/31 cases (90.3%) of the training set. A less biased estimate, using jackknifed training and testing, yielded the same results (90.3% correct). The preliminary results of this approach are very promising in characterizing solitary nodules using quantitative measures extracted from HRCT images. Future work involves including contrast enhancement and three-dimensional measures extracted from volumetric CT scans, as well as the use of several pattern classifiers.

Biophysical Phenomena↗
PubMed2006

Assignment of Staphylococcus isolates to groups by spa typing, SmaI macrorestriction analysis, and multilocus sequence typing.

The implementation of the new clustering algorithm Based Upon Repeat Pattern (BURP) into the Ridom StaphType software tool enables clustering based on spa typing data for Staphylococcus aureus. We compared clustering results obtained by spa typing/BURP to those obtained by currently well-established methods, i.e., SmaI macrorestriction analysis and multilocus sequence typing/eBURST. A total of 99 clinical S. aureus strains, including MRSA and representing major clonal lineages associated with important kinds of infections which have been prevalent in Germany and Central Europe during the last 10 years, were used for comparison. SmaI macrorestriction analysis revealed the highest discriminatory power, and clustering results for all three methods resulted in concordance values ranging from 96.8% between the two sequence-based methods to 93.4% between spa typing/BURP and SmaI macrorestriction/cluster analysis. The results of this study indicate that spa typing, together with BURP clustering, is a useful tool in S. aureus epidemiology, especially because of ease of use and the advantages of unambiguous sequence analysis as well as reproducibility and exchange of typing data.

Bacterial Typing Techniques↗
PubMed2003

Typing of methicillin-resistant Staphylococcus aureus in a university hospital setting by using novel software for spa repeat determination and database management.

The spa gene of Staphylococcus aureus encodes protein A and is used for typing of methicillin-resistant Staphylococcus aureus (MRSA). We used sequence typing of the spa gene repeat region to study the epidemiology of MRSA at a German university hospital. One hundred seven and 84 strains were studied during two periods of 10 and 4 months, respectively. Repeats and spa types were determined by Ridom StaphType, a novel software tool allowing rapid repeat determination, data management and retrieval, and Internet-based assignment of new spa types following automatic quality control of DNA sequence chromatograms. Isolates representative of the most abundant spa types were subjected to multilocus sequence typing and pulsed-field gel electrophoresis. One of two predominant spa types was replaced by a clonally related variant in the second study period. Ten unique spa types, which were equally distributed in both study periods, were recovered. The data show a rapid dynamics of clone circulation in a university hospital setting. spa typing was valuable for tracking of epidemic isolates. The data show that disproval of epidemiologically suggested transmissions of MRSA is one of the main objectives of spa typing in departments with a high incidence of MRSA.

Germany↗
PubMedDate not supplied

Representing information in patient reports using natural language processing and the extensible markup language.

OBJECTIVE: To design a document model that provides reliable and efficient access to clinical information in patient reports for a broad range of clinical applications, and to implement an automated method using natural language processing that maps textual reports to a form consistent with the model. METHODS: A document model that encodes structured clinical information in patient reports while retaining the original contents was designed using the extensible markup language (XML), and a document type definition (DTD) was created. An existing natural language processor (NLP) was modified to generate output consistent with the model. Two hundred reports were processed using the modified NLP system, and the XML output that was generated was validated using an XML validating parser. RESULTS: The modified NLP system successfully processed all 200 reports. The output of one report was invalid, and 199 reports were valid XML forms consistent with the DTD. CONCLUSIONS: Natural language processing can be used to automatically create an enriched document that contains a structured component whose elements are linked to portions of the original textual report. This integrated document model provides a representation where documents containing specific information can be accurately and efficiently retrieved by querying the structured components. If manual review of the documents is desired, the salient information in the original reports can also be identified and highlighted. Using an XML model of tagging provides an additional benefit in that software tools that manipulate XML documents are readily available.

Humans↗
PubMed2004

An evidence ontology for use in pathway/genome databases.

An important emerging need in Model Organism Databases (MODs) and other bioinformatics databases (DBs) is that of capturing the scientific evidence that supports the information within a DB. This need has become particularly acute as more DB content consists of computationally predicted information, such as predicted gene functions, operons, metabolic pathways, and protein properties. This paper presents an ontology for encoding the type of support and the degree of support for DB assertions, and for encoding the literature source in which that support is reported. The ontology includes a hierarchy of 35 evidence codes for modeling different types of wet-lab and computational evidence for the existence of operons and metabolic pathways, and for gene functions. We also describe an implementation of the ontology within the Pathway Tools software environment, which is used to query and update Pathway/Genome DBs such as EcoCyc, MetaCyc, and HumanCyc.

Computational Biology↗
PubMed2001

Computational cell biology: spatiotemporal simulation of cellular events.

The field of computational cell biology has emerged within the past 5 years because of the need to apply disciplined computational approaches to build and test complex hypotheses on the interacting structural, physical, and chemical features that underlie intracellular processes. To meet this need, newly developed software tools allow cell biologists and biophysicists to build models and generate simulations from them. The construction of general-purpose computational approaches is especially challenging if the spatial complexity of cellular systems is to be explicitly treated. This review surveys some of the existing efforts in this field with special emphasis on a system being developed in the authors' laboratory, Virtual Cell. The theories behind both stochastic and deterministic simulations are discussed. Examples of respective applications to cell biological problems in RNA trafficking and neuronal calcium dynamics are provided to illustrate these ideas.

Animals↗
PubMed2006

Distribution of stage I lung cancer growth rates determined with serial volumetric CT measurements.

PURPOSE: To retrospectively determine the distribution of stage I lung cancer growth rates with serial volumetric computed tomographic (CT) measurements. MATERIALS AND METHODS: This study was institutional review board approved and HIPAA compliant. The informed consent requirement was waived. Patients (n = 149) with stage I lung cancer who underwent two pretreatment CT examinations 25 or more days apart were identified. At the first and last examinations, tumor perimeters were manually inscribed by using software tools and the cross-sectional area was calculated. To calculate tumor volume, the summed areas were multiplied by the section increment and a formula was applied to reduce partial volume effects. Doubling time (DT) was calculated by using the volume and interscanning interval. The percentages of tumors that would surpass volume increase thresholds of 5%-25% for detectable growth at different time intervals were calculated. Age at diagnosis was compared with the reciprocal of DT, time interval between CT examinations, and initial tumor volume by using Pearson correlation. P < .05 denoted statistical significance. RESULTS: Lung cancer was stage IA in 99 patients and stage IB in 50. Median patient age was 72 years, and median interscanning interval was 130 days. Median tumor volumes were 3000 and 6213 mm3 at the first and last examinations, respectively. Median DT was 207 days; 21 tumors did not increase in volume between examinations. The interscanning interval required for 90% of growing tumors to surpass the growth threshold ranged from 8 weeks (5% threshold) to 37 weeks (25% threshold). Fifty-three percent of growing tumors would surpass the 25% threshold at 8 weeks, and 95% would surpass it at 1 year. Age at diagnosis was negatively correlated with growth rate (P = .047); there was no correlation between growth rate and either age at diagnosis or interscanning interval. CONCLUSION: At serial volumetric CT measurements, there was wide variability in growth rates. Some biopsy-proved cancers decreased in volume between examinations.

Adult↗
PubMed2001

Novel candidate genes for atherosclerosis are identified by representational difference analysis-based transcript profiling of cholesterol-loaded macrophages.

OBJECTIVES: To analyze the early gene expression in macrophages accompanying the phenotypic changes into foam cells upon exposure to oxidized low-density lipoprotein. To identify candidate genes and markers for further studies into the pathogenesis of atherosclerosis. METHODS: Cells of the monocytic cell line THP-1 were activated by PMA and exposed to oxidized low-density lipoprotein. Gene expression profiles were investigated after 24 h, using a solid phase cDNA representational difference analysis (RDA) method and shotgun sequencing. Results were verified by microarray hybridization, and analyzed in the virtual chip display of a novel software tool for transcript profile exploration. RESULTS: By comparing transcript profiles of exposed/unexposed cells, 1,984 transcript sequences, representing a total of 921 genes with altered expression levels in response to oxidized low-density lipoprotein exposure, were identified. Genes that are central to cell cycle control and proliferation, inflammatory response, and of pathways not previously implicated in atherosclerosis were identified. The data obtained is also made available on-line at http:// biobase.biotech.kth.se/thp1a for further exploration. CONCLUSION: The identification of new candidate genes for atherosclerotic disease through RDA-based transcript profiling facilitates further functional genomic studies in coronary artery disease. Candidate genetic polymorphism markers of potential clinical relevance can be identified by filtering information in genome variation databases through the virtual chip analysis of the transcript profiles and subsequently tested in association studies.

Arteriosclerosis↗
PubMedDate not supplied

Characteristics of fricatives and sentence duration after cochlear implantation.

Ten postlingually deafened patients (5 male, 5 female) were examined after cochlear implantation to measure improvements in their quality of speech. Parameters such as the spectral maximum of fricatives and the duration of utterances were analysed in speech recordings taken at regular intervals after implantation. The speech samples were recorded in an audiological chamber. Parameters were analysed using ST(x) (S-Tools Software). Frequency analyses based on the fast Fourier transform and spectral estimation methods, as well as fundamental frequency and formant extraction (cepstrum, LPC = linear prediction coding) and digital filter implementations were prepared. The results indicate a tendency towards improvement in the spectral maximum of the fricatives and affricates and a shortening of the duration of the fricative parts in affricates and of sentences in nearly all our subjects. These results showed the restored auditory feedback produced by cochlear implantation to have a favourable effect on speech production.

Adolescent↗
PubMed2003

Systematic isolation of genes differentially expressed in normal and cancerous tissue of the pancreas.

BACKGROUND: There is increasing knowledge about the genetic basis of pancreatic cancer (PaCa). Tumor suppressor genes (TSGs; e.g. p53 and DPC4) and oncogenes (e.g. K-ras) have been shown to be involved in the development of PaCa. However, the extent of chromosomal changes (gains and losses) implicates that many more genes may be involved in the multistep progression of PaCa. Identification of these genes is essential for understanding the molecular events in the development of PaCa. METHODS: We assembled public and proprietary libraries of more than 4 million expressed sequence tags using newly developed software tools. RESULTS: We identified a total of 249 genes with specific expression patterns in normal and cancerous tissue of the pancreas. Of these, 27 genes were found to be preferentially expressed in normal tissue of the pancreas, while 222 genes showed significant upregulation of expression in PaCa. Of the 249 genes, 232 (93.2%) were found to represent known human genes or putative human homologues of genes characterized previously in other species, while 17 (6.8%) represent putative new genes. CONCLUSION: These genes may represent a valuable source to identify novel TSGs and oncogenes involved in the carcinogenesis of PaCa.

DNA, Complementary↗
PubMed2003

AGRIS: Arabidopsis gene regulatory information server, an information resource of Arabidopsis cis-regulatory elements and transcription factors.

BACKGROUND: The gene regulatory information is hardwired in the promoter regions formed by cis-regulatory elements that bind specific transcription factors (TFs). Hence, establishing the architecture of plant promoters is fundamental to understanding gene expression. The determination of the regulatory circuits controlled by each TF and the identification of the cis-regulatory sequences for all genes have been identified as two of the goals of the Multinational Coordinated Arabidopsis thaliana Functional Genomics Project by the Multinational Arabidopsis Steering Committee (June 2002). RESULTS: AGRIS is an information resource of Arabidopsis promoter sequences, transcription factors and their target genes. AGRIS currently contains two databases, AtTFDB (Arabidopsis thaliana transcription factor database) and AtcisDB (Arabidopsis thaliana cis-regulatory database). AtTFDB contains information on approximately 1,400 transcription factors identified through motif searches and grouped into 34 families. AtTFDB links the sequence of the transcription factors with available mutants and, when known, with the possible genes they may regulate. AtcisDB consists of the 5' regulatory sequences of all 29,388 annotated genes with a description of the corresponding cis-regulatory elements. Users can search the databases for (i) promoter sequences, (ii) a transcription factor, (iii) a direct target genes for a specific transcription factor, or (vi) a regulatory network that consists of transcription factors and their target genes. CONCLUSION: AGRIS provides the necessary software tools on Arabidopsis transcription factors and their putative binding sites on all genes to initiate the identification of transcriptional regulatory networks in the model dicotyledoneous plant Arabidopsis thaliana. AGRIS can be accessed from http://arabidopsis.med.ohio-state.edu.

3' Untranslated Regions↗
PubMed2005

The yeast kinome displays scale free topology with functional hub clusters.

BACKGROUND: The availability of interaction databases provides an opportunity for researchers to utilize immense amounts of data exclusively in silico. Recently there has been an emphasis on studying the global properties of biological interactions using network analysis. While this type of analysis offers a wide variety of global insights it has surprisingly not been used to examine more localized interactions based on mechanism. In as such we have particular interest in the role of key topological components in signal transduction cascades as they are vital regulators of healthy and diseased cell states. RESULTS: We have used publicly available databases and a novel software tool termed Hubview to model the interactions of a subset of the yeast interactome, specifically protein kinases and their interaction partners. Analysis of the connectivity distribution has inferred a fat-tailed degree distribution with parameters consistent with those found in other biological networks. In addition, Hubview identified a functional clustering of a large group of kinases, distributed between three separate groupings. The complexity and average degree for each of these clusters is indicative of a specialized function (cell cycle propagation, DNA repair and pheromone response) and relative age for each cluster. CONCLUSION: Using connectivity analysis on a functional subset of proteins we have evidence that reinforces the scale free topology as a model for protein network evolution. We have identified the hub components of the kinase network and observed a tendency for these kinases to cluster together on a functional basis. As such, these results suggest an inherent trend to preserve scale free characteristics at a domain based modular level within large evolvable networks.

Multigene Family↗
PubMed2006

A case study in pathway knowledgebase verification.

BACKGROUND: Biological databases and pathway knowledge-bases are proliferating rapidly. We are developing software tools for computer-aided hypothesis design and evaluation, and we would like our tools to take advantage of the information stored in these repositories. But before we can reliably use a pathway knowledge-base as a data source, we need to proofread it to ensure that it can fully support computer-aided information integration and inference. RESULTS: We design a series of logical tests to detect potential problems we might encounter using a particular knowledge-base, the Reactome database, with a particular computer-aided hypothesis evaluation tool, HyBrow. We develop an explicit formal language from the language implicit in the Reactome data format and specify a logic to evaluate models expressed using this language. We use the formalism of finite model theory in this work. We then use this logic to formulate tests for desirable properties (such as completeness, consistency, and well-formedness) for pathways stored in Reactome. We apply these tests to the publicly available Reactome releases (releases 10 through 14) and compare the results, which highlight Reactome's steady improvement in terms of decreasing inconsistencies. We also investigate and discuss Reactome's potential for supporting computer-aided inference tools. CONCLUSION: The case study described in this work demonstrates that it is possible to use our model theory based approach to identify problems one might encounter using a knowledge-base to support hypothesis evaluation tools. The methodology we use is general and is in no way restricted to the specific knowledge-base employed in this case study. Future application of this methodology will enable us to compare pathway resources with respect to the generic properties such resources will need to possess if they are to support automated reasoning.

Algorithms↗
PubMed2006

A methodology for the structural and functional analysis of signaling and regulatory networks.

BACKGROUND: Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks. RESULTS: We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical) interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed) interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA). LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets) in cellular networks. LSSA also reveals network regions whose parametrization and initial states are crucial for the dynamic behavior. We have implemented these methods in our software tool CellNetAnalyzer (successor of FluxAnalyzer) and illustrate their applicability using a logical model of T-Cell receptor signaling providing non-intuitive results regarding feedback loops, essential elements, and (logical) signal processing upon different stimuli. CONCLUSION: The methods and formalisms we propose herein are another step towards the comprehensive functional analysis of cellular interaction networks. Their potential, shown on a realistic T-cell signaling model, makes them a promising tool.

Animals↗
PubMed2003

Geographic information systems and the spiritual dimension of health: a short position paper.

The WHO's well known definition of health stressed the indivisibility of human well-being, physical and otherwise, by stating that health is "not merely the absence of disease or infirmity". The spiritual dimension of health is well covered in the medical literature. Different locations on Earth are associated with different interrelated profiles: physical, biological, environmental, socio-economic, cultural, and also spiritual profiles, that do affect and are affected by health (including its spiritual dimension), disease, healthcare, and pastoral care. A number of reviews have been recently published covering the use of Geographic Information Systems (GIS) in understanding and harnessing the importance of location in the health sector. However, no publication so far has discussed the role of GIS in relation to the spiritual dimension of health. This position paper is an attempt to fill in this gap without going into deep details. GIS role in pastoral care ranges from assisting in pattern and trend detection, and in informed decision-making and resource management, to providing routing and educational functions, and even assessing the impact of missionary radio broadcasts. A review of some of the software tools that are currently available in this field is also provided. GIS are ideal tools for improving and coordinating the integration of the health (physical), social, and spiritual/ pastoral dimensions of individual and community care. However to achieve the full potential of GIS in these areas, we still need to combat many cultural and organisational barriers, while making the tools cheaper and much easier to learn and use.

Journal Article↗
PubMed2002

Design and implementation of microarray gene expression markup language (MAGE-ML).

BACKGROUND: Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies. RESULTS: To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems. CONCLUSIONS: MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.

Computer Simulation↗
PubMed2004

Genomic neighborhoods for Arabidopsis retrotransposons: a role for targeted integration in the distribution of the Metaviridae.

BACKGROUND: Retrotransposons are an abundant component of eukaryotic genomes. The high quality of the Arabidopsis thaliana genome sequence makes it possible to comprehensively characterize retroelement populations and explore factors that contribute to their genomic distribution. RESULTS: We identified the full complement of A. thaliana long terminal repeat (LTR) retroelements using RetroMap, a software tool that iteratively searches genome sequences for reverse transcriptases and then defines retroelement insertions. Relative ages of full-length elements were estimated by assessing sequence divergence between LTRs: the Pseudoviridae were significantly younger than the Metaviridae. All retroelement insertions were mapped onto the genome sequence and their distribution was distinctly non-uniform. Although both Pseudoviridae and Metaviridae tend to cluster within pericentromeric heterochromatin, this association is significantly more pronounced for all three Metaviridae sublineages (Metavirus, Tat and Athila). Among these, Tat and Athila are strictly associated with pericentromeric heterochromatin. CONCLUSIONS: The non-uniform genomic distribution of the Pseudoviridae and the Metaviridae can be explained by a variety of factors including target-site bias, selection against integration into euchromatin and pericentromeric accumulation of elements as a result of suppression of recombination. However, comparisons based on the age of elements and their chromosomal location indicate that integration-site specificity is likely to be the primary factor determining distribution of the Athila and Tat sublineages of the Metaviridae. We predict that, like retroelements in yeast, the Athila and Tat elements target integration to pericentromeric regions by recognizing a specific feature of pericentromeric heterochromatin.

Arabidopsis↗