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PubMed2005

Modelling novice clinical reasoning for a computerized decision support system.

AIM: The aim of this paper is to introduce the theoretical framework that directs the project. BACKGROUND: The Novice Computer Decision Support (N-CODES) Project is developing a point-of-care system to assist novice acute care nurses while making clinical judgements. Unlike prior approaches, N-CODES is guided by a theoretical understanding of nurses' decision-making processes, including the manner by which novices develop this skill. FRAMEWORK: Assumptions within information processing theory guided the clinical decision-making framework. The framework is composed of a clinical decision-making model and a second embedded model depicting the clinical reasoning development of novice nurses. MODELS: The model is developed within a pluralistic perspective synthesizing theoretical and empirical knowledge on clinical decision-making and the development of novice reasoning skills. A visual representation of experienced nurse decision-making is presented. A central element is the nurse's use of pre-encounter data and working knowledge. A second model integrates empirical data on the developing clinical reasoning of the novice. This knowledge is loosely scattered through 25 years of literature. The intersection of these models provides a novel perspective on the way novices begin to identify working knowledge patterns and develop a sense of saliency. CONCLUSIONS: Previous attempts to build comprehensive clinical decision support systems have disregarded important theoretical considerations hindering the success of these projects. Grounding a Decision Support System in a theoretical model of novice nurse decision-making will strengthen the utility and acceptance of the Decision Support System. Additionally, a conceptualization of novice nurse development is an asset to nurse educators, managers and scientists interested in improving clinical decision-making.

Clinical Competence↗
PubMed2025

Global siRNA screen identifies human host factors critical for SARS-CoV-2 replication and late stages of infection.

Defining the subset of cellular factors governing SARS-CoV-2 replication can provide critical insights into viral pathogenesis and identify targets for host-directed antiviral therapies. While a number of genetic screens have previously reported SARS-CoV-2 host dependency factors, most of these approaches relied on utilizing pooled genome-scale CRISPR libraries, which are biased toward the discovery of host proteins impacting early stages of viral replication. To identify host factors involved throughout the SARS-CoV-2 infectious cycle, we conducted an arrayed genome-scale siRNA screen. Resulting data were integrated with published functional screens and proteomics data to reveal (i) common pathways that were identified in all OMICs datasets-including regulation of Wnt signaling and gap junctions, (ii) pathways uniquely identified in this screen-including NADH oxidation, or (iii) pathways supported by this screen and proteomics data but not published functional screens-including arachionate production and MAPK signaling. The identified proviral host factors were mapped into the SARS-CoV-2 infectious cycle, including 32 proteins that were determined to impact viral replication and 27 impacting late stages of infection, respectively. Additionally, a subset of proteins was tested across other coronaviruses revealing a subset of proviral factors that were conserved across pandemic SARS-CoV-2, epidemic SARS-CoV-1 and MERS-CoV, and the seasonal coronavirus OC43-CoV. Further studies illuminated a role for the heparan sulfate proteoglycan perlecan in SARS-CoV-2 viral entry and found that inhibition of the non-canonical NF-kB pathway through targeting of BIRC2 restricts SARS-CoV-2 replication both in vitro and in vivo. These studies provide critical insight into the landscape of virus-host interactions driving SARS-CoV-2 replication as well as valuable targets for host-directed antivirals.

Humans↗
PubMed2005

A multiple-pattern biosequence analysis method for diverse source association mining.

BACKGROUND: In order to understand the intricacy of biomolecules more comprehensively, significant patterns extracted from related data collected from diverse sources must be integrated. These data sources may be local or distributed, possibly with different representation schemes. Often, related data from different sources correspond only with respect to some of their values. METHODS: In biological sequence analysis, a goal is to identify new, previously unknown, relevant patterns, to obtain additional insights into the biomolecule. This is known as a pattern discovery task, rather than a pattern matching task. In this research, we present a method to tackle this problem typically found in molecular sequence analysis when the alignment of the sequences is represented as a relation. In this article, we propose an information measure to select attribute values that reflect multiple patterns of significant interdependence information. Based on these selected values, the patterns are evaluated with data values from other sources. RESULTS: In the experiments, a cancer-suppressor gene known as TP53 (encoding tumour protein p53) is analysed with the mutation records of patients. The experiments identify previously unknown points in the molecule that have patterns negatively associated with the occurrence of cancer. CONCLUSION: Since the evaluated interdependence pattern is a global property of the molecule, we conjecture that the identified points might also be a reflection of the molecule's cancer-suppressor characteristics. The experiments also confirm the usefulness of the proposed method.

Amino Acid Sequence↗
PubMed2002

New advances in the management of anxiety disorders.

Anxiety disorders are highly prevalent and associated with significant symptomatic distress, increased morbidity, and increased mortality. Although efficacious pharmacologic and psychosocial therapies for the anxiety disorders are available, many patients who improve with treatment remain at least somewhat symptomatic. This article reviews the epidemiology, phenomenology, and associated complications of panic disorder, social anxiety disorder, posttraumatic stress disorder, and generalized anxiety disorder. Recent guidelines developed for application in the assessment of outcome of the anxiety disorders are discussed, and illustrative data from a number of treatment trials integrating remission data in assessment of outcome are examined.

Anxiety Disorders↗
PubMed1995

Mapping of human and macaque sensorimotor areas by integrating architectonic, transmitter receptor, MRI and PET data.

The human and macaque sensorimotor cortex was subdivided into numerous areas by a correlative analysis based on cytoarchitectonics, myeloarchitecture and the distribution of transmitter receptors. Receptor densities and laminar distribution patterns differ not only between motor and somatosensory regions, but also between different areas within these regions of the cortex. Changes in receptor distribution often match architectonically defined borders. Receptor findings provide new criteria for a more detailed mapping in the human brain which cannot be achieved by cytoarchitectonic analysis alone. Morphological data on these areas were integrated with functional data from positron emission tomography (PET) on the basis of a recently developed computerised brain atlas. The central sulcus marks the border between (1) the agranular motor cortex with a generally low density of glutamatergic, muscarinic, GABAergic and serotoninergic receptors, and (2) the granular somatosensory cortex with higher densities of these receptors. Rostral to the primary motor cortex, 2 isocortical areas are found on the mesial cortex which probably represent the functionally defined supplementary motor areas (SMA) SMA-proper (caudally) and pre-SMA (rostrally). Below SMA-proper the areas 24d (macaque) and the caudal cingulate motor area cmc (human) are located in the cingulate sulcus. Both regions correspond to the 'posterior cingulate motor areas' of recent PET studies and to the posterior part of the agranular cingulate cortex of architectonic studies. Below pre-SMA the area 24c (macaque) and the rostral cingulate motor area cmr (human) are located in the cingulate sulcus; they correspond to the 'anterior cingulate motor areas' of recent PET observations and to the anterior part of the agranular cingulate cortex of architectonic studies. Homologous sensorimotor areas can be defined in both species on the basis of common architectonic features.

Animals↗
PubMed1998

Guidelines for quality assurance in multicenter trials: a position paper.

In the wake of reports of falsified data in one of the trials of the National Surgical Adjuvant Project for Breast and Bowel Cancer supported by the National Cancer Institute, clinical trials came under close scrutiny by the public, the press, and Congress. Questions were asked about the quality and integrity of the collected data and the analyses and conclusions of trials. In 1995, the leaders of the Society for Clinical Trials (the Chair of the Policy Committee, Dr. David DeMets, and the President of the Society, Dr. Sylvan Green) asked two members of the Society (Dr. Genell Knatterud and Dr. Frank Rockhold) to act as co-chairs of a newly formed subcommittee to discuss the issues of data integrity and auditing. In consultation with Drs. DeMets and Green, the co-chairs selected other members (Ms. Franca Barton, Dr. C.E. Davis, Dr. Bill Fairweather, Dr. Stephen George, Mr. Tom Honohan, Dr. Richard Mowery, and Dr. Robert O'Neill) to serve on the subcommittee. The subcommittee considered "how clean clinical trial data should be, to what extent auditing procedures are required, and who should conduct audits and how often." During the initial discussions, the subcommittee concluded that data auditing was insufficient to achieve data integrity. Accordingly, the subcommittee prepared this set of guidelines for standards of quality assurance for multicenter clinical trials. We include recommendations for appropriate action if problems are detected.

Bias↗
PubMed2000

Integration of macromolecular diffraction data using radial basis function networks.

This paper presents a novel approach for intensity calculation of X-ray diffraction spots based on a two-stage radial basis function (RBF) network. The first stage uses pre-determined reference profiles from a database as basis functions in order to locate the diffraction spots and identify any overlapping regions. The second-stage RBF network employs narrow basis functions capable of local modifications of the reference profiles leading to a more accurate observed diffraction spot approximation and therefore accurate determination of spot positions and integrated intensities.

Journal Article↗
PubMed2006

[Integrating obtained knowledge from transcriptome data by a new framework for data analysis].

Microarray analyses facilitate the investigation of quantitative information coded in the genome by measuring transcriptome, which records the decoded information from the genome. The state of a cell and differences from other states can be studied through genome information, by comparing one set of transcriptome data to other sets. Clearly, those data should be shared and compared with researchers, and the knowledge should be integrated. Unfortunately, at present data comparisons in microarray analyses are quite difficult; the accuracy as well as the reproducibility is low. The difficulties are originated from data analyses methods. Data comparison requires an intelligent framework, such as that discussed by philosopher Sir Karl R Popper. Frameworks for microarray analyses have been developed by many efforts of bioinformatitians. The frameworks currently used are being inspected and critically discussed. By checking the mathematical models that form the practical frameworks, arbitrariness such as the lack of falsifiability has been pointed out. The paradigm in this field of analyses is also criticized by disagreement with the scientific standard, and it is shown as the origin of errors in analyses. The excessive numbers of frameworks produced in an ad hoc manner has also been criticized, since the existence of so many allows researchers to select different frameworks, discussions beyond frameworks are always difficult. A new framework that uses a parametric model is introduced with an explanation of the bases of the framework and the process of testing. Additionally, differences of obtained results by these frameworks are presented using GeneChip data, in stability of log-ratio measurements and reproducibility of analyses. The possibility of artificial decoding of genome information by an extended framework is also discussed.

Gene Expression Profiling↗
PubMed2006

Pre- and intraoperative processing and integration of various anatomical and functional data in neurosurgery.

A software system is presented, capable of integrating various information sources for neurosurgical procedures. These include anatomical data such as a standard 3D DICOM image stacks, atlas data, as well as functional information (e.g. fmri, MEG, EEG). The system is programmed in C++ using Open GL for visualisation, and was developed in a close cooperation with a neurosurgical department to match existing needs. Preoperatively the data may be combined, registered by a rigid or elastic matching process, enriched by user specified planning information such as annotations or trajectories, and visualised in a standard fashion using different segmentation schemes, interactive rotation, zooming etc. Selected portions of the gathered and generated information may then be exported for neuronavigation input in DICOM or a vendor specific format. Intraoperatively, this information may, on the one hand, be simply used as an integrational part of the routinely used navigational data. On the other hand, the system is also capable of interacting with the navigational system to integrate the actual spatial information of the ongoing procedure into the preoperative data, thus allowing further planning and visualisation beyond the scope of the navigational unit. Furthermore, intraoperatively updated information such as intraoperative MR images or electrophysiological data may be integrated and correlated to the existing information. Ongoing developments comprise redistribution of the relevant data for injection onto the screen of the navigational system or into the optical pathway of the (3D capable) microscope display/ocular. This also includes information about the actual automatically optimized accuracy of the navigation process in relation to the head markers in use.

Humans↗
PubMed2006

Integrating hospital medical care data with pharmaceutical education materials for diabetes self management.

Diabetic patients need long-term treatment and follow-up exams as well as appropriate self-care pharmaceutical education to get the disease under control and to prevent possible complications. Pharmaceutical treatment plays an essential role in diabetes. If patients don't understand the medicines and dosages they take, their blood glucose control may be affected. In addition, the possibility of developing hypoglycemia may be increased. In this paper, we enhance the POEM system, previously developed for diabetic patient education, by providing diabetic patients' pharmaceutical education. The new system integrates both diabetic patients' pharmaceutical education information and medical care information to provide them with more comprehensive personalized medication information so that they can access the on-line system afterwards. It also strengthens patients' understanding of pharmaceutical functions, side-effects and relevant knowledge thus increasing patients' adherence of medication orders and having better control in their blood glucose levels.

Diabetes Mellitus↗
PubMed2004

An integrated tool for microarray data clustering and cluster validity assessment.

UNLABELLED: In this paper we present a data mining system, which allows the application of different clustering and cluster validity algorithms for DNA microarray data. This tool may improve the quality of the data analysis results, and may support the prediction of the number of relevant clusters in the microarray datasets. This systematic evaluation approach may significantly aid genome expression analyses for knowledge discovery applications. The developed software system may be effectively used for clustering and validating not only DNA microarray expression analysis applications but also other biomedical and physical data with no limitations. AVAILABILITY: The program is freely available for non-profit use on request at http://www.cs.tcd.ie/Nadia.Bolshakova/Machaon.html CONTACT: Nadia.Bolshakova@cs.tcd.ie.

Algorithms↗
PubMed1993

Trunk strength and lumbar paraspinal muscle activity during isometric exercise in chronic low-back pain patients and controls.

The purpose of this study was to describe trunk strength and lumbar paraspinal muscle activity across five angles of flexion during isometric exercise and rest in chronic low-back pain patients and control subjects. High muscle tension as measured by surface integrated electromyography is predicted by a muscle spasm model, and low muscle tension is predicted by a muscle deficiency model. Prior lumbar surgery had no affect on peak torque or maximum surface integrated electromyography data. Both groups produced greater torque and less surface integrated electromyography in more flexed positions. Chronic low-back pain patients exhibited lower peak torque and lower maximum surface integrated electromyography bilaterally during isometric extension effort across all angles. A muscle deficiency model of chronic low back pain was supported by these data and a muscle spasm model was not supported. Discriminant analyses indicated that monitoring maximum surface integrated electromyography of lumbar muscles during isometric effort facilitates classification of chronic low-back pain patients. Future directions are discussed in terms of applying psychophysiologic methods to pain rehabilitation.

Adult↗
PubMed2004

The integration of medical images with the electronic patient record and their web-based distribution.

Medical images are currently created digitally and stored in the radiology department's picture archiving and communication system. Reports are usually stored in the electronic patient record of other information systems, such as the radiology information system (RIS) and the hospital information system (HIS). But high-quality services can only be provided if electronic patient record data is integrated with digital images in picture archiving and communication systems. Clinicians should be able to access both systems' data in an integrated and consistent way as part of their regular working environment, whether HIS or RIS. Also, this system should allow for teleconferencing with other users, eg, for consultation with a specialist in the radiology department. This article describes a web-based solution that integrates the digital images of picture archiving and communication systems with electronic patient record/HIS/RIS data and has built-in teleconferencing functionality. This integration has been successfully tested using three different commercial RIS and HIS products.

Humans↗
PubMed2005

Selective integration of multiple biological data for supervised network inference.

MOTIVATION: Inferring networks of proteins from biological data is a central issue of computational biology. Most network inference methods, including Bayesian networks, take unsupervised approaches in which the network is totally unknown in the beginning, and all the edges have to be predicted. A more realistic supervised framework, proposed recently, assumes that a substantial part of the network is known. We propose a new kernel-based method for supervised graph inference based on multiple types of biological datasets such as gene expression, phylogenetic profiles and amino acid sequences. Notably, our method assigns a weight to each type of dataset and thereby selects informative ones. Data selection is useful for reducing data collection costs. For example, when a similar network inference problem must be solved for other organisms, the dataset excluded by our algorithm need not be collected. RESULTS: First, we formulate supervised network inference as a kernel matrix completion problem, where the inference of edges boils down to estimation of missing entries of a kernel matrix. Then, an expectation-maximization algorithm is proposed to simultaneously infer the missing entries of the kernel matrix and the weights of multiple datasets. By introducing the weights, we can integrate multiple datasets selectively and thereby exclude irrelevant and noisy datasets. Our approach is favorably tested in two biological networks: a metabolic network and a protein interaction network. AVAILABILITY: Software is available on request.

Algorithms↗
PubMed1999

Use of a Web-based process model to implement security and data protection as an integral component of clinical information management.

Delivery of health care at Scott and White, a large integrated health care delivery system, is supported by an Electronic Medical Record (EMR) system repository of six million SGML-based documents. Control of document access is currently based on standard commercial security and confidentiality methodologies. Given the planned release in Fall 1999 of new federal security and confidentiality requirements, we have developed a web-based security process model that "wraps" existing EMR documents with HTML-compliant security attributes. Resulting logical documents are filtered regarding user queries by mapping the security attributes of the data to specific user role characteristics. A key virtue of our approach is that source EMR data do not undergo alteration by the imposition of the security process. It also places no additional work load or query pressure on the existing EMR system.

Computer Security↗
PubMed2005

Putting microarrays in a context: integrated analysis of diverse biological data.

In recent years, multiple types of high-throughput functional genomic data that facilitate rapid functional annotation of sequenced genomes have become available. Gene expression microarrays are the most commonly available source of such data. However, genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower-quality data than traditional experimental methods. Thus sophisticated analysis methods are necessary to make accurate functional interpretation of these large-scale data sets. This review presents an overview of recently developed methods that integrate the analysis of microarray data with sequence, interaction, localisation and literature data, and further outlines current challenges in the field. The focus of this review is on the use of such methods for gene function prediction, understanding of protein regulation and modelling of biological networks.

Algorithms↗
PubMed2006

Role of transmembrane domain/transmembrane domain interfaces of P-glycoprotein (ABCB1) in solute transport. Convergent information from photoaffinity labeling, site directed mutagenesis and in silico importance prediction.

Human P-glycoprotein (P-gp, ABCB1) plays an important role in the development of resistance to anticancer therapy. This ABC-transporter (ATP-binding cassette transporter) intercepts drugs at the level of the plasma membrane and effluxes them before they are able to reach their intracellular target structures. Inhibition of P-gp by low molecular weight compounds has been advocated as a concept for resensitization of cells to anticancer agents and several clinical studies in oncological patients have advanced to phase III. Even more importantly, P-glycoprotein also represents an antitarget. Its expression in cells lining the intestinal tract, the canalicular side of hepatocytes, renal tubuli and the blood brain barrier lead to interference with pharmacokinetics of compounds that are recognized as pump substrates. An early prediction of ADMET (Absorption-Distribution-Metabolism-Excretion-Toxicity) properties is important during drug development, since interference of a compound with P-gp might compromise its future development into a drug. Despite considerable efforts, the mechanism by which P-gp binds and transports its solutes remains unclear. Generation of homology models of the protein allowed integration of data obtained by photoaffinity labeling, in silico prediction of functional importance by evolutionary tracing and site directed mutagenesis. An integral view of data indicates that these three lines of evidence converge to indicate two pseudosymmetric P-gp drug binding pockets located at the two transmembrane domain interfaces.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2005

Comparing statistical and semantic approaches for identifying change from land cover datasets.

In this paper, we examine methods for integrating spatial data which apparently should be comparable because they are of the same data type or theme, but which are incompatible or discordant because the classes of that theme are different. For a variety of reasons including changes in methods, in understanding of the resource, and in policy initiatives in the commissioning of the survey, this problem is widespread in the results of natural resources surveys. We present two generic methods: one method is grounded in a statistical approach using discriminant analysis, and the other exploits the knowledge of experts. We use the context of land cover mapping of Great Britain to explore these approaches for integrating discordant data. We demonstrate that the expert-based approach gives very good levels of identification of locations with incompatible classifications at different times, and gives a much better rate of recognition of change. Some conclusions are made about the need to expand current metadata and data quality reporting to include descriptions of:- data conceptualisations, semantics and ontologies;- who decided and defined what the features of interest in a dataset are, and why. If the benefits of spatial data initiatives such as GRID, E-science and INSPIRE are to be fully realised then some method needs to be found to communicate that information most effectively to the potential user of the data.

Conservation of Natural Resources↗