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Consequences of analysing complex survey data using inappropriate analysis and software computing packages.

In the analysis of complex survey data such as stratified multi-stage cluster samples, ignoring the design effects such as clustering and stratification usually will lead to erroneous conclusions. In this paper, we will demonstrate the consequences in the estimation of means and proportions by two examples from a stratified two-stage cluster sample. A brief review of methodology will be presented, and some suggestions on computational issues will be provided.

Adult↗

Reverse-docking as a computational tool for the study of asymmetric organocatalysis.

A novel methodology for 'reverse-docking' a cationic peptide-based organocatalyst to a rigid anionic transition state (TS) model for the conjugate addition of azide to alpha,beta-unsaturated carbonyl substrates is described. The resulting docking poses serve as simplified TS models for enantioselective catalysis. Molecular mechanics-based scoring and ranking of the docking poses, followed by clustering and structural analysis, reveal a clear energetic preference for docking to the S-enantiomeric azidation TS model, in agreement with experiment. Clear energetic trends emerged from docking the catalyst to both enantiomers of all six azidation TS models of this study. Structural analysis of the most favorable pose suggests a mechanism for enantioselective catalysis that is consistent with principles of molecular recognition, catalysis, and experimental data.

Azides↗

POHEM--a framework for understanding and modelling the health of human populations.

A variety of developments have come together to serve as both an impetus to and foundation for the development of a new POpulation HEalth Model (POHEM) at Statistics Canada. Part of the impetus is statistical and derives from weaknesses in Canada's health statistics programme--particularly the lack of balance between information on health outcomes and health care resource consumption, and the absence of a coherent statistical structure. The other major impetus is the need for rational processes for managing and allocating resources to improve the health of Canadians. The foundation for the development of this model has come from the revolution in computing. Dramatic improvements have opened up new methodological opportunities, particularly sophisticated simulation modelling and detailed analyses of large volumes of microdata. POHEM is designed to build on these increasingly powerful methods in order to meet health statistical and policy needs. At this time, POHEM is like a partially-completed building. This article reviews its motivation, the overall architectural plan, and the portion of the structure already completed. A major portion of POHEM is devoted to the explicit modelling of chronic disease processes, using monte carlo microsimulation methods. The article concludes with illustrations of a few recent applications, focusing on the joint patterns of smoking, cholesterol and heart disease, osteoarthritis and lung cancer morbidity. While POHEM has been developed in a Canadian context, work is under way to create a version that can be used in other countries.

Adolescent↗

Bioinformatics and genomic medicine.

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational science. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolution in both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high-throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever, in much the same way that biochemistry did a generation ago. This paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine-learning algorithms are discussed. Use of integrative biochip informatics technologies, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the integrated management of biomolecular databases, are also discussed.

Computational Biology↗

Combining molecular modeling with experimental methodologies: mechanism of membrane permeation and accumulation of ofloxacin.

The interaction between ofloxacin, as a model drug of the fluoroquinolone class, and biomembranes was examined as the possible initial step in a transmembrane diffusion process. Dipalmitoylphosphatidylcholine was used for the preparation of biomembrane models. The influence of environmental conditions and protonation on molecular physicochemical behavior, and hence on the membrane interaction, was investigated by differential scanning calorimetry (DSC). This technique has been shown to be very effective in the interpretation of interactions of drug microspeciations with biomembranes. These findings suggest that the interaction occurred owing to ionic and hydrophobic forces showing how the passage through the membrane is mainly favored in the pH interval 6-7.4. It was demonstrated that a pH gradient through model membranes may be responsible for a poorly homogeneous distribution of ofloxacin (or other related fluoroquinolones), which justifies the in vivo accumulation properties of this drug. DSC experiments, which are in agreement with computational data, also showed that the complexing capability of ofloxacin with regard to Mg(++) or Ca(++) may govern the drug entrance into bacterial cells before the DNA Girase inhibition and could ensure the formation of hydrophobic and more fluid phospholipid domains on the surface of the model membrane. These regions are more permeable with regard to various solutes, as well as ofloxacin, allowing a so-called 'self-promoted entrance pathway'. The combination of experimental methodologies with computational data allowed a further rationalization of the results and opened new perspectives into the mechanism of action of ofloxacin, namely its interaction with lipid bilayers and drug-divalent cation complex formation, which might be extended to the entire fluoroquinolone class. Ofloxacin accumulation within Escherichia coli ATCC 25922 was measured as a function of time. Also in this example, the environmental conditions influenced ofloxacin penetration and accumulation. The in vitro experiments, reported here, show that a suitable balance of hydrophilic and hydrophobic fluoroquinolone properties needs to occur for there to be increased drug permeation.

1,2-Dipalmitoylphosphatidylcholine↗

Time lines and computer-based visual editing: new techniques for assessing exposure in epidemiologic studies.

We describe a time-line-based methodology for collecting exposure data for epidemiologic studies and for processing these data for statistical analysis with readily available software for the personal computer. The four components to this approach are: (1) collecting data in a memory-enhancing time-line format; (2) entering data from time lines into a computer database and editing them; (3) making a quantitative estimate of exposure, intake, or dose for each exposure event; and (4) creating analysis datasets by 'slicing' the quantified time lines based on desired exposure intervals or disease latent periods. Compared with fixed-format interviews, time-line-based interviews help subjects organize remembered events, thereby reducing confusion. They do not restrict responses to predetermined categorical exposure responses. The time-line methodology also facilitates the collection of supplementary data necessary for computing doses for complex exposures and the packaging of quantified exposures into analysis datasets for any time period of interest.

Child↗

New diagnostic tool for robotic psychology and robotherapy studies.

Robotic psychology and robotherapy as a new research area employs a systematic approach in studying psycho-physiological, psychological, and social aspects of person-robot communication. An analysis of the mechanisms underlying different forms of computer-mediated behavior requires both an adequate methodology and research tools. In the proposed article we discuss the concept, basic principles, structure, and contents of the newly designed Person-Robot Complex Interactive Scale (PRCIS), proposed for the purpose of investigating psychological specifics and therapeutic potentials of multilevel person-robot interactions. Assuming that human-robot communication has symbolic meaning, each interactive pattern evaluated via the newly developed scale is assigned certain psychological value associated with the person's past life experiences, likes and dislikes, emotional, cognitive, and behavioral traits or states. PRCIS includes (1) assessment of a person's individual style of communication with the robotic creature based on direct observations; (2) the participant's evaluation of his/her new experiences with an interactive robot and evaluation of its features, advantages and disadvantages, as well as past experiences with modern technology; and (3) the instructor's overall evaluation of the session.

Animals↗

The influence of the biarticularity of the gastrocnemius muscle on vertical-jumping achievement.

Hypotheses concerning the influence of changes in the design of the human musculoskeletal system on performance cannot be tested experimentally. Computer modelling and simulation provide a research methodology that does allow manipulation of the system's design. In the present study this methodology was used to test a recently formulated hypothesis concerning the role of the biarticularity of the gastrocnemius muscle (GAS) in vertical jumping [Bobbert and van Ingen Schenau, J. Biomechanics 21, 249-262 (1988)]. This was done by comparing maximal jump heights for a model equipped with biarticular GAS with a model equipped with a monoarticular GAS. It was found that jump height decreased by 10 mm when GAS was changed into a monoarticular muscle. Thus, the hypothesis formulated by Bobbert was substantiated, although quantitatively the effect is small. Our result differs from that of Pandy and Zajac [J. Biomechanics 24, 1-10 (1991)], who performed similar model calculations. It is shown that the results described by these authors can be explained from the moment-arm-joint-angle relation of GAS at the knee in their model.

Ankle Joint↗

Stereology, morphometry, and mapping: the whole is greater than the sum of its parts.

The latest developments in computer-based stereology build upon the similarities of classical stereology and computer microscopy to provide refined and effective spatial analyses that also permit mapping of anatomical regions. Classical stereology and computer microscopy have developed along independent pathways as methodologies to provide a quantitative understanding of the structure of the brain. They approach brain morphology and brain morphometry from different points of view. On one hand, stereology has concentrated upon the unbiased numerical estimation of parameters, such as length, area, volume, and population size that characterize entire regions of the brain, e.g. hippocampus, as well as individual elements within them, e.g. cell volume. On the other hand, computer microscopy has concentrated upon providing accurate three-dimensional maps of the morphology of entire regions of the brain as well as of individual elements within them, e.g. neuronal dendrite and axon systems. The differences in point of view are not so extensive as to keep the two methodologies separate. They share, after all, a similar manner of controlling microscope data input and analyzing the images the microscope provides. The incorporation of data archiving permits easier access to previous studies, as well as the sharing of stereological findings and their related maps throughout the scientific community. Some of the stereological systems now integrate spatial mapping with stereological analyses to provide more comprehensive methods to analyze brain tissue.

Animals↗

Splenic abscess: diagnosis and management.

BACKGROUND/AIMS: To evaluate the usefulness of a combination of computed tomography and sonography for splenic abscess diagnosis and management determination. METHODOLOGY: From January 1986 to June 1999, 30 patients of pyogenic splenic abscess were collected in our hospital. Computed tomograms of the spleen were performed on all of the patients, and abdominal sonographies were performed on 26 of them. The imaging findings of all the patients were reviewed with respect to the clinical presentations, predisposing factors, infective organisms, method of treatment and clinical outcome. RESULTS: The clinical triad of splenic abscess was the main presentation of the 30 patients; it included fever (92%), left upper abdominal pain (77%) and leukocytosis (66%). Infective bacteria were identified in 19 patients, and the most offending bacteria were aerobes (82.6%). The radiological findings included single abscess were found in 16 patients and multiple abscesses were noted in 14 patients. The computed tomography and sonography findings included abnormal gas content (6 cases), progressive enlargement of lesion (6 cases), subcapsular extension of lesion (6 cases), extracapsular fluid collection (8 cases) and cystic lesion (7 cases). 59% of the cases had at least one of the above imaging findings. With the combination of the clinical triad and the imaging findings, the diagnostic rate rose up to 86.7%. CONCLUSIONS: Although splenic abscess is rare, it has a high mortality rate if there is delay in diagnosis and treatment. With the combination of computed tomography, sonography and clinical features, early diagnosis and treatment can be made. Percutaneous drainage for single abscess and splenectomy for multiple abscesses are the safe and effective treatment choice. The computed tomography and sonography appearance of splenic abscess is a valuable predictor of outcome of splenic abscess drainage. Medical treatment alone was definitely insufficient.

Abscess↗

RECPAM: a computer program for recursive partition amalgamation for censored survival data and other situations frequently occurring in biostatistics. II. Applications to data on small cell carcinoma of the lung (SCCL).

The RECPAM methodology previously presented in part I (A. Ciampi et al., Comput. Methods Programs Biomed. 26 (1988) 239-256) is applied to the analysis of survival data on small cell carcinoma of the lung (SCCL). It is shown how RECPAM can help answer the following questions which occur frequently in the analysis of clinical data: Is it possible to find a classification of patients with a certain disease into distinct prognostic groups? Given a covariate of special interest, does it have an independent prognostic significance even after confounding is taken into account? Does the prognostic significance of a covariate of special interest vary across patient subgroups? For the SCCL data, a prognostic classification is obtained and the tumor marker LDH is treated as a variable of special interest. Many features of RECPAM are illustrated, including, among others, Forward and Backward (Pruning) Stopping Rules, treatment of missing data, and use of several dissimilarity measures.

Biomarkers, Tumor↗

[The use of knowledge in public health nursing activities in child health care; a methodological study].

The purpose of this research is to study the selection and use of nursing knowledge in two simulated practical situations in child health care. The study introduces a computer-simulated test based on the decision-making process. The contents of the simulations are a reality-based case description including theoretical and experimental knowledge about child's development, care and education. The target group consists of 61 public health nurses. The computer simulations was implemented in workplaces of public health nurses. The results of the study prove that the main focus in the work is on the child and his/her health status, development and care but it includes also family and environment. The use of knowledge was not always systematic and relative to the child's and the family needs.

Child↗

Delivering bioinformatics training: bridging the gaps between computer science and biomedicine.

Biomedical researchers have always sought innovative methodologies to elucidate the underlying biology in their experimental models. As the pace of research has increased with new technologies that 'scale-up' these experiments, researchers have developed acute needs for the information technologies which assist them in managing and processing their experiments and results into useful data analyses that support scientific discovery. The application of information technology to support this discovery process is often called bioinformatics. We have observed a 'gap' in the training of those individuals who traditionally aid in the delivery of information technology at the level of the end-user (e.g. a systems analyst working with a biomedical researcher) which can negatively impact the successful application of technological solutions to biomedical research problems. In this paper we describe the roots and branches of bioinformatics to illustrate a range of applications and technologies that it encompasses. We then propose a taxonomy of bioinformatics as a framework for the identification of skills employed in the field. The taxonomy can be used to assess a set of skills required by a student to traverse this hierarchy from one area to another. We then describe a curriculum that attempts to deliver the identified skills to a broad audience of participants, and describe our experiences with the curriculum to show how it can help bridge the 'gap'.

Computational Biology↗

Computer-aided stereotactic functional neurosurgery enhanced by the use of the multiple brain atlas database.

This paper introduces a computer-aided atlas-based functional neurosurgery methodology and describes NeuroPlanner, a software system which supports it. NeuroPlanner provides four groups of functions: 1) data-related for data reading, interpolation, reformatting, and image processing; 2) atlas-related for multiple atlases reading, atlas-to-data global and local registrations, two-way anatomical indexing, and multiple labeling in two and three dimensions; 3) atlas-data exploration-related for three-dimensional (3-D) display and real-time manipulation of cerebral structures, continuous navigation, two-dimensional (2-D), triplanar, 3-D presentations, and 2-D interaction in four views; and 4) neurosurgery-related for targeting, trajectory planning, mensuration, simulating the insertion of microelectrode, and simulating therapeutic lesioning. All operations, excluding atlas and data reading, are real time. The combined anatomical index of the multiple brain atlas database containing complementary 2-D and 3-D atlases has about 1000 structures per hemisphere, and over 400 sulcal patterns. Neurosurgical planning with mutually preregistered multiple brain atlases in all three orthogonal orientations is novel. The approach is validated with 24 intraoperative and postoperative datasets for thalamotomies, thalamic stimulations, pallidotomies, and pallidal stimulations. Its potential benefits include increased accuracy of target definition, reduced time of the surgical procedure by decreasing the number of tracts, facilitated planning of more sophisticated trajectories, lowered cost by reducing the number of microelectrodes used, reduced surgical complications, and the extra degree of confidence given to the neurosurgeon.

Brain Mapping↗

PET/CT: will it change the way that we use CT in cancer imaging?

Accurate staging of cancer is of fundamental importance to treatment selection and planning. Current staging paradigms focus, first, on a detailed delineation of the primary tumour in order to determine its suitability for resection, and, thereafter, on assessment of the presence of metastatic spread that would alter the surgical approach, or mandate non-surgical therapies. This approach has, at its core, the assumption that the best, and sometimes the only, way to cure a patient of cancer is by surgical resection. Unfortunately, all non-invasive techniques in current use have imperfect ability to identify those primary tumours that are able to be completely excised, and even worse ability to define the extent of metastatic spread. Nevertheless, because of relatively low cost and widespread availability, computed tomography (CT) scanning is the preferred methodology for tumour, nodal and systemic metastasis (TNM) staging. This is often supplemented by other tests that have improved performance in particular staging domains. For example, magnetic resonance imaging (MRI), mammography, or endoscopic ultrasound may be used as complementary tests for T-staging; surgical nodal sampling for N-staging; and bone scanning, MRI or ultrasound for M-staging. Accordingly, many patients undergo a battery of investigations but, even then, are found to have been incorrectly staged based on subsequent outcomes. Even for those staged surgically, pathology can only identify metastases within the resection specimens and has no capability for detecting remote disease. As a result of this, many patients undergo futile operations for disease that could never have been cured by surgery. In the case of restaging, the situation is even worse. The sequelae of prior treatment can be difficult to differentiate from residual cancer and the likelihood of successful salvage therapy is even less than at presentation. More deleteriously, patients may be subjected to additional morbid treatments when cure has already been achieved. Thus, in post-treatment follow-up, the presence and extent of disease is equally critical to treatment selection and patient outcome as it is in primary staging. One of the major strengths of positron emission tomography (PET)/CT as a cancer staging modality is its ability to identify systemic metastases. At any phase of cancer evaluation, demonstration of systemic metastasis has profound therapeutic and prognostic implications. Only in the absence of systemic metastasis does nodal status become important, and only when unresectable nodal metastasis has been excluded does T-stage become important. There are now accumulating data that PET/CT could be used as the first, rather than the last test to assess M- and N-stage for evaluating cancers with an intermediate to high pre-test likelihood of metastatic disease based on poor long-term survival. In this scenario, there is great opportunity for subsequently selecting and tailoring the performance of anatomically based imaging modalities to define the structural relations of abnormalities identified by PET, when this information would be of relevance to management planning. Primary staging of oesophageal cancer and restaging of colorectal cancer are illustrative examples of a new paradigm for cancer imaging.

Adenocarcinoma↗

Pharmacokinetic considerations in the PET and SPECT evaluation of CNS receptors.

Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) are the only functional imaging methodologies that allow to evaluate, in vivo in human, specific binding proteins such as receptors, transporters or enzymes. PET and SPECT have already proved to be unique tools to follow, in the living human brain, the kinetics of the interaction of a radiolabelled ligand with its receptors. However, these imaging techniques measure the radioligand concentration in regions of interest (ROIs) as a function of time but they do not allow the direct measurement of the binding parameters, i.e. receptor concentration and radioligand affinity. To estimate these physiological parameters a mathematical model must be designed to simulate the kinetics of the radioligand. The modelling of the data obtained using such equilibrium or dynamic models allow to extract from the kinetic data these physiological parameters. PET and SPECT imaging methodologies have then opened a new era in brain biochemistry and have already important applicants in brain physiopathology, clinical pharmacology and drug development.

Brain↗

Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac).

The need to integrate massively increasing amounts of data on the mammalian brain has driven several ambitious neuroscientific database projects that were started during the last decade. Databasing the brain's anatomical connectivity as delivered by tracing studies is of particular importance as these data characterize fundamental structural constraints of the complex and poorly understood functional interactions between the components of real neural systems. Previous connectivity databases have been crucial for analysing anatomical brain circuitry in various species and have opened exciting new ways to interpret functional data, both from electrophysiological and from functional imaging studies. The eventual impact and success of connectivity databases, however, will require the resolution of several methodological problems that currently limit their use. These problems comprise four main points: (i) objective representation of coordinate-free, parcellation-based data, (ii) assessment of the reliability and precision of individual data, especially in the presence of contradictory reports, (iii) data mining and integration of large sets of partially redundant and contradictory data, and (iv) automatic and reproducible transformation of data between incongruent brain maps. Here, we present the specific implementation of the 'collation of connectivity data on the macaque brain' (CoCoMac) database (http://www.cocomac.org). The design of this database addresses the methodological challenges listed above, and focuses on experimental and computational neuroscientists' needs to flexibly analyse and process the large amount of published experimental data from tracing studies. In this article, we explain step-by-step the conceptual rationale and methodology of CoCoMac and demonstrate its practical use by an analysis of connectivity in the prefrontal cortex.

Animals↗

Knowledge engineering for clinical consultation programs: modeling the application area.

Developers of computer-based decision-support tools frequently adopt either pattern recognition or artificial intelligence techniques as the basis for their programs. Because these developers often choose to accentuate the differences between these alternative approaches, the more fundamental similarities are frequently overlooked. The principal challenge in the creation of any clinical consultation program - regardless of the methodology that is used - lies in creating a computational model of the application domain. The difficulty in generating such a model manifests itself in symptoms that workers in the expert systems community have labeled "the knowledge-acquisition bottleneck" and "the problem of brittleness". This paper explores these two symptoms and shows how the development of consultation programs based on pattern-recognition techniques is subject to analogous difficulties. The expert systems and pattern recognition communities must recognize that they face similar challenges, and must unite to develop methods that assist with the process of building of models of complex application tasks.

Decision Support Techniques↗