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The thought behind the words: a view of schizophrenic speech and thinking disorders.

Chaika (1982) has proposed that what is frequently viewed as a schizophrenic thought disorder should more precisely be regarded as a speech disorder. We suggest, however, that one should emphasize constructs concerning disordered schizophrenic thinking. We support this position since the schizophrenic's strange speech can fit into a larger view about his disordered thinking which is grounded in a nomological net involving various different types of strange behavior. Other support comes from (1) the use of tests assessing disordered nonverbal behavior, (2) evidence that schizophrenics intermingle personal concerns (ideas) into their verbalizations, (3) bizarre schizophrenic behavior, and (4) the very large percent of schizophrenics with delusions. There is an intricate link between language--which includes a system of symbols, words, and meanings--and thinking. Thus, we have proposed that the disturbance most frequently observed in schizophrenic verbalizations be viewed as involving conceptual-linguistic activity, and not just a problem of speech activity.

Cognition Disorders↗

A knowledge discovery object model API for Java.

BACKGROUND: Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized. RESULTS: This work describes an application programming interface (API) that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually. CONCLUSIONS: The Knowledge Discovery Object Model (KDOM) API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at http://www.bcgsc.ca/bioinfo/software.

Artificial Intelligence↗

The systems approach to the oculomotor system.

Recent progress in understanding the oculomotor system is briefly reviewed. This progress is largely due to technological advances such as the ability to record from neurons in behaving animals. Furthermore, parts of the oculomotor system are now well-enough understood that the techniques of exact science, such as quantitation and mathematical description, are becoming useful. This, in turn, leads to the use of the language of systems analysis, and the vestibulo-ocular reflex is examined as an example of such a description. Systems analysis not only organizes current knowledge but leads to predictions by way of hypotheses known as models. A model of time integration by neurons is given as an example. It is put forward to illustrate that our biggest problem at the moment is an inability to test such models at the neuronal network level.

Animals↗

A computational approach to prefrontal cortex, cognitive control and schizophrenia: recent developments and current challenges.

In this chapter we consider the mechanisms involved in cognitive control-from both a computational and a neurobiological perspective- and how these might be impaired in schizophrenia. By 'control', we mean the ability of the cognitive system to flexibly adapt its behaviour to the demands of particular tasks, favouring the processing of task-relevant information over other sources of competing information, and mediating task-relevant behaviour over habitual, or otherwise prepotent responses. There is a large body of evidence to suggest that the prefrontal cortex (PFC) plays a critical role in cognitive control. In previous work, we have used a computational framework to understand and develop explicit models of this function of PFC, and its impairment in schizophrenia. This work has lead to the hypothesis that PFC houses a mechanism for representing and maintaining context information. We have demonstrated that this mechanism can account for the behavioural inhibition and active memory functions commonly ascribed to PFC, and for human performance in simple attention, language and memory tasks that draw upon these functions for cognitive control. Furthermore, we have used our models to simulate detailed patterns of cognitive deficit observed in schizophrenia, an illness associated with marked disturbances in cognitive control, and well established deficits of PFC. Here, we review results of recent empirical studies that test predictions made by our models regarding schizophrenic performance in tasks designed specifically to probe the processing of context. These results showed selective schizophrenic deficits in tasks conditions that placed the greatest demands on memory and inhibition, both of which we have argued rely on the processing of context. Furthermore, we observed predicted patterns of deterioration in first episode vs multi-episode patients. We also discuss recent developments in our computational work, that have led to refinements of the models that allow us to simulate more detailed aspects of task performance, such as reaction time data and manipulations of task parameters such as interstimulus delay. These refined models make several provocative new predictions, including conditions in which schizophrenics and control subjects are expected to show similar reaction time performance, and we provide preliminary data in support of these predictions. These successes notwithstanding, our theory of PFC function and its impairment in schizophrenia is still in an early stage of development. We conclude by presenting some of the challenges to the theory in its current form, and new directions that we have begun to take to meet these challenges. In particular, we focus on refinements concerning the mechanisms underlying active maintenance of representations within PFC, and the characteristics of these representations that allow them to support the flexibility of cognitive control exhibited by normal human behaviour. Taken in toto, we believe that this work illustrates the value of a computational approach for understanding the mechanisms responsible for cognitive control, at both the neural and psychological levels, and the specific manner in which they break down in schizophrenia.

Cognition↗

New computing paradigms suggested by DNA computing: computing by carving.

Inspired by the experiments in the emerging area of DNA computing, a somewhat unusual type of computation strategy was recently proposed by one of us: to generate a (large) set of candidate solutions of a problem, then remove the non-solutions such that what remains is the set of solutions. This has been called a computation by carving. This idea leads both to a speculation with possible important consequences--computing non-recursively enumerable languages--and to interesting theoretical computer science (formal language) questions.

Animals↗

Australian nurses in general practice based heart failure management: implications for innovative collaborative practice.

BACKGROUND: The growing global burden of heart failure (HF) necessitates the investigation of alternative methods of providing co-ordinated, integrated and client-focused primary care. Currently, the models of nurse-coordinated care demonstrated to be effective in randomized controlled trials are only available to a relative minority of clients and their families with HF. This current gap in service provision could prove fertile ground for the expansion of practice nursing [The Nurse in Family Practice: Practice Nurses and Nurse Practitioners in primary health care. 1988, Scutari Press, London: Impact of rural living on the experience of chronic illness. Australian Journal of Rural Health, 2001. 9: 235-240]. AIM: This paper aims to review the published literature describing the current and potential role of the practice nurse in HF management in Australia. METHODS: Searches of electronic databases, the reference lists of published materials and the internet were conducted using key words including 'Australia', 'practice nurse', 'office nurse', 'nurs*', 'heart failure', 'cardiac' and 'chronic illness'. Inclusion criteria for this review were English language literature; nursing interventions for heart failure (HF) and the role of practice nurses in primary care. RESULTS: There is currently a paucity of data evaluating the potential role for practice nurses in a reconfigured, collaborative health care system. Those studies that were identified were, largely, of a descriptive nature. In addition to identifying the practice nurse as a largely unexplored resource, key themes that emerged from the review include: (1) current general practice services face significant barriers to the implementation of evidence-based HF practice; (2) there is considerable variation in the practice nurse role between general practices; (3) there are significant barriers to the expansion of the practice nurse role; (4) multidisciplinary interventions can effectively deliver secondary prevention strategies; (5) practice nurses can potentially facilitate these multidisciplinary interventions; and (6) practice nurses are favorably perceived by consumers although there is some confusion about the nature of their role. CONCLUSION: On the basis of this literature review, practice nurses represent a potentially useful adjunct to current models of service provision in HF management. Further research needs to comprehensively investigate the role of the practice nurse in the Australian context with a view to developing effective and sustainable frameworks for clinical practice. In particular, high-level evidence is required to evaluate the efficacy of the practice nurse role compared to current disease management strategies.

Attitude of Health Personnel↗

Benefits of adding a drug to a single-agent or a 2-agent chemotherapy regimen in advanced non-small-cell lung cancer: a meta-analysis.

CONTEXT: Randomized trials have demonstrated that adding a drug to a single-agent or to a 2-agent regimen increased the tumor response rate in patients with advanced non-small-cell lung cancer (NSCLC), although its impact on survival remains controversial. OBJECTIVE: To evaluate the clinical benefit of adding a drug to a single-agent or 2-agent chemotherapy regimen in terms of tumor response rate, survival, and toxicity in patients with advanced NSCLC. DATA SOURCES AND STUDY SELECTION: Data from all randomized controlled trials performed between 1980 and 2001 (published between January 1980 and October 2003) comparing a doublet regimen with a single-agent regimen or comparing a triplet regimen with a doublet regimen in patients with advanced NSCLC. There were no language restrictions. Searches of MEDLINE and EMBASE were performed using the search terms non-small-cell lung carcinoma/drug therapy, adenocarcinoma, large-cell carcinoma, squamous-cell carcinoma, lung, neoplasms, clinical trial phase III, and randomized trial. Manual searches were also performed to find conference proceedings published between January 1982 and October 2003. DATA EXTRACTION: Two independent investigators reviewed the publications and extracted the data. Pooled odds ratios (ORs) for the objective tumor response rate, 1-year survival rate, and toxicity rate were calculated using the fixed-effect model. Pooled median ratios (MRs) for median survival also were calculated using the fixed-effect model. ORs and MRs lower than unity (<1.0) indicate a benefit of a doublet regimen compared with a single-agent regimen (or a triplet regimen compared with a doublet regimen). DATA SYNTHESIS: Sixty-five trials (13 601 patients) were eligible. In the trials comparing a doublet regimen with a single-agent regimen, a significant increase was observed in tumor response (OR, 0.42; 95% confidence interval [CI], 0.37-0.47; P<.001) and 1-year survival (OR, 0.80; 95% CI, 0.70-0.91; P<.001) in favor of the doublet regimen. The median survival ratio was 0.83 (95% CI, 0.79-0.89; P<.001). An increase also was observed in the tumor response rate (OR, 0.66; 95% CI, 0.58-0.75; P<.001) in favor of the triplet regimen, but not for 1-year survival (OR, 1.01; 95% CI, 0.85-1.21; P =.88). The median survival ratio was 1.00 (95% CI, 0.94-1.06; P =.97). CONCLUSION: Adding a second drug improved tumor response and survival rate. Adding a third drug had a weaker effect on tumor response and no effect on survival.

Antineoplastic Combined Chemotherapy Protocols↗

A parallel implementation of the backward error propagation neural network training algorithm: experiments in event identification.

An artificial neural-network-based (ANN) event detection and alarm generation system has been developed to aid clinicians in the identification of critical events commonly occurring in the anesthesia breathing circuit. To detect breathing circuit problems, the system monitored CO2 gas concentration, gas flow, and airway pressure. Various parameters were extracted from each of these input waveforms and fed into an artificial neural network. To develop truly robust ANNs, investigators are required to train their networks on large training data sets, requiring enormous computing power. We implemented a parallel version of the backward error propagation neural network training algorithm in the widely portable parallel programming language C-Linda. A maximum speedup of 4.06 was obtained with six processors. This speedup represents a reduction in total run-time from 6.4 to 1.5 h. By reducing the total run time of the computation through parallelism, we were able to optimize many of the neural network's initial parameters. We conclude that use of the master-worker model of parallel computation is an excellent method for speeding up the backward error propagation neural network training algorithm.

Algorithms↗

The processing of prosody: Evidence of interhemispheric specialization at the age of four.

Beyond its multiple functions in language comprehension and emotional shaping, prosodic cues play a pivotal role for the infant's amazingly rapid acquisition of language. However, cortical correlates of prosodic processing are largely controversial, even in adults, and functional imaging data in children are sparse. We here use an approach which allows to experimentally determine brain activations correlating to the perception and processing of sentence prosody during childhood. In 4-year-olds, we measured focal brain activation using near-infrared spectroscopy and demonstrate that processing prosody in isolation elicits a larger right fronto-temporal activation whereas a larger left hemispheric activation is elicited by the perception of normal language with full linguistic content. Hypothesized by the dual-pathway-model, the present data provide experimental evidence that in children specific language processes rely on interhemispheric specialization with a left hemispheric dominance for processing segmental (i.e. phonological) and a right hemispheric dominance for processing suprasegmental (i.e. prosodic) information. Generally in accordance with the imaging data reported in adults, our finding underlines the notion that interhemispheric specialization is a continuous process during the development of language.

Brain↗

Towards an integrated protein-protein interaction network: a relational Markov network approach.

Protein-protein interactions play a major role in most cellular processes. Thus, the challenge of identifying the full repertoire of interacting proteins in the cell is of great importance and has been addressed both experimentally and computationally. Today, large scale experimental studies of protein interactions, while partial and noisy, allow us to characterize properties of interacting proteins and develop predictive algorithms. Most existing algorithms, however, ignore possible dependencies between interacting pairs and predict them independently of one another. In this study, we present a computational approach that overcomes this drawback by predicting protein-protein interactions simultaneously. In addition, our approach allows us to integrate various protein attributes and explicitly account for uncertainty of assay measurements. Using the language of relational Markov networks, we build a unified probabilistic model that includes all of these elements. We show how we can learn our model properties and then use it to predict all unobserved interactions simultaneously. Our results show that by modeling dependencies between interactions, as well as by taking into account protein attributes and measurement noise, we achieve a more accurate description of the protein interaction network. Furthermore, our approach allows us to gain new insights into the properties of interacting proteins.

Algorithms↗

Automated alignment and pattern recognition of single-molecule force spectroscopy data.

Recently, direct measurements of forces stabilizing single proteins or individual receptor-ligand bonds became possible with ultra-sensitive force probe methods like the atomic force microscope (AFM). In force spectroscopy experiments using AFM, a single molecule or receptor-ligand pair is tethered between the tip of a micromachined cantilever and a supporting surface. While the molecule is stretched, forces are measured by the deflection of the cantilever and plotted against extension, yielding a force spectrum characteristic for each biomolecular system. In order to obtain statistically relevant results, several hundred to thousand single-molecule experiments have to be performed, each resulting in a unique force spectrum. We developed software and algorithms to analyse large numbers of force spectra. Our algorithms include the fitting polymer extension models to force peaks as well as the automatic alignment of spectra. The aligned spectra allowed recognition of patterns of peaks across different spectra. We demonstrate the capabilities of our software by analysing force spectra that were recorded by unfolding single transmembrane proteins such as bacteriorhodopsin and NhaA. Different unfolding pathways were detected by classifying peak patterns. Deviant spectra, e.g. those with no attachment or erratic peaks, can be easily identified. The software is based on the programming language C++, the GNU Scientific Library (GSL), the software WaveMetrics IGOR Pro and available open-source at http://bioinformatics.org/fskit/.

Algorithms↗

An SAS/IML procedure for maximum likelihood factor analysis.

Maximum likelihood factor analysis (MLFA), originally introduced by Lawley (1940), is based on a firm mathematical foundation that allows hypothesis testing when normality is assumed with large sample sizes. MLFA has gained in popularity since Jöreskog (1967) implemented an iterative algorithm to estimate parameters. This article presents a concise program using matrix language SAS/IML with the optimization subroutine NLPQN to obtain MLFA solutions. The program is pedagogically useful because it shows the step-by-step computational processes for MLFA, whereas almost all other statistical packages for MLFA are in "black boxes." It is also demonstrated that this approach can be extended to other multivariate methods requiring numerical optimizations, such as the widely used structural equation modeling. Researchers may find this program useful in conducting Monte Carlo simulation studies to investigate the properties of multivariate methods that involve numerical optimizations.

Algorithms↗

[Cognitive processes and neuronal networks].

It is clear that computers are but a poor brain models: the nervous system has many "processors" (neurons) in parallel, whereas von Neuman's machines work sequentially on a single processor. In complex systems, emergent properties cannot be inferred from the behaviour of single elements. Anthills display collective "meaningful" moves, while each ant seems to obey local interactions only. Likewise, large parallel networks of processing elements elicit emergent properties. Like brains, some of them are self-organizing systems. In large parallel processing networks, each unit performs an elementary computation: adding inputs from other units. Large nets display surprising spontaneous computational abilities: associative memories, classes, generalizations may be seen as emergent properties of the network. Symbols are dynamical entities, whose handing is driven by local interactions of activation/inhibition of related representations. In such models, representations (memories) are distributed in the whole network, as stable configurations. Indeed, the basic properties of representation in connectionist models seem closer to human mental objects than the classic Artificial Intelligence concepts. Connectionist models have been used in many fields, namely simulations of real neural networks, pattern recognition and artificial vision, speech recognition, language understanding and knowledge representation, problem solving... Connectionist models have been thus used in neurobiology as well as cognition. One basic structure seems indeed able to account for a range of cognitive functions, from perception to problem solving and high level cognitive tasks. Nevertheless studies about "pathological" networks are yet rare, still an open field... We explore some of these fields.

Artificial Intelligence↗

Implementing a low-cost computer-based patient record: a controlled vocabulary reduces data base design complexity.

In order to build a computer-based patient record (CPR) system suitable for use in solo and small group practice settings it is necessary to use development methods that minimize cost. Design complexity is a major source of high cost. Reducing complexity should result in lower development, deployment and maintenance costs as well as higher reliability. We have developed a simplified relational model and have used that model, in conjunction with a controlled vocabulary, to implement a CPR that can capture and store patient examinations and other forms of clinical notes as well as laboratory and other test results. The information can be viewed in a familiar document format and it can accessed for other types of processing using standard Structured Query Language (SQL) techniques. The database, as implemented, uses inexpensive components resulting in a system that is not prohibitively expensive for solo practitioners and small groups. In addition the architecture is scaleable and can accommodate very large numbers of patients and practitioners.

Computer Systems↗

WWW creates new interactive 3D graphics and collaborative environments for medical research and education.

Virtual Reality Modelling Language (VRML) is the start of a new era for medicine and the World Wide Web (WWW). Scientists can use VRML across the Internet to explore new three-dimensional (3D) worlds, share concepts and collaborate together in a virtual environment. VRML enables the generation of virtual environments through the use of geometric, spatial and colour data structures to represent 3D objects and scenes. In medicine, researchers often want to interact with scientific data, which in several instances may also be dynamic (e.g. MRI data). This data is often very large and is difficult to visualise. A 3D graphical representation can make the information contained in such large data sets more understandable and easier to interpret. Fast networks and satellites can reliably transfer large data sets from computer to computer. This has led to the adoption of remote tale-working in many applications including medical applications. Radiology experts, for example, can view and inspect in near real-time a 3D data set acquired from a patient who is in another part of the world. Such technology is destined to improve the quality of life for many people. This paper introduces VRML (including some technical details) and discusses the advantages of VRML in application developing.

Computer Communication Networks↗

FPV: fast protein visualization using Java 3D.

MOTIVATION: Many tools have been developed to visualize protein structures. Tools that have been based on Java 3D((TM)) are compatible among different systems and they can be run remotely through web browsers. However, using Java 3D for visualization has some performance issues with it. The primary concerns about molecular visualization tools based on Java 3D are in their being slow in terms of interaction speed and in their inability to load large molecules. This behavior is especially apparent when the number of atoms to be displayed is huge, or when several proteins are to be displayed simultaneously for comparison. RESULTS: In this paper we present techniques for organizing a Java 3D scene graph to tackle these problems. We have developed a protein visualization system based on Java 3D and these techniques. We demonstrate the effectiveness of the proposed method by comparing the visualization component of our system with two other Java 3D based molecular visualization tools. In particular, for van der Waals display mode, with the efficient organization of the scene graph, we could achieve up to eight times improvement in rendering speed and could load molecules three times as large as the previous systems could. AVAILABILITY: EPV is freely available with source code at the following URL: http://www.cs.ucsb.edu/~tcan/fpv/

Computer Graphics↗

A review of medical imaging informatics.

This review of medical imaging informatics is a survey of current developments in an exciting field. The focus is on informatics issues rather than traditional data processing and information systems, such as picture archiving and communications systems (PACS) and image processing and analysis systems. In this review, we address imaging informatics issues within the requirements of an informatics system defined by the American Medical Informatics Association. With these requirements as a framework, we review, in four sections: (1) Methods to present imaging and associated data without causing an overload, including image study summarization, content-based medical image retrieval, and natural language processing of text data. (2) Data modeling techniques to represent clinical data with focus on an image data model, including general-purpose time-based multimedia data models, health-care-specific data models, knowledge models, and problem-centric data models. (3) Methods to integrate medical data information from heterogeneous clinical data sources. Advances in centralized databases and mediated architectures are reviewed along with a discussion on our efforts at data integration based on peer-to-peer networking and shared file systems. (4) Visualization schemas to present imaging and clinical data: the large volume of medical data presents a daunting challenge for an efficient visualization paradigm. In this section we review current multimedia visualization methods including temporal modeling, problem-specific data organization, including our problem-centric, context and user-specific visualization interface.

Databases, Factual↗

Visual setup of logical models of signaling and regulatory networks with ProMoT.

BACKGROUND: The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to analyze large signaling and regulatory networks using this formalism. Even though there is a large number of tools to set up models describing biological networks using a biochemical (kinetic) formalism, however, they do not support logical models. RESULTS: Herein we present a flexible framework for setting up large logical models in a visual manner with the software tool ProMoT. An easily extendible library, ProMoT's inherent modularity and object-oriented concept as well as adaptive visualization techniques provide a versatile environment. Both the graphical and the textual description of the logical model can be exported to different formats. CONCLUSION: New features of ProMoT facilitate an efficient set-up of large Boolean models of biochemical interaction networks. The modeling environment is flexible; it can easily be adapted to specific requirements, and new extensions can be introduced. ProMoT is freely available from http://www.mpi-magdeburg.mpg.de/projects/promot/.

Animals↗