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PubMed2003

ARMADA--a computer model of the impact of environmental factors on health.

Environmental impact assessments are conducted on many developments as part of the planning process. There is currently wide interest in developing tools for assessing the impact on the health of the local population of proposed developments that will cause environmental changes. A computer model called ARMADA (Age Related Morbidity And Death Analysis) is described that provides a framework for investigating such health impacts. ARMADA generates estimates of age-related patterns of morbidity and mortality within the local population. These estimates incorporate the demographic features of the population in question and base-line information about the incidence of the disease classes being considered.

Age Factors↗

PubMedDate not supplied

Assessment of computer learning needs and priorities of registered nurses practicing in hospitals.

The purpose of this study was to identify computer learning needs of practicing nurses at the bedside. Knowles' adult learning theory clearly implies that learners have a role in identifying their learning needs. Expert opinion is the second source of needs identification and complements learner input. This principle served to underpin the conceptual framework of this study. A Delphi technique was used to solicit expert opinions from nurse informaticians about the computer learning needs of practicing nurses. A 75 knowledge/skill item questionnaire was developed from the expert consensus of the Delphi and distributed to 150 registered nurses considered to be computer novices. Novices' responses were compared to the experts' responses to identify content essential for nurses to be able to use computers in their practice. Further, sequence for content delivery was postulated through the comparison of expert and novice opinion relative to the essential/nonessential nature of the content.

Clinical Competence↗

PubMed2005

An adaptive prediction and detection algorithm for multistream syndromic surveillance.

BACKGROUND: Surveillance of Over-the-Counter pharmaceutical (OTC) sales as a potential early indicator of developing public health conditions, in particular in cases of interest to biosurvellance, has been suggested in the literature. This paper is a continuation of a previous study in which we formulated the problem of estimating clinical data from OTC sales in terms of optimal LMS linear and Finite Impulse Response (FIR) filters. In this paper we extend our results to predict clinical data multiple steps ahead using OTC sales as well as the clinical data itself. METHODS: The OTC data are grouped into a few categories and we predict the clinical data using a multichannel filter that encompasses all the past OTC categories as well as the past clinical data itself. The prediction is performed using FIR (Finite Impulse Response) filters and the recursive least squares method in order to adapt rapidly to nonstationary behaviour. In addition, we inject simulated events in both clinical and OTC data streams to evaluate the predictions by computing the Receiver Operating Characteristic curves of a threshold detector based on predicted outputs. RESULTS: We present all prediction results showing the effectiveness of the combined filtering operation. In addition, we compute and present the performance of a detector using the prediction output. CONCLUSION: Multichannel adaptive FIR least squares filtering provides a viable method of predicting public health conditions, as represented by clinical data, from OTC sales, and/or the clinical data. The potential value to a biosurveillance system cannot, however, be determined without studying this approach in the presence of transient events (nonstationary events of relatively short duration and fast rise times). Our simulated events superimposed on actual OTC and clinical data allow us to provide an upper bound on that potential value under some restricted conditions. Based on our ROC curves we argue that a biosurveillance system can provide early warning of an impending clinical event using ancillary data streams (such as OTC) with established correlations with the clinical data, and a prediction method that can react to nonstationary events sufficiently fast. Whether OTC (or other data streams yet to be identified) provide the best source of predicting clinical data is still an open question. We present a framework and an example to show how to measure the effectiveness of predictions, and compute an upper bound on this performance for the Recursive Least Squares method when the following two conditions are met: (1) an event of sufficient strength exists in both data streams, without distortion, and (2) it occurs in the OTC (or other ancillary streams) earlier than in the clinical data.

Algorithms↗

PubMedDate not supplied

Computational study of the conformational domains of peptide T.

The conformational preferences of peptide T (ASTTTNYT) were analysed by means of computational methods. A thorough exploration of the conformational space was carried out within the framework of the molecular mechanics approach, using simulated annealing as a searching strategy. Specifically, in order to obtain a subset of low-energy conformations with energies close to the global minimum as complete as possible, a simulated annealing protocol was repeated several times in a recursive fashion. The results of the search indicate that the peptide exhibits a alpha-helical character although most of the conformations characterized, including the global minimum, can be described as bent conformations. Conformations exhibiting beta-turn motives previously proposed from NMR studies were also characterized, although they are not very predominant in the set of low-energy conformations.

Computer Simulation↗

PubMed1978

[Computer-supported basic documentation at the accident-surgical clinic of the Hannover Medical School].

On the example of the computer-aided basic documentation at the Department of Traumatology Hannover, the necessity of constructive cooperation between the clinic staff and the medical data processors is shown. The system of basic documentation is primarily explained in its conception as far as the clinic is concerned. The fundamental principles, daily routine, and clinical application of this system are described, as are the tasks assigned to the clinical staff within the framework of medical data processing. The necessity of clinical staff quality controls by means of a computer short card is emphasized. The system has been in use for 3 years.

Accidents↗

PubMed1997

Image segmentation based on oscillatory correlation.

We study the image segmentation on the basis of locally excitatory, globally inhibitory oscillator networks (LEGION), whereby the phases of oscillators encode the binding of pixels. We introduce a lateral potential for each oscillators so that only oscillators with strong connections from their neighborhood can develop high potentials. Based on the concept of the lateral potential, a solution to remove noisy regions in an image is proposed for LEGION, so that it suppresses the oscillators corresponding to noisy regions but without affecting those corresponding to major regions. We show that the resulting oscillator network separates an image into several major regions, plus a background consisting of all noisy regions, and we illustrate network properties by computer stimulation. The network exhibits a natural capacity in segmenting images. The oscillatory dynamics leads to a computer algorithm, which is applied successfully to segmenting real gray-level images. A number of issues regarding biological plausibility and perceptual organization are discussed. We argue that LEGION provides a novel and effective framework for image segmentation and figure-ground segregation.

Algorithms↗

PubMedDate not supplied

Structure, function, and evolution of ferritins.

The ferritins of animals and plants and the bacterioferritins (BFRs) have a common iron-storage function in spite of differences in cytological location and biosynthetic regulation. The plant ferritins and BFRs are more similar to the H chains of mammals than to mammalian L chains, with respect to primary structure and conservation of ferroxidase center residues. Hence they probably arose from a common H-type ancestor. The recent discovery in E. coli of a second type of iron-storage protein (FTN) resembling ferritin H chains raises the question of what the relative roles of these two proteins are in this organism. Mammalian L ferritins lack ferroxidase centers and form a distinct group. Comparison of the three-dimensional structures of mammalian and invertebrate ferritins, as well as computer modeling of plant ferritins and of BFR, indicate a well conserved molecular framework. The characterisation of numerous ferritin homopolymer variants has allowed the identification of some of the residues involved in iron uptake and an investigation of some of the functional differences between mammalian H and L chains.

Amino Acid Sequence↗

PubMed1998

The two-process model of cellular aging.

To understand the mechanism of aging at the cellular level, cellular senescence has been extensively studied as an experimental model of aging in vitro. Although several hypotheses have been proposed for the mechanism of cellular senescence, none of them could give a comprehensive framework to the mechanism. In this study, we showed our results of extensive computer simulation designed to identify possible molecular models of cellular senescence. By examining representative cases of various molecular models, we elucidated the requirements for the plausible mechanism of cellular senescence. Based on these simulation results, we proposed a new molecular model of cellular senescence--the two-process model. In this model, we assumed that two independent, but time-aligned regulatory processes functioned in individual cells. We defined these two processes as S- and C-processes. The S-process mainly determines the rate of decline in the proliferative potential of the cell population. The simulation results suggested that the growth-inhibitory cell-to-cell interaction was required to drive the S-process. The C-process determines the latent proliferative potential of individual cells. The effector genes for the C-process are suggested to be regulated by a certain threshold-type mechanism. Both growth kinetics and senescence-associated gene expression were generated with high accuracy by the combined effect of these two processes. We also succeeded in simulating the effects of simian virus 40 large T antigen and its inducible variant on cellular senescence. From these theoretical considerations, we discuss the validity of the two-process model and the possible involvement of the heterochromatin structure as a determinant of the replicative lifespan of cells.

Cell Division↗

PubMed2002

Hippocampal and neocortical contributions to memory: advances in the complementary learning systems framework.

The complementary learning systems framework provides a simple set of principles, derived from converging biological, psychological and computational constraints, for understanding the differential contributions of the neocortex and hippocampus to learning and memory. The central principles are that the neocortex has a low learning rate and uses overlapping distributed representations to extract the general statistical structure of the environment, whereas the hippocampus learns rapidly using separated representations to encode the details of specific events while minimizing interference. In recent years, we have instantiated these principles in working computational models, and have used these models to address human and animal learning and memory findings, across a wide range of domains and paradigms. Here, we review a few representative applications of our models, focusing on two domains: recognition memory and animal learning in the fear-conditioning paradigm. In both domains, the models have generated novel predictions that have been tested and confirmed.

Journal Article↗

PubMed2003

Relative stability in alpha- and beta-Wells-Dawson heteropolyanions: a DFT study of [P2M18O62]n- (M = W and Mo) and [P2W15V3O62]n-.

To determine the relative stability of alpha and beta rotational isomers of the Wells-Dawson structure, the energies of some fully oxidized, single- and 2-fold-reduced systems were calculated by means of DFT calculations. The thermodynamics of the alpha/beta equilibrium for P(2)M(18) Wells-Dawson anions is slightly shifted toward the alpha structure, but the difference in stability is smaller than in the Keggin anions. Tungstates (2:18) and vanadotungstates (2:3:15) show minimal redox differences between isomers, as the electronic structure of the frontier orbitals appears to be nearly the same. In addition, an alternative arrangement is proposed that have long and short Mo-O bonds in beta-P(2)Mo(18) with an idealized C(3) symmetry. This arrangement was computed to be about 8.2 kcal mol(-1) more stable than the nonalternate framework of C(3)(v)() symmetry. The P(2)Mo(18) is the Wells-Dawson anion for which the alpha/beta equilibrium most resembles that of the Keggin anions.

Journal Article↗

PubMed2025

Adapting systems biology to address the complexity of human disease in the single-cell era.

Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent experimental and computational advances - from single-cell and spatial profiling to CRISPR genome editing and machine learning - have raised the exciting possibility of leveraging such strategies to prevent, diagnose and treat human diseases. However, adapting systems-inspired approaches to dissect human disease complexity is challenging, given that discrepancies between the biological features of human tissues and the experimental models typically used to probe function (which we term 'translational distance') can confound insight. Here we review how samples, measurements and analyses can be contextualized within overall multiscale human disease processes to mitigate data and representation gaps. We then examine ways to bridge the translational distance between systems-inspired human discovery loops and model system validation loops to empower precision interventions in the era of single-cell genomics.

Humans↗

PubMed1999

Numerical simulation of the hemodynamic response to hemodialysis-induced hypovolemia.

To provide a framework for analyzing cardiovascular response to hemodialysis-induced hypovolemia, we developed a computer model which simulates arterial pressure changes caused by loss of blood volume. The model includes arterial and venous systemic circulation, Starling's law and inotropic regulation of heart, arterial and cardiopulmonary baroreflex control of capacitance, and resistance vessels. The performance of this model was assessed by analyzing the hemodynamic responses recorded in 12 patients undergoing chronic hemodialysis, 6 classified as hypotension resistant (stable group) and 6 as hypotension prone (unstable group). Arterial pressure, heart rate, and blood volume were recorded during regular hemodialysis. Blood volume and heart rate were used as inputs to the simulator whereas the arterial pressure response obtained by simulation was fitted to the measured data by tuning simulator parameters relative to the capacitance and resistance controls. Although analyzed pressure responses exhibited a wide variety of time patterns, for each one it was possible to identify an optimal set of parameters allowing the recorded pressure data to be accurately reproduced by the model. Sensitivity analysis performed with the model indicated that pressure response strongly depends on the parameter Kv accounting for the capability to control vascular capacitance. According to these results, the parameter Kv in the stable group was 9 times that of the unstable group, thereby suggesting a possible cause of their different hemodynamic behavior.

Analysis of Variance↗

PubMed1996

Fast protein folding in the hydrophobic-hydrophilic model within three-eighths of optimal.

We present performance-guaranteed approximation algorithms for the protein folding problem in the hydrophobic-hydrophilic model (Dill, 1985). Our algorithms are the first approximation algorithms in the literature with guaranteed performance for this model (Dill, 1994). The hydrophobic-hydrophilic model abstracts the dominant force of protein folding: the hydrophobic interaction. The protein is modeled as a chain of amino acids of length n that are of two types; H (hydrophobic, i.e., nonpolar) and P (hydrophilic, i.e., polar). Although this model is a simplification of more complex protein folding models, the protein folding structure prediction problem is notoriously difficult for this model. Our algorithms have linear (3n) or quadratic time and achieve a three-dimensional protein conformation that has a guaranteed free energy no worse than three-eighths of optimal. This result answers the open problem of Ngo et al. (1994) about the possible existence of an efficient approximation algorithm with guaranteed performance for protein structure prediction in any well-studied model of protein folding. By achieving speed and near-optimality simultaneously, our algorithms rigorously capture salient features of the recently proposed framework of protein folding by Sali et al. (1994). Equally important, the final conformations of our algorithms have significant secondary structure (antiparallel sheets, beta-sheets, compact hydrophobic core). Furthermore, hypothetical folding pathways can be described for our algorithms that fit within the framework of diffusion-collision protein folding proposed by Karplus and Weaver (1979). Computational limitations of algorithms that compute the optimal conformation have restricted their applicability to short sequences (length < or = 90). Because our algorithms trade computational accuracy for speed, they can construct near-optimal conformations in linear time for sequences of any size.

Algorithms↗

PubMed2004

Spin models with random anisotropy and reflection symmetry.

We study the critical behavior of a general class of cubic-symmetric spin systems in which disorder preserves the reflection symmetry s(a) --> -s(a) , s(b) --> s(b) for b not equala . This includes spin models in the presence of random cubic-symmetric anisotropy with probability distribution vanishing outside the lattice axes. Using nonperturbative arguments we show the existence of a stable fixed point corresponding to the random-exchange Ising universality class. The field-theoretical renormalization-group flow is investigated in the framework of a fixed-dimension expansion in powers of appropriate quartic couplings, computing the corresponding beta functions to five loops. This analysis shows that the random Ising fixed point is the only stable fixed point that is accessible from the relevant parameter region. Therefore, if the system undergoes a continuous transition, it belongs to the random-exchange Ising universality class. The approach to the asymptotic critical behavior is controlled by scaling corrections with exponent Delta= -alpha(r) , where alpha(r) approximately -0.05 is the specific-heat exponent of the random-exchange Ising model.

Journal Article↗

PubMed2001

Learning to coordinate in a complex and nonstationary world.

We study analytically and by computer simulations a complex system of adaptive agents with finite memory. Borrowing the framework of the minority game and using the replica formalism we show the existence of an equilibrium phase transition as a function of the ratio between the memory lambda and the learning rates Gamma of the agents. We show that, starting from a random configuration, a dynamic phase transition also exists, which prevents agents from reaching optimal coordination. Furthermore, in a nonstationary environment, we show by numerical simulations that the phase transition becomes discontinuous.

Game Theory↗

PubMed2003

Identification of differentially expressed genes in high-density oligonucleotide arrays accounting for the quantification limits of the technology.

In DNA microarray analysis, there is often interest in isolating a few genes that best discriminate between tissue types. This is especially important in cancer, where different clinicopathologic groups are known to vary in their outcomes and response to therapy. The identification of a small subset of gene expression patterns distinctive for tumor subtypes can help design treatment strategies and improve diagnosis. Toward this goal, we propose a methodology for the analysis of high-density oligonucleotide arrays. The gene expression measures are modeled as censored data to account for the quantification limits of the technology, and two gene selection criteria based on contrasts from an analysis of covariance (ANCOVA) model are presented. The model is formulated in a hierarchical Bayesian framework, which in addition to making the fit of the model straightforward and computationally efficient, allows us to borrow strength across genes. The elicitation of hierarchical priors, as well as issues related to parameter identifiability and posterior propriety, are discussed in detail. We examine the performance of our proposed method on simulated data, then present a detailed case study of an endometrial cancer dataset.

Biometry↗

PubMed1983

Nurse therapist trainee variability: the implications for selection and training.

This paper examines some of the data obtained from the Joint Board of Clinical Nursing Studies Course Number 650, which ran at the Bethlem Royal and Maudsley Hospitals, London, 1978-1979. During this particular training programme, eight nurse therapist trainees treated a total of 251 patients assessed as suitable for behaviour therapy. Data were collected from patients by trainees on four separate occasions; before treatment, after treatment, and at follow-up intervals of 1 and 6 months. It was suggested that therapists would vary systematically in terms of the assessment scores used to measure outcome. This was explored using analysis of variance techniques, where several treatment outcome measures were used as dependent variables. The analyses, which were undertaken using SPSS and GLIM computer packages, clearly demonstrated therapist variability. The results are discussed within the theoretical framework of Sudman & Braburn's (1974) interviewing model and O'Muircheartaigh & Wiggins' (1981) consideration of response errors. The implications for the selection and training of nurse therapists are presented. The final conclusion of the paper is that, although the patient's clinical outcome may be related to therapist allocation, the eight trainees allowed themselves to 'open' their activities to this evaluative approach--which in turn demonstrates their professionalism.

Adolescent↗

PubMed2026

Selection profiles in RNA viruses reflect the characteristics of viruses more than individual proteins.

Proteins that are exposed on the surface of a virus are frequently subject to strong selection to escape from neutralizing antibodies. To investigate whether surface-exposed (SE) and non-exposed (NE) proteins encoded by RNA viruses exhibit different patterns of evolution under selection, we analyzed 244 protein-coding genes from 28 species of RNA viruses representing 15 taxonomic families. First, we show that gene-wide rates of non-synonymous (dN) and synonymous (dS) substitutions do not differentiate between SE and NE proteins. To incorporate variation in substitution rates among codon sites, we inferred the posterior distribution over a fixed grid of dN and dS rates for each alignment. This 'evolutionary fingerprint' provides a common framework for comparing the selection profiles of non-homologous genes. Next, we computed the Wasserstein distance for every pair of fingerprints, which is analogous to amount of work required to reshape one distribution to another. After compensating for differences in genetic variation among alignments, we found a small but significant difference between the fingerprints of SE and NE proteins (PERMANOVA, P = 0.03). However, we observed larger and more significant effects of whether the virus is enveloped (P < 10-5) and the interaction between these factors (P=6.9×10-4). The latter effects were driven by high levels of purifying selection in capsid proteins of Picornaviruses. Furthermore, greater amounts of variation in fingerprints were explained by significant differences among virus families and modes of transmission (P < 10-5). These results imply the pattern of selection on a virus protein is shaped more by characteristics of the virus than the protein itself.

RNA Viruses↗