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Methods of meta-analysis, computer modeling, and issue analysis are used to answer four key questions related to efficacy, cost, and political feasibility of legislating insurance coverage for mammography. The findings are presented, and the strengths and weaknesses of the combined use of these methods to inform policy debate at the regional level are discussed.
A computer model of "a sense of humor" is formulated. The humorous effect is treated as a specific malfunction in the processing of information conditioned by the necessity of a quick deletion from consciousness of a false version. The biological function of a sense of humor consists in quickening the transmission of processed information into consciousness and in a more effective use of brain resources.
Better understanding of the underlying working mechanism of the neural control of the lower urinary tract will facilitate the treatment of dysfunction with a neurogenic cause. We developed a computer model to study the effect of a neural control system on lower urinary tract behavior. To model the mechanical properties and neural control, assumptions had to be made. These assumptions were based, as much as possible, on knowledge and hypotheses taken from the literature. With valid assumptions, it should be possible to simulate normal as well as pathological behavior. To test the computer model, first, normal behavior of the lower urinary tract was simulated, and secondly, the known features of bladder outlet obstruction were simulated after the properties of the urethra were changed. The simulation results are comparable with measured data, so the assumptions on which the model is based could be valid. If the assumptions are valid, the feedback loops used in the model are also important feedback loops in vivo, and the model can be used to gain insight into the underlying mechanism of neural control.
The processes required for object naming were addressed in a study of patients with semantic dementia (a selective decline of semantic memory resulting from progressive temporal lobe atrophy) and in a computational model of single-word production. Although all patients with semantic dementia are impaired in both single-word production and comprehension, previous reports had indicated two different patterns: (a) a parallel decline in accuracy of naming and comprehension, with frequent semantic naming errors, suggesting a purely semantic basis for the anomia and (b) a dramatic progressive anomia without commensurate decline in comprehension, which might suggest a mainly postsemantic source of the anomia. Longitudinal data for 16 patients with semantic dementia reflected these two profiles, but with the following additional important specifications: (1) despite a few relatively extreme versions of one or other profile, the full set of cases formed a continuum in the extent of anomia for a given degree of degraded comprehension; (2) the degree of disparity between these two abilities was associated with relative asymmetry in laterality of atrophy: a parallel decline in the two measures characterized patients with greater right- than left-temporal atrophy, while disproportionate anomia occurred with a predominance of atrophy in the left-temporal lobe. In an implemented computational model of naming, semantic representations were distributed across simulated left- and right-temporal regions, but the semantic units on the left were more strongly connected to left-lateralized phonological representations. Asymmetric damage to semantic units reproduced the longitudinal patient profiles of naming relative to comprehension, plus additional characteristics of the patients' naming performance. On the basis of both the neuropsychological and computational evidence, we propose that semantic impairment alone can account for the full range of word production deficits described here.
Multiple regional myocardial ischemia that leads to depressed left ventricular (LV) function is commonplace. Quantitative analysis of the hemodynamic consequences, however, has been limited. We investigated this aspect using a novel computer model of the cardiovascular system. The model consists of an LV with two ischemic zones (IZs) and a normal zone (NZ), the preload, and the arterial system afterload. The IZ size and activation timing could be altered. Results show that the greater the size and activation asynchronization between NZ and IZ, the more severe the LV dysfunction. Increased preload during ischemia improved LV function. This computer model predicts features that agree well with reported experimental observations and is particularly useful for myocardial ischemic function analysis.
The perceived motion of two added sinusoidal gratings of similar amplitude and spatial frequency but different orientations is often coherent. However, when either relative grating contrast or frequency are varied, perception may transform to a motion transparency. For plaids, both multiplicative and additive transparent percepts are reported. To explain perception, several computational models of motion transparency are proposed. The most general model considered is, however, a quadratic form with five unknowns. To stabilize the transparent model, additional constraints are introduced so that two velocities may be detected from the motion of plaid patterns. It is shown how this model may be realised by a two-layer (linear) feedforward network and how network learning paradigms may be used to explain some facets of visual perception. To describe the motion of plaid patterns there is an ambiguity because computational models of both coherent and transparent motion may be used to detect image velocity. In view of this competition between models, the issue of model selection is addressed; especially for cases where two or more models fit the image measurements without a residual error. The computational approach that is proposed affords one explanation why perception selects transparency in favour of coherence for plaid patterns by adjustments of relative grating contrast and frequency.
The hippocampal region, a group of brain structures important for learning and memory, has been the focus of a large number of computational models. These tend to fall into two groups: (1) models of the role of the hippocampal region in incremental learning, which focus on the development of new representations that are sensitive to stimulus regularities and environmental context; (2) models that focus on the role of the hippocampal region in the rapid storage and retrieval of episodic memories. Rather than being in conflict, it is becoming apparent that both approaches are partially correct and might reflect the different functions of substructures of the hippocampal region. Future computational models will help to elaborate how these different substructures interact.
Method of creation computer models of upper floor of abdomen organs: liver, gallbladder, duodenum, pancreas, stomach, blood vessels with using computer system "DUCT" was described. Details of modelled structures of the cylindric and complicated forms were noted.
Bone fractures are major problems for osteoporosis patients. To avoid such fractures, more information is needed about the factors that determine the bone fracture risk. In this chapter, it is discussed how recently developed finite element computer models that can represent the trabecular architecture in full detail can provide such information. It is concluded that a computer modeling approach to this problem is feasible, required and promising. It is expected that, eventually, such models can be used as a basis for an accurate diagnosis of the bone fracture risk.
A computational model of gas transport in the lung is described which remedies many of the deficiencies of previous models, as listed by Chang and Farhi (1973), in that it allows for fluctuating lung dimensions, gas exchange, simultaneous convection and diffusion, and the enhanced effective diffusion that occurs when convective flow is also present. The results of calculations using the model are presented, showing the maximum effect of Taylor diffusion. The actual magnitude of Taylor diffusion, suitably modified to allow for the disturbed conditions within the lung, is considered in the light of recent experiments.
We present a computational model for the mammalian circadian clock based on the intertwined positive and negative regulatory loops involving the Per, Cry, Bmal1, Clock, and Rev-Erb alpha genes. In agreement with experimental observations, the model can give rise to sustained circadian oscillations in continuous darkness, characterized by an antiphase relationship between Per/Cry/Rev-Erbalpha and Bmal1 mRNAs. Sustained oscillations correspond to the rhythms autonomously generated by suprachiasmatic nuclei. For other parameter values, damped oscillations can also be obtained in the model. These oscillations, which transform into sustained oscillations when coupled to a periodic signal, correspond to rhythms produced by peripheral tissues. When incorporating the light-induced expression of the Per gene, the model accounts for entrainment of the oscillations by light-dark cycles. Simulations show that the phase of the oscillations can then vary by several hours with relatively minor changes in parameter values. Such a lability of the phase could account for physiological disorders related to circadian rhythms in humans, such as advanced or delayed sleep phase syndrome, whereas the lack of entrainment by light-dark cycles can be related to the non-24h sleep-wake syndrome. The model uncovers the possible existence of multiple sources of oscillatory behavior. Thus, in conditions where the indirect negative autoregulation of Per and Cry expression is inoperative, the model indicates the possibility that sustained oscillations might still arise from the negative autoregulation of Bmal1 expression.
INTRODUCTION: Following atrial premature beats, the AV node may exhibit sustained reentrant tachyarrhythmias, isolated echo beats, or discontinuities in the recovery curve (the plot of conduction time versus atrial cycle length). A computer model was used to examine the hypothesis that spatial variation of AV nodal passive electrical resistance may account for these phenomena. METHODS AND RESULTS: A computer model of a rectangular lattice of electrotonically linked elements whose ionic kinetics simulated nodal ionic flux was developed. The model showed that there exists a resistance value that minimizes the effective refractory period, because high resistance prevents depolarization of distal elements, while low resistance allows leakage of depolarizing current by electrotonic transmission, preventing activation of proximal elements. High resistances stabilized reentry by slowing conduction. Simulations incorporating equal resistance values between elements predicted increased AV nodal conduction times with increasing prematurity of atrial impulses. A model with a gradual change in resistance between fibers produced discontinuities and tachycardia, but not both simultaneously. Uniform anisotropy produced preferential transverse block, leading to echo beats and "fast-slow" tachycardia, but not recovery curve discontinuities. Nonuniform anisotropy could produce reentry, but tachycardia often occurred without discontinuities. Dividing the lattice into two electrotonically linked parallel pathways with different resistance values ("dual pathway model") predicted recovery curve discontinuities, echo beats, and tachycardia. At critical atrial cycle lengths, only the (high resistance) slow pathway conducted antegradely, while the fast pathway conducted retrogradely, to generate the typical "slow-fast" tachycardia. Responses of the dual pathway model to ablation were consistent with clinical data, including the previous observation of a decrease in fast pathway effective refractory period after slow pathway ablation. CONCLUSION: Differences in passive electrical resistance of electronically linked dual pathways within the AV node may account for functional longitudinal dissociation, reentrant arrhythmias, and responses to catheter ablation therapy.
The techniques of systems analysis have been applied to the metabolism of phenylalanine in healthy subjects and in phenylketonuria to derive a computer model. The model consists of seven compartments and four biological functions. Enzyme reactions are assumed to obey Michaelis-Menten kinetics. The computer program is written in FORTRAN. A biological validation of the model has been performed. The computer model has potential value for estimating concentrations of key metabolites in human organs which are not accessible to direct analysis from measurements of metabolites in blood and urine and phenylalanine intake. Such estimates would be helpful in clinical decisions concerning modification or termination of dietary treatment in phenylketonuria.
A computational model that accounts for blood-tissue interaction under physiological flow conditions was developed and applied to a thin-walled model of the left heart. This model consisted of the left ventricle, left atrium, and pulmonary vein flow. The input functions for the model included the pulmonary vein driving pressure and time-dependent relationship for changes in chamber tissue properties during the simulation. The Immersed Boundary Method was used for the interaction of the tissue and blood in response to fluid forces and changes in tissue pathophysiology, and the fluid mass and momentum conservation equations were solved using Patankar's Semi-Implicit Method for Pressure Linked Equations (SIMPLE). This model was used to examine the flow fields in the left heart under abnormal diastolic conditions of delayed ventricular relaxation, delayed ventricular relaxation with increased ventricular stiffness, and delayed ventricular relaxation with an increased atrial contraction. The results obtained from the left heart model were compared to clinically observed diastolic flow conditions, and to the results from simulations of normal diastolic function in this model [1]. Cases involving impairment of diastolic function were modeled with changes to the input functions for fiber relaxation/contraction of the chambers. The three cases of diastolic dysfunction investigated agreed with the changes in diastolic flow fields seen clinically. The effect of delayed relaxation was to decrease the early filling magnitude, and this decrease was larger when the stiffness of the ventricle was increased. Also, increasing the contraction of the atrium during atrial systole resulted in a higher late filling velocity and atrial pressure. The results show that dysfunction can be modeled by changing the relationships for fiber resting-length and/or stiffness. This provides confidence in future modeling of disease, especially changes to chamber properties to examine the effect of local dysfunction on global flow fields.
Cyclin dependent kinase (Cdk) 5, an atypical member of the Cdk family, plays a fundamental role in the development of the nervous system, and may also be involved in the pathogenesis of certain neurodegenerative diseases. Further, Cdk5 is activated by the specific regulatory proteins p39, p35, or p25 rather than cyclins, and in contrast to other members of the Cdk family is not involved in the progression of the cell cycle. A three-dimensional computer model of Cdk5-p25-ATP has been generated previously [Chou et al., Biochem Biophys Res Commun 1999;259:420-428], providing a structural basis for the study of the mechanisms of Cdk5 activation. To assess the predicted ATP and p25 binding domains at the N-terminal of Cdk5, two mutants of Cdk5 were prepared in which amino acids 9-15 (Delta9-15) or 9-47 (Delta9-47) were deleted. The results of these studies clearly demonstrate that an N-terminal loop and the PSSALRE helix are indispensable for Cdk5-p25 interactions, and amino acids 9-15 are necessary for ATP binding but are not involved in Cdk5-p25 interactions. Predicted models of Delta9-15 Cdk5 and Delta9-47 Cdk5 were generated, and were used to interpret the experimental data. The experimental and molecular modeling results confirm and extend specific aspects of the original predicted computer model, and may provide useful information for the design of highly selective inhibitors of Cdk5, which could be used in the treatment of certain neurodegenerative conditions.
Neurulation, the curling of the neuroepithelium to form the neural tube, is an essential component of the development of animal embryos. Defects of neural tube formation, which occur with an overall frequency of one in 500 human births, are the cause of severe and distressing congenital abnormalities. However, despite the fact that there is increasing information from animal experiments about the mechanisms which effect neural tube formation, much less is known about the fundamental causes of neural tube defects (NTD). The use of computer models provides one way of gaining clues about the ways in which neurulation may be compromised. Here we employ one computer model to examine the robustness of different cellular mechanisms which are thought to contribute to neurulation. The model, modified from that of Odell et al (Odell, G.M., Oster, G., Alberch, P. and Burnside, B., (1981)) mimics neurulation by laterally propagating a wave of apical contraction along an active zone within a ring of cells. We link the results to experimental evidence gained from studies of embryos in which neurulation has been perturbed. The results indicate that alteration of one of the properties of non-neural tissue can delay or inhibit neurulation, supporting the idea, gained from observation of embryos bearing genes which predispose to NTD, that the tissue underlying the neuroepithelium may contribute to the elevation of the neural folds. The results also show that reduction of the contractile properties of a small proportion of the neuroepithelial cell population may have a profound effect on overall tissue profiling. The results suggest that the elevation of the neural folds, and hence successful neurulation, may be vulnerable to relatively minor deficiencies in cell properties.
Recent studies have suggested that autocrine signaling through epidermal growth factor receptor (EGFR) might be involved in generating or maintaining an intrinsic polarity in tissue cells, possibly via spatial localization of EGFR-mediated signaling. The difficulty of experimental investigation of autocrine signaling makes especially valuable an application of computational modeling for critical hypotheses about the dynamic operation of the underlying signaling circuits, both intracellular and extracellular. Toward this end, we develop and analyze here a spatially distributed dynamic computational model of autocrine EGFR signaling. Under certain conditions, the model spontaneously evolves into a state wherein sustained signaling is spatially localized on smaller than cell dimension, conferring a polarity to the otherwise nonpolar model cell. Conditions of a sufficiently large rate of autocrine EGFR ligand release and of a sufficiently small exogenous ligand concentration are qualitatively consistent with experimental observations of EGFR-mediated migration. Thus, computational analysis supports the concept that autocrine EGFR signaling circuits could play a role in helping generate and/or maintain an intrinsic cell spatial polarity, possibly related to migration as well as tissue organization. We additionally offer particular suggestions for critical nodes in the EGFR signaling circuits governing this self-organization capability.
OBJECTIVE: The authors evaluated systemic venous insulin release as a cause of the hyperinsulinemia (HNS) associated with pancreatic transplantation (PTX) with respect to the mechanism and metabolic consequences. SUMMARY BACKGROUND DATA: Many investigators believe the postoperative anatomy associated with common PTX techniques to be the sole cause of the two- to threefold posttransplantation HINS. However, this concept remains to be conclusively proved and characterized quantitatively. METHODS: The authors used three approaches to achieve their objectives. First, a computer model was generated based on established data concerning blood flow and tissue insulin extraction to determine whether it was mathematically possible for HINS to be caused by systemic insulin release. Second, HINS clamps were applied to normal dogs using the Andres clamp technique to quantify the in vivo differences in peripheral insulin levels and the metabolic consequences of systemic versus portal insulin infusion. Third, prolonged insulin half-life was evaluated as a possible mechanism of HINS from systemic insulin release by determination of biexponential rates of plasma disappearance from an endogenous pulse of insulin in surgically induced dog models of systemic and portal insulin release. RESULTS: First, the computer model calculated a 1.4- to 2.9-fold increase in peripheral venous insulin levels with systemic versus portal insulin release, verifying mathematically the concept of HINS resulting from systemic insulin release. Second, the actual systemic insulin infusion produced a 1.3- to 1.4-fold increase in peripheral venous insulin levels compared with portal infusion (p < 0.05). No significant differences in hepatic glucose output, total glucose disposal, or glucose infusion requirements were seen. Third, although the basal insulin level was twofold higher in the surgically induced animal models with systemic insulin release (p < 0.003), there were no differences in biexponential insulin clearance parameters. CONCLUSIONS: The HINS produced by systemic insulin release did not significantly alter glucose metabolism and was not the result of altered peripheral insulin clearance parameters. In vivo systemic venous insulin infusion studies produce HINS, but not to the degree calculated by mathematic modeling or that occurs after clinical PTX, making it likely that other factors also play a role in the HINS after PTX.