Computer study of thyroid diseases. I. Methodology.
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Free energy component analysis for drug design: a case study of HIV-1 protease-inhibitor binding.
A theoretically rigorous and computationally tractable methodology for the prediction of the free energies of binding of protein-ligand complexes is presented. The method formulated involves developing molecular dynamics trajectories of the enzyme, the inhibitor, and the complex, followed by a free energy component analysis that conveys information on the physicochemical forces driving the protein-ligand complex formation and enables an elucidation of drug design principles for a given receptor from a thermodynamic perspective. The complexes of HIV-1 protease with two peptidomimetic inhibitors were taken as illustrative cases. Four-nanosecond-level all-atom molecular dynamics simulations using explicit solvent without any restraints were carried out on the protease-inhibitor complexes and the free proteases, and the trajectories were analyzed via a thermodynamic cycle to calculate the binding free energies. The computed free energies were seen to be in good accord with the reported data. It was noted that the net van der Waals and hydrophobic contributions were favorable to binding while the net electrostatics, entropies, and adaptation expense were unfavorable in these protease-inhibitor complexes. The hydrogen bond between the CH2OH group of the inhibitor at the scissile position and the catalytic aspartate was found to be favorable to binding. Various implicit solvent models were also considered and their shortcomings discussed. In addition, some plausible modifications to the inhibitor residues were attempted, which led to better binding affinities. The generality of the method and the transferability of the protocol with essentially no changes to any other protein-ligand system are emphasized.
Algorithms↗
Visualization of dynamic subcutaneous vasomotor response by computer-assisted thermography.
Infrared thermography is a noninvasive and nonionizing imaging modality which detects thermally significant subcutaneous blood vessels as linear heat patterns projected onto the skin surface. In clinical thermography, pseudo-colors are typically used to represent isothermal regions. However, pseudo-colors destroy the connectivity of vascular patterns since the intravenous temperature of a subcutaneous blood vessel varies along its length. This representation also confounds estimates of vessel boundary location since boundary information is rendered by temperature gradients, and not by isotherms. This paper describes two computer-assisted methodologies for the visualization of peripheral subcutaneous vasomotor events. The first approach, which utilizes a three-stage segmentation strategy based on edge detection, can visualize temperature differences of approximately 3.5 degrees C between the subcutaneous vessel boundaries and surrounding tissue. The second approach requires user interaction with an adaptive filtering algorithm that selectively enhances vascular patterns in the thermogram while decreasing background noise artifacts. The user interactively selects decision thresholds used by the algorithm to develop symbolic, axiomatic models of homogeneous and bimodal local contrast regions. The result of this trained filter is then employed in a technique called digital subtraction thermographic venography for the extraction of subcutaneous venous patterns. This second approach shows less ambiguity and higher sensitivity than the edge detection approach in resolving subtle temperature differences of approximately 1.2 degrees C between the vessel and surrounding tissue. Computer-processed frames from both of these approaches are used for the dynamic visualization of normal and pathological vasomotor responses to thermal challenges, thereby providing diagnostic visual cues which are unavailable in the original thermograms.
Algorithms↗
The impact of cross-training on team effectiveness.
The authors examined the role of cross-training in developing shared team-interaction mental models, coordination, and performance in a 2-experiment study using computer simulation methodology (for Experiment 1, N = 45 teams; for Experiment 2, N = 49 teams). Similar findings emerged across the 2 experiments. First, cross-training enhanced the development of shared team-interaction models. Second, coordination mediated the relationship between shared mental models and team performance. However, there was some inconsistency in the findings concerning the depth of cross-training necessary for improving shared mental models. Results are discussed in terms of the impact of different levels of cross-training on team effectiveness.
Adolescent↗
Computationally-assisted approach to the vibrational spectra of molecular crystals: study of hydrogen-bonding and pseudo-polymorphism.
A new computationally-assisted methodology (PiMM), which accounts for the effects of intermolecular interactions in the crystal, is applied to the complete assignment of the Raman and infrared vibrational spectra of room temperature forms of crystalline caffeine, theobromine, and theophylline. The vibrational shifts due to crystal packing interactions are evaluated from ab initio calculations for a set of suitable molecular pairs, using the B3LYP/6-31G* approach. The proposed methodology provides an answer to the current demand for a reliable assignment of the vibrational spectra of these methyl-xanthines, and clarifies several misleading assignments. The most relevant intermolecular interactions in each system and their effect on the vibrational spectra are considered and discussed. Based on these results, significant insights are obtained for the structure of caffeine in the anhydrous form (stable at room temperature), for which no X-ray structure has been reported. A possible structure based on C((8))--H...N((9)) and C((1,3))--H...O intermolecular interactions is suggested.
Caffeine↗
Atomistic simulations of competition between substrates binding to an enzyme.
Although the idea that electrostatic potentials generated by enzymes can guide substrates to active sites is well established, it is not always appreciated that the same potentials can also promote the binding of molecules other than the intended substrate, with the result that such enzymes might be sensitive to the presence of competing molecules. To provide a novel means of studying such "electrostatic competition" effects, computer simulation methodology has been developed to allow the diffusion and association of many solute molecules around a single enzyme to be simulated. To demonstrate the power of the methodology, simulations have been conducted on an artificial fusion protein of citrate synthase (CS) and malate dehydrogenase (MDH) to assess the chances of oxaloacetate being channeled between the MDH and CS active sites. The simulations demonstrate that the probability of channeling is strongly dependent on the concentration of the initial substrate (malate) in the solution. In fact, the high concentrations of malate used in experiments appear high enough to abolish any channeling of oxaloacetate. The simulations provide a resolution of a serious discrepancy between previous simulations and experiments and raise important questions relating to the observability of electrostatically mediated substrate channeling in vitro and in vivo.
Binding Sites↗
A maximum likelihood method for studying gene-environment interactions under conditional independence of genotype and exposure.
Given the biomedical interest in gene-environment interactions along with the difficulties inherent in gathering genetic data from controls, epidemiologists need methodologies that can increase precision of estimating interactions while minimizing the genotyping of controls. To achieve this purpose, many epidemiologists suggested that one can use case-only design. In this paper, we present a maximum likelihood method for making inference about gene-environment interactions using case-only data. The probability of disease development is described by a logistic risk model. Thus the interactions are model parameters measuring the departure of joint effects of exposure and genotype from multiplicative odds ratios. We extend the typical inference method derived under the assumption of independence between genotype and exposure to that under a more general assumption of conditional independence. Our maximum likelihood method can be applied to analyse both categorical and continuous environmental factors, and generalized to make inference about gene-gene-environment interactions. Moreover, the application of this method can be reduced to simply fitting a multinomial logistic model when we have case-only data. As a consequence, the maximum likelihood estimates of interactions and likelihood ratio tests for hypotheses concerning interactions can be easily computed. The methodology is illustrated through an example based on a study about the joint effects of XRCC1 polymorphisms and smoking on bladder cancer. We also give two simulation studies to show that the proposed method is reliable in finite sample situation.
DNA-Binding Proteins↗
Application of a computer-based zero-one methodology to the assignment of nurses to a clinical rotation schedule.
This article discusses the application of a zero-one approach to the development of a total program schedule that assigns students to all required clinical courses in an academic nursing program. The approach is based on an operations research technique, zero-one programming. Unlike zero-one programming, the objective function in this formulation is arbitrary; any solution that meets the constraints of the system is acceptable. Also described in this article are the constraints that limit flexibility of student assignments (i.e., available clinical sites and units, instructors, day or evening, maximum class sizes, order of courses), a solution to the scheduling problem at Saint Joseph's (which involves 1,067 equations), and suggestions for the general utility of a zero-one approach for similar administrative problems.
Computers↗
Advanced soft computing diagnosis method for tumour grading.
OBJECTIVE: To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. MATERIAL AND METHODS: One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. RESULTS: The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. CONCLUSIONS: An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.
Algorithms↗
A molecular level picture of the stabilization of A-DNA in mixed ethanol-water solutions.
Advances in computer power, methodology, and empirical force fields now allow routine "stable" nanosecond-length molecular dynamics simulations of DNA in water. The accurate representation of environmental influences on structure remains a major, unresolved issue. In contrast to simulations of A-DNA in water (where an A-DNA to B-DNA transition is observed) and in pure ethanol (where disruption of the structure is observed), A-DNA in approximately 85% ethanol solution remains in a canonical A-DNA geometry as expected. The stabilization of A-DNA by ethanol is likely due to disruption of the spine of hydration in the minor groove and the presence of ion-mediated interhelical bonds and extensive hydration across the major groove.
Computer Simulation↗
Quantitative fitting of atomic models into observed densities derived by electron microscopy.
A new methodology for fitting atomic models into density distributions is described. This approach is based on a global density correlation analysis that can be optionally supplemented by biochemical as well as biophysical data. The procedure is completely general and enables an objective evaluation of the resulting docking in the light of available biochemical and biophysical information as well as density correlation alone. In this paper we describe the implementation of the algorithm and its application to two biological systems. In both cases the procedure provided an interface model on the atomic level and located parts of the structure that were missing in the atomic model but present in the electron-microscopic construct. It also detected and quantified conformational changes in actomyosin complexes.
Actin Cytoskeleton↗
In vivo imaging of the brain cannabinoid receptor.
The CB1 cannabinoid receptor is expressed in the brain at levels sufficient to serve as potential target for in vivo imaging using positron emission tomography (PET) or single photon emission computed tomography methodology. To date, the most promising radioligands for the in vivo imaging of this receptor have structures based on that of the cannabinoid antagonist, SR141716A. Rodent data obtained using these in vivo radiotracers has demonstrated that both the behavioral and neurochemical effects of cannabinoids occur at very low levels of receptor occupancy. More recently, an agonist radiotracer based on the structure of aminoalkylindole cannabinoids has also been examined for in vivo labeling of CB1 receptors. Although rodent studies have indicated that in vivo imaging of CB1 receptors is feasible, at the present time this receptor has still to be successful imaged in a human PET study.
Animals↗
Abnormalities of brain structure and density in schizophrenia.
Quantitative and qualitative measures of brain morphology were derived through CT scans using computer-assisted methodology in patients with schizophrenia or schizo-affective psychosis and headache controls. Schizophrenics had significantly higher density of white matter, together with greater right vs. left asymmetry in density of white matter than controls. Schizophrenics tended to have larger widths of cortical sulci than headache patients. In our sample of schizophrenics, however, no significant differences were found on measures of lateral ventricle (LV) width, LV area, VBR, or other measures of ventricular size compared to headache controls. There were no differences between CT scan measures taken in patients with schizophrenia vs. schizo-affective psychosis.
Adult↗
The combination of a decision tree technique with the computer-assisted microscope analysis of Feulgen-stained nuclei to assess aggressiveness in lipomatous and smooth muscle tumors.
The present study describes a computer-assisted methodology whose purpose is to reduce the degree of subjectivity in the diagnosis of soft tissue tumors. This methodology associates three complementary techniques, namely digital cell image analysis, the discretisation of numerical data and a Decision Tree technique (DT). The first technique relies on the use of the digital cell image analysis of Feulgen-stained nuclei, a technique which makes possible a quantitative and thus objective description of nuclei with the help of 24 numerical parameters (15 morphonuclear and 9 DNA content- (ploidy level and proliferation activity) related). The second technique transforms each numerical parameter into an ordinal one with a small number of values (2 to 4) so that only the relevant physical significance of the parameters is retained. The Decision Tree technique generates classification rules on the basis of the discretised parameters quoted above. This methodology was applied to 53 human soft tissue tumors which included 26 lipomatous tumors (13 malignant liposarcomas and 13 benign lipomas) and 27 smooth muscle tumors (11 malignant leiomyosarcomas and 16 benign leiomyomas). The results show that a distinction between benign (lipoma) and malignant (liposarcoma) lipomatous tumors can easily be made by means of simple logical rules depending on only four discretised cytological parameters (two ploidy- and two morphonuclear-related). In contrast, no stable or predictive characterisation can be obtained with respect to the difference between leiomyosarcomas and the leiomyomas. Hence, while lipomas and liposarcomas appeared to be two completely distinct biological entities, leiomyomas and leiomyosarcomas seem to involve a continuous biological process.
Cell Nucleus↗
ROSE: decision trees, automatic learning and their applications in cardiac medicine.
Computerized information systems, especially decision support systems, have acquired an increasingly important role in medical applications, particularly in those where important decisions must be made effectively and reliably. But the possibility of using computers in medical decision making is limited by many difficulties, including the complexity of conventional computer languages, methodologies, and tools. Thus a conceptual simple decision making model with the possibility of automating learning should be used. In this paper, we introduce a cardiological knowledge-based system based on the decision tree approach supporting the mitral valve prolapse determination. Prolapse is defined as the displacement of a bodily part from its normal position. The term mitral valve prolapse (PMV), therefore, implies that the mitral leaflets are displaced relative to some structure, generally taken to be the mitral annulus. The implications of the PMV are: disturbed normal laminar blood flow, turbulence of the blood flow, injury of the chordae tendinae, the possibility of thrombus's composition, bacterial endocarditis, and, finally, hemodynamic changes defined as mitral insufficiency and mitral regurgitation. Uncertainty persists about how it should be diagnosed and about its clinical importance. It is our deep belief that the echocardiography enables properly trained expert armed with proper criteria to evaluate PMV almost 100%. But, unfortunately, there are some problems concerned with the use of echocardiography. With this in mind, we have decided to start a research project aimed at finding new criteria and enabling the general practitioner to evaluate the PMV using conventional methods and to select potential patients from the general population. To empower doctors to perform needed activities, we have developed a computer tool called ROSE (computeRized prOlaps Syndrome dEtermination) based on algorithms of automatic learning. This tool supports the definition of new criteria and the selection of potential PMV-patients. The ROSE is based on concepts of decision trees and automatic learning. The decisions and learning process can be presented with an easily visualized two dimensional model; thus decision trees are straightforward to build and interpret. Decision trees use different object attributes to classify different subsets of objects. (Their great advantage is that they don't use a fixed number of predetermined attributes.) In the decision tree approach, the members of a set of objects are classified as either positive or negative instances (in our case patients with PMV Syndrome or without it). Candidate attributes that may possibly describe the concept are then outlined. A decision tree construction tool uses outlined attributes to formulate the appropriate decision tree that identifies all positive instances of the underlying concept according to objects with known classification. (In our case the classification is done with the echo examination). The first set of objects used for the tree generation is usually called the training set. This decision tree characterization next becomes a basis: 1) forecasting whether an object previously unseen is a positive or negative instance of the concept being modeled, and 2) the hierarchical representation of the most important attributes of the concept being investigated. Our main interest and idea is to discover symptoms, syndromes, and illnesses related to PMV that can be distinguished by general practitioners in their everyday job and which should help them to identify possible PMV candidate patients. To this end, we constructed a computerized tool called ROSE. According to the principles presented above, we first taught ROSE using the sample of 400 examined volunteers. ROSE, considering that the clinical PMV diagnosis is practically not researched, is relatively successful. (abstract truncated)
Algorithms↗
Computer-assisted morphometric analysis of the heart.
OBJECTIVE: To assess the applicability of the image analyzer for morphometric study of cardiomyopathies. STUDY DESIGN: A computer-assisted methodology for the morphometric study of ischemic cardiomyopathy, dilated cardiomyopathy and right ventricular dysplasia. RESULTS: In each heart, 200 nuclear lengths and myocyte diameters, 160 fields for nuclear density, 420 fields for interstitial fibrosis and 350 fields for replacement fibrosis were evaluated. In ischemic cardiomyopathy, the multiple foci of replacement fibrosis of the myocardium, in addition to interstitial fibrosis, appear to be the major cause of ventricular remodelling. In dilated cardiomyopathy the major pathologic processes are myocyte cell death and segmental, replacement and interstitial fibrosis. In right ventricular dysplasia the heart develops congestive failure due to a conspicuous increase in the volume of the right ventricle without an appreciable loss of the number of myocytes. CONCLUSION: The traditional morphometric methods based on test grids for the study of pathologic hearts can be enhanced using an image analyzer. In this way one can study a large area of the myocardium and collect a very large number of data. This may be the method of choice for analyses of pathologic human hearts.
Cardiomyopathies↗
Invited review: motor unit estimation: methods, results, and present status.
The renewed interest in motor unit estimation (counting) has coincided with the introduction of computer-based methodology and with the application of the technique to proximal as well as distal muscles. The advantages and disadvantages of the different methods are considered, together with the assumptions inherent in this type of examination. In normal subjects, the extensor digitorum brevis (EDB) muscle has approximately 200 motor units while each of the intrinsic muscles of the hand has about 100 units; larger muscles in the limbs contain greater numbers of units. Beyond the age of 60 years, there is a decline in the number of functioning motor units in both proximal and distal muscles. In denervating disorders, motor unit estimation is useful for diagnosis and assessment; abnormal values may often be observed in muscles judged clinically to be unaffected. Serial studies have enabled the rate of motor unit loss to be determined in ALS and in spinal muscular atrophy. Depletion of motor units has also been found following upper motoneuron lesions caused by injury to the spinal cord or by cerebral hemorrhage; trans-synaptic dysfunction has been presumed responsible. Rather surprisingly, reduced numbers of motor units have been observed in a variety of myopathic disorders; of these, the most consistent abnormalities have been reported in myotonic muscular dystrophy.
Computers↗
Computer-aided dosage form design. III. Feasibility assessment for an oral prolonged-release phenytoin product.
Previous publications described computer-aided methodology for assessing the feasibility of designing prolonged release oral dosage forms containing linear-disposition drugs. Those methods determined all useful release rates and examined those rates to decide whether product development was warranted. The present study developed software to obtain similar information for phenytoin, which exhibits Michaelis-Menten disposition. The values for Vmax, Km, and Vd in 27 patients were employed to assess the ability of prolonged absorption to maintain steady-state plasma concentrations between 10 and 20 mg/liter following oral administration at 8-, 12-, and 24-hr intervals. Phenytoin steady-state plasma concentrations in this range were controlled by elimination and were not extended by prolonged absorption. Furthermore, single i.v. bolus doses resulting in an initial plasma level of 20 mg/liter provided concentrations above 10 mg/liter for approximately 1 to 3 days. When an oral multiple-dose regimen was found to maintain steady-state concentrations between 10 and 20 mg/liter, that dose and interval produced concentrations within that range regardless of the absorption rate. While absorption rate was not important, each patient's dose ranges were extremely narrow, emphasizing that dose size was the dominant factor in the control of phenytoin levels.
Absorption↗