A structural model for the patient care operation.
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Models, Structural↗
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[Use of a structural model for the automatic classification of middle ear states].
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Computers↗
[Highly permeable contacts and the electrical characteristics of normal liver tissue and hepatomas. II. A structural model and calculation of the cell membrane permeability of induced mouse hepatomas].
The values of specific resistances of non-junctional (Rm) and junctional (Rj) membranes of mouse induced hepatoma cells were calculated with the aid of the syncytium theory equations and on the basis of the previously measured input resistances and electrotonic potential spread curves. A three-dimensional model with cable element length equal to two cell diameters, with the length constant value of 600 mkm, and with three contacts per cell was used for calculations. For this model, Rm and Rj were found to be 3300-5600 Ohm . cm2 and 2 . 10(-2) Ohm . cm2, respectively. For the three-dimensional model of normal liver, Rm and Rj amounted to 2400-7200 Ohm . cm2 and 6.5 . 10(-2) Ohm . cm2, respectively.
Animals↗
CARD: a drawing tool for RNA secondary structure models.
A graphical editor was developed to create publication-quality representations of RNA secondary structure models. A user-defined model can be gradually assembled from structural elements such as helix segments and loops. The type of structural element to be drawn is chosen from a menu. Its nucleotide sequence has to be entered from the keyboard. Afterwards, drawings can be manipulated by moving, deleting, rotating, copying or changing the structural elements separately. An example of a secondary structure model is given for a complete 18S rRNA molecule.
Nucleic Acid Conformation↗
Xenopus laevis 28S ribosomal RNA: a secondary structure model and its evolutionary and functional implications.
Based upon the three experimentally derived models of E. coli 23S rRNA (1-3) and the partial model for yeast 26S rRNA (4), which was deduced by homology to E. coli, we derived a secondary structure model for Xenopus laevis 28S rRNA. This is the first complete model presented for eukaryotic 28S rRNA. Compensatory base changes support the general validity of our model and offer help to resolve which of the three E. coli models is correct in regions where they are different from one another. Eukaryotic rDNA is longer than prokaryotic rDNA by virtue of introns, expansion segments and transcribed spacers, all of which are discussed relative to our secondary structure model. Comments are made on the evolutionary origins of these three categories and the processing fates of their transcripts. Functionally important sites on our 28S rRNA secondary structure model are suggested by analogy for ribosomal protein binding, the GTPase center, the peptidyl transferase center, and for rRNA interaction with tRNA and 5S RNA. We discuss how RNA-RNA interactions may play a vital role in translocation.
Animals↗
Eukaryotic translation elongation factor 1 gamma contains a glutathione transferase domain--study of a diverse, ancient protein superfamily using motif search and structural modeling.
Using computer methods for multiple alignment, sequence motif search, and tertiary structure modeling, we show that eukaryotic translation elongation factor 1 gamma (EF1 gamma) contains an N-terminal domain related to class theta glutathione S-transferases (GST). GST-like proteins related to class theta comprise a large group including, in addition to typical GSTs and EF1 gamma, stress-induced proteins from bacteria and plants, bacterial reductive dehalogenases and beta-etherases, and several uncharacterized proteins. These proteins share 2 conserved sequence motifs with GSTs of other classes (alpha, mu, and pi). Tertiary structure modeling showed that in spite of the relatively low sequence similarity, the GST-related domain of EF1 gamma is likely to form a fold very similar to that in the known structures of class alpha, mu, and pi GSTs. One of the conserved motifs is implicated in glutathione binding, whereas the other motif probably is involved in maintaining the proper conformation of the GST domain. We predict that the GST-like domain in EF1 gamma is enzymatically active and that to exhibit GST activity, EF1 gamma has to form homodimers. The GST activity may be involved in the regulation of the assembly of multisubunit complexes containing EF1 and aminoacyl-tRNA synthetases by shifting the balance between glutathione, disulfide glutathione, thiol groups of cysteines, and protein disulfide bonds. The GST domain is a widespread, conserved enzymatic module that may be covalently or noncovalently complexed with other proteins. Regulation of protein assembly and folding may be 1 of the functions of GST.
Amino Acid Sequence↗
Modeling incomplete longitudinal and cross-sectional data using latent growth structural models.
In this paper we describe some mathematical and statistical models for identifying and dealing with changes over age. We concentrate specifically on the use of a latent growth structural equation model approach to deal with issues of: (1) latent growth models of change, (2) differences in longitudinal and cross-sectional results, and (3) differences due to longitudinal attrition. This is a methodological paper using simulated data, but we base our models on practical and conceptual principles of modeling change in developmental psychology. Our results illustrate both benefits and limitations using structural models to analyze incomplete longitudinal data.
Aging↗
Applications of covariance structure modeling in psychology: cause for concern?
Methods of covariance structure modeling are frequently applied in psychological research. These methods merge the logic of confirmatory factor analysis, multiple regression, and path analysis within a single data analytic framework. Among the many applications are estimation of disattenuated correlation and regression coefficients, evaluation of multitrait-multimethod matrices, and assessment of hypothesized causal structures. Shortcomings of these methods are commonly acknowledged in the mathematical literature and in textbooks. Nevertheless, serious flaws remain in many published applications. For example, it is rarely noted that the fit of a favored model is identical for a potentially large number of equivalent models. A review of the personality and social psychology literature illustrates the nature of this and other problems in reported applications of covariance structure models.
Analysis of Variance↗
[Latent structure model of physicians' opinions on National Health Insurance].
The purpose of this study is to construct the latent structure models of physicians' opinions on National Health Insurance (NHI). The data for the analysis came from a mail survey of 1619 physicians in January of 1990. Five latent structure models were established as follows: Structure 1. Physicians' viewpoint on NHI. Hospital physicians: Steady, 69%; Turn-Over, 26%; Career-change, 5%. Clinic physicians: Steady-with Insurance Contract, 55%; Steady-without Insurance Contract, 41%; Career-Change, 4%. Structure 2. Physicians' expected impact of NHI. Hospital physicians: Pessimistic, 45%; Disadvantaged, 38%; Constant, 17%. Clinic physicians: Pessimistic, 72%; Constant, 12%; Ambitious, 16%. Structure 3. Physicians' expected workload change due to the implement of NHI. Hospital physicians: Decreasing, 30%; No-Change, 18%; Increasing, 52%. Clinic physicians: Decreasing, 30%; Non-Change, 23%; Increasing, 48%. Structure 4. Ideal practice pattern. Hospital physicians: Traditional, 47%; Transitional, 42%; Practice Abandoned, 12%. Clinic physicians: Traditional, 20%; Transitional, 21%; Rural-Orientated 59%. Structure 5. Expected payment methods for physicians. Hospital physicians: Credentiality-Specialty-based, 44%; Specialty-Equal Pay-based, 11%; Equal Pay-Specialty-based, 42%; Equal Pay-Credentiality-based, 4%. Clinic physicians: Credentiality-based, 24%; Mixed, 11%; Equal Service-Equal Pay-based, 60%; Urbanization Level-based, 5%.
Attitude of Health Personnel↗
Secondary structure model for 23S ribosomal RNA.
A secondary structure model for 23S ribosomal RNA has been constructed on the basis of comparative sequence data, including the complete sequences from E. coli. Bacillus stearothermophilis, human and mouse mitochondria and several partial sequences. The model has been tested extensively with single strand-specific chemical and enzymatic probes. Long range base-paired interactions organize the molecule into six major structural domains containing over 100 individual helices in all. Regions containing the sites of interaction with several ribosomal proteins and 5S RNA have been located. Segments of the 23S RNA structure corresponding to eucaryotic 5.8S and 25 RNA have been identified, and base paired interactions in the model suggest how they are attached to 28S RNA. Functionally important regions, including possible sites of contact with 30S ribosomal subunits, the peptidyl transferase center and locations of intervening sequences in various organisms are discussed. Models for molecular 'switching' of RNA molecules based on coaxial stacking of helices are presented, including a scheme for tRNA-23S RNA interaction.
Animals↗
[An analysis of health related behavior using interpretive structural modeling].
In order for people to know about and to adopt and maintain healthy living practices, 1) a theoretical overview regarding factors associated with health behavior, and 2) an understanding of the actual pattern of behavior in given situations are needed. While theoretical models are helpful in providing a perspective, these models are not practical enough for understanding actual patterns of behavior. In the present study, the ISM (Interpretive Structural Modeling) method was utilized to understand the actual pattern of health related behaviors. The ISM method is used in systems engineering for structurally modeling complex systems. In this study, the ISM method was applied to grasp the structure of coping behavior in the case of fever caused by a common cold under the following two conditions; i) a simplified situation using eight elementary behaviors, and ii) a more complicated situation using more than eight elementary behaviors. i) Subjects were 30 students of public health nursing. The sequence of eight elementary behaviors was determined by paired comparisons using the ISM matrix. The microcomputer made a network diagram of elementary behaviors. The 30 diagrams, none of which were the same, were classified into three types: 1) simple linear (7 subjects), 2) one junction (12 subjects), 3) two or more junctions (11 subjects). After the experiment, subjects were instructed to evaluate the validity of the ISM method. More than 80 percent of the subjects rated the ISM method as effective in increasing their cognition of the hierarchical structure of health related behaviors. ii) Two subjects (A and B) were instructed to come up with as many possible coping behaviors as they could imagine.(ABSTRACT TRUNCATED AT 250 WORDS)
Health Behavior↗
A structured model for immobilized cell kinetics.
An intrinsic, structured model has been formulated to describe the kinetics of viable (living) cells immobilized within porous supports. Predictions of steady-state internal biomass concentration distributions, biocatalyst substrate profiles, and immobilized cell growth and leakage from the support are in qualitative agreement with the literature. Simulation studies indicate that carrier pore structure is a particularly important design variable to be optimized.
Catalysis↗
Protein structure modelling of the bacterial light-harvesting complex.
Protein structure modelling offers a method of obtaining 3-dimensional information that can be tested and used to plan mutagenesis experiments when a crystallographically determined structure is not available. At its simplest a model may consist of little more than a secondary structure prediction coupled with a determination of the likely regions of transmembrane/membrane surface/globular configuration. These methods can yield an interesting topology map of the protein, which places the residues in their likely positions with respect to, for example, the membrane interface. If it is a member of a large family of related proteins then aligned protein sequences can be used to predict the residues that have an important function as these will be largely conserved in the alignments. Using all these methods a model can be constructed (using for example, the Nicholson Molecular Modelling Kit) to visualize the proposed structure in three dimensions following the premise of good design, that is, avoiding obvious steric clashes, packing of helices in a realistic manner, observing the correct H-bond lengths, etc. In this latter exercise the review of Chothia (Annu. Rev. Biochem. 53, 537-572, 1984) of the principles of protein structure is particularly helpful as it clearly sets out how proteins pack and their preferred configuration. There is a wealth of information about individual amino acid conformational preferences and observed frequencies of occurrence in known protein structures, which can help decide how the residues in the model can be oriented. In this article we have collated the various protein models of the bacterial light-harvesting complexes and present our own model, which is a synthesis of the available biophysical data and theoretical predictions, and show its performance in explaining recent results of site-directed mutants of the LH1 and LH2 light-harvesting complexes of Rhodobacter sphaeroides.
Amino Acid Sequence↗
The mitochondrial ribosomal RNA genes of the nematodes Caenorhabditis elegans and Ascaris suum: consensus secondary-structure models and conserved nucleotide sets for phylogenetic analysis.
The small- and large-subunit mitochondrial ribosomal RNA genes (mt-s-rRNA and mt-l-rRNA) of the nematode worms Caenorhabditis elegans and Ascaris suum encode the smallest rRNAs so far reported for metazoa. These size reductions correlate with the previously described, smaller, structurally anomalous mt-tRNAs of C. elegans and A. suum. Using primer extension analysis, the 5' end nucleotides of the mt-s-rRNA and mt-l-rRNA genes were determined to be adjacent to the 3' end nucleotides of the tRNA(Glu) and tRNA(His) genes, respectively. Detailed, consensus secondary-structure models were constructed for the mt-s-rRNA genes and the 3' 64% of mt-l-rRNA genes of the two nematodes. The mt-s-rRNA secondary-structure model bears a remarkable resemblance to the previously defined universal core structure of E. coli 16S rRNA: most of the nucleotides that have been classified as variable or semiconserved in the E. coli model appear to have been eliminated from the C. elegans and A. suum sequences. Also, the secondary structure model constructed for the 3' 64% of the mt-l-rRNA is similar to the corresponding portion of the previously defined E. coli 23S rRNA core secondary structure. The proposed C. elegans/A. suum mt-s-rRNA and mt-l-rRNA models include all of the secondary-structure element-forming sequences that in E. coli rRNAs contain nucleotides important for A-site and P-site (but not E-site) interactions with tRNAs. Sets of apparently homologous sequences within the mt-s-rRNA and mt-l-rRNA core structures, derived by alignment of the C. elegans and A. suum mt-rRNAs to the corresponding mt-rRNAs of other eukaryotes, and E. coli rRNAs were used in maximum-likelihood analyses. The patterns of divergence of metazoan phyla obtained show considerable agreement with the most prevalent metazoan divergence patterns derived from more classical, morphological, and developmental data.
Animals↗
Drug use and personality in adolescence and young adulthood: structural models with nonnormal variables.
An introduction to structural modeling with nonnormal continuous variables is provided using the equations language of the micro-mainframe program EQS in the context of a longitudinal study of adolescent development that followed about 700 adolescents across an 8-year span into young adulthood. 2 models relating drug use and personality are developed to assess the influence of drug use on personality, and personality on drug use. A high level of self-acceptance is shown to have a small but significant inoculating effect against subsequent cannabis use in both early and late adolescence, while a small positive effect of cannabis use on subsequent self-acceptance occurs only during early adolescence. Substantial stability of self-derogation, cannabis use, and law abidance are demonstrated, with self-derogation during adolescence leading to increased law abidance during young adulthood.
Adolescent↗
Mutational analysis supports a structural model for the cell cycle protein kinase p34.
Structural models for the eukaryotic cell cycle control protein p34 from human, S. pombe and S. cerevisiae have been derived from the crystallographic coordinates of the cAMP-dependent protein kinase (cAPK) catalytic subunit (active conformation) and compared with the structure of inactive CDK2 apoenzyme. Differences between the p34 and cAPK catalytic sites provide a possible explanation for their different substrate specificities. The p34 models localize Tyr15 and Thr14 close to the sites of catalysis and substrate recognition where their phosphorylation could inhibit p34 kinase activity either by blocking MgATP or substrate binding. The conserved sequences PSTAIRE and LYLIFEFL are both close to the catalytic site and accessible on the protein surface available to mediate interactions with other proteins. It is predicted that p34 has an active-site cleft composed almost entirely of sequences common to all protein kinases and sequences unique to the p34 protein family. Genetic and biochemical analyses of p34 have shown that it interacts extensively with a number of other proteins. The model allows the relative disposition of these sites of mutation to each other and to the sites of catalysis and substrate recognition to be appreciated. Surface regions on p34 that are important for function have been identified. These sites identify residues that may interact with p13suc1, cyclin, p107wee1 and p80cdc25.
Amino Acid Sequence↗
A structural model of the acetylcholine receptor channel based on partition energy and helix packing calculations.
A structural model of the transmembrane portion of the acetylcholine receptor was developed from sequences of all its subunits by using transfer energy calculations to locate transmembrane alpha-helices and to calculate which helical side chains should be in contact with water inside the channel, with portions of other transmembrane helices, or with lipid hydrocarbon chains. "Knobs-into-holes" side chain packing calculations were used with other factors to stack the transmembrane alpha-helices together. In the model each subunit has the following structures in order along the sequence from the NH2 terminus: a large extracellular domain of undetermined structure, a short apolar alpha-helix that lies on the extracellular lipid surface of the membrane; three apolar transmembrane alpha-helices (I, II, and III), a cytoplasmic domain of undetermined structure, an amphipathic transmembrane alpha-helix (L) that forms the channel lining, a short extracellular alpha-helix, another apolar transmembrane alpha-helix (IV), and a small cytoplasmic domain formed by the COOH-terminal end of the chain. Three concentric layers form the pore. A bundle of five amphipathic L helices forms the channel lining. This bundle is surrounded by a bundle of 10 alternating II and III helices. Helices I and IV cover portions of the outer surface of the bundle formed by helices II and III. Positions of disulfide bridges are predicted and a mechanism for opening and closing conformational changes is proposed that requires tilting transmembrane helices and possibly a thiol-disulfide interchange reaction.
Amino Acid Sequence↗
Structure from function: screening structural models with functional data.
Structural constraints derived from different antibody epitopes on human growth hormone (hGH) were used to screen three-dimensional models of hGH that were generated by computer algorithms. Previously, alanine-scanning mutagenesis defined the residues that modulate binding to 21 different monoclonal antibodies to hGH. These functional epitopes were composed of 4-14 side chains whose alpha-carbons clustered within 4-23 A. Distance and topographic constraints for these functional epitopes were virtually the same as constraints derived from known x-ray structures of protein-antigen complexes. The constraints were used to evaluate about 1400 models of hGH that were computer-generated by a secondary-structure prediction and packing algorithm. On average each functional epitope reduced the number of models in the pool by a factor of 2, so that 8 monoclonal antibodies could reduce the number of possible models to < 10. The average root-mean-square deviation of alpha-carbon coordinates between the x-ray structure and either the pool of starting models or final models ranged from 13 to 16 A or 4 to 7 A, respectively, depending on the pool of starting models and the level of constraints imposed. All of the final models had the correct folding topography, and the best model was within 3.8 A root-mean-square deviation of the x-ray coordinates. This model was as close as it could have been because the models were built by using ideal helices and those in the x-ray structure are not. Our studies suggest that epitope mapping data can effectively screen structural models and, when coupled to predictive algorithms, can help to generate low-resolution models of a protein.
Amino Acid Sequence↗