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PubMed1986

A model for the role of hyaluronic acid and fibrin in the early events during the inflammatory response and wound healing.

A model is presented outlining the molecular and cellular events that occur during the early stages of the wound healing process. The underlying theme is that there is a specific binding interaction between fibrin, the major clot protein, and hyaluronic acid (HA), a constituent of the wound extracellular matrix. This binding interaction, which could also be stabilized by other cross-linking components, provides the driving force to organize a three-dimensional HA matrix attached to and interdigitated with the initial fibrin matrix. The HA-fibrin matrix plays a major role in the subsequent tissue reconstruction processes. We suggest that HA and fibrin have both structural and regulatory functions at different times during the wound healing process. The concentration of HA in blood and in the initial clot is very low. This is consistent with the proposed interaction between HA and fibrin(ogen), which could interfere with either fibrinogen activation or fibrin assembly and cross-linking. We propose that an activator (e.g. derived from a plasma precursor, platelets or surrounding cells) is produced during the clotting reaction and then stimulates one or more blood cell types to synthesize and secrete HA into the fibrin matrix of the clot. We predict that HA controls the stability of the matrix by regulating the degradation of fibrin. The new HA-fibrin matrix increases or stabilizes the volume and porosity of the clot and then serves as a physical support, a scaffold through which cells trapped in the clot or cells infiltrating from the peripheral edge of the wound can migrate. The HA-fibrin matrix also actively stimulates or induces cell motility and activates and regulates many functions of blood cells, which are involved in the inflammatory response, including phagocytosis and chemotaxis. The secondary HA-fibrin matrix itself is then modified as cells continue to migrate into the wound, secreting hyaluronidase and plasminogen activator to degrade the HA and fibrin. At the same time these cells secrete collagen and glycosaminoglycans to make a more differentiated matrix. The degradation products derived from both fibrin and HA are, in turn, important regulatory molecules which control cellular functions involved in the inflammatory response and new blood vessel formation in the healing wound. The proposed model generates a number of testable experimental predictions.

Blood Coagulation↗
PubMed1990

Nonuniform radiolabeling of VLDL apolipoprotein B: implications for the analysis of studies of the kinetics of the metabolism of lipoproteins containing apolipoprotein B.

Radiolabeling of whole lipoproteins or individual apolipoproteins has been an essential tool for the determination of the kinetics of apolipoprotein metabolism in vivo. Mathematical analysis of specific radioactivity (SA) or total radioactivity data has demonstrated the existence of significant complexity in the plasma decay curves of several apolipoproteins. Results obtained during development of methods to study the metabolism of apolipoprotein B (apoB) in very low density lipoprotein (VLDL) subclasses isolated according to flotation (Sf) rates from whole radiolabeled (d less than 1.006 g/ml) VLDL suggested nonuniform radiolabeling of apoB in the three Sf subclasses being studied. We therefore determined apoB SA in VLDL Sf subclasses in ten hypertriglyceridemic and five normal subjects. After radioiodination of apoB in whole VLDL, different apoB SA were found in Sf 400-100, Sf 100-60, and Sf 60-20. The pattern of labeling was quite variable among subjects. On average, apoB SA in the VLDL tracer was greatest in Sf 400-100, and least in Sf 60-20. Nonuniform labeling could also be demonstrated in five studies in which samples were obtained 3 min after intravenous injection of the tracer into subjects with a wide range of plasma triglycerides. Nonuniform labeling of apoB in whole VLDL was also demonstrated in two of the subjects by isolating subclasses of their VLDL that did not bind to an anti-apolipoprotein E immunoaffinity column. These results indicate that the usual assumption of homogeneous labeling of apoB may be erroneous. We have derived a simple mathematical formula to study the consequences of this assumption in estimating kinetic parameters. It is shown that an erroneous assumption of homogeneous tracer labeling may significantly underestimate or overestimate the true production rate, even in a simple two-pool model. Identification of labeling characteristics and incorporation of this information into the mathematical analysis of the plasma radioactivity data can improve the accuracy of the analysis as well as the sensitivity of compartmental models generated by such data.

Apolipoproteins B↗
PubMed2004

An estimate of the U.S. Government's undercount of nonfatal occupational injuries.

Debate surrounds the size of the underestimate of nonfatal occupational injuries produced by the U.S. Bureau of Labor Statistics (BLS). We developed models that separated categories of injuries: BLS Annual Survey, federal government, agriculture, state and local government, self-employed outside agriculture, and all other. The models generated varying estimates depending on the assumptions for each category pertaining to job risks and amount of underreporting. We offered justification for the assumptions based on published studies as well as our own analyses of BLS data. The models suggested the Annual Survey missed from 0% to 70% of the number of injuries (from private firms, excluding the self-employed) it was designed to capture. However, when we included firms and governments the Annual Survey was not designed to capture, and considered reasonable assumptions regarding underreporting, we estimated the BLS missed between 33% and 69% of all injuries. We concluded that there was substantial undercapture in the BLS Annual Survey, some due to the excluded categories of government workers and the self-employed, as well as some due to underreporting.

Accidents, Occupational↗
PubMed1996

Genotypic and phenotypic analysis of zwittermicin A-producing strains of Bacillus cereus.

Many strains of Bacillus cereus produce zwittermicin A, a novel antibiotic that contributes to the ability of B. cereus to suppress certain plant diseases. The purpose of this study was to identify molecular indicators of zwittermicin A production in B, cereus strains, contribute to an understanding of the ecology and evolution of this group of bacteria, and identify potential agents for control of plant disease. The fatty acid composition of 20 strains known to be zwittermicin A producers and 20 strains known to be non-producers was determined. Cluster analysis of the fatty acid methyl ester (FAME) profiles revealed that zwittermicin A producers grouped together in two clusters, apart from most non-producers. Discriminant analysis of the FAME profiles generated models that correctly predicted the zwittermicin A-production phenotype in 17 of 20 zwittermicin A producers and 17 of 20 non-producers. Sixteen random oligonucleotide primers were tested in PCR, and one primer was identified that generated a fragment of 0.48 kb or 0.49 kb from total DNA from 26 of 28 strains known to produce zwittermicin A, whereas PCR with this primer did not generate bands of that size from 16 of 20 non-producing strains. PCR with primers designed to amplify zmaR, a gene from B. cereus that confers resistance to zwittermicin A, generated DNA fragments of 1.1 kb and 1.0 kb in all 29 zwittermicin A-producing strains tested, amplified a fragment of 0.3 kb in some of the zwittermicin A-producing strains, and amplified no fragments in 20 of 23 non-producing strains in a stock collection of B. cereus strains. The zmaR primers were tested for their ability to identify new zwittermicin A-producing isolates of B. cereus from two soils. All 12 of the isolates that produced the banding pattern characteristic of this primer pair produced zwittermicin A, and none of the 12 isolates that did not have the banding pattern produced detectable zwittermicin A. Seven of the 12 isolates initially identified as zwittermicin A producers with the zmaR primers significantly suppressed damping-off of alfalfa, whereas only one of the non-producers suppressed this disease. The results show that FAME and PCR analyses distinguish B. cereus strains that produce zwittermicin A from other B. cereus strains, that PCR with the primers designed to amplify zmaR is the most reliable method of those tested for identification of zwittermicin A producers, and that this method can be used to identify new strains with disease-suppressive activity.

Anti-Bacterial Agents↗
PubMed1995

Magnetic backprojection imaging of the vascular lumen.

Current injected into a phantom model generated a magnetic field which was distorted above a simulated atherosclerotic lesion. The output of a Hall effect magnetic sensor was used in a backprojection to reconstruct the centroid of the simulated blood flow and thus localize the modeled atherosclerotic plaque region.

Arteries↗
PubMed2000

De novo protein structure determination using sparse NMR data.

We describe a method for generating moderate to high-resolution protein structures using limited NMR data combined with the ab initio protein structure prediction method Rosetta. Peptide fragments are selected from proteins of known structure based on sequence similarity and consistency with chemical shift and NOE data. Models are built from these fragments by minimizing an energy function that favors hydrophobic burial, strand pairing, and satisfaction of NOE constraints. Models generated using this procedure with approximately 1 NOE constraint per residue are in some cases closer to the corresponding X-ray structures than the published NMR solution structures. The method requires only the sparse constraints available during initial stages of NMR structure determination, and thus holds promise for increasing the speed with which protein solution structures can be determined.

Humans↗
PubMed2006

Examining the potential effects of species aggregation on the network structure of food webs.

One of the key measures that have been used to describe the topological properties of complex networks is the "degree distribution", which is a measure that describes the frequency distribution of number of links per node. Food webs are complex ecological networks that describe the trophic relationships among species in a community, and the topological properties of empirical food webs, including degree distributions, have been examined previously. Previously, the "niche model" has been shown to accurately predict degree distributions of empirical food webs, however, the niche model-generated food webs were referenced against empirical food webs that had their species grouped together based on their taxonomic and/or trophic relationships (aggregated food webs). Here, we explore the effects of species aggregation on the ability of the niche model to predict the total- (sum of prey and predator links per node), in- (number of predator links per node), and out- (number of prey links per node) degree distributions of empirical food webs by examining two food webs that can be aggregated at different levels of resolution. The results showed that (1) the cumulative total- and out-degree distributions were consistent with the niche model predictions when the species were aggregated, (2) when the species were disaggregated (i.e., higher resolution), there were mixed conclusions with regards to the niche model's ability to predict total- and out-degree distributions, (3) the model's ability to predict the in-degree distributions of the two food webs was generally inadequate. Although it has been argued that universal functional form based on the niche model could describe the degree distribution patterns of empirical food webs, we believe there are some limitations to the model's ability to accurately predict the structural properties of food webs.

Animals↗
PubMed1996

Synthesis of an anaesthetic agent administration system using fuzzy inductive reasoning.

Control of the depth of anaesthesia is a difficult undertaking. Progress has been made during recent years by use of different methodologies and monitoring systems that suggest the safe amount of an anaesthetic drug, considering the condition of an individual patient. Despite these improvements, anaesthetists still rely heavily on personal experience when suggesting the anaesthetic dosage during surgical operations. The purposes of this paper are twofold. One is a description of the design of an anaesthetic agent control system using a qualitative modelling and simulation methodology called Fuzzy Inductive Reasoning (FIR). A comparison with a system developed for the same application using a neural network approach is also presented. The second purpose is a discussion of the problem of separating system-generic from patient-specific behaviour in the context of inductive modeling using the FIR methodology. In order to be useful, the model generated by FIR should reflect upon system-generic behavioural characteristics exclusively, while suppressing patient-specific behavioural patterns. A technique based on combining knowledge obtained from different patients is designed that makes it possible to derive a single model characterizing a specific class of similar patients undergoing similar operations, preserving the common characteristics of all these patients while filtering out the specific behavioural patterns of any one of the individual patients from whom the data were obtained.

Anesthetics↗
PubMed2003

Equilibrium protein folding-unfolding process involving multiple intermediates.

Mathematical models for the protein folding-unfolding process involving multiple intermediates have been derived. Computer fitting of the experimental data to this model generates various thermodynamic parameters for the folding-unfolding process. In this way, the complex folding-unfolding process of the multi-domain proteins can be analysed in a quantitative way. The application of the folding-unfolding model involving seven stages in human placental alkaline phosphatase is described.

Alkaline Phosphatase↗
PubMedDate not supplied

Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection.

One of the most important characteristics of Quantitative Structure Activity Relashionships (QSAR) models is their predictive power. The latter can be defined as the ability of a model to predict accurately the target property (e.g., biological activity) of compounds that were not used for model development. We suggest that this goal can be achieved by rational division of an experimental SAR dataset into the training and test set, which are used for model development and validation, respectively. Given that all compounds are represented by points in multidimensional descriptor space, we argue that training and test sets must satisfy the following criteria: (i) Representative points of the test set must be close to those of the training set; (ii) Representative points of the training set must be close to representative points of the test set; (iii) Training set must be diverse. For quantitative description of these criteria, we use molecular dataset diversity indices introduced recently (Golbraikh, A., J. Chem. Inf. Comput. Sci., 40 (2000) 414-425). For rational division of a dataset into the training and test sets, we use three closely related sphere-exclusion algorithms. Using several experimental datasets, we demonstrate that QSAR models built and validated with our approach have statistically better predictive power than models generated with either random or activity ranking based selection of the training and test sets. We suggest that rational approaches to the selection of training and test sets based on diversity principles should be used routinely in all QSAR modeling research.

Algorithms↗
PubMed2002

Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection.

One of the most important characteristics of Quantitative Structure Activity Relashionships (QSAR) models is their predictive power. The latter can be defined as the ability of a model to predict accurately the target property (e.g., biological activity) of compounds that were not used for model development. We suggest that this goal can be achieved by rational division of an experimental SAR dataset into the training and test set, which are used for model development and validation, respectively. Given that all compounds are represented by points in multidimensional descriptor space, we argue that training and test sets must satisfy the following criteria: (i) Representative points of the test set must be close to those of the training set; (ii) Representative points of the training set must be close to representative points of the test set; (iii) Training set must be diverse. For quantitative description of these criteria, we use molecular dataset diversity indices introduced recently (Golbraikh, A., J. Chem. Inf. Comput. Sci., 40 (2000) 414-425). For rational division of a dataset into the training and test sets, we use three closely related sphere-exclusion algorithms. Using several experimental datasets, we demonstrate that QSAR models built and validated with our approach have statistically better predictive power than models generated with either random or activity ranking based selection of the training and test sets. We suggest that rational approaches to the selection of training and test sets based on diversity principles should be used routinely in all QSAR modeling research.

Algorithms↗
PubMed2003

Things aren't as bad as they seem: a comment on Storms et al. (2003).

G. Storms, T. Dirikx, J. Saerens, S. Verstraeten, and P. P. De Deyn (2003) criticized the use of scaling techniques, in proposing "semantic storage deficits" in Alzheimer's disease and schizophrenic patients in some studies, arguing that most reported multidimensionalscaling (MDS) models for patients were not adequately fit and did not differ from models generated by random data. The studies cited by G. Storms et al. were reexamined and all available data relevant to their claim were compared. A more complete review revealed somewhat different conclusions; it showed that many of the MDS models seem to meet the criteria of adequate fit, and it does not seem to support the notion that patients' performance is close to random. Suggestions are made to improve the validity of scaling analysis in neuropsychological studies.

Alzheimer Disease↗
PubMed2006

Dragon Promoter Mapper (DPM): a Bayesian framework for modelling promoter structures.

UNLABELLED: Dragon Promoter Mapper (DPM) is a tool to model promoter structure of co-regulated genes using methodology of Bayesian networks. DPM exploits an exhaustive set of motif features (such as motif, its strand, the order of motif occurrence and mutual distance between the adjacent motifs) and generates models from the target promoter sequences, which may be used to (1) detect regions in a genomic sequence which are similar to the target promoters or (2) to classify other promoters as similar or not to the target promoter group. DPM can also be used for modelling of enhancers and silencers. AVAILABILITY: http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/ CONTACT: vlad@sanbi.ac.za SUPPLEMENTARY INFORMATION: Manual for using DPM web server is provided at http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/html/manual/manual.htm.

Algorithms↗
PubMed1994

Prediction of runoff transport of fallout 90Sr.

A model is described for the prediction of runoff transfer of fallout 90Sr without recourse to long-term measurements. The values of model parameters can be readily established from few field measurements of the solid/solution partitioning of 90Sr and a natural, atmospherically delivered radionuclide such as 210Pb, and the usually well documented fallout and hydrologic data. The model-generated profiles of 90Sr for two major Canadian watersheds compare favorably to those established through long-term monitoring of receiving waters.

Forecasting↗
PubMed2001

Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairs.

Identification of genes involved in complex traits by traditional (lod score) linkage analysis is difficult due to many complicating factors. An unfortunate drawback of non-parametric procedures in general, though, is their low power to detect genetic effects. Recently, Dudoit and Speed [2000] proposed using a (likelihood-based) score test for detecting linkage with IBD data on sib pairs. This method uses the likelihood for theta, the recombination fraction between a trait locus and a marker locus, conditional on the phenotypes of the two sibs to test the null hypothesis of no linkage (theta = (1/2)). Although a genetic model must be specified, the approach offers several advantages. This paper presents results of simulation studies characterizing the power and robustness properties of this score test for linkage, and compares the power of the test to the Haseman-Elston and modified Haseman-Elston tests. The score test is seen to have impressively high power across a broad range of true and assumed models, particularly under multiple ascertainment. Assuming an additive model with a moderate allele frequency, in the range of p = 0.2 to 0.5, along with heritability H = 0.3 and a moderate residual correlation rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models. Generally, our results indicate that this score test for linkage offers a high degree of protection against wrong assumptions due to its strong robustness when used with the recommended additive model.

Computer Simulation↗
PubMed1970

A physical model for muscular behavior.

A model for muscular behavior has been developed by a generalization of the laws governing the viscoelastic behavior of polymeric materials. The model simulates events thought to take place during stretch, loading, and stimulation of muscle, whether smooth or striated. The equations of motion were solved with an analogue computer for several types of perturbation, and stress, strain, and strainrate curves were generated. Model parameters were selected by fitting experimental stress-relaxation data. The resulting equations predicted the frequency dependence of dynamic modulus and phase angle within experimental error. With appropriate boundary conditions and suitable values for model parameters, the computed results also closely resembled experimental curves of contraction velocity vs. time, isometric tension development vs. time, force-velocity curves, and temperature-tension relationships. These results call attention to the relationship between the behavior of various kinds of muscle and open the way for quantifying muscular behavior in general.

Animals↗
PubMed1998

Assessment of body composition in infants and children.

The aims of this review are to consider 1) the applications of pediatric body composition methodology; 2) criteria for determining choice of method; and 3) some future developments. The major applications are: development and validation of new methods; assessment of growth or nutritional status; public health applications, such as monitoring the increasing prevalence of pediatric obesity; interpretation of data on energy expenditure; and testing the functional significance of variation in body composition. An appreciation of the underlying theoretical models (two-component and multicomponent models) is essential to an understanding of the methodology, as is an appreciation of the fact that infants and children are not "chemically mature." The two-component model generates methods that, though limited by variation in the composition of fat-free mass, have accuracy that is acceptable so long as the method in question is chosen with care. Criteria for determining choice of method are provided. Multicomponent models have a more rigorous theoretical basis, but require access to techniques that are not universally available and not always practical for pediatric use. Bedside methods, notably bioelectrical impedance and skinfold thickness, can provide acceptable accuracy, but the precision of all methods limits their ability to measure changes in body composition.

Body Composition↗
PubMed2003

Structural studies of ammonia and metallic lithium-ammonia solutions.

The technique of hydrogen/deuterium isotopic substitution has been used to extract detailed information concerning the solvent structure in pure ammonia and metallic lithium-ammonia solutions. In pure ammonia we find evidence for approximately 2.0 hydrogen bonds around each central nitrogen atom, with an average N-H distance of 2.4 A. On addition of alkali metal, we observe directly significant disruption of this hydrogen bonding. At 8 mol % metal there remains only around 0.7 hydrogen bond per nitrogen atom. This value decreases to 0.0 for the saturated solution of 21 mol % metal, as all ammonia molecules have then become incorporated into the tetrahedral first solvation spheres of the lithium cations. In conjunction with a classical three-dimensional computer modeling technique, we are now able to identify a well-defined second cationic solvation shell. In this secondary shell the nitrogen atoms tend to reside above the faces and edges of the primary tetrahedral shell. Furthermore, the computer-generated models reveal that on addition of alkali metal the solvent molecules form voids of approximate radius 2.5-3.0 A. Our data therefore provide new insight into the structure of the polaronic cavities and tunnels, which have been theoretically predicted for lithium-ammonia solutions.

Journal Article↗