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PubMed1993

A comparative study of Scatchard-type and linear lattice models for the analysis of EPR competition experiments with spin-labeled nucleic acids and single-strand binding proteins.

An EPR competition formalism is developed which provides relative affinities of proteins for nucleic acids. Two models for analyzing protein-nucleic acid interactions, one assuming independent binding sites (Model 1) and the other considering site overlap (Model 2), are examined with respect to their validity and limitations. The models are employed to derive affinity ratio relationships which are used to calculate the relative affinities of gene 32, gene 5, and SSB proteins for various nucleic acids. It is determined that although Model 2 must be used when determining absolute binding constants, by taking the ratio of binding constants the site overlap becomes unimportant under conditions of moderate to high cooperativity and relatively small site size. This allows Model 1 to considerably simplify binding analyses. Both models are applied to the single-strand binding proteins of bacteriophage T4 gene 32, bacteriophage fd gene 5, and the Escherichia coli ssb gene, and the results are compared.

Allosteric Regulation↗
PubMed1996

Analysis of load-relaxation in compressed segments of lumbar spine.

Load-relaxation was measured in 12 segments of human cadaveric lumbar spine. Each segment consisted of an intact intervertebral disc attached to half of its adjacent vertebrae with the posterior elements removed. Six specimens were each compressed at six different strains (corresponding to initial loads of 0.5-2.5 kN) and, for each strain, the load-relaxation was measured for a period of 20 min at room temperature. These load-relaxation curves were used to plot three isochrones for each specimen. All isochrones were linear (r values in the range 0.95-0.99). This result indicated that a linear model could be used to represent load-relaxation. Four specimens were tested at a single strain (corresponding to an initial load of about 2 kN) at 37 degrees C for a period of 4-6 h. Load was plotted against the logarithm of time. The resulting plots did not show any peaks, indicating that relaxation effects did not predominate at any particular times during load-relaxation. However, it was possible to model the load-relaxation as a simple linear system which can be represented as two Maxwell elements in parallel. These elements were characterized by relaxation times of 16 +/- 8 min and 4.6 +/- 0.8 h. Fourier transformation of the load-relaxation curves showed a gradual increase in the storage modulus and a gradual decrease in the loss modulus for frequencies of about 1 Hz and above. At these frequencies, the spine cannot function as a shock-absorber in pure compression.

Aged↗
PubMed2006

Derivation of predicted no effect concentrations (PNEC) for marine environmental risk assessment: application of different approaches to the model contaminant Linear Alkylbenzene Sulphonates (LAS) in a site-specific environment.

Four sediment-dwelling marine organisms were exposed to sediments spiked with increasing concentrations of Linear Alkylbenzene Sulphonate (LAS). The selected endpoint mortality was reported daily and acute LC(50) (96 h), as well as final LC(10) values were calculated for the derivation of environmentally safe predicted no effect concentrations (PNEC) for the sediment compartment. PNECs were estimated by both application of assessment factors (AF) and the equilibrium partitioning method (EPM) as proposed by the EU TGD. Finally, environmental risk assessment in a site-specific environment, the Sancti Petri Channel, South Iberian Peninsula, was carried out at three different sampling stations with known environmental LAS concentrations. PNECs obtained by the assessment factor approach with acute toxicity data were one to two orders of magnitude lower than those from the equilibrium partitioning method. On the other hand, when applying lower AFs to the estimated LC(10) values, the PNECs obtained by both approaches were more similar. Environmental risk assessment carried out with the estimated PNECs in a site specific environment with known sediment LAS concentrations revealed that PNECs obtained with acute toxicity data were over conservative whereas those obtained with AF=10 on LC(10) data and EPM produced more realistic results in accordance with field observations carried out in the study area.

Alkanesulfonic Acids↗
PubMed2005

Generalized modeling approaches to risk adjustment of skewed outcomes data.

There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., ordinary least square (OLS) on ln(y)); and (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches. In this paper, we encompass these two classes of models using the three parameter generalized Gamma (GGM) distribution, which includes several of the standard alternatives as special cases-OLS with a normal error, OLS for the log-normal, the standard Gamma and exponential with a log link, and the Weibull. Using simulation methods, we find the tests of identifying distributions to be robust. The GGM also provides a potentially more robust alternative estimator to the standard alternatives. An example using inpatient expenditures is also analyzed.

Models, Statistical↗
PubMed2004

Intra-unit correlations in seroconversion to Actinobacillus pleuropneumoniae and Mycoplasma hyopneumoniae at different levels in Danish multi-site pig production facilities.

In this paper, multilevel logistic models which take into account the multilevel structure of multi-site pig production were used to estimate the variances between pigs produced in Danish multi-site pig production facilities regarding seroconversion to Actinobacillus pleuropneumoniae serotype 2 (Ap2) and Mycoplasma hyopneumoniae (Mh). Based on the estimated variances, three newly described computational methods (model linearisation, simulation and linear modelling) and the standard method (latent-variable approach) were used to estimate the correlations (intra-class correlation components, ICCs) between pigs in the same production unit regarding seroconversion. Substantially different values of ICCs were obtained from the four methods. However, ICCs obtained by the simulation and the model linearisation were quite consistent. Data used for estimation were collected from 1161 pigs from 429 litters reared in 36 batches at six Danish multi-site farms chronically infected with the agents. At the farms, weaning age was 3-4.5 weeks, after which batches of pigs were reared using all-in/all-out management by room. Blood samples were collected shortly before: weaning, transfer from weaning-site to finishing-site, and sending the first pigs in the batch for slaughter (third sampling). Few pigs seroconverted at the weaning-sites, whereas considerable variation in seroconversion was observed at the finishing-sites. Multilevel logistic models (initially including four levels: farm, batch, litter, pig) were used to decompose the variation in seroconversion at the finishing-site. However, there was essentially no clustering at the litter level-leading to the use of three-level models. In the case of Ap2, clustering within batch was so high that the data eventually were reduced to two levels (farm, batch). For seroconversion to Ap2, ICC between pigs within batches was approximately 90%, whereas the ICC between pigs within batches for Mh was approximately 40%. This indicates that the possibility for Mh to spread between pigs within batches is lower than for Ap2. The diversity in seroconversion between batches within the same farm was large for Ap2 (ICC approximately 10%), whereas there was a relative strongly ICC (approximately 50%) between batches for Mh. This indicates that the transmission of Mh is more consistent within a farm, whereas the presence of Ap2 varies between batches within a farm.

Actinobacillus Infections↗
PubMed2003

Solid stress generated by spheroid growth estimated using a linear poroelasticity model.

The unchecked growth of a solid tumor produces solid stress, causing deformation of the surrounding tissue. This stress can result in clinical complications, especially in confined environments such as the brain, and may also be responsible for pathophysiological anomalies such as the collapse of blood and lymphatic vessels. High stress levels may also inhibit further cell division within tumors. Unfortunately, little is known about the dynamics of stress accumulation in tumors or its effects on cell biology. We present a mathematical model for tumor growth in a confined, elastic environment such as living tissue. The model, developed from theories of thermal expansion using the current configuration of the material element, allows the stresses within the growing tumor and the surrounding medium to be calculated. The experimental observation that confining environments limit the growth of tumor spheroids to less than the limit imposed by nutrient diffusion is incorporated into the model using a stress dependent rate for tumor growth. The model is validated against experiments for MU89 tumor spheroid growth in Type VII agarose gel. Using the mathematical model and the experimental evidence we show that the tumor cell size is reduced by solid stress inside the tumor spheroid. This leads to the interesting possibility that cell size could be a direct indicator of solid stress level inside the tumors in clinical setting.

Animals↗
PubMed1996

Transduction dynamics of intrapulmonary CO2 receptors.

We have developed a functional model for quantitatively characterizing the transduction dynamics of the intrapulmonary CO2 receptors (IPC) in the snake lung. The model was based on experiments in which the neural discharges of several IPCs were recorded in response to abrupt step changes in CO2 concentration. Initial attempts to model the transduction dynamics linearly proved inadequate, although the linear model captured gross features such as rate sensitivity and the existence of two time constants in the adaptation time-course. However, with the incorporation of two static nonlinear features, namely, thresholding and preferential directionality of the rate-sensitive component, it was possible to account for over 80% of the total variation in the data. The model produced accurate predictions of IPC responses to other inputs, such as pseudorandom binary changes in CO2. The model also allows the prediction of IPC discharge in spontaneous breathing given measurements of lung CO2 concentration, and may serve as a starting point for further studies of transduction mechanisms at the cellular level.

Animals↗
PubMed1999

On the identifiability of mixtures-of-experts.

In mixtures-of-experts (ME) models, "experts" of generalized linear models are combined, according to a set of local weights called the "gating function". The invariant transformations of the ME probability density functions include the permutations of the expert labels and the translations of the parameters in the gating functions. Under certain conditions, we show that the ME systems are identifiable if the experts are ordered and the gating parameters are initialized. The conditions are validated for Poisson, gamma, normal and binomial experts.

Journal Article↗
PubMed2006

Self-consistent field modeling of linear nonionic micelles.

A self-consistent field theory is used to predict structural, mechanical, and thermodynamical properties of linear micelles of selected nonionic surfactants of the type C(n)()E(m). Upon increase in surfactant concentration the sudden micelle shape transition from spherical to cylindrical (second critical micelle concentration (cmc)) is analyzed. The cylindrical micelles consist of a body (with radius R(c) and length L) and two slightly swollen endcaps. For small L, the shape resembles a dumbbell. With increase in the length of the body, an oscillatory behavior in the grand potential of the micelle is found. The wavelength of the oscillation (lambda(d)) is proportional to the surfactant tail length n. The amplitude of these oscillations decreases exponentially with a decay length xi. In the limit of very long micelles, the grand potential converges to the endcap (free) energy E(c). This endcap energy increases approximately quadratic with the tail length and diminishes by increasing the headgroup size m. The micelle size distribution is generated showing non-monotonic features due to the presence of short dumbbells and becomes exponential when L >> 8R(c). It is also shown that the endcap energy can be estimated in first order by the grand potential of the spherical micelle that coexists with infinitely long cylindrical micelles. The persistence length l(p) of these linear micelles is evaluated to estimate the relative importance of conformational entropy for these micelles.

Journal Article↗
PubMed2005

Using multilevel models to analyze couple and family treatment data: basic and advanced issues.

Couple and family treatment data present particular challenges to statistical analyses. Partners and family members tend to be more similar to one another than to other individuals, which raises interesting possibilities in the data analysis but also causes significant problems with classical, statistical methods. The present article presents multilevel models (also called hierarchical linear models, mixed-effects models, or random coefficient models) as a flexible analytic approach to couple and family longitudinal data. The article reviews basic properties of multilevel models but focuses primarily on 3 important extensions: missing data, power and sample size, and alternative representations of couple data. Information is presented as a tutorial, with a Web appendix providing datasets with SPSS and R code to reproduce the examples.

Couples Therapy↗
PubMed2004

The role of coding time in estimating and interpreting growth curve models.

The coding of time in growth curve models has important implications for the interpretation of the resulting model that are sometimes not transparent. The authors develop a general framework that includes predictors of growth curve components to illustrate how parameter estimates and their standard errors are exactly determined as a function of receding time in growth curve models. Linear and quadratic growth model examples are provided, and the interpretation of estimates given a particular coding of time is illustrated. How and why the precision and statistical power of predictors of lower order growth curve components changes over time is illustrated and discussed. Recommendations include coding time to produce readily interpretable estimates and graphing lower order effects across time with appropriate confidence intervals to help illustrate and understand the growth process.

Child↗