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At least 253 records · Page 14Linked to original sources

PubMed2002

Pharmacodynamic modeling of chemotherapeutic effects: application of a transit compartment model to characterize methotrexate effects in vitro.

The time course of chemotherapeutic effect is often delayed relative to the time course of chemotherapeutic exposure. In many cases, this delay is difficult to characterize mathematically through the use of standard pharmacodynamic models. In the present work, we investigated the relationship between methotrexate (MTX) exposure and the time course of MTX effects on tumor cell growth in culture. Two cancer cell lines, Ehrlich ascites cells and sarcoma 180 cells, were exposed for 24 hours to MTX concentrations that varied more than 700-fold (0.19-140 micro g/mL). Viable cells were counted on days 1, 3, 5, 7, 9, 11, 13, 15, 17, 20, 22, and 24 for Ehrlich ascites cells and on days 1, 2, 3, 5, 7, 9, 11, 13, 14, 15, 17, 19, and 21 for sarcoma 180 cells, through the use of a tetrazolium assay. Although MTX was removed 24 hours after application, cell numbers reached nadir values more than 100 hours after MTX exposure. Data from each cell line were fitted to 3 pharmacodynamic models of chemotherapeutic cell killing: a cell cycle phase-specific model, a phase-nonspecific model, and a transit compartment model (based on the general model recently reported by Mager and Jusko, Clin Pharmacol Ther. 70:210-216, 2001). The transit compartment model captured the data much more accurately than the standard pharmacodynamic models, with correlation coefficients ranging from 0.86 to 0.999. This report shows the successful application of a transit compartment model for characterization of the complex time course of chemotherapeutic effects; such models may be very useful in the development of optimization strategies for cancer chemotherapy.

Animals↗

PubMed2006

Application of a model-based optimisation methodology for nutrient removing SBRs leads to falsification of the model.

Recently, a model-based optimisation methodology for SBR operation has been developed and an optimal operation scenario proposed to improve N and P removal in a pilot-scale SBR. In this study, this optimal operation scenario was implemented and evaluated. The results of the implementation showed that the SBR performance was improved by approximately 50 and 40% for total nitrogen and phosphorous removal, respectively, which was better than predicted by the model. However, the long-term SBR performance was found to be unstable, particularly owing to settling problems developed after the implementation. When confronted with reality, the model used for the optimisation of the operation was found to be invalid. The model was unable to predict the nitrite build-up provoked by the optimal operation scenario. These results imply that changing the operation of an SBR system using a model may significantly change the behaviour of the system beyond the (unknown) application domain of the model. This is simply because the mechanistic models currently do not cover all the aspects of activated sludge systems, e.g. settling and adaptation of the microbial community. To further improve model-application practices, expert knowledge (not contained in the models) can be valuable and should be incorporated into model-based process optimisations.

Bioreactors↗

PubMed2005

Semiparametric animal models via penalized splines as alternatives to models with contemporary groups.

Contemporary groups (CG) are used in genetic evaluation to account for systematic environmental effects of management, nutritional level, or any other differentially expressed group effect; however, because the functional form of the distribution of those effects is unknown, CG serve as an approximation to a time-varying mean. Conversely, in semiparametric models, there is no need to assume any functional form for the time-varying effects. In this research, we present a semiparametric animal model (AMS) using the covariate day of birth (DOB) by means of penalized splines (P-splines), as an alternative to fitting CG. In the AMS, the functionality of the data on DOB is expressed by means of a Basic segmented polynomial line (B-spline) basis, and proper covariance matrices are used to reflect the serial correlation among the points of support (or knots) at different times. Three different covariance matrices that reflect either short- or long-range dependences among knots are discussed. Different models were fitted to birth weight data from Polled Hereford calves. Models compared were an animal model with CG, an animal model with CG and the covariate DOB nested within CG (CG + DOB), and P-splines with the first difference penalty matrix and three different AMS with 20, 40, 60, 80, or 120 knots. Models were compared using a modified Akaike information criterion (AICC), which was calculated as a byproduct of the estimation of variance components by REML using the expectation maximization algorithm. All three AMS had smaller (better) values of AICC than the regular model with CG, while producing almost the same ranking of predicted breeding values and similar average predicted error variance. In all AMS, the inference and all measures of comparison were similar when the number of knots was equal > or = 40. The model CG + DOB had analogous performance to the AMS, but at the expense of using more parameters. It is concluded that the use of penalized regression splines using a B-spline basis with proper covariance matrices is a competitive method to the fitting of CG into animal models for genetic evaluation, without having to assume any functional form for the covariate DOB.

Animals↗

PubMed1991

Regressive logistic models for familial diseases: a formulation assuming an underlying liability model.

Statistical models have been developed to delineate the major-gene and non-major-gene factors accounting for the familial aggregation of complex diseases. The mixed model assumes an underlying liability to the disease, to which a major gene, a multifactorial component, and random environment contribute independently. Affection is defined by a threshold on the liability scale. The regressive logistic models assume that the logarithm of the odds of being affected is a linear function of major genotype, phenotypes of antecedents and other covariates. An equivalence between these two approaches cannot be derived analytically. I propose a formulation of the regressive logistic models on the supposition of an underlying liability model of disease. Relatives are assumed to have correlated liabilities to the disease; affected persons have liabilities exceeding an estimable threshold. Under the assumption that the correlation structure of the relatives' liabilities follows a regressive model, the regression coefficients on antecedents are expressed in terms of the relevant familial correlations. A parsimonious parameterization is a consequence of the assumed liability model, and a one-to-one correspondence with the parameters of the mixed model can be established. The logits, derived under the class A regressive model and under the class D regressive model, can be extended to include a large variety of patterns of family dependence, as well as gene-environment interactions.

Environment↗

PubMed1997

Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.

The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is not a priori evident why these models work. This article presents a derivation of the two models from the framework of canonical modeling. It begins with a general description of the dynamics between risk sources and disease development, formulates this description in the canonical representation of an S-system, and shows how the linear-logistic model and Cox's proportional hazard model follow naturally from this representation. The article interprets the model parameters in terms of epidemiological concepts as well as in terms of general systems theory and explains the assumptions and limitations generally accepted in the application of these epidemiological models.

Communicable Diseases↗

PubMed2001

Modelling the line of action for the oblique abdominal muscles using an elliptical torso model.

When modelling the line of action of a muscle, anatomical considerations must be included if the model is to realistically mimic the muscle behaviour. The internal and external oblique muscles are examples of muscles that do not follow a straight line between origin and insertion, instead having to wrap around the torso. A model is presented which describes the shape of the torso using a right elliptical cylinder of varying dimensions. The muscle lines of action are then calculated based on this underlying torso shape. The model has been successfully fitted to the data reported by Stokes and Gardner-Morse (Journal of Biomechanics 32(3) (1999) 311). When compared to a linear model, the use of the torso model results in a 15% increase in the axial twist moment, and decreases in the lateral bend and extension moments (5% and 2%, respectively), able to be generated by the internal and external oblique muscles combined in upright stance. These differences become larger (up to 37%) when the torso is flexed, extended or twisted. The structure of the torso model allows it to be used to model any posture without significant increases in the overall model complexity.

Abdominal Muscles↗

PubMed2003

Economic weights for feed intake in the growing pig derived from a growth model and an economic model.

Economic weights are obtained for feed intake using a growth model and an economic model. The underlying concept of the growth model is the linear plateau model. Parameters of this model are the marginal ratio (MR) of extra fat and extra protein deposition with increasing feed intake (FI) and the maximum protein deposition (Pd(max)). The optimum feed intake (FI0) is defined as the minimum feed intake that meets energy requirements for Pd(max). The effect of varying FI and MR on performance traits was determined. An increase in FI results in a larger increase in growth rate with lower MR. For a given MR, feed conversion ratio is lowest when FI equals FI0. Lean meat percentage (LMP) is largest for a low MR in combination with a low FI. The decrease in LMP with higher FI islargest when FI exceeds FI0. Economic weights for FI, MR and Pd(max) depend on FI in relation to FI0. Economic weights for FI are positive when FI is less than FI0 and negative when FI is larger than FI0. The MR has only then a negative economic weight, when FI is below FI0. Economic weights of FI and MR have a larger magnitude with lower MR and lower Fl. In contrast, economic weights for growth rate and FI derived from the economic model only change in magnitude and not in sign with different levels of these traits. The economic model always puts a negative economic weight on FI since it expresses profit due to a decrease in FI with constant growth rate and LMP. This holds the risk of continuous decrease in FI in pig breeding programs. In contrast, the use of growth models for genetic improvement allows direct selection for an optimum feed intake which maximizes feed efficiency in combination with maximum lean meat growth. It is concluded that recording procedures have to be adapted to collect the data necessary to implement growth models in practical pig breeding applications.

Adipose Tissue↗

PubMed1998

[Stereolithography models vs. milled 3D models. Production, indications, accuracy].

Anatomic, life-like, three-dimensional models have a definite place in cranio-maxillofacial surgery. Our experience with 541 computer tomographic (CT)-based three-dimensional (3D)-models for diagnostic purposes, preoperative planning and model operations in our department was gained using stereolithographic and milled models. The question of which production method is preferable is a matter of controversy in the literature. Both methods are based on CT and magnetic resonance imaging data, but the differences in production give rise to specific advantages and disadvantages. For comparison we scanned two measurement models, fabricated milled and stereolithographic models, and analyzed the differences concerning accuracy and shape of specific structures. The scan distance (feed) is the limiting factor for the accuracy for both methods. Milled models show the highest precision in the plane of CT scanning--the more oblique the measurements became to this plane, the greater the decrease in accuracy. Hollows and undercuts can only be produced by splitting the model. Stereolithographic models show higher deviations with randomly distributed errors. The mean deviation was 0.81 mm on stereolithography and 0.54 mm on milled models. The accuracy of both methods is sufficient for clinical use. In routine cases the milling method seems to be superior because of shorter production time and lower costs. In special cases, where hollows and fine structures play a major role, stereolithography is the method of choice.

Humans↗

PubMed2000

A comparison of video modeling with in vivo modeling for teaching children with autism.

The present study was designed to compare the effectiveness of video modeling with in vivo modeling for teaching developmental skills to children with autism. A multiple baseline design across five children and within child across the two modeling conditions (video and in vivo) and across tasks was used. Each child was presented two similar tasks from his or her curriculum; one task was used for the video condition, while the other was used for the in vivo condition. Video modeling consisted of each child watching a videotape of models performing the target behavior, whereas in vivo modeling consisted of the children observing live models perform the target behavior. After the observations, children were tested for acquisition and generalization of target behaviors. Results suggest that video modeling led to faster acquisition of tasks than in vivo modeling and was effective in promoting generalization. Results are discussed in terms of video modeling's motivating and attention maintaining qualities.

Autistic Disorder↗

PubMed1994

Comparison of the transport characteristics of D- and L-methionine in a human intestinal epithelial model (Caco-2) and in a perfused rat intestinal model.

Absorption mechanisms of L- and D-methionine (MET) in an in vitro cultured human intestinal epithelial cell model (Caco-2) and an in situ perfused rat intestinal model were investigated to determine if the kinetic characteristics of absorption are comparable in these two popular absorption models. The results indicate that the transport of L- and D-MET were concentration-dependent in both model systems, and displayed comparable Km values. The Km value for L-MET is 1.34 mM in the Caco-2 model and 3.6 mM in the perfused rat intestinal model, while the Km value for D-MET is 1.79 mM in the Caco-2 model and 2.87 mM in the perfused rat intestinal model. Although the Jmax values were not comparable because of significant methodology differences, the Jmax values for L-MET were always higher than that for D-MET. In addition, transport of L- and D-MET across the Caco-2 cell monolayers were also inhibited by 10 mM Phe and Lys while MeAIB, Pro and Glu were generally ineffective. Similar results were also observed with these inhibitors in the perfused rat intestinal model with the exception that a combination of Pro and Glu stimulated the uptake of L-MET. In conclusion, the transport characteristics of L- and D-MET are comparable in both model systems.

Animals↗

PubMed2005

Knockin of SV40 Tag oncogene in a mouse adenocarcinoma of the prostate model demonstrates advantageous features over the transgenic model.

Prostate cancer (CaP) is the most common cancer in adult men in North America. Since there is no naturally occurring prostate cancer in the mouse, preclinical studies stipulate for the establishment of a genetically manipulated mouse CaP model with features close to the human situation. In view of the limitations of transgenic technique-derived CaP models, herein we report the first application of knockin technology to establish a new mouse adenocarcinoma prostate model (PSP-KIMAP) by targeting of SV40 Tag to a prostate tissue-specific gene, PSP94 (prostate secretory protein of 94 amino acids). In order to demonstrate its novelty, we compared KIMAP to a PSP94 gene-directed transgenic mouse adenocarcinoma of the prostate (PSP-TGMAP) model. The CaP development of the PSP-KIMAP mice started almost immediately after puberty at 10 weeks of age from mouse prostatic intraepithelial neoplasia (mPIN) with microinvasion to well-differentiated CaP, and demonstrated a close-to-human kinetics of prolonged tumor growth and a predominance of well and moderately differentiated tumors. The invasive nature of KIMAP model was demonstrated by multitissue metastases (lymph node, lung and liver etc) and also by immunohistochemical study of multiple invasive prostate tumor markers. PSP-KIMAP model is responsive to androgen deprivation (castration). The knockin technology in our KIMAP model demonstrates highly predictive CaP development procedures and many advantageous features, which the traditional transgenic technique-derived CaP models could not reach for both basic and clinical studies. These features include the high stability of both phenotype and genotype, highly synchronous prostate cancer development, high and precise prostate tissue targeting and with no founder line variation. The differences between the two CaP models were attributed to the introduction of a single endogenous knockin mutation, resulting in a CaP model self-regulated and controlled by a prostate gene promoter/enhancer of PSP94.

Adenocarcinoma↗

PubMed1985

Mathematical models of central pattern generators in locomotion: II. Single limb models for locomotion in the cat.

Three mathematical models of central pattern generation for locomotion in the single limb of the cat are presented. In each model, the activities in populations of neurons controlling limb joint flexors and extensors are described by a system of nonlinear differential equations. Each solution of the system for a different set of parameters corresponds to a simulation of some gait of the cat. Model I is based on unit generators for each limb joint muscle group and assumes that flexors inhibit their paired extensors, but not vice-versa. Model IIa assumes that flexors and extensors are mutually inhibitory, but that only the flexors have inherent oscillatory capability. Model IIb assumes flexors and extensors are mutually inhibitory and that both flexors and extensors have oscillatory capability. The properties of each of these models are explored, compared and contrasted, and discussed in relation to the experimental literature. All three models are shown to be capable of generating patterns consistent with various stepping rates of the cat and to show appropriate muscle sequencing and flexor-extensor interactions. Further, all three models exhibit smooth initiation and termination of stepping. However, Model I seems to provide a more parsimonious account of producing changes in stepping rate and is preferred, therefore, over models IIa and IIb.

Journal Article↗

PubMed1997

Learning versus correct models: influence of model type on the learning of a free-weight squat lift.

It has been assumed that demonstrating the correct movement is the best way to impart task-relevant information. However, empirical verification with simple laboratory skills has shown that using a learning model (showing an individual in the process of acquiring the skill to be learned) may accelerate skill acquisition and increase retention more than using a correct model. The purpose of the present study was to compare the effectiveness of viewing correct versus learning models on the acquisition of a sport skill (free-weight squat lift). Forty female participants were assigned to four learning conditions: physical practice receiving feedback, learning model with model feedback, correct model with model feedback, and learning model without model feedback. Results indicated that viewing either a correct or learning model was equally effective in learning correct form in the squat lift.

Analysis of Variance↗

PubMed2004

Mental model construction in linear reasoning: evidence for the construction of initial annotated models.

According to the mental model theory, reasoners build an initial model representing the information given in the premises. In the context of relational reasoning, the question arises as to which kind of representation is used to cope with indeterminate or multimodel problems. The present article presents an array of possible answers arising from the initial construction of complete explicit models, partial explicit models, partial implicit models, a single "isomeric" model, or a single annotated model. Predictions generated from these views are tested in two experiments that vary the problem structure and the number of models consistent with the premises. Analyses of the premise processing times, answering times and accuracy show that the annotated model yields the best fit of the data. Implications of these findings for the mental model theory as developed for relational reasoning are discussed.

Humans↗

PubMed1999

A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG.

The spherical head model has been used in magnetoencephalography (MEG) as a simple forward model for calculating the external magnetic fields resulting from neural activity. For more realistic head shapes, the boundary element method (BEM) or similar numerical methods are used, but at greatly increased computational cost. We introduce a sensor-weighted overlapping-sphere (OS) head model for rapid calculation of more realistic head shapes. The volume currents associated with primary neural activity are used to fit spherical head models for each individual MEG sensor such that the head is more realistically modelled as a set of overlapping spheres, rather than a single sphere. To assist in the evaluation of this OS model with BEM and other head models, we also introduce a novel comparison technique that is based on a generalized eigenvalue decomposition and accounts for the presence of noise in the MEG data. With this technique we can examine the worst possible errors for thousands of dipole locations in a realistic brain volume. We test the traditional single-sphere model, three-shell and single-shell BEM, and the new OS model. The results show that the OS model has accuracy similar to the BEM but is orders of magnitude faster to compute.

Brain↗

PubMed2004

Ultra high molecular weight polyethylene (UHMWPE) model can provide results comparable to cadaveric models.

The in vitro biomechanical models using a cadaveric spine specimen have long been used in understanding normal and abnormal functions of spines as well as for strength and stability testing of the spine specimen or spinal construct. Little effort has been made to describe the similarities or differences between UHMWPE and cadaveric models. Eight cadaveric lumbar spines were harvested generating six FSU and three corpectomy models. Six UHMWPE blocks were fabricated to form FSU and corpectomy models. All were tested intact, with posterior instrumentation, and with anterior instrumentation consisting of Moss-Miami 4.0 mm stainless steel rods, uni-axial stainless steel screws and DePuy Harm's cages. All models were tested in axial compression. The cadaveric model and UHMPWE model yielded axial stiffness values of comparable magnitude with respect to instrumentation applied using the posterior approach (P>0.05). Under an FSU configuration, only in the case of anterior instrumentation without the addition of a Harm's cage did both the cadaveric and UHMPWE models provide comparable axial stiffness results (P>0.05). While in vitro cadaveric models are considered the gold standard for biomechanical testing of the spine, the data suggests that under specific approaches and surgical models UHMWPE can be used to infer mechanical performance of instrumentation in cadaveric material.

Biomimetic Materials↗

PubMed1995

Time-dependent pharmacodynamic models in cancer chemotherapy: population pharmacodynamic model for glutathione depletion following modulation by buthionine sulfoximine (BSO) in a Phase I trial of melphalan and BSO.

The development of time-dependent pharmacodynamic models in cancer chemotherapy has been extremely limited. A population approach was used to develop such a model to describe the effect of buthionine sulfoximine (BSO), via its active S-isomer (S-BSO), on glutathione (GSH) depletion in peripheral mononuclear cells. The Phase I trial utilized escalating doses of BSO, from 5 to 17 gm/m2, as a multiple infusion regimen. The population model consisted of a linear 2-compartment pharmacokinetic model coupled to an indirect response model. The indirect response model consisted of a GSH compartment with input and output rate processes that are modulated as a function of S-BSO and GSH concentrations. The model predicted the observed gradual depletion of GSH, a nadir at approximately 30 h after the last dose of BSO, and a return to baseline GSH levels. On the basis of an IC50 estimate of about 1.6 microM for inhibition of gamma-glutamylcysteine synthetase, the target enzyme of BSO, the population model predicted near identical GSH concentration time profiles over the dose range studied. Time-dependent pharmacodynamic models are seen as a powerful means to design dosing regimens and to provide a mathematical platform for mechanistic based models.

Adult↗

PubMed1996

Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

Multivariable regression models are powerful tools that are used frequently in studies of clinical outcomes. These models can use a mixture of categorical and continuous variables and can handle partially observed (censored) responses. However, uncritical application of modelling techniques can result in models that poorly fit the dataset at hand, or, even more likely, inaccurately predict outcomes on new subjects. One must know how to measure qualities of a model's fit in order to avoid poorly fitted or overfitted models. Measurement of predictive accuracy can be difficult for survival time data in the presence of censoring. We discuss an easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities. Both types of predictive accuracy should be unbiasedly validated using bootstrapping or cross-validation, before using predictions in a new data series. We discuss some of the hazards of poorly fitted and overfitted regression models and present one modelling strategy that avoids many of the problems discussed. The methods described are applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes. Methods are illustrated with a survival analysis in prostate cancer using Cox regression.

Clinical Trials as Topic↗