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At least 55 records · Page 3Linked to original sources
PubMedDate not supplied

Identification of parameters for the middle ear model.

This paper presents a method of parameter identification for a finite-element model of the human middle ear. The parameter values are estimated using a characterization of the difference in natural frequencies and mode shapes of the tympanic membrane between the model and the specimens. Experimental results were obtained from temporal bone specimens under sound excitation (300-3,000 Hz). The first 3 modes of the tympanic membrane could be observed with a laser scanning vibrometer and were used to estimate the stiffness parameters for the orthotropic finite-element model of the eardrum. A further point of discussion is the parameter sensitivity and its implication for the identification process.

Acoustic Stimulation↗
PubMed2001

An illuminative example of nonlinear identification.

The parameter identification of a nonlinear system is often difficult to handle. Through the study of a particular nonlinear system with a limit cycle, corresponding to a biological system with an endogenous rhythm, we show that it is useful to take into account additional algebraic or geometric features of the system to achieve parameter identification.

Homeostasis↗
PubMed2006

Integral-based identification of patient specific parameters for a minimal cardiac model.

A minimal cardiac model has been developed which accurately captures the essential dynamics of the cardiovascular system (CVS). However, identifying patient specific parameters with the limited measurements often available, hinders the clinical application of the model for diagnosis and therapy selection. This paper presents an integral-based parameter identification method for fast, accurate identification of patient specific parameters using limited measured data. The integral method turns a previously non-linear and non-convex optimization problem into a linear and convex identification problem. The model includes ventricular interaction and physiological valve dynamics. A healthy human state and four disease states, valvular stenosis, pulmonary embolism, cardiogenic shock and septic shock are used to test the method. Parameters for the healthy and disease states are accurately identified using only discretized flows into and out of the two cardiac chambers, the minimum and maximum volumes of the left and right ventricles, and the pressure waveforms through the aorta and pulmonary artery. These input values can be readily obtained non-invasively using echo-cardiography and ultra-sound, or invasively via catheters that are often used in Intensive Care. The method enables rapid identification of model parameters to match a particular patient condition in clinical real time (3-5 min) to within a mean value of 4-10% in the presence of 5-15% uniformly distributed measurement noise. The specific changes made to simulate each disease state are correctly identified in each case to within 10% without false identification of any other patient specific parameters. Clinically, the resulting patient specific model can then be used to assist medical staff in understanding, diagnosis and treatment selection.

Algorithms↗
PubMedDate not supplied

A combinatorial optimization scheme for parameter structure identification in ground water modeling.

This research develops a methodology for parameter structure identification in ground water modeling. For a given set of observations, parameter structure identification seeks to identify the parameter dimension, its corresponding parameter pattern and values. Voronoi tessellation is used to parameterize the unknown distributed parameter into a number of zones. Accordingly, the parameter structure identification problem is equivalent to finding the number and locations as well as the values of the basis points associated with the Voronoi tessellation. A genetic algorithm (GA) is allied with a grid search method and a quasi-Newton algorithm to solve the inverse problem. GA is first used to search for the near-optimal parameter pattern and values. Next, a grid search method and a quasi-Newton algorithm iteratively improve the GA's estimates. Sensitivities of state variables to parameters are calculated by the sensitivity-equation method. MODFLOW and MT3DMS are employed to solve the coupled flow and transport model as well as the derived sensitivity equations. The optimal parameter dimension is determined using criteria based on parameter uncertainty and parameter structure discrimination. Numerical experiments are conducted to demonstrate the proposed methodology, in which the true transmissivity field is characterized by either a continuous distribution or a distribution that can be characterized by zones. We conclude that the optimized transmissivity zones capture the trend and distribution of the true transmissivity field.

Algorithms↗
PubMed1998

The humoral immune response to Haemophilus influenzae type b: a mathematical model based on T-zone and germinal center B-cell dynamics.

Through careful mapping of the physiology of the T-zone and GC B-blast dynamics to a mathematical representation of the cell processes including proliferation, migration, differentiation, and cell death, a mathematical model is constructed to capture the dominant nominal primary, late follicular, and secondary humoral response to Haemophilus influenzae Type b. This model explicitly incorporates the dynamics of memory B-cells, T-zone and GC B-dynamics, IgM and IgG antibodies, avidity maturation, and IC presentation by FDCs into a coherent framework. This paper describes the relevant immunology, the pertinent physiological assumptions, the developed model, and the parameter identification procedure. The model parameters were found using a parameter identification procedure that capitalizes on the timing and interactions of certain dominant physiological attributes. Simulation results and validation tests indicate that the model reflects not only a nominal primary and secondary humoral immune response but also the tertiary and T-independent responses. The model shows robustness to variations in infection dosage, bacterial growth rate (virulence of the strain), and onset-timing of the secondary response. The utility of this model in studying the humoral immune response is demonstrated through suggested physiological assumptions, mechanisms, and rates to be eventually clinically evaluated as well as insights into vaccination design. The model and parameter identification techniques are easily adapted to other diseases which primarily evoke a humoral immune response.

Antibodies, Bacterial↗
PubMed1993

Pharmacokinetic model identification and parameter estimation as an ill-posed problem.

For model identification and parameter estimation in the framework of linear pharmacokinetics it is most often assumed that the disposition function is a finite sum of exponential functions with time constants lambda i and associated coefficients Ci. Least-square fitting procedures are used to estimate the coefficients Ci and the corresponding discrete locations lambda i on the lambda-axes. This work presents an alternative approach. It does not assume that the non-zero coefficients are located at sharply defined values of lambda, but that they are represented by a continuous function h(lambda), the spectrum of the disposition function. This turns the non-linear least-square problem into a linear problem, which is known to be as so-called "ill-posed". Regularization methods have been developed in recent years as suitable tools for the treatment of such ill-posed problems. Application of Tikhonov regularization to the case of the bolus kinetics of propofol in 8 volunteers is demonstrated. In 7 of the 8 cases a spectrum with 4 to 5 peaks was found, and in one volunteer there were only 2 peaks. All spectra with more than 2 peaks showed negative values of h(lambda). The method used is described and the results are compared with those of conventional compartment analysis.

Humans↗
PubMedDate not supplied

Generalized sensitivity functions in physiological system identification.

Parameters of physiological models are commonly associated in an input-output experiment with a specific pattern of the system response. This association is often made on an intuitive basis by traditional sensitivity analysis, i.e., by inspecting the variations of model output trajectories with respect to parameter variations. However, this approach provides limited information since, for instance, it ignores correlation among parameters. The aim of this study is to propose a new set of sensitivity functions, called the generalized sensitivity functions (GSF), for the analysis of input-output identification experiments. GSF are based on information theoretical criteria and provide, as compared to traditional sensitivity analysis, a more accurate picture on the information content of measured outputs on individual model parameters at different times. Case studies are presented on an input-output model and on two structural circulatory and respiratory models. GSF allow the definition of relevant time intervals for the identification of specific parameters and improve the understanding of the role played by specific model parameters in describing experimental data.

Animals↗
PubMed2006

Predicting tumor outcome following cancer vaccination by monitoring quantitative and qualitative CD8+ T cell parameters.

Identification of reliable surrogate predictors for evaluation of cancer vaccine efficacy is a critical issue in immunotherapy. We analyzed quantitative and qualitative CD8+ T cell parameters in a large pool of BALB/c mice that were DNA-vaccinated against P1A self tumor-specific Ag. After immunization, mice were splenectomized and kept alive for a subsequent tumor challenge to correlate results of immune monitoring assays with tumor regression or progression in each individual animal, and to assess the prognostic value of the assays. The parameters tested were 1) percentage of in vivo vaccine-induced tumor-specific CD8+ T cells; 2) results of ELISPOT tests from fresh splenocytes; 3) percentage of tumor-specific CD8+ T cells in culture after in vitro restimulation; 4) in vitro increase of tumor-specific CD8+ T cell population expressed as fold of expansion; and 5) antitumor lytic activity of restimulated cultures. Except for the ELISPOT assay, each parameter tested was shown by univariate statistical analysis to correlate with tumor regression. However, multivariate analysis revealed that only in vitro percentage of Ag-specific CD8+ T cells was an independent prognostic factor that predicted tumor outcome. These findings should be considered in the design of new immune monitoring systems used in cancer immunotherapy studies.

Animals↗
PubMedDate not supplied

Investigations of reaction kinetics for immobilized enzymes--identification of parameters in the presence of diffusion limitation.

A method is proposed for identification of kinetic parameters when diffusion of substrates is limiting in reactions catalyzed by immobilized enzymes. This method overcomes conventional sequential procedures, which assume immobilization does not affect the conformation of the enzyme and, thus, consider intrinsic and inherent kinetics to be the same. The coupled equations describing intraparticle mass transport are solved simultaneously using numerical methods and are used for direct estimation of kinetic parameters by fitting modeling results to time-course measurements in a stirred tank reactor. While most traditional procedures were based on Michaelis-Menten kinetics, the method presented here is applicable to more complex kinetic mechanisms involving multiple state variables, such as ping-pong bi-bi. The method is applied to the kinetic resolution of (R/S)-1-methoxy-2-propanol with vinyl acetate catalyzed by Candida antarctica lipase B. A mathematical model is developed consisting of irreversible ping-pong bi-bi kinetics, including competitive inhibition of both enantiomers. The kinetic model, which fits to experimental data over a wide range of both substrates (5-95%) and temperatures (5-56 degrees C), is used for simulations to study typical behavior of immobilized enzyme systems.

Biotechnology↗
PubMed2026

Host-aware Identification of Intrinsic Gene Expression Biopart Parameters using Combinatorial Libraries.

Model-based design in synthetic biology is limited because bioparts are typically characterised by relative metrics that vary across genetic and physiological contexts. To address this, we introduce a host-aware framework for quantitatively characterising bioparts in combinatorial libraries of plasmid-based constitutive expression constructs. The approach integrates a digital twin of Escherichia coli, conditioned on measured growth rate, with model-in-the-loop parameter identification to separate biopart-associated properties from host-dependent effects. Using structured combinatorial libraries, we identify mechanistically interpretable, transferable parameters for plasmid origins, promoters and ribosome binding sites. In particular, we define an intrinsic translation initiation capacity that captures the dominant RBS-associated contribution to translation while context-dependent expression emerges from host physiology and local sequence context. The resulting parameterisation accurately predicts protein synthesis across physiological conditions, supports incremental library expansion, and reveals localised failures of modularity, providing a scalable foundation for predictive host-aware design in synthetic biology.

Escherichia coli↗
PubMed2000

Intra- and interinstrument reproducibility of migration parameters in capillary electrophoresis for substance identification in systematic toxicological analysis.

The intra- and interinstrument reproducibilities of four capillary electrophoresis instruments were studied for identification purposes in systematic toxicological analysis (STA). A test set of 20 acidic test compounds and 5 reference compounds were analyzed for five days on each instrument using capillary zone electrophoresis (CZE) and micellar electrokinetic chromatography (MEKC). The buffers consisted of 90 mM borate set at pH 8.4 (CZE) and 20 mM phosphate and 50 mM sodium dodecyl sulfate set at pH 7.5 (MEKC). All analyses were carried out using fused silica capillaries at an electric field strength of 52.6 kV/m. The use of a reproducible identification parameter is very important in STA. To deal with the poor reproducibility of the migration time, we recently introduced the corrected effective mobility. In this study, we investigated the intra- and interinstrument reproducibility of the migration time, the effective mobility, and the corrected effective mobility. Large differences in intra-instrument reproducibility were found when the migration time was used. The calculation of the effective mobility and the corrected effective mobility diminished these differences and enhanced the interinstrument reproducibility roughly by a factor 3. For (corrected) effective mobilities, intrainstrument reproducibilities were between 0.8-2.6% and interinstrument reproducibilities were between 3.2-3.9%.

Chromatography, Micellar Electrokinetic Capillary↗
PubMed1980

Identification and parameter estimation of the mechanical ventilatory system.

Oesophageal pressure and mouth volume were measured by oesophageal balloon and pneumotachography, respectively, in 10 men (both normal and diseases) under different experimental conditions, i.e. spontaneous ventilation, quasi-static manoeuvres and respiration at high frequencies. The recorded data were then analyzed by an identification and parameter estimation computer programme, to determine a mathematical model for the process. Contrary to other recently published papers dealing with frequency analysis, we studied a time-dependent model, represented by a linear time-invariant differential equation. The results were quite satisfactory since a relatively second-order model seems to be adequate for describing the process. Differences in the parameter values between normal and diseased subjects were characterized by increases in the patients' lung viscous component. In conclusion, our identification test results in the mechanical ventilatory system seem to indicate that a simple second-order mathematical model is consistent with the experimental data.

Adult↗