MINMOD: a computer program to calculate insulin sensitivity and pancreatic responsivity from the frequently sampled intravenous glucose tolerance test

Insulin sensitivity and pancreatic responsivity are the two main factors controlling glucose tolerance. We have proposed a method for measuring these two factors, using computer analysis of a frequently-sampled intravenous glucose tolerance test (FSIGT). This 'minimal modelling approach' fits two mathematical models with FSIGT glucose and insulin data: one of glucose disappearance and one of insulin kinetics. MINMOD is the computer program which identifies the model parameters for each individual. A nonlinear least squares estimation technique is used, employing a gradient-type of estimation algorithm, and the first derivatives (not known analytically) are computed according to the 'sensitivity approach'. The program yields the parameter estimates and the precision of their estimation. From the model parameters, it is possible to extract four indices: SG, the ability of glucose per se to enhance its own disappearance at basal insulin, SI, the tissue insulin sensitivity index, phi 1, first phase pancreatic responsivity, and phi 2, second phase pancreatic responsivity. These four characteristic parameters have been shown to represent an integrated metabolic portrait of a single individual.     

Application of the SAAM modeling program to minimal model analysis of intravenous glucose tolerance test data

The minimal model approach to analysis of intravenous glucose tolerance tests (IVGTT) yields estimates of parameters representing insulin sensitivity, glucose-mediated glucose disposal and pancreatic responsiveness. The precision of these estimates can deteriorate if the glucose and insulin data lack well-defined structure or freedom from data noise (random error). The precision of parameter estimates can be enhanced if data sets from two or more IVGTTs, obtained under different experimental conditions in the same subject, are analysed together in one data file. Following initial fitting using CONSAM, the conversational version of the modeling program SAAM, those parameters whose estimates remain at the same value under the different experimental conditions are constrained. This effectively reduces the number of adjustable parameters, and their estimates can then be fine-tuned with enhanced precision using the batch version of SAAM.     

TurboTree: a fast algorithm for minimal trees

A branch and bound algorithm is described for searching rapidly for minimal length trees from biological data. The algorithm adds characters one at a time, rather than adding taxa, as in previous branch and bound methods. The algorithm has been programmed and is available from the authors. A worked example is given with 33 characters and 15 taxa. About 8 x 10(12) binary trees are possible with 15 taxa but the branch and bound program finds the minimal tree in less than 5 min on an IBM PC.     

Model-based assessment of insulin sensitivity of glucose disposal and endogenous glucose production from double-tracer oral glucose tolerance test

A new mathematical model of short-term glucose regulation by insulin is proposed to exploit the oral glucose tolerance test (OGTT), which is commonly used for clinical diagnosis of glucose intolerance and diabetes. Contributions of endogenous and exogenous sources to measured plasma glucose concentrations have been separated by means of additional oral administration and constant intravenous infusion of glucose labeled with two different tracers. Twelve type 2 diabetic patients (7 males and 5 females) and 10 control subjects (5 males and 5 females) with normal glucose tolerance and matched body mass index (BMI) participated in this study. Blood samples for measurement of concentrations/activity of unlabeled and double-tracer glucose and insulin were collected every 15 min for 3 h following the oral glucose load. A minimal model combined with non-linear mixed-effects population parameter estimation has been devised to characterize group-average and between-patient variability of: (i) gastrointestinal glucose absorption; (ii) endogenous glucose production (EGP), and (iii) glucose disposal rate. Results indicate that insulin-independent glucose clearance does not vary significantly with gender or diabetic state and that the latter strongly affects, as expected, insulin-dependent clearance (insulin sensitivity). Inhibition of EGP, interpreted in terms of variations from basal of insulin concentrations, does not appear to be affected by diabetes but rather by BMI, i.e. by the degree of obesity. This study supports the utility of a minimal modelling approach, combined with population parameter estimation, to characterize glucose absorption, production and disposition during double-tracer OGTT experiments. The model provides a means for planning further experiments to validate the new hypothesis on the influence of individual factors, such as BMI and diabetes, on glucose appearance and disappearance, and for designing new simplified clinical tests.     

Tolerance design of manipulator parameters using design of experiment approach

A robotic arm must manipulate objects with high accuracy and repeatability to perform precise tasks. There are many factors that cause variations in performance and they referred as noise factors. A probabilistic approach has been used to model the effects of noise factors and an experimental design technique has been adopted to select optimal tolerance of kinematic and dynamic parameters for minimal performance variations. The control and noise factor arrays are employed to identify statistically significant parameters and their interactions. The performance measures like signal to noise ratio and reliability have been utilized and results are validated by Monte Carlo simulations. The proposed design of experiment methodology requires minimal computations. The tolerance design methodology of manipulator is illustrated by 2-DOF revolute–revolute planar manipulator following cubic and quintic trajectory to perform a task. The statistical analysis of simulated performances is carried out using analysis of variance technique, which showed that statistically significant parameters are independent of trajectory. The individual parameter tolerance sensitivity has also been carried out.     

Monte Carlo analysis of a new model-based method for insulin sensitivity testing

Insulin resistance (IR), or low insulin sensitivity, is a major risk factor in the pathogenesis of type 2 diabetes and cardiovascular disease. A simple, high resolution assessment of IR would enable earlier diagnosis and more accurate monitoring of intervention effects. Current assessments are either too intensive for clinical settings (Euglycaemic Clamp, IVGTT) or have too low resolution (HOMA, fasting glucose/insulin). Based on high correlation of a model-based measure of insulin sensitivity and the clamp, a novel, clinically useful test protocol is designed with: physiological dosing, short duration (<1 h), simple protocol, low cost and high repeatability. Accuracy and repeatability are assessed with Monte Carlo analysis on a virtual clamp cohort (N=146). Insulin sensitivity as measured by this test has a coefficient of variation (CV) of CV(SI)=4.5% (90% CI: 3.8-5.7%), slightly higher than clamp ISI (CV(ISI)=3.3% (90% CI: 3.0-4.0%)) and significantly lower than HOMA (CV(HOMA)=10.0% (90% CI: 9.1-10.8%)). Correlation to glucose and unit normalised ISI is r=0.98 (90% CI: 0.97-0.98). The proposed protocol is simple, cost effective, repeatable and highly correlated to the gold-standard clamp.     

A circulatory model for the estimation of insulin sensitivity

Insulin sensitivity is commonly assessed by analysing intravenous glucose tests with a simple model, called the minimal model. However, the physiological meaning of the insulin sensitivity indices estimated using this model is not transparent. To overcome this problem, a circulatory model was developed to analyse intravenous glucose tests in which a tracer was injected together with glucose. Physiological parameters, such as glucose volume, clearance and production, were estimated. Insulin sensitivity was defined in terms of glucose clearance. The parameter values estimated in 5 normal subjects were in good agreement with the values reported in previous independent studies.     

A protein secondary structure prediction scheme for the IBM PC and compatibles

A prediction scheme has been developed for the IBM PC and compatibles containing computer programs which make use of the protein secondary structure prediction algorithms of Nagano (1977a,b), Garnier et al. (1978), Burgess et al. (1974), Chou and Fasman (1974a,b), Lim (1974) and Dufton and Hider (1977). The results of the individual prediction methods are combined as described by Hamodrakas et al. (1982) by the program PLOTPROG to produce joint prediction histograms for a protein, for three types of secondary structure: alpha-helix, beta-sheet and beta-turns. The scheme requires uniform input for the prediction programs, produced by any word processor, spreadsheet, editor or database program and produces uniform output on a printer, a graphics screen or a file. The scheme is independent of any additional software and runs under DOS 2.0 or later releases.     

A didactic computer simulation of the environmental impact of a pollution discharge

Algorithms for simulating the response of a benthic animal community and several abiotic environmental variables to organic pollution are described. An IBM PC compatible computer program incorporating these methods has been written. The program simulates the abundance response of 23 species, the redox potential depth profile and several other sediment variables at any distance from a point source of pollution. The program has been designed as a teaching tool and examples of its use to study pollution biology and biometrics are given.     

Computer model of cardiac repolarization processes and of the recovery sequence

A computer model simulating both excitation and recovery processes within a block of heart muscle tissue has been developed and implemented on different IBM PC AT compatible computers. The model incorporates blocks of tissue consisting of several thousand elements and introduces phenomena which are completely or partly omitted in other existing cardiac electrophysiology models. These phenomena include the electric anisotropy of the tissue, different durations of repolarization in different layers of tissue, and the different shapes of action potential which correspond to cells excited when not fully recovered. Implementation of the model on small personal computers requires the use of a special data structure management and an effective algorithmic background. The program of the model is written in PASCAL and uses dynamically allocated data structures and the asynchronous simulation technique of event planing. These techniques are described in detail. The model has been used in various experiments. Results of simulation studies are presented in the form of modeled three-lead electrocardiographic records. The experimental series which are described include basic patterns of regular activation sequences, modeling of premature beats, simulation of effects due to fast pacing, models of ischemia and infarction, simulation of reentry mechanisms with a special reference to the initiation of ventricular fibrillation, and models of late potentials. The future development of more realistic models of the cardiac recovery process is also discussed.     

ISEC: a program to calculate insulin secretion

ISEC (Insulin SECretion) is a computer program which calculates pre-hepatic insulin secretion from plasma C-peptide measurements. The program uses a regression (population) model to derive parameters of C-peptide kinetics from subject's gender, type (normal, obese, non-insulin dependent diabetes mellitus), age, weight, and height. Insulin secretion is calculated as a piece-wise constant (step) function with flexible step length allowing for a fine resolution of the secretion profile between measurements. A constrained regularisation method of deconvolution is employed to carry out the calculations. The calculated profile satisfies three properties: (i) it fits the measurement within the given level of the measurement error, (ii) it is non-negative, and (iii) it has a minimum value of a regularisation criterion (norm of second differences) which quantifies the degree of deviation of the secretion profile from a straight line. Both theoretical aspects and specific features related to ISEC are considered. To exemplify the use of ISEC, pre-hepatic insulin secretion is calculated during meal tolerance test, frequently sampled intravenous glucose tolerance test, hyperinsulinaemic euglycaemic glucose clamp, and basal conditions with frequent sampling.     

A system for compartmental modelling and simulation

The paper describes a software package for modelling and simulating compartmental systems based upon a generalisation of the equations of compartmental systems. The aim is a versatile package which can be used for rapid model development. Its use is first illustrated in a number of simple classical examples. The power of the software--and more generally the methodology--is demonstrated by showing its application in developing a model-based system for insulin planning for diabetic patients. The software has been written in Pascal and runs on IBM PC and compatible computers.     

A pharmacodynamic approach to optimizing insulin therapy

We have developed a program for simulation and optimization of insulin therapy in patients with insulin-dependent diabetes. The program, denoted GLUCOJECT, is based on a physiologic model of minimal complexity, which describes the pharmacokinetics of absorption and clearance of subcutaneous insulin and the dynamics of glucose utilization as dependent on both prevailing glucose and insulin levels. With self-monitored glucose values and insulin doses collected with one of several commercially available memory meters, GLUCOJECT reconstructs an average or 'typical' daily plasma glucose and insulin profile and displays them in a graph. The program then calculates the expected rate of glucose utilization, which permits calculation of the rate of glucose entry into plasma from both endogenous (hepatic) and exogenous (dietary) sources. In turn, this allows one to calculate an 'ideal' plasma insulin profile required to maintain a relatively constant 'ideal' plasma glucose level. GLUCOJECT can evaluate several different insulin regimens involving various combinations of short-, intermediate- and long-acting insulins, and select the one(s) most closely approximating the ideal or optimal insulin profile, using a least-squares criterion. For any optimized insulin regimen, GLUCOJECT calculates and displays the predicted time course of plasma glucose. These features make the program attractive as an educational tool for both patients and health care professionals and could potentially assist in the management of patients with insulin-dependent diabetes.     

A microcomputer program for individualizing factor VIII dosage in hemophilia patients undergoing major surgery

A pharmacokinetic program that allows individualization of Factor VIII dosage regiments in hemophilia patients undergoing major surgery is described. The program, which is designed for the IBM PC microcomputer and compatible machines, is based upon the one-compartment open model with instantaneous input. In the framework of such a pharmacokinetic model, it is assumed that the elimination of Factor VIII is faster during the early post-operative period and that it decreases progressively over the following days. Since Factor VIII half-life is dependent on the time elapsed since the operation (short half-life values during the early post-operative period, longer half-life values thereafter), the pharmacokinetic model is a nonlinear one. A first-order 'variation' rate constant is used to describe the prolongation of Factor VIII half-life from the initial value immediately after surgery to the final value achieved several days later. Individualized estimation of the patient's kinetic parameters (initial half-life, 'variation' rate constant and volume of distribution) is performed through the Bayesian method. Therefore, for such estimation the program exploits the Factor VIII plasma levels measured in the individual patient as well as the population pharmacokinetic data of Factor VIII. After estimating the individual's Bayesian parameters, the program predicts the dosage regimen that will elicit the desired time-course of Factor VIII plasma levels. If requested, the program is able to calculate the least-squares estimates for the parameters of the pharmacokinetic model and dosage prediction can also be made on the basis of such estimates. The least-squares estimates are useful for calculating population pharmacokinetic parameters according to the Standard Two-Stage method. Some examples of clinical use of the program are presented.     

智能型多方案综合评价支持系统的设计与实现

本文提出了一个智能型多方案综合评价支持系统的基本结构框架；描述了多目标多层次模糊综合评价的数学模型；讨论了ＩＡＣＥＳＳ的主要实现方法与技术。整个ＩＡＣＥＳＳ已在ＩＢＭ ＰＣ机上实现。     

Graphical program to display a testbed block diagram with real-time data on an IBM personal computer

A graphical program called TESTBED was written in Pascal in summer 1985 for NASA Lewis Research Center, Cleveland, Ohio. TESTBED displays on an IBM Personal Computer/XT a block diagram of the DC testbed for the power management and distribution system for the space station. When the testbed, which will contain photovoltaic arrays, batteries, and loads, is deployed in the field, it will be permanently connected to the IBM PC/XT via direct memory access. Sensors attached to the testbed in the field will continually collect and updata data in real time. The program will superimpose the real-time data on the block diagram of the testbed displayed on the screen of the IBM PC/XT. The program uses procedures contained in Metawindow, a software package of graphics utilities written by Metagraphics Corp., Mountain View, California.     

FAST (Flexible Analysis by Software Tool) and CHAMP (CHemico-physical AMinoacidic Parameter data bank): a new tool to investigate protein structure

A flexible package designed to study protein structure is described. The package is devoted to the analysis of protein sequences by drawing structural profiles of specific structure-related amino acid parameters. An Aminoacidic Parameters Data Bank (CHAMP) containing 32 different series of physico-chemical parameters of amino acids is available. Sequences can be loaded from any ASCII format data bank or from keyboard. The program possesses a routine which enables easy updating of the protein data bank and CHAMP Data Bank. FAST reads statistical correlations between two plots in order to identify structural similarities. Plots can be printed, saved or used for correlation, comparison or graph overlap by using common spreadsheets (e.g. Lotus 123). Plots can be smoothed by a running mean or a running median. The program also has a special feature--a global flexibility analysis of proteins. The package runs on IBM or compatibles and requires DOS 3.0 or later.     

Programs for evaluating and characterising bacterial taxonomic data

Three programs are described for evaluating and characterising data collected during numerical taxonomic studies of bacteria. The program VARIANCE compares replicate cultures and evaluates the reproducibility of each character. Also it identifies those characters that should be excluded from subsequent taxonomic analysis because of their poor reproducibility. GPROPS summarises the properties of clusters of strains that have been defined from a cluster analysis, it can produce a probabilistic identification matrix and compares each strain within a cluster with the Hypothetical Mean Organism (HMO) of that cluster. OVCLUST is an implementation of the program described by Sneath (1979) which calculates overlap statistics between major clusters. These programs are designed to complement the CLUSTAN package (Wishart, 1982) which is often used for cluster analysis of bacterial taxonomic data. The programs were written in FORTRAN 77 and implemented on an IBM PC using MS-DOS.     

Genetic algorithm based NARX model identification for evaluation of insulin sensitivity

The evaluation of insulin sensitivity plays an important role in the clinical investigation of glucose related diseases. Mathematical models based on non-invasive tests provide an estimate of insulin sensitivity by solving a nonlinear optimization problem. However traditional optimization methods suffer from convergence problem and the final estimate is heavily dependent on the initial parameterization. This paper proposes a model based on the hybrid approach of nonlinear autoregressive with exogenous input (NARX) modeling and genetic algorithm (GA) for deriving an index of insulin sensitivity. The model does not need an initial parameterization and the convergence is always guaranteed. The index derived from the proposed model is found to correlate well with the widely used minimal model based insulin sensitivity, with a significantly higher accuracy of fit.