Epinephrine effects on insulin-glucose dynamics: the labeled IVGTT two-compartment minimal model approach

The hyperglycemic effects of epinephrine (Epi) are established; however, the modulation of Epi-stimulated endogenous glucose production (EGP) by glucose and insulin in vivo in humans is less clear. Our aim was to determine the effect of exogenously increased plasma Epi concentrations on insulin and glucose dynamics. In six normal control subjects, we used the labeled intravenous glucose tolerance test (IVGTT) interpreted with the two-compartment minimal model, which provides not only glucose effectiveness (S(G)(2*)), insulin sensitivity (S(I)(2*)), and plasma clearance rate (PCR) at basal state, but also the time course of EGP. Subjects were randomly studied during either saline or Epi infusion (1.5 microg/min). Exogenous Epi infusion increased plasma Epi concentration to a mean value of 2,034 +/- 138 pmol/l. During the stable-label IVGTT, plasma glucose, tracer glucose, and insulin concentrations were significantly higher in the Epi study. The hormone caused a significant (P < 0.05) reduction in PCR in the Epi state when compared with the basal state. The administration of Epi has a striking effect on EGP profiles: the nadir of the EGP profiles occurs at 21 +/- 7 min in the basal state and at 55 +/- 13 min in the Epi state (P < 0.05). In conclusion, we have shown by use of a two-compartment minimal model of glucose kinetics that elevated plasma Epi concentrations have profound effects at both hepatic and tissue levels. In particular, at the liver site, this hormone deeply affects, in a time-dependent fashion, the inhibitory effect of insulin on glucose release. Our findings may explain how even a normal subject may have the propensity to develop glucose intolerance under the influence of small increments of Epi during physiological stress.     

The iterative two-stage population approach to IVGTT minimal modeling: improved precision with reduced sampling. Intravenous glucose tolerance test

The minimal model method is widely used to estimate glucose effectiveness (S(G)) and insulin sensitivity (S(I)) from intravenous glucose tolerance test (IVGTT) data. In the standard protocol (sIVGTT, 0.33 g/kg glucose bolus given at time 0), which allows the simultaneous assessment of beta-cell function, the precision of the individualized estimates often degrades and particularly so in the presence of reduced sampling schedules. Here, we investigated the use of a population approach, the iterative two-stage (ITS) approach, to analyze 16 sIVGTTs in healthy subjects and to obtain refined estimates of S(G) and S(I) in the population and in the individual subjects. The ITS is based on calculation of the population mean and standard deviation of the parameters at each iteration and then use of them as prior information for the individual analyses. Theoretically, the use of a prior in the ITS should improve the precision of the individual estimates. The customary approach (standard two stage, STS), where modeling is performed separately for each individual subject, does not take the population knowledge into account. We used both frequent (FSS, 30 samples) and (quasi-optimally) reduced (RSS, 14 samples) sampling schedules. For the FSS, STS gave estimates (mean +/- SD) for S(G) = 2.66 +/- 1.09 x 10(-2). min(-1) and S(I) = 6.46 +/- 6.99 10(-4). min(-1). microU(-1). ml, with an average precision of 51 (range 5-176) and 33% (3-91), respectively. RSS radically worsened the precision of both S(G) and S(I). However, RSS and ITS gave S(G) = 2.59 +/- 0.73 and S(I) = 6.06 +/- 7.28, with an average precision of 23 (12-42) and 27% (), respectively. In conclusion, population minimal modeling of sIVGTT data improves the precision of individual estimates of glucose effectiveness and insulin sensitivity, as the theory predicts, and, even with reduced sampling, the improvement is substantial.     

The range of time delay and the global stability of the equilibrium for an IVGTT model

Diabetes mellitus has become a prevalent disease in the world. Diagnostic protocol for the onset of diabetes mellitus is the initial step in the treatments. The intravenous glucose tolerance test (IVGTT) has been considered as the most accurate method to determine the insulin sensitivity and glucose effectiveness. It is well known that there exists a time delay in insulin secretion stimulated by the elevated glucose concentration level. However, the range of the length of the delay in the existing IVGTT models are not fully discussed and thus in many cases the time delay may be assigned to a value out of its reasonable range. In addition, several attempts had been made to determine when the unique equilibrium point is globally asymptotically stable. However, all these conditions are delay-independent. In this paper, we discuss the range of the time delay and provide easy-to-check delay-dependent conditions for the global asymptotic stability of the equilibrium point for a recent IVGTT model through Liapunov function approach. Estimates of the upper bound of the delay for global stability are given in corollaries. In addition, the numerical simulation in this paper is fully incorporated with functional initial conditions, which is natural and more appropriate in delay differential equation systems.     

The rate enhancement produced by the ribosome: an improved model

As a model for mechanistic comparison with peptidyl transfer within the ribosome, the reaction of aqueous glycinamide with N-formylphenylalanine trifluoroethyl ester (fPhe-TFE) represents an improvement over earlier model reactions involving Tris. The acidity of trifluoroethanol (pKa 12.4) resembles that of tRNA (12.98) more closely than do the acidities of model reactants described earlier, and the reactivity of the simple nucleophile glycinamide is free of potential complications that arise from alternative reaction pathways available to Tris. At 25 degrees C, the uncatalyzed reaction of glycinamide with fPhe-TFE proceeds with a second-order rate constant of 3 x 10(-5) M-1 s-1; DeltaH(++) = +7.8 kcal/mol; TDeltaS(++)= -15.7 kcal/mol. The ribosomal reaction of puromycin with fMet-tRNA proceeds 3 x 107-fold more rapidly, with a second-order rate constant (kcat/Km) of 1 x 10(3) M-1 s-1; DeltaH(++) = +16.0 kcal/mol; TDeltaS(++)= +2.0 kcal/mol. That rate enhancement, an order of magnitude larger than estimated earlier, is fully explained by the more favorable entropy of activation of the ribosomal reaction. Experiments involving ethylene glycol esters suggest that neighboring -OH group effects are negligible in the presence of solvent water, which itself acts as a general base catalyst. In the desolvated interior of the ribosome, the vicinal 2'-OH group of aminoacyl-tRNA probably replaces water as a general base catalyst. But the catalytic effect of the ribosome itself is overwhelmingly entropic in origin, suggesting that the ribosome achieves its effect by physical desolvation and/or juxtaposition of the reactants in a manner conducive to peptidyl transfer.     

Impact of protein binding on receptor occupancy: A two-compartment model

In this paper we analyse the impact of protein-, lipid- and receptor-binding on receptor occupancy in a two-compartment system, with proteins in both compartments and lipids and receptors in the peripheral compartment only. We do this for two manners of drug administration: a bolus administration and a constant rate infusion, both into the central compartment. We derive explicit approximations for the time-curves of the different compounds valid for a wide range of realistic values of rate constants and initial concentrations of proteins, lipids, receptors and the drug. These approximations are used to obtain both qualitative and quantitative insight into such critical properties as the distribution of the drug over the two compartments, the maximum receptor occupancy and the area under the drug-receptor complex curve. In particular we focus on assessing the impact of the dissociation constants, K_P, K_L and K_R of the drug with, respectively, the proteins, the lipids and the receptors, the permeability and the surface area of the membrane between compartments, and the rate the drug is eliminated from the system.     

S(G), S(I), and EGP of exercise-trained middle-aged men estimated by a two-compartment labeled minimal model

To examine the effects of physical training on glucose effectiveness (S(G)), insulin sensitivity (S(I)), and endogenous glucose production (EGP) in middle-aged men, stable-labeled frequently sampled intravenous glucose tolerance tests (FSIGTT) were performed on 11 exercise-trained middle-aged men and 12 age-matched sedentary men. The time course of EGP during the FSIGTT was estimated by nonparametric stochastic deconvolution. Glucose uptake-specific indexes of glucose effectiveness (S(2*)(G) x 10(2): 0.81 +/- 0.08 vs. 0.60 +/- 0.05 dl. min(-1). kg(-1), P < 0.05) and insulin sensitivity [S(2*)(I) x 10(4): 24.59 +/- 2.98 vs. 11.89 +/- 2.36 dl. min(-1). (microU/ml)(-1). kg(-1), P < 0.01], which were analyzed using the two-compartment minimal model, were significantly greater in the trained group than in the sedentary group. Plasma clearance rate (PCR) of glucose was consistently greater in the trained men than in sedentary men throughout FSIGTT. Compared with sedentary controls, EGP of trained middle-aged men was higher before glucose load. The EGP of the two groups was similarly suppressed by approximately 70% within 10 min, followed by an additional suppression after insulin infusion. EGP returned to basal level at approximately 60 min in the trained men and at 100 min in the controls, followed by its overshoot, which was significantly greater in the trained men than in the controls. In addition, basal EGP was positively correlated with S(2*)(G) . The higher basal EGP and greater EGP overshoot in trained middle-aged men appear to compensate for the increased insulin-independent (S(2*)(G)) and -dependent (S(2*)(I)) glucose uptake to maintain glucose homeostasis.     

Development of an improved chemically defined minimal medium for Listeria monocytogenes.

A chemically defined minimal medium for Listeria monocytogenes has been developed by modification of Welshimer's medium. The growth factors required by L. monocytogenes Scott A are leucine, isoleucine, arginine, methionine, valine, cysteine (each at 100 mg/liter), riboflavin and biotin (each at 0.5 micrograms/ml), thiamine (1.0 micrograms/ml), and thioctic acid (0.005 micrograms/ml). Growth was stimulated by 20 micrograms of Fe3+ per ml as ferric citrate. Glucose (1%) and glutamine (600 mg/liter) are required as primary sources of carbon and nitrogen. Glucose could not be replaced by various organic acids or amino acids. Of several sugars tested, fructose, mannose, cellobiose, trehalose, maltose (weak), glycerol (weak), and the amino sugars glucosamine, N-acetylglucosamine, and N-acetylmuramic acid supported growth in the absence of glucose. Evidence was found that chitin and cell walls of starter bacteria (Lactococcus lactis) supported survival of L. monocytogenes, which suggests that the pathogen may obtain carbon and energy sources during colonization of some foods, such as cheeses, by assimilating bacteria or molds that are present.     

The COG database: an updated version includes eukaryotes

Background

The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies.

Results

We describe here a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs) from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted) proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs) include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens), one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe), and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or ~54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of ~20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (~1% of the COGs). In part, this difference is probably due to the small number of included eukaryotic genomes, but it could also reflect the relative compactness of eukaryotes as a clade and the greater evolutionary stability of eukaryotic genomes.

Conclusion

The updated collection of orthologous protein sets for prokaryotes and eukaryotes is expected to be a useful platform for functional annotation of newly sequenced genomes, including those of complex eukaryotes, and genome-wide evolutionary studies.     

The minimal model of glucose disappearance: optimal input studies

The “minimal model” of glucose disappearance provides noninvasive estimates of important metabolic parameters, among them the effect of insulin on glucose uptake. We study here the design of optimal inputs for the identification of the model, i.e., for estimating its parameters with maximum precision. The scalar case is examined first and solved via Pontryagin's maximum principle for two input classes: equienergy and equidose. For the equidose class the vector case is then studied by simulation for clinically realizable glucose inputs in both the normal and the diabetic case. Finally, recent experimental developments proposed for the identification of the model, i.e., a glucose input involving a concomitant drug stimulus and a tracer labeled glucose input, are examined in the context of optimal input design.     

Toxoplasma gondii: an improved rat model of congenital infection

The objective of this study was to refine the rat model of congenital toxoplasmosis. In Fischer rats we found that visualization of spermatozoa in vaginal exudates and the detection of at least 6 g body weight increase between days 9 and 12 of pregnancy, allowed the diagnosis and timing of pregnancy with 60% specificity and 84% sensitivity. A dose of 10⁴Toxoplasma gondii bradyzoites or 10²T. gondii oocysts of the Prugniaud strain resulted in more than 50% of congenital infection of the rat litters. Transmission of T. gondii via lactation was not detected in rats inoculated with either bradyzoites or oocysts. Bioassays of 51 neonates born from mothers inoculated with bradyzoites (in tissue cysts) and 29 neonates from mothers inoculated with oocysts demonstrated that both liver and lungs can be used for the diagnosis of congenital transmission in this model.     

The development of an improved model trap for monitoring Ephestia cautella

Delta, Covered funnel and Uni-traps containing pheromone used for monitoring male Ephestia cautella (Walker) (Lepidoptera: Phycitidae) moths were compared in a wind tunnel in moving and still air. The shape and design of the traps and the form of pheromone plume emitted from them determined the moth's latency time, numbers orientating, alighting on the traps and captured. To improve trap design, the visual responses of the moths to rectangles of different colours and sizes and to brown and white stripes, showed that more moths were attracted to darker coloured 6×50 cm vertical rectangles on a white background and to 7.5 mm brown and white stripes. A cylindrical trap containing pheromone incorporating these features captured 90% and 80% of the moths released in the wind tunnel in moving and still air respectively, compared with 70% and 35% for the best commercial traps.     

On the time-dependent reversible stochastic compartmental model—I. The general two-compartment system

The distribution of the two-compartment, reversible system with time-dependent transitions is proposed and verified. Inasmuch as the required probabilities cannot, in general, be expressed in closed form, a method of approximating these probabilities is described. An example with specific inverse functions of time is presented.     

An advanced version of the dynamic receptor pattern generation model: The flux model

In the recently described simple model of dynamic receptor pattern generation we used a two-dimensional hexagonal area of a regular triangular network, formed by a statistically constant distribution of unit electrostatic charges in a dynamic equilibrium. A set of 16 transition rules was applied to all units simultaneously; the next state of each unit depended only on the previous state of its six nearest neighbours, and the transition of the total pattern into the new one occurred in a single jump. Hence we designated the initial simple model as jump model. In this paper we describe an advanced version of the model, in which simplified rules are applied to one unit after the other in a sequential order, from left to right, starting with the top row of units. In the advanced version the state of a unit depends not only on that of its six nearest neighbours, but also on the state of all units preceding in sequence the one actually considered. This results in flux-like transitions. We therefore designated the advanced version as the flux model. It is shown that the flux model represents a closer approximation of physical and biological realities than the original jump model.