Biomedical subjects

L Claret

Publications and source records attributed to L Claret.

9 recordsLinked to original sources

PubMed2001

Fractal volume of drug distribution: it scales proportionally to body mass.

PURPOSE: To develop the physiologically sound concept of fractal volume of drug distribution, vf, and evaluate its utility and applicability in interspecies pharmacokinetic scaling. METHODS: Estimates for vf of various drugs in different species were obtained from the relationship: vf = (v - Vpl)(Vap - Vpl)/V + Vpl where v is the total volume of the species (equivalent to its total mass assuming a uniform density Ig/mL), Vpl is the plasma volume of the species and Vap is the conventional volume of drug distribution. This equation was also used to calculate the fractal analogs of various volume terms of drug distribution (the volume of central compartment, Vc, the steady state volume of distribution, Vss, and the volume of distribution following pseudodistribution equilibrium, Vz). The calculated fractal volumes of drug distribution were correlated with body mass of different mammalian species and allometric exponents and coefficients were determined. RESULTS: The calculated values of vf for selected drugs in humans provided meaningful and physiologically sound estimates for the distribution of drugs in the human body. For all fractal volume terms utilized, the allometric exponents were found to be either one or close to unity. The estimates of the allometric coefficients were found to be in the interval (0,1). These decimal values correspond to a fixed fraction of the fractal volume term relative to body mass in each one of the species. CONCLUSIONS: Fractal volumes of drug distribution scale proportionally to mass. This confirms the theoretically expected relationship between volume and mass in mammalian species.

Animals↗

PubMed2001

A stochastic model describes the heterogeneous pharmacokinetics of cyclosporin.

The pharmacokinetics of cyclosporin (CsA) are unusual because of several heterogeneous features which include the presence of more than one conformer, considerable accumulation in erythrocytes and lipoproteins, extensive plasma protein binding, distribution into deep tissues, biliary secretion and hepatic clearance involving a large number of metabolites. In this study, a stochastic compartmental model was developed to describe the heterogeneous elimination kinetics of CsA. This new approach relies on a probabilistic transfer model with a gamma distributed probability intensity coefficient for drug elimination. For comparative purposes both the stochastic model and compartmental deterministic models were fitted to real post infusion data from patients receiving CsA as a 2-hr intravenous infusion. The criteria for selecting the best model showed that the stochastic model, although simpler than the compartmental deterministic models, is more flexible and gives a better fit to the kinetic data of CsA than the compartmental deterministic models. The stochastic model with a random rate intensity coefficient adequately describes the heterogeneous pharmacokinetics of CsA.

Cyclosporine↗

PubMed2001

Information tools for exploratory data analysis in population pharmacokinetics.

For a group of individuals, population pharmacokinetic studies describe the interindividual variability through a statistical distribution. These studies conducted during the drug development serve as a useful marker of the safety of the drug, provide information that might be decisive for future experiments and, in a clinical context, help establish guidelines for optimal use in each patient. As complementary tools to the existing statistical and graphical techniques for population pharmacokinetic data analysis, indexes derived from information theory were used to select the most appropriate modelfor the statistical distribution, to detect atypical individuals, and to screen influential covariates. The rationale for using these indexes is shown using simulated and real data.

Humans↗

PubMed2001

The Escherichia coli histone-like protein HU regulates rpoS translation.

Escherichia coli HU protein is a major component of the bacterial nucleoid. HU stabilizes higher order nucleoprotein complexes and belongs to a family of DNA architectural proteins. Here, we report that HU is required for efficient expression of the sigma S subunit of RNA polymerase. This rpoS-encoded alternative sigmaS factor induces a number of genes implicated in cell survival in stationary phase and in multiple stress resistance. By analysis of rpoS-lacZ fusions and by pulse-chase experiments, we show that the efficiency of rpoS translation is reduced in cells lacking HU, whereas neither rpoS transcription nor protein stability is affected by HU. Gel mobility shift assays show that HU is able to bind specifically an RNA fragment containing the translational initiation region of rpoS mRNA 1000-fold more strongly than double-stranded DNA. Together with the in vivo data, this finding strongly suggests that, by binding to rpoS mRNA, HU directly stimulates rpoS translation. We demonstrate here that HU, an abundant DNA-binding, histone-like protein, is able specifically to recognize an RNA molecule and therefore play a role in post-transcriptional regulation.

Bacterial Proteins↗

PubMed2000

Functions of the subunits in the FlhD(2)C(2) transcriptional master regulator of bacterial flagellum biogenesis and swarming.

In enterobacteria like Salmonella, biogenesis of cell surface flagella needed for motility is dependent upon the master operon flhDC at the apex of the flagellar gene hierarchy. The operon products FlhD and FlhC act together in a FlhD(2)C(2 )heterotetramer to induce flagellar gene transcription, while FlhD also represses cell septation. The flhDC operon is pivotal to differentiation into elongated hyperflagellated swarm cells that undergo multicellular migration, most strikingly in Proteus. We set out to establish the mechanism of action of the FlhD(2)C(2) multimer. In Proteus swarm cell extracts, all the FlhC was assembled into the FlhD(2)C(2 )transcription activator, but FlhD additionally formed approximately equimolar amounts of a FlhD(2) homodimer. Both FlhD and FlhC subunits homodimerised in vivo and in vitro, suggesting that self-interactions stabilise the FlhD(2)C(2 )complex. The FlhC and FlhD subunit proteins were separately expressed and purified, and the FlhD(2)C(2)heterotetramer was reconstituted in vitro. Purified FlhC bound specifically and cooperatively to the promoter region of the flhDC-regulated flhB flagellar gene in the absence of FlhD. Purified FlhD was unable to bind this target DNA, but binding by the FlhD(2)C(2)complex was approximately tenfold greater than the FlhC subunit alone, suggesting that FlhD potentiated the FlhC/DNA interaction. In support of this possibility, pre-incubation of FlhC with FlhD reduced the apparent dissociation constant, K(D), for the FlhC/DNA complex from 100 nM to 13 nM. Furthermore, in competition assays, FlhD substantially increased the specificity of DNA recognition by FlhC, and also stabilised the resultant labile protein/DNA complex, prolonging its half-life from around two minutes to more than 40 minutes. FlhD(2)C(2)is therefore an atypical prokaryotic transcription activator in which interaction of the FlhC subunit with DNA target sequences is enhanced by the coexpressed helper subunit FlhD.

Allosteric Site↗

PubMed2000

Rapid turnover of FlhD and FlhC, the flagellar regulon transcriptional activator proteins, during Proteus swarming.

The enterobacterial flhDC master operon activates expression of the flagellar biogenesis gene hierarchy and also represses cell division. During Proteus mirabilis differentiation into elongated hyperflagellated swarm cells, flhDC transcription is strongly but transiently increased. We show that concentration of the FlhD and FlhC proteins is also tightly controlled at the posttranslational level. This is achieved by protein degradation, which is most severe after differentiation when the half-life of both proteins is ca. 2 min. Degradation is energy dependent and putatively involves the Lon protease.

Bacterial Proteins↗

PubMed1997

Variation in HU composition during growth of Escherichia coli: the heterodimer is required for long term survival.

The histone-like dimeric HU protein of Escherichia coli is encoded by two closely related genes, hupA and hupB. We show here that expression from the single hupA promoter and from the three hupB promoters varies during growth phase. The weak hupB-P4 promoter is active immediately after dilution. Transcription of the hupA gene is activated early in logarithmic phase. A little later, at mid to late exponential phase, RNA originating at the hupB-P2 promoter is detected. The hupB-P3 promoter is activated last when the cells enter stationary phase. Although the hup mRNAs are unstable, the HU protein is very stable so that the variations in the mRNAs synthesis are reflected in the level of the two HU subunits and in the composition of HU dimers. Cells growing exponentially contain a mixture of homodimeric alpha 2 and heterodimeric alpha beta but no beta 2 is detected. In stationary cells, the predominant form is the heterodimer alpha beta. The presence of the heterodimeric form is required for optimal survival of E. coli after prolonged starvation. The three forms of HU are not equivalent, since beta 2 is incapable of promoting formation of DNA supercoiling like alpha beta and alpha 2 do. The putative roles of each form of HU are discussed.

Bacterial Proteins↗

PubMed1996

Regulation of HU alpha and HU beta by CRP and FIS in Escherichia coli.

The dimeric histone-like protein HU, one of the most abundant DNA binding proteins of Escherichia coli, is encoded by two closely related but unlinked genes, hupA and hupB. Overproduction of one or the other of the subunits has been shown to induce the SOS response and mucoidy. To understand how the synthesis of this protein is coordinated, we studied the transcription control of the two hup genes. We show here that CRP stimulated the transcription of both genes. In contrast, the FIS protein, one of the major positive regulators of the stable RNA operons, stimulated the transcription of the hupA gene, whereas it repressed that of the hupB gene. Moreover, stringent control, which like FIS also regulates the transcription of the stable RNA operons, affected the hupB transcription while it had no effect on hupA. This opposite regulation of the transcription of the two HU genes is reflected at the protein level signifying that changes in the composition of HU occur upon changes in the environment. It is rather unexpected that such divergent transcriptional regulation controls the two genes encoding a dimeric protein.

Amino Acid Sequence↗

PubMed1996

Nonparametric density estimation applied to population pharmacokinetics.

Kinetic parameters are estimated to assess absorption, distribution, metabolism, and elimination of a drug in a subject. In a group of subjects, pharmacokinetic population studies are developed to describe the variability and to detect particular subsets by establishing the relationships between kinetic parameters and easily measurable subject characteristics, the covariates (age, body weight, etc.). The usually proposed methods are based on linear regression equations relating kinetic parameters to the covariates. We propose to measure these dependencies and describe the interindividual variability through the joint probability density function. This function is estimated by a nonparametric method superposing potential functions or kernels over the sample. In this estimation, the Shannon information theory was applied to determine the number of individuals needed to describe the variability reliably and to screen informative covariates with respect to the kinetic parameters. This approach was used to obtain the nonparametric conditional probability density functions of the kinetic parameters, given the covariates. These functions supplied prior information for a Bayesian estimation. The feasibility of the global approach was illustrated by a simulation in which nonlinear relations link covariates and pharmacokinetic parameters. The performance of this new estimator using covariates was compared with that of the usual Bayesian estimation.

Animals↗