The population genetics of clonal and partially clonal diploids.

The consequences of variable rates of clonal reproduction on the population genetics of neutral markers are explored in diploid organisms within a subdivided population (island model). We use both analytical and stochastic simulation approaches. High rates of clonal reproduction will positively affect heterozygosity. As a consequence, nearly twice as many alleles per locus can be maintained and population differentiation estimated as F(ST) value is strongly decreased in purely clonal populations as compared to purely sexual ones. With increasing clonal reproduction, effective population size first slowly increases and then points toward extreme values when the reproductive system tends toward strict clonality. This reflects the fact that polymorphism is protected within individuals due to fixed heterozygosity. Contrarily, genotypic diversity smoothly decreases with increasing rates of clonal reproduction. Asexual populations thus maintain higher genetic diversity at each single locus but a lower number of different genotypes. Mixed clonal/sexual reproduction is nearly indistinguishable from strict sexual reproduction as long as the proportion of clonal reproduction is not strongly predominant for all quantities investigated, except for genotypic diversities (both at individual loci and over multiple loci).

SIMULIT : manuel de l'utilisateur

SIMULIT est un programme permettant la simulation de l'occupation des lits des hôpitaux de soins aigus. La mise en oeuvre de SIMULIT et des programmes annexes requiert de l'utilisateur qu'il sache créer et modifier un fichier à l'aide d'un éditeur, et lancer l'exécution d'un programme sur la machine dont il dispose. Le schéma général de la mise en oeuvre se trouve à l'annexe 1 de ce cahier.

Groupes diagnostiques utilisés sur SIMULIT 13

La nomenclature des diagnostics est celle de la Classification internationale des maladies (9e révision), utilisée par la Statistique médicale VESKA depuis 1980. Les trois premiers chiffres du code ont été utilisés; seul le premier diagnostic a été retenu.

Population consequences of environmental sex reversal.

When sex determination in a species is predominantly genetic but environmentally reversible, exposure to (anthropogenic) changes in the environment can lead to shifts in a population's sex ratio. Such scenarios may be common in many fishes and amphibians, yet their ramifications remain largely unexplored. We used a simple model to study the (short-term) population consequences of environmental sex reversal (ESR). We examined the effects on sex ratios, sex chromosome frequencies, and population growth and persistence after exposure to environmental forces with feminizing or masculinizing tendencies. When environmental feminization was strong, X chromosomes were driven to extinction. Analogously, extinction of normally male-linked genetic factors (e.g., Y chromosomes) was caused by continuous environmental masculinization. Although moderate feminization was beneficial for population growth in the absence of large viability effects, our results suggest that the consequences of ESR are generally negative in terms of population size and the persistence of sex chromosomes. Extreme sex ratios resulting from high rates of ESR also reduced effective population sizes considerably. This may limit any evolutionary response to the deleterious effects of ESR. Our findings suggest that ESR changes population growth and sex ratios in some counter-intuitive ways and can change the predominant factor in sex determination from genetic to fully environmental, often within only a few tens of generations. Populations that lose genetic sex determination may quickly go extinct if the environmental forces that cause sex reversal cease.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

A surface-based approach to quantify local cortical gyrification.

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

Quantification of brain glycogen concentration and turnover through localized 13C NMR of both the C1 and C6 resonances.

We have recently shown that at isotopic steady state (13)C NMR can provide a direct measurement of glycogen concentration changes, but that the turnover of glycogen was not accessible with this protocol. The aim of the present study was to design, implement and apply a novel dual-tracer infusion protocol to simultaneously measure glycogen concentration and turnover. After reaching isotopic steady state for glycogen C1 using [1-(13)C] glucose administration, [1,6-(13)C(2)] glucose was infused such that isotopic steady state was maintained at the C1 position, but the C6 position reflected (13)C label incorporation. To overcome the large chemical shift displacement error between the C1 and C6 resonances of glycogen, we implemented 2D gradient based localization using the Fourier series window approach, in conjunction with time-domain analysis of the resulting FIDs using jMRUI. The glycogen concentration of 5.1 +/- 1.6 mM measured from the C1 position was in excellent agreement with concomitant biochemical determinations. Glycogen turnover measured from the rate of label incorporation into the C6 position of glycogen in the alpha-chloralose anesthetized rat was 0.7 micromol/g/h.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Development of an erythropoietin prescription simulator to improve abilities for the prescription of erythropoietin stimulating agents: is it feasible?

BACKGROUND: The increasing use of erythropoietins with long half-lives and the tendency to lengthen the administration interval to monthly injections call for raising awareness on the pharmacokinetics and risks of new erythropoietin stimulating agents (ESA). Their pharmacodynamic complexity and individual variability limit the possibility of attaining comprehensive clinical experience. In order to help physicians acquiring prescription abilities, we have built a prescription computer model to be used both as a simulator and education tool. METHODS: The pharmacokinetic computer model was developed using Visual Basic on Excel and tested with 3 different ESA half-lives (24, 48 and 138 hours) and 2 administration intervals (weekly vs. monthly). Two groups of 25 nephrologists were exposed to the six randomised combinations of half-life and administration interval. They were asked to achieve and maintain, as precisely as possible, the haemoglobin target of 11-12 g/dL in a simulated naïve patient. Each simulation was repeated twice, with or without randomly generated bleeding episodes. RESULTS: The simulation using an ESA with a half-life of 138 hours, administered monthly, compared to the other combinations of half-lives and administration intervals, showed an overshooting tendency (percentages of Hb values > 13 g/dL 15.8 ± 18.3 vs. 6.9 ± 12.2; P < 0.01), which was quickly corrected with experience. The prescription ability appeared to be optimal with a 24 hour half-life and weekly administration (ability score indexing values in the target 1.52 ± 0.70 vs. 1.24 ± 0.37; P < 0.05). The monthly prescription interval, as suggested in the literature, was accompanied by less therapeutic adjustments (4.9 ± 2.2 vs. 8.2 ± 4.9; P < 0.001); a direct correlation between haemoglobin variability and number of therapy modifications was found (P < 0.01). CONCLUSIONS: Computer-based simulations can be a useful tool for improving ESA prescription abilities among nephrologists by raising awareness about the pharmacokinetic characteristics of the various ESAs and recognizing the factors that influence haemoglobin variability.

The activation process of the alpha1B-adrenergic receptor: potential role of protonation and hydrophobicity of a highly conserved aspartate.

In this study, a quantitative approach was used to investigate the role of D142, which belongs to the highly conserved E/DRY sequence, in the activation process of the alpha1B-adrenergic receptor (alpha1B-AR). Experimental and computer-simulated mutagenesis were performed by substituting all possible natural amino acids at the D142 site. The resulting congeneric set of proteins together with the finding that all the receptor mutants show various levels of constitutive (agonist-independent) activity enabled us to quantitatively analyze the relationships between structural/dynamic features and the extent of constitutive activity. Our results suggest that the hydrophobic/hydrophilic character of D142, which could be regulated by protonation/deprotonation of this residue, is an important modulator of the transition between the inactive (R) and active (R*) state of the alpha1B-AR. Our study represents an example of quantitative structure-activity relationship analysis of the activation process of a G protein-coupled receptor.

Simulations of action of DNA topoisomerases to investigate boundaries and shapes of spaces of knots.

The configuration space available to randomly cyclized polymers is divided into subspaces accessible to individual knot types. A phantom chain utilized in numerical simulations of polymers can explore all subspaces, whereas a real closed chain forming a figure-of-eight knot, for example, is confined to a subspace corresponding to this knot type only. One can conceptually compare the assembly of configuration spaces of various knot types to a complex foam where individual cells delimit the configuration space available to a given knot type. Neighboring cells in the foam harbor knots that can be converted into each other by just one intersegmental passage. Such a segment-segment passage occurring at the level of knotted configurations corresponds to a passage through the interface between neighboring cells in the foamy knot space. Using a DNA topoisomerase-inspired simulation approach we characterize here the effective interface area between neighboring knot spaces as well as the surface-to-volume ratio of individual knot spaces. These results provide a reference system required for better understanding mechanisms of action of various DNA topoisomerases.

Simulations in evolution. II. Relative fitness and the propagation of mutants.

In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous article presented a histogram model [1] consisting in populations of individuals whose number changed under the influence of variation and/or fitness, the total population remaining constant. Individuals are classified into bins, and the content of each bin is calculated generation after generation by an Excel spreadsheet. Here, we apply the histogram model to a stable population with fitness F(1)=1.00 in which one or two fitter mutants emerge. In a first scenario, a single mutant emerged in the population whose fitness was greater than 1.00. The simulations ended when the original population was reduced to a single individual. The histogram model was validated by excellent agreement between its predictions and those of a classical continuous function (Eqn. 1) which predicts the number of generations needed for a favorable mutation to spread throughout a population. But in contrast to Eqn. 1, our histogram model is adaptable to more complex scenarios, as demonstrated here. In the second and third scenarios, the original population was present at time zero together with two mutants which differed from the original population by two higher and distinct fitness values. In the fourth scenario, the large original population was present at time zero together with one fitter mutant. After a number of generations, when the mutant offspring had multiplied, a second mutant was introduced whose fitness was even greater. The histogram model also allows Shannon entropy (SE) to be monitored continuously as the information content of the total population decreases or increases. The results of these simulations illustrate, in a graphically didactic manner, the influence of natural selection, operating through relative fitness, in the emergence and dominance of a fitter mutant.

Relaxation times of non-Markovian processes

We consider a general class of non-Markovian processes defined by stochastic differential equations with Ornstein-Uhlenbeck noise. We present a general formalism to evaluate relaxation times associated with correlation functions in the steady state. This formalism is a generalization of a previous approach for Markovian processes. The theoretical results are shown to be in satisfactory agreement both with experimental data for a cubic bistable system and also with a computer simulation of the Stratonovich model. We comment on the dynamical role of the non-Markovianicity in different situations.

Numerical algorithm for Ginzburg-Landau equations with multiplicative noise: Application to domain growth

We consider stochastic partial differential equations with multiplicative noise. We derive an algorithm for the computer simulation of these equations. The algorithm is applied to study domain growth of a model with a conserved order parameter. The numerical results corroborate previous analytical predictions obtained by linear analysis.