Energy consumption of European and African shrews

Is the extremely high oxygen consumption of shrews due to an unusually high basal metabolism? In an attempt to answer this long-standing question, we have measured the oxygen consumption of 13 species of shrews of different origin: from Europe - Sorex araneus, S. Minutus, Neomys fodiens, Crocidura russula, and Suncus etruscus; from Africa - Crocidura bottegi, C. bicolor, C. jouvenetae; C. poensis, C. theresae, C. Wimmeri, C. flavescens, and C. giffardi, The measurements, taken over a period of 20-30 minutes, were made in small, closed-system chambers at 25°C. The metabolic rat our shrews of the subfamily Soricinae lies between the eman and minimum values of the Soricini (M=126.2 W0.52 cal/h and M=82.6 W0.53 cal/h, respectively), as recorded in the literature. Zhe average for the African Crocidurinae is much lower (M= 43.6 W0.67). The metabolic rate of the European Croccidura russula agrees with that of the African species. Thus, the Crocidurinae are characterized by a relatively low metabolic rate; the Soricinae, and in particular the tribe of the Soricini, by an extremely high metabolic rate. The tribes Neomyini and Blarinini occupy an intermediate position. These differences are also to be found at the level of the basal metabolism. This main difference between the two sub-families can most likely be explained by evolution in geographical isolation under differential climatic conditions: the Crocidurinae having evolved in tropical Africa and the Soricinae in temperate Eurasia

Brain energy consumption induced by electrical stimulation promotes systemic glucose uptake.

BACKGROUND: Controlled transcranial stimulation of the brain is part of clinical treatment strategies in neuropsychiatric diseases such as depression, stroke, or Parkinson's disease. Manipulating brain activity by transcranial stimulation, however, inevitably influences other control centers of various neuronal and neurohormonal feedback loops and therefore may concomitantly affect systemic metabolic regulation. Because hypothalamic adenosine triphosphate-sensitive potassium channels, which function as local energy sensors, are centrally involved in the regulation of glucose homeostasis, we tested whether transcranial direct current stimulation (tDCS) causes an excitation-induced transient neuronal energy depletion and thus influences systemic glucose homeostasis and related neuroendocrine mediators.METHODS: In a crossover design testing 15 healthy male volunteers, we increased neuronal excitation by anodal tDCS versus sham and examined cerebral energy consumption with (31)phosphorus magnetic resonance spectroscopy. Systemic glucose uptake was determined by euglycemic-hyperinsulinemic glucose clamp, and neurohormonal measurements comprised the parameters of the stress systems.RESULTS: We found that anodic tDCS-induced neuronal excitation causes an energetic depletion, as quantified by (31)phosphorus magnetic resonance spectroscopy. Moreover, tDCS-induced cerebral energy consumption promotes systemic glucose tolerance in a standardized euglycemic-hyperinsulinemic glucose clamp procedure and reduces neurohormonal stress axes activity.CONCLUSIONS: Our data demonstrate that transcranial brain stimulation not only evokes alterations in local neuronal processes but also clearly influences downstream metabolic systems regulated by the brain. The beneficial effects of tDCS on metabolic features may thus qualify brain stimulation as a promising nonpharmacologic therapy option for drug-induced or comorbid metabolic disturbances in various neuropsychiatric diseases.

Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis.

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2K(b) system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method.

Combined simulation and mutagenesis analyses reveal the involvement of key residues for peroxisome proliferator-activated receptor alpha helix 12 dynamic behavior.

The dynamic properties of helix 12 in the ligand binding domain of nuclear receptors are a major determinant of AF-2 domain activity. We investigated the molecular and structural basis of helix 12 mobility, as well as the involvement of individual residues with regard to peroxisome proliferator-activated receptor alpha (PPARalpha) constitutive and ligand-dependent transcriptional activity. Functional assays of the activity of PPARalpha helix 12 mutants were combined with free energy molecular dynamics simulations. The agreement between the results from these approaches allows us to make robust claims concerning the mechanisms that govern helix 12 functions. Our data support a model in which PPARalpha helix 12 transiently adopts a relatively stable active conformation even in the absence of a ligand. This conformation provides the interface for the recruitment of a coactivator and results in constitutive activity. The receptor agonists stabilize this conformation and increase PPARalpha transcription activation potential. Finally, we disclose important functions of residues in PPARalpha AF-2, which determine the positioning of helix 12 in the active conformation in the absence of a ligand. Substitution of these residues suppresses PPARalpha constitutive activity, without changing PPARalpha ligand-dependent activation potential.

Brownian dynamics simulation of DNA condensation.

DNA condensation observed in vitro with the addition of polyvalent counterions is due to intermolecular attractive forces. We introduce a quantitative model of these forces in a Brownian dynamics simulation in addition to a standard mean-field Poisson-Boltzmann repulsion. The comparison of a theoretical value of the effective diameter calculated from the second virial coefficient in cylindrical geometry with some experimental results allows a quantitative evaluation of the one-parameter attractive potential. We show afterward that with a sufficient concentration of divalent salt (typically approximately 20 mM MgCl(2)), supercoiled DNA adopts a collapsed form where opposing segments of interwound regions present zones of lateral contact. However, under the same conditions the same plasmid without torsional stress does not collapse. The condensed molecules present coexisting open and collapsed plectonemic regions. Furthermore, simulations show that circular DNA in 50% methanol solutions with 20 mM MgCl(2) aggregates without the requirement of torsional energy. This confirms known experimental results. Finally, a simulated DNA molecule confined in a box of variable size also presents some local collapsed zones in 20 mM MgCl(2) above a critical concentration of the DNA. Conformational entropy reduction obtained either by supercoiling or by confinement seems thus to play a crucial role in all forms of condensation of DNA.

Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.

Microsatellites can be misleading: an empirical and simulation study.

It has been long recognized that highly polymorphic genetic markers can lead to underestimation of divergence between populations when migration is low. Microsatellite loci, which are characterized by extremely high mutation rates, are particularly likely to be affected. Here, we report genetic differentiation estimates in a contact zone between two chromosome races of the common shrew (Sorex araneus), based on 10 autosomal microsatellites, a newly developed Y-chromosome microsatellite, and mitochondrial DNA. These results are compared to previous data on proteins and karyotypes. Estimates of genetic differentiation based on F- and R-statistics are much lower for autosomal microsatellites than for all other genetic markers. We show by simulations that this discrepancy stems mainly from the high mutation rate of microsatellite markers for F-statistics and from deviations from a single-step mutation model for R-statistics. The sex-linked genetic markers show that all gene exchange between races is mediated by females. The absence of male-mediated gene flow most likely results from male hybrid sterility.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

Effects of increased intensity of intermittent training in runners with differing VO2 kinetics.

The purpose of this study was to test the hypothesis that athletes having a slower oxygen uptake ( VO(2)) kinetics would benefit more, in terms of time spent near VO(2max), from an increase in the intensity of an intermittent running training (IT). After determination of VO(2max), vVO(2max) (i.e. the minimal velocity associated with VO(2max) in an incremental test) and the time to exhaustion sustained at vVO(2max) ( T(lim)), seven well-trained triathletes performed in random order two IT sessions. The two IT comprised 30-s work intervals at either 100% (IT(100%)) or 105% (IT(105%)) of vVO(2max) with 30-s recovery intervals at 50% of vVO(2max) between each repeat. The parameters of the VO(2) kinetics (td(1), tau(1), A(1), td(2), tau(2), A(2), i.e. time delay, time constant and amplitude of the primary phase and slow component, respectively) during the T(lim) test were modelled with two exponential functions. The highest VO(2) reached was significantly lower ( P<0.01) in IT(100%) run at 19.8 (0.9) km(.)h(-1) [66.2 (4.6) ml(.)min(-1.)kg(-1)] than in IT(105%) run at 20.8 (1.0) km(.)h(-1) [71.1 (4.9) ml(.)min(-1.)kg(-1)] or in the incremental test [71.2 (4.2) ml(.)min(-1.)kg(-1)]. The time sustained above 90% of VO(2max) in IT(105%) [338 (149) s] was significantly higher ( P<0.05) than in IT(100%) [168 (131) s]. The average T(lim) was 244 (39) s, tau(1) was 15.8 (5.9) s and td(2) was 96 (13) s. tau(1) was correlated with the difference in time spent above 90% of VO(2max) ( r=0.91; P<0.01) between IT(105%) and IT(100%). In conclusion, athletes with a slower VO(2) kinetics in a vVO(2max) constant-velocity test benefited more from the 5% rise of IT work intensity, exercising for longer above 90% of VO(2max) when the IT intensity was increased from 100 to 105% of vVO(2max).

SIMULIT : description du modèle de simulation

Le modèle développé à l'Institut universitaire de médecine sociale et préventive de Lausanne utilise un programme informatique pour simuler les mouvements d'entrées et de sorties des hôpitaux de soins généraux. Cette simulation se fonde sur les données récoltées de routine dans les hôpitaux; elle tient notamment compte de certaines variations journalières et saisonnières, du nombre d'entrées, ainsi que du "Case-Mix" de l'hôpital, c'est-à-dire de la répartition des cas selon les groupes cliniques et l'âge des patients.

NO rebinding to myoglobin: a reactive molecular dynamics study.

The rebinding of NO to myoglobin after photolysis is studied using the 'reactive molecular dynamics' method. In this approach the energy of the system is evaluated on two potential energy surfaces that include the heme-ligand interactions which change between liganded and unliganded myoglobin. This makes it possible to take into account in a simple way, the high dimensionality of the transition seam connecting the reactant and product states. The dynamics of the dissociated NO molecules are examined, and the geometrical and energetic properties of the transition seam are studied. Analysis of the frequency of recrossing shows that the height of the effective rebinding barrier is dependent on the time after photodissociation. This effect is due mainly to protein relaxation and may contribute to the experimentally observed non-exponential rebinding rate of NO, as has been suggested previously.