Synchronization and collective swimming patterns in fish (Hemigrammus bleheri).

In this work, we address the case of red nose tetra fish Hemigrammus bleheri swimming in groups in a uniform flow, giving special attention to the basic interactions and cooperative swimming of a single pair of fish. We first bring evidence of synchronization of the two fish, where the swimming modes are dominated by 'out-phase' and 'in-phase' configurations. We show that the transition to this synchronization state is correlated with the swimming speed (i.e. the flow rate), and thus with the magnitude of the hydrodynamic pressure generated by the fish body during each swimming cycle. From a careful spatio-temporal analysis corresponding to those synchronized modes, we characterize the distances between the two individuals in a pair in the basic schooling pattern. We test the conclusions of the analysis of fish pairs with a second set of experiments using groups of three fish. By identifying the typical spatial configurations, we explain how the nearest neighbour interactions constitute the building blocks of collective fish swimming.

Social integration of robots into groups of cockroaches to control self-organized choices.

Collective behavior based on self-organization has been shown in group-living animals from insects to vertebrates. These findings have stimulated engineers to investigate approaches for the coordination of autonomous multirobot systems based on self-organization. In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions. Even when in the minority, robots can modulate the collective decision-making process and produce a global pattern not observed in their absence. These results demonstrate the possibility of using intelligent autonomous devices to study and control self-organized behavioral patterns in group-living animals.

Individual discrimination capability and collective decision-making.

Amplification is the main component of many collective phenomena in social and gregarious insects. In a society, individuals face a mixed palette of odours coming from different groups (lines, strains) and individuals present discrimination capabilities. However, often at the collective level, different groups may cooperate and act together. To understand this apparent contradiction, we use a model of food recruitment where each group of foragers have its own blend of pheromone trail that is partly recognized by the others groups. The model shows that a low level of recognition between signals is sufficient to produce a collaborative pattern between groups and that beyond a critical value of recognition, only the aggregation of all the groups around the same food source is observed. The comparison between this model and one describing the site selection by gregarious insects (e.g. cockroach) suggests that such collective response is a generic property of social phenomena governed by amplification processes.

[Sublingual hyposensitization]. / L'hyposensibilisation par voie sublinguale.

Specific hyposensitization remains the only way to alter profoundly the progress of the allergic disease. The last discoveries in immunology allow better to understand the mechanisms of action. Now, we can use more purified and standardised solutions to improve the results. Subcutaneous way remains the gold method. But, since 10 years, European screws publishes the results of their works about alternative ways like sublingual way. Less dangerous and less compelling, it allows to begin the treatment earlier in the live and to give more important doses. The results are equivalent to the subcutaneous method. Recently, W.H.O. decided to consider sublingual immunotherapy as un full treatment of some allergic diseases.

[Deterministic and stochastic models for circadian rhythms]. / Modèles déterministes et stochastiques pour les rythmes circadiens.

Circadian rhythms, characterized by a period of about 24h, are generated in nearly all living organisms by the negative autoregulation of clock gene expression. Deterministic models based on this genetic regulation account for circadian oscillations in constant environmental conditions (e.g., in constant darkness) and for entrainment of these rhythms by light-dark cycles. When the number of clock mRNA and protein molecules is low, it is necessary to resort to stochastic simulations to assess the influence of molecular noise on circadian oscillations. Indeed, it is possible that the autoregulatory mechanism of gene expression might not produce stable rhythms due to fluctuations if the number of molecules involved in the clock mechanism remains too low. We have compared the deterministic and stochastic approaches for a model based on the negative autoregulation of a clock gene. We show by means of stochastic simulations that robust circadian oscillations can already occur when the maximum number of mRNA and protein molecules is of the order of a few tens or hundreds, respectively. Furthermore, the results indicate that the cooperativity characterizing the repression of the transcription process strenghtens the robustness of circadian rhythms and that entrainment by light-dark cycles stabilizes the phase of the oscillations.

The follicular automaton model: effect of stochasticity and of synchronization of hair cycles.

Human scalp hair consists of a set of about 10(5)follicles which progress independently through developmental cycles. Each hair follicle successively goes through the anagen (A), catagen (C), telogen (T) and latency (L) phases that correspond, respectively, to growth, arrest and hair shedding before a new anagen phase is initiated. Long-term experimental observations in a group of ten male, alopecic and non-alopecic volunteers allowed determination of the characteristics of hair follicle cycles. On the basis of these observations, we previously proposed a follicular automaton model to simulate the dynamics of human hair cycles and the development of different patterns of alopecia [Halloy et al. (2000) Proc. Natl Acad. Sci. U.S.A.97, 8328-8333]. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states A, T, L and the subsequent return to A. These transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a standard deviation. The follicular automaton model was shown to account both for the dynamical transitions observed in a single follicle, and for the behaviour of an ensemble of independently cycling follicles. Here, we extend these results and investigate additional properties of the model. We present a deterministic version of the follicular automaton. We show that numerical simulations of the stochastic version of the automaton yield steady-state level of follicles in the different phases which approach the levels predicted by the deterministic equations as the number of follicles progressively increases. Only the stochastic version can successfully reproduce the fluctuations of the fractions of follicles in each of the three phases, observed in small follicle populations. When the standard deviation is reduced or when the follicles become otherwise synchronized, e.g. by a periodic external signal inducing the transition of anagen follicles into telogen phase, large-amplitude oscillations occur in the fractions of follicles in the three phases. These oscillations are not observed in humans but are reminiscent of the phenomenon of moulting observed in a number of mammalian species.

Deterministic versus stochastic models for circadian rhythms.

Circadian rhythms which occur with a period close to 24 h in nearly all living organisms originate from the negative autoregulation of gene expression.Deterministic models based on genetic regulatory processes account for theoccurrence of circadian rhythms in constant environmental conditions (e.g.constant darkness), for entrainment of these rhythms by light-dark cycles, and for their phase-shifting by light pulses. At low numbers of protein and mRNA molecules, it becomes necessary to resort to stochastic simulations to assess the influence of molecular noise on circadian oscillations. We address the effect of molecular noise by considering two stochastic versions of a core model for circadian rhythms. The deterministic version of this core modelwas previously proposed for circadian oscillations of the PER protein in Drosophila and of the FRQ protein in Neurospora. In the first, non-developed version of the stochastic model, we introduce molecular noise without decomposing the deterministic mechanism into detailed reaction steps while in the second, developed version we carry out such a detailed decomposition. Numerical simulations of the two stochastic versions of the model are performed by means of the Gillespie method. We compare the predictions of the deterministic approach with those of the two stochastic models, with respect both to sustained oscillations of the limit cycle type and to the influence of the proximity of a bifurcation point beyond which the system evolves to a stable steady state. The results indicate that robust circadian oscillations can occur even when the numbers of mRNA and nuclear protein involved in the oscillatory mechanism are reduced to a few tens orhundreds, respectively. The non-developed and developed versions of the stochastic model yield largely similar results and provide good agreement with the predictions of the deterministic model for circadian rhythms.

Modeling the dynamics of human hair cycles by a follicular automaton.

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

The frequency encoding of pulsatility.

Examples of pulsatile signalling abound in intercellular communication, suggesting that this phenomenon represents a major function of biological rhythms. Pulsatile signals can be encoded in terms of their frequency and prove more efficient than monotonous ones whenever constant stimulation induces desensitization of target cells. We address the main examples of frequency encoding of pulsatility, besides those of neuronal nature. Considered in turn are cAMP oscillations in the slime mould Dictyostelium discoideum, the pulsatile secretion of hormones such as gonadotropin-releasing hormone or growth hormone, intracellular Ca2+ oscillations, and circadian rhythms. Models based on receptor desensitization show the possibility of optimizing cellular responses to cAMP signals in Dictyostelium or to pulsatile hormonal stimulation. The models indicate how the optimal duration of the pulsatile signal and the optimal interval between successive pulses vary as a function of the rates or receptor desensitization and resensitization and of the maximum ligand level during stimulation. The frequency encoding of intracellular Ca2+ oscillations appears to rely on another molecular mechanism. Models based on protein phosphorylation by a Ca(2+)-calmodulin activated kinase show that the mean level of phosphorylated protein increases with the frequency of calcium spikes--which itself rises with the degree of stimulation--and that distinct levels of different phosphorylated proteins can be reached for a Ca2+ signal of given frequency.

Modeling oscillations and waves of cAMP in Dictyostelium discoideum cells.

We examine the theoretical aspects of temporal and spatiotemporal organization in the cAMP signaling system of Dictyostelium discoideum amoebae which aggregate in a wavelike manner after starvation, in response to pulses of cAMP emitted with a periodicity of several minutes by cells behaving as aggregation centers. We first extend the model based on receptor desensitization, previously proposed by Martiel and Goldbeter, by incorporating the role of G proteins in signal transduction. The extended model accounts for observations on the response of the signaling system to successive step increases in extracellular cAMP. In the presence of the positive feedback loop in cAMP synthesis, this model generates sustained oscillations in cAMP and in the fraction of active cAMP receptor, similar to those obtained in the simpler model where the role of the G proteins is not taken into account explicitly. We use the latter model to address the formation of concentric and spiral waves of cAMP in the course of D. discoideum aggregation. Previous analyses of the model showed that a progressive increase in the activity of adenylate cyclase and phosphodiesterase can account for the transitions no relay-relay-oscillations-relay observed in the experiments. We show that the degree of cellular synchronization on such a developmental path in parameter space markedly affects the nature of the spatial patterns generated by the model. These patterns range from concentric waves to a small number of large spirals, and finally to a large number of smaller spirals, as the degree of developmental desynchronization between cells increases.

Coexistence of multiple propagating wave-fronts in a regulated enzyme reaction model: link with birhythmicity and multi-threshold excitability.

We analyze the spatial propagation of wave-fronts in a biochemical model for a product-activated enzyme reaction with non-linear recycling of product into substrate. This model was previously studied as a prototype for the coexistence of two distinct types of periodic oscillations (birhythmicity). The system is initially in a stable steady state characterized by the property of multi-threshold excitability, by which it is capable of amplifying in a pulsatory manner perturbations exceeding two distinct thresholds. In such conditions, when the effect of diffusion is taken into account, two distinct wave-fronts are shown to propagate in space, with distinct amplitudes and velocities, for the same set of parameter values, depending on the magnitude of the initial perturbation. Such a multiplicity of propagating wave-fronts represents a new type of coexistence of multiple modes of dynamic behavior, besides the coexistence involving, under spatially homogeneous conditions, multiple steady states, multiple periodic regimes, or a combination of steady and periodic regimes.

Desynchronization of cells on the developmental path triggers the formation of spiral waves of cAMP during Dictyostelium aggregation.

Whereas it is relatively easy to account for the formation of concentric (target) waves of cAMP in the course of Dictyostelium discoideum aggregation after starvation, the origin of spiral waves remains obscure. We investigate a physiologically plausible mechanism for the spontaneous formation of spiral waves of cAMP in D. discoideum. The scenario relies on the developmental path associated with the continuous changes in the activity of enzymes such as adenylate cyclase and phosphodiesterase observed during the hours that follow starvation. These changes bring the cells successively from a nonexcitable state to an excitable state in which they relay suprathreshold cAMP pulses, and then to autonomous oscillations of cAMP, before the system returns to an excitable state. By analyzing a model for cAMP signaling based on receptor desensitization, we show that the desynchronization of cells on this developmental path triggers the formation of fully developed spirals of cAMP. Developmental paths that do not correspond to the sequence of dynamic transitions no relay-relay-oscillations-relay are less able or fail to give rise to the formation of spirals.

Suppression of chaos and other dynamical transitions induced by intercellular coupling in a model for cyclic AMP signaling in Dictyostelium cells.

The effect of intercellular coupling on the switching between periodic behavior and chaos is investigated in a model for cAMP oscillations in Dictyostelium cells. We first analyze the dynamic behavior of a homogeneous cell population which is governed by a three-variable differential system for which bifurcation diagrams are obtained as a function of two control parameters. We then consider the mixing of two populations behaving in a chaotic and periodic manner, respectively. Cells are coupled through the sharing of a common chemical intermediate, extracellular cAMP, which controls its production and release by the cells into the extracellular medium; the dynamics of the mixed suspension is governed by a five-variable differential system. When the two cell populations differ by the value of a single parameter which measures the activity of the enzyme that degrades extracellular cAMP, the bifurcation diagram established for the three-variable homogeneous population can be used to predict the dynamic behavior of the mixed suspension. The analysis shows that a small proportion of periodic cells can suppress chaos in the mixed suspension. Such a fragility of chaos originates from the relative smallness of the domain of aperiodic oscillations in parameter space. The bifurcation diagram is used to obtain the minimum fraction of periodic cells suppressing chaos. These results are related to the suppression of chaos by the small-amplitude periodic forcing of a strange attractor. Numerical simulations further show how the coupling of periodic cells with chaotic cells can produce chaos, bursting, simple periodic oscillations, or a stable steady state; the coupling between two populations at steady state can produce similar modes of dynamic behavior.

Suppression of chaos by periodic oscillations in a model for cyclic AMP signalling in Dictyostelium cells.

We investigate how the introduction of cells oscillating periodically affects the behaviour of a suspension of Dictyostelium discoideum amoebae undergoing chaotic oscillations of cyclic AMP. The analysis of a model indicates that a tiny proportion of periodic cells suffices to transform chaos into periodic oscillations in such suspensions. A similar result is obtained by forcing the aperiodic oscillations by a small-amplitude, periodic input of cyclic AMP. The results provide an explanation for the observation of regular oscillations in suspensions of a putatively chaotic mutant of Dictyostelium discoideum. More generally, the results show how chaos in biological systems may disappear through the coupling with periodic oscillations.

Changes in regional and overall lung function after bronchography.

This investigation compares the effects of unilateral bronchography on classical pulmonary function parameters (spirometry, CO transfer, flow-volume curve, and arterial blood gases) and radioisotopic measurements by means of 99mTc-labeled microspheres and 81mKr. The regional changes of ventilation and perfusion were quantified by a radioisotopic index, which was established for each zone of interest: explored lung and unexplored lung. The quantitative study of regional perfusion and ventilation reveals significant reduction of ventilation for lung bases, but not for lung apices. The radioisotopic measurements show a reduction of perfusion parallel to the reduction of ventilation. There is no significant correlation between traditional pulmonary function parameters and isotopic indices. Radioisotopy proved a sensitive tool for investigation of unilateral alterations.