Deciphering the immune microenvironment of a tissue by digital imaging and cognition network.

Evidence has highlighted the importance of immune cells in various gut disorders. Both the quantification and localization of these cells are essential to the understanding of the complex mechanisms implicated in these pathologies. Even if quantification can be assessed (e.g., by flow cytometry), simultaneous cell localization and quantification of whole tissues remains technically challenging. Here, we describe the use of a computer learning-based algorithm created in the Tissue Studio interface that allows for a semi-automated, robust and rapid quantitative analysis of immunofluorescence staining on whole colon sections according to their distribution in different tissue areas. Indeed, this algorithm was validated to characterize gut immune microenvironment. Its application to the preclinical colon cancer APCMin/+ mouse model is illustrated by the simultaneous counting of total leucocytes and T cell subpopulations, in the colonic mucosa, lymphoid follicles and tumors. Moreover, we quantify T cells in lymphoid follicles for which quantification is not possible with classical methods. Thus, this algorithm is a new and robust preclinical research tool, for investigating immune contexture exemplified by T cells but it is also applicable to other immune cells such as other myeloid and lymphoid populations or other cellular phenomenon along mouse gut.

Invasive species threat: parasite phylogenetics reveals patterns and processes of host-switching between non-native and native captive freshwater turtles.

One of the major threats to biodiversity involves biological invasions with direct consequences on the stability of ecosystems. In this context, the role of parasites is not negligible as it may enhance the success of invaders. The red-eared slider, Trachemys scripta elegans, has been globally considered among the worst invasive species. Since its introduction through the pet trade, T. s. elegans is now widespread and represents a threat for indigenous species. Because T. s. elegans coexists with Emys orbicularis and Mauremys leprosa in Europe, it has been suggested it may compete with the native turtle species and transmit pathogens. We examined parasite transfer from American captive to the two native species that co-exist in artificial pools of a Turtle Farm in France. As model parasite species we used platyhelminth worms of the family Polystomatidae (Monogenea) because polystomes have been described from American turtles in their native range. Phylogenetic relationships among polystomes parasitizing chelonian host species that are geographically widespread show patterns of diversification more complex than expected. Using DNA barcoding to identify species from adult and/or polystome eggs, several cases of host switching from exotic to indigenous individuals were illustrated, corroborating that parasite transmission is important when considering the pet trade and in reintroduction programmes to reinforce wild populations of indigenous species.

Evolution and diversification within the intertidal brown macroalgae Fucus spiralis/F. vesiculosus species complex in the North Atlantic.

We examined 733 individuals of Fucusspiralis from 21 locations and 1093 Fucusvesiculosus individuals from 37 locations throughout their northern hemisphere ranges using nuclear and mitochondrial markers. Three genetic entities of F. spiralis were recovered. In northern and sympatric populations, the presence of "F. spiralis Low" in the mid-intertidal and "F. spiralis High" in the high-intertidal was confirmed and both co-occurred with the sister species F. vesiculosus. The third and newly-discovered entity, "F. spiralis South", was present mainly in the southern range, where it did not co-occur with F. vesiculosus. The South entity diverged early in allopatry, then hybridized with F. vesiculosus in sympatry to produce F. spiralis Low. Ongoing parallel evolution of F. spiralis Low and F. spiralis High is most likely due to habitat preference/local selection and maintained by preferentially selfing reproductive strategies. Contemporary populations of F. spiralis throughout the North Atlantic stem from a glacial refugium around Brittany involving F. spiralis High; F. spiralis South was probably unaffected by glacial episodes. Exponential population expansion for F. vesiculosus began during the Cromer and/Holstein interglacial period (300,000-200,000 yrs BP). Following the last glacial maximum (30,000-22,000 yrs BP), a single mtDNA haplotype from a glacial refugium in SW Ireland colonized Scandinavia, the Central Atlantic islands, and the W Atlantic.

Learning in multilevel games with incomplete information. I.

A model is presented of learning automata playing stochastic games at two levels. The high level represents the choice of the game environment and corresponds to a group decision. The low level represents the choice of action within the selected game environment. Both of these decision processes are affected by delays in the information state due to inherent latencies or to the delayed broadcast of state changes. Analysis of the intrinsic properties of this Markov process is presented along with simulated iterative behavior and expected iterative behavior. The results show that simulation agrees with expected behavior for small step lengths in the iterative map. A Feigenbaum diagram and numerical computation of the Lyapunov exponents show that, for very small penalty parameters, the system exhibits chaotic behavior.

Learning in multilevel games with incomplete information. II.

Multilevel games are abstractions of situations where decision makers are distributed in a network environment. In Part I of this paper, the authors present several of the challenging problems that arise in the analysis of multilevel games. In this paper a specific set up is considered where the two games being played are zero-sum games and where the decision makers use the linear reward-inaction algorithm of stochastic learning automata. It is shown that the effective game matrix is decided by the willingness and the ability to cooperate and is a convex combination of two zero-sum game matrices. Analysis of the properties of this effective game matrix and the convergence of the decision process shows that players tend toward noncooperation in these specific environments. Simulation results illustrate this noncooperative behavior.

Adaptation in a stochastic Prisoner's Dilemma with delayed information.

Players in a Prisoner's Dilemma are modeled as learning automata that receive feedback from the environment and coadaptively adjust their strategies. Theory and simulations show the coevolutionary dynamics of the reward-inaction and reward-penalty schemes. The players are assumed to be physically distributed or, at least, in an environment where the effects of decisions are lagged. These systems include biological and social systems with constraints on instantaneous information or where environmental responses do not necessarily reflect the true state of the system. Linear stability analysis determines the conditions for persistent oscillations in the players' mixed strategies. Using a parameterized stochastic version of the dilemma, the results indicate that if the environment modifies the payoffs, and thus 'releases' the prisoners from their dilemma, the prisoners become prone to instabilities in their strategies given sufficient delays. Again, the prisoners fail to coordinate their actions.

Evolutionary strategies of stochastic learning automata in the prisoner's dilemma.

Stochastic learning automata (SLA) model stimulus-response species which receive feedback from the environment and adjust their mixed strategies in a Prisoner's Dilemma. A large heterogeneous population consists of SLA applying different strategies (i.e. different learning parameters) and other players applying deterministic strategies, Tit-For-Tat (TFT) or Always-Defect (ALLD). The predicted equilibria determine the payoffs within a generation for applying particular strategies and these equilibria are confirmed by simulation. The resultant population dynamics over many generations show that SLA with insensitive penalty responses strongly favor defection and dominate in subsequent generations over SLA with sensitive penalty responses. The SLA strategies are not evolutionarily stable as they can be invaded by TFT or ALLD. With the introduction of memory in the stimulus-response model, SLA learn to cooperate with TFT players.

[Respiratory sensitization to molds in children: myth or reality?]. / La sensibilisation respiratoire aux moisissures chez l'enfant: mythe ou réalité?

The authors have made a systematic study by PRICK-test and RAST, sometimes followed by a rhino-manometric provocation, of the frequency of sensitization to the two moulds Alternaria and Cladosporium in 200 "all comers" children in a paediatric consultation. The frequency was low, only 10% for those consulting in the groups of asthma, rhinitis, pollinosis, repeated respiratory infections and syndromes of obstructed expiration taken together, and 13% for allergic asthma only. This sensitivity is rarely isolated, but is most often accompanied, or complicated by, other pneumoallergens, such as dust, mites, pollens and sometimes cockroaches. It imposes certain particular clinical traits on asthma (summer asthma or recurring asthma) and in others appears to be strongly influenced by the habitat. The skin tests seem to be very weak and RAST insufficient to be sure of real sensitization. Diagnosis, always difficult, is probably best done by a provocation test (preferably rhino-manometry) and this jumps over the bundle of clinical and biological arguments, as well as being, at least in our country, the most useful mimic of atmospheric moulds. The authors insist on the importance of the interrogation which should be concerned with the chronological and environmental circumstances and all respiratory infections that are suspected of having an allergic factor.