The evolution of purinergic receptors involved in recognition of a blood meal by hematophagous insects

Many blood feeders use adenine nucleotides as cues for locating blood meal. Structure-activity relationship of adenine nucleotides as phagostimulants varies between closely-related species of blood feeders. It is suggested that a preexisting diverse pool of nucleotide-binding proteins present in all living cells, serves as a source of receptor proteins for the gustatory receptors involved in blood detection. It is proposed that the selection of any such nucleotide-binding protein is random.

A Model-to-model analysis of the repeated Prisoners' Dilemma: genetic algorithms vs. evolutionary dynamics

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Brittle cornea syndrome: recognition, molecular diagnosis and management.

Brittle cornea syndrome (BCS) is an autosomal recessive disorder characterised by extreme corneal thinning and fragility. Corneal rupture can therefore occur either spontaneously or following minimal trauma in affected patients. Two genes, ZNF469 and PRDM5, have now been identified, in which causative pathogenic mutations collectively account for the condition in nearly all patients with BCS ascertained to date. Therefore, effective molecular diagnosis is now available for affected patients, and those at risk of being heterozygous carriers for BCS. We have previously identified mutations in ZNF469 in 14 families (in addition to 6 reported by others in the literature), and in PRDM5 in 8 families (with 1 further family now published by others). Clinical features include extreme corneal thinning with rupture, high myopia, blue sclerae, deafness of mixed aetiology with hypercompliant tympanic membranes, and variable skeletal manifestations. Corneal rupture may be the presenting feature of BCS, and it is possible that this may be incorrectly attributed to non-accidental injury. Mainstays of management include the prevention of ocular rupture by provision of protective polycarbonate spectacles, careful monitoring of visual and auditory function, and assessment for skeletal complications such as developmental dysplasia of the hip. Effective management depends upon appropriate identification of affected individuals, which may be challenging given the phenotypic overlap of BCS with other connective tissue disorders.

Recognition of RNA virus by RIG-I results in activation of CARD9 and inflammasome signaling for interleukin 1 beta production.

Interleukin 1 beta (IL-1 beta) is a potent proinflammatory factor during viral infection. Its production is tightly controlled by transcription of Il1b dependent on the transcription factor NF-kappaB and subsequent processing of pro-IL-1 beta by an inflammasome. However, the sensors and mechanisms that facilitate RNA virus-induced production of IL-1 beta are not well defined. Here we report a dual role for the RNA helicase RIG-I in RNA virus-induced proinflammatory responses. Whereas RIG-I-mediated activation of NF-kappaB required the signaling adaptor MAVS and a complex of the adaptors CARD9 and Bcl-10, RIG-I also bound to the adaptor ASC to trigger caspase-1-dependent inflammasome activation by a mechanism independent of MAVS, CARD9 and the Nod-like receptor protein NLRP3. Our results identify the CARD9-Bcl-10 module as an essential component of the RIG-I-dependent proinflammatory response and establish RIG-I as a sensor able to activate the inflammasome in response to certain RNA viruses.

Fast numerical algorithms for the computation of invariant tori in Hamiltonian systems

In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.

Theoretical study on receptor-G protein recognition: new insights into the mechanisms of the alpha1b-adrenergic recptor activation

This work compares the structural/dynamics features of the wild-type alb-adrenergic receptor (AR) with those of the D142A active mutant and the agonist-bound state. The two active receptor forms were compared in their isolated states as well as in their ability to form homodimers and to recognize the G alpha q beta 1 gamma 2 heterotrimer. The analysis of the isolated structures revealed that, although the mutation- and agonist-induced active states of the alpha 1b-AR are different, they, however, share several structural peculiarities including (a) the release of some constraining interactions found in the wild-type receptor and (b) the opening of a cytosolic crevice formed by the second and third intracellular loops and the cytosolic extensions of helices 5 and 6. Accordingly, also their tendency to form homodimers shows commonalties and differences. In fact, in both the active receptor forms, helix 6 plays a crucial role in mediating homodimerization. However, the homodimeric models result from different interhelical assemblies. On the same line of evidence, in both of the active receptor forms, the cytosolic opened crevice recognizes similar domains on the G protein. However, the docking solutions are differently populated and the receptor-G protein preorientation models suggest that the final complexes should be characterized by different interaction patterns.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Bihippocampal damage with emotional dysfunction: impaired auditory recognition of fear.

A right-handed man developed a sudden transient, amnestic syndrome associated with bilateral hemorrhage of the hippocampi, probably due to Urbach-Wiethe disease. In the 3rd month, despite significant hippocampal structural damage on imaging, only a milder degree of retrograde and anterograde amnesia persisted on detailed neuropsychological examination. On systematic testing of recognition of facial and vocal expression of emotion, we found an impairment of the vocal perception of fear, but not that of other emotions, such as joy, sadness and anger. Such selective impairment of fear perception was not present in the recognition of facial expression of emotion. Thus emotional perception varies according to the different aspects of emotions and the different modality of presentation (faces versus voices). This is consistent with the idea that there may be multiple emotion systems. The study of emotional perception in this unique case of bilateral involvement of hippocampus suggests that this structure may play a critical role in the recognition of fear in vocal expression, possibly dissociated from that of other emotions and from that of fear in facial expression. In regard of recent data suggesting that the amygdala is playing a role in the recognition of fear in the auditory as well as in the visual modality this could suggest that the hippocampus may be part of the auditory pathway of fear recognition.

Trypanosoma cruzi recognition by macrophages and muscle cells: perspectives after a 15-year study

Macrophages and muscle cells are the main targets for invasion of Trypanosoma cruzi. Ultrastructural studies of this phenomenon in vitro showed that invasion occurs by endocytosis, with attachment and internalization being mediated by different components capable of recognizing epi-or trypomastigotes (TRY). A parasitophorus vacuole was formed in both cell types, thereafter fusing with lysosomes. Then, the mechanism of T. cruzi invasion of host cells (HC) is essentially similar (during a primary infection in the abscence of a specific immune response), regardless of wether the target cell is a professional or a non-professional phagocytic cell. Using sugars, lectins, glycosidases, proteinases and proteinase inhibitors, we observed that the relative balance between exposed sialic acid and galactose/N-acetyl galactosamine (GAL) residues on the TRY surface, determines the parasite's capacity to invade HC, and that lectin-mediated phagocytosis with GAL specificity is important for internalization of T. cruzi into macrophages. On the other hand, GAL on the surface to heart muscle cells participate on TRY adhesion. TRY need to process proteolytically both the HC and their own surface, to expose the necessary ligands and receptors that allow binding to, and internalization in the host cell. The diverse range of molecular mechanisms which the parasite could use to invade the host cell may correspond to differences in the available "receptors"on the surface of each specific cell type. Acute phase components, with lectin or proteinase inhibitory activities (a-macroglobulins), may also be involved in T. cruzi-host cell interaction.