A nongenomic mechanism for progesterone-mediated immunosuppression: Inhibition of K+ channels, Ca2+ signaling, and gene expression in T lymphocytes

The mechanism by which progesterone causes localized suppression of the immune response during pregnancy has remained elusive. Using human T lymphocytes and T cell lines, we show that progesterone, at concentrations found in the placenta, rapidly and reversibly blocks voltage-gated and calcium-activated K+ channels (KV and KCa, respectively), resulting in depolarization of the membrane potential. As a result, Ca2+ signaling and nuclear factor of activated T cells (NF-AT)-driven gene expression are inhibited. Progesterone acts distally to the initial steps of T cell receptor (TCR)-mediated signal transduction, since it blocks sustained Ca2+ signals after thapsigargin stimulation, as well as oscillatory Ca2+ signals, but not the Ca2+ transient after TCR stimulation. K+ channel blockade by progesterone is specific; other steroid hormones had little or no effect, although the progesterone antagonist RU 486 also blocked KV and KCa channels. Progesterone effectively blocked a broad spectrum of K+ channels, reducing both Kv1.3 and charybdotoxin-resistant components of KV current and KCa current in T cells, as well as blocking several cloned KV channels expressed in cell lines. Progesterone had little or no effect on a cloned voltage-gated Na+ channel, an inward rectifier K+ channel, or on lymphocyte Ca2+ and Cl- channels. We propose that direct inhibition of K+ channels in T cells by progesterone contributes to progesterone-induced immunosuppression

Wide range and tunable linear TMR sensor using two exchange pinned electrodes

A magnetic tunnel junction sensor is proposed, with both the detection and the reference layers pinned by IrMn. Using the differences in the blocking temperatures of the IrMn films with different thicknesses, crossed anisotropies can be induced between the detection and the reference electrodes. The pinning of the sensing electrode ensures a linear and reversible output. It also allows tuning both the sensitivity and the linear range of the sensor. The authors show that the sensitivity varies linearly with the ferromagnetic thickness of the detection electrode. It is demonstrated that an increased thickness leads to a rise of sensitivity and a reduction of the operating range

Paradigm shift in engineering education More time is needed

AbstractInformation Technology (IT) becomes: innovation motor, engineering toolbox; basic part of curricula. The impact on engineering education is due to shifting from industrial towards post-industrial engineering. IT is the most suitable domain to bear the paradigmatic shifts able to lessen the paradox of temporal dissociation between the present process of teaching and its future mirroring in life-long learning. Hence, a modern approach to time and to its related concepts is focused upon. The essence of applying new paradigms in education is exemplified via the advanced subdomain of artificial intelligence. Conclusion: carrying out such educational innovations is urgent, painless and affordable

From Algorithms to (Sub-)Symbolic Inferences in Multi-Agent Systems

Extending metaphorically the Moisilean idea of “nuanced-reasoning logic” and adapting it to the e-world age of Information Technology (IT), the paper aims at showing that new logics, already useful in modern software engineering, become necessary mainly for Multi-Agent Systems (MAS), despite obvious adversities. The first sections are typical for a position paper, defending such logics from an anthropocentric perspective. Through this sieve, Section 4 outlines the features asked for by the paradigm of computing as intelligent interaction, based on “nuances of nuanced-reasoning”, that should be reflected by agent logics. To keep the approach credible, Section 5 illustrates how quantifiable synergy can be reached - even in advanced challenging domains, such as stigmergic coordination - by injecting symbolic reasoning in systems based on sub-symbolic “emergent synthesis”. Since for future work too the preferred logics are doxastic, the conclusions could be structured in line with the well-known agent architecture: Beliefs, Desires, Intentions

Rapid earthquake loss updating of spatially distributed systems via sampling-based bayesian inference

Within moments following an earthquake event, observations collected from the affected area can be used to define a picture of expected losses and to provide emergency services with accurate information. A Bayesian Network framework could be used to update the prior loss estimates based on ground-motion prediction equations and fragility curves, considering various field observations (i.e., evidence). While very appealing in theory, Bayesian Networks pose many challenges when applied to real-world infrastructure systems, especially in terms of scalability. The present study explores the applicability of approximate Bayesian inference, based on Monte-Carlo Markov-Chain sampling algorithms, to a real-world network of roads and built areas where expected loss metrics pertain to the accessibility between damaged areas and hospitals in the region. Observations are gathered either from free-field stations (for updating the ground-motion field) or from structure-mounted stations (for the updating of the damage states of infrastructure components). It is found that the proposed Bayesian approach is able to process a system comprising hundreds of components with reasonable accuracy, time and computation cost. Emergency managers may readily use the updated loss distributions to make informed decisions

Ant Colony Solving Multiple Constraints Problem: Vehicle Route Allocation

Ant colonies are successfully used nowadays as multi-agent systems (MAS) to solve difficult optimization problems such as travelling salesman (TSP), quadratic assignment (QAP), vehicle routing (VRP), graph coloring and satisfiability problem. The objective of the research presented in this paper is to adapt an improved version of Ant Colony Optimisation (ACO) algorithm, mainly: the Elitist Ant System (EAS) algorithm in order to solve the Vehicle Route Allocation Problem (VRAP). After a brief introduction in the first section about MAS and their characteristics, the paper presents the rationale within the second section where ACO algorithm and its common extensions are described. In the approach (the third section) are explained the steps that must be followed in order to adapt EAS for solving the VRAP. The resulted algorithm is illustrated in the fourth section. Section five closes the paper presenting the conclusions and intentions

Synthetic Genes for Artificial Ants. Diversity in Ant Colony Optimization Algorithms

Inspired from the fact that the real world ants from within a colony are not clones (although they may look alike, they are different from one another), in this paper, the authors are presenting an adapted ant colony optimisation (ACO) algorithm that incorporates methods and ideas from genetic algorithms (GA). Following the first (introductory) section of the paper is presented the history and the state of the art, beginning with the stigmergy and genetic concepts and ending with the latest ACO algorithm variants as multiagent systems (MAS). The rationale and the approach sections are aiming at presenting the problems with current stigmergy-based algorithms and at proposing a (possible - yet to be fully verified) solution to some of the problems ("synthetic genes" for artificial ants). A model used for validating the proposed solution is presented in the next section together with some preliminary simulation results. Some of the conclusions regarding the main subject of the paper (synthetic genes: agents within the MAS with different behaviours) that are closing the paper are: a) the convergence speed of the ACO algorithms can be improved using this approach; b) these "synthetic genes" can be easily implemented (as local variables or properties of the agents); c) the MAS is self-adapting to the specific problem that needs to be optimized

Towards the implementation of Computer-Aided Semiosis

Computer-Aided Semiosis (CAS) is a concept coined by a team of researchers a couple of years ago. Since it is a promising domain due to the fact that responds to actual trans-cultural communication needed in the broad-band society - where often the message behind the words does not come clear - the subject ought being inquired more detailed as promised in other papers of the same authors. This interesting idea was inspired from Eco’s theory of communication which states that the receiver "fills the message with significance"; hence it is vital for any communication and is strongly dependent on the cultures involved. In line with Eco’s theory, the research in this area must be trans-disciplinary and anthropocentric. In the intention of narrowing the existing gap between the technological offers and user expectations the macro-architectural feature is that translation will progress from textual, semantically correct, to multimodal, culturally adequate, based on common concepts and "grammar" (rules to combine them into meaningful sentences); thus, this paper will present possible approaches towards the implementation of CAS. Given the fact the ontologies are considered to be the pillars of Semantic Web but also a key tool in implementing CAS, both will be a subject of this paper in the light of finding an implementation solution. The paper is structured on five sections: the first will present the defining aspects of the concept relating it with previous research; the second section will deal with CAS approach and architecture, following with the state of the art regarding ontologies and their relation with Semantic Web. Among the conclusions, one is already noticeable: CAS could not be possible without a trans-cultural ontology

Exponential Distribution of Locomotion Activity in Cell Cultures

In vitro velocities of several cell types have been measured using computer controlled video microscopy, which allowed to record the cells' trajectories over several days. On the basis of our large data sets we show that the locomotion activity displays a universal exponential distribution. Thus, motion resulting from complex cellular processes can be well described by an unexpected, but very simple distribution function. A simple phenomenological model based on the interaction of various cellular processes and finite ATP production rate is proposed to explain these experimental results.Comment: 4 pages, 3 figure

Graded and Binary Responses in Stochastic Gene Expression

Recently, several theoretical and experimental studies have been undertaken to probe the effect of stochasticity on gene expression (GE). In experiments, the GE response to an inducing signal in a cell, measured by the amount of mRNAs/proteins synthesized, is found to be either graded or binary. The latter type of response gives rise to a bimodal distribution in protein levels in an ensemble of cells. One possible origin of binary response is cellular bistability achieved through positive feedback or autoregulation. In this paper, we study a simple, stochastic model of GE and show that the origin of binary response lies exclusively in stochasticity. The transitions between the active and inactive states of the gene are random in nature. Graded and binary responses occur in the model depending on the relative stability of the activated and deactivated gene states with respect to that of mRNAs/proteins.The theoretical results on binary response provide a good description of the ``all-or-none'' phenomenon observed in an eukaryotic system.Comment: to be published in Physical Biolog