Vortex phase transition and superconducting properties of organic quasi-two-dimensional k-(BEDT-TTF) 2 Cu[N(CN) 2 ]Br

International audienceWe report investigations of the low temperature dc susceptibility and the magnetization on the layered organic superconductor κ-(BEDT-TTF)2Cu[N(CN)2]Br near 80K and the effect of disorder on the superconducting transition temperature Tc. The shielding effect (S) and the critical current density Jc were studied (with H parallel to the c axis of the crystal). Jc can be estimated by analysis of magnetic hysteresis measurement using the Bean model. For each temperature value, we observed two regimes in the critical current density Jc(H). This result implies that there exists a first-order phase transition in the vortex system in this organic superconductor. Our results show that the magnetic properties of these compounds depend strongly on the cooling rate. The structural transformation which occurs at the vicinity of 80K very strongly influences the physics of vortex lattice and the associated magnetic behavior

Mathematical analysis of the Escherichia coli chemotaxis signalling pathway

We undertake a detailed mathematical analysis of a recent nonlinear ordinary differential equation (ODE) model describing the chemotactic signalling cascade within an {\it Escherichia coli} cell. The model includes a detailed description of the cell signalling cascade and an average approximation of the receptor activity. A steady-state stability analysis reveals the system exhibits one positive real steady-state which is shown to be asymptotically stable. Given the occurrence of a negative feedback between phosphorylated CheB (CheB-P) and the receptor state, we ask under what conditions, the system may exhibit oscillatory type behaviour. A detailed analysis of parameter space reveals that whilst variation in kinetic rate parameters within known biological limits is unlikely to lead to such behaviour, changes in the total concentration of the signalling proteins does. We postulate that experimentally observed overshoot behaviour can actually be described by damped oscillatory dynamics and consider the relationship between overshoot amplitude, total cell protein concentration and the magnitude of the external ligand stimulus. Model reductions of the full ODE model allow us to understand the link between phosphorylation events and the negative feedback between CheB-P and receptor methylation, as well as elucidate why some mathematical models exhibit overshoot and others do not. Our manuscript closes by discussing intercell variability of total protein concentration as means of ensuring the overall survival of a population as cells are subjected to different environments

Indeterminacy of Reverse Engineering of Gene Regulatory Networks: The Curse of Gene Elasticity

Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. A number of reverse engineering approaches have been developed to help uncover the regulatory networks giving rise to the observed gene expression profiles. However, this is an overspecified problem due to the fact that more than one genotype (network wiring) can give rise to the same phenotype. We refer to this phenomenon as “gene elasticity.” In this work, we study the effect of this particular problem on the pure, data-driven inference of gene regulatory networks.We simulated a four-gene network in order to produce “data” (protein levels) that we use in lieu of real experimental data. We then optimized the network connections between the four genes with a view to obtain the original network that gave rise to the data. We did this for two different cases: one in which only the network connections were optimized and the other in which both the network connections as well as the kinetic parameters (given as reaction probabilities in our case) were estimated. We observed that multiple genotypes gave rise to very similar protein levels. Statistical experimentation indicates that it is impossible to differentiate between the different networks on the basis of both equilibrium as well as dynamic data.We show explicitly that reverse engineering of GRNs from pure expression data is an indeterminate problem. Our results suggest the unsuitability of an inferential, purely data-driven approach for the reverse engineering transcriptional networks in the case of gene regulatory networks displaying a certain level of complexity

A Theoretical Exploration of Birhythmicity in the p53-Mdm2 Network

Experimental observations performed in the p53-Mdm2 network, one of the key protein modules involved in the control of proliferation of abnormal cells in mammals, revealed the existence of two frequencies of oscillations of p53 and Mdm2 in irradiated cells depending on the irradiation dose. These observations raised the question of the existence of birhythmicity, i.e. the coexistence of two oscillatory regimes for the same external conditions, in the p53-Mdm2 network which would be at the origin of these two distinct frequencies. A theoretical answer has been recently suggested by Ouattara, Abou-Jaoudé and Kaufman who proposed a 3-dimensional differential model showing birhythmicity to reproduce the two frequencies experimentally observed. The aim of this work is to analyze the mechanisms at the origin of the birhythmic behavior through a theoretical analysis of this differential model. To do so, we reduced this model, in a first step, into a 3-dimensional piecewise linear differential model where the Hill functions have been approximated by step functions, and, in a second step, into a 2-dimensional piecewise linear differential model by setting one autonomous variable as a constant in each domain of the phase space. We find that two features related to the phase space structure of the system are at the origin of the birhythmic behavior: the existence of two embedded cycles in the transition graph of the reduced models; the presence of a bypass in the orbit of the large amplitude oscillatory regime of low frequency. Based on this analysis, an experimental strategy is proposed to test the existence of birhythmicity in the p53-Mdm2 network. From a methodological point of view, this approach greatly facilitates the computational analysis of complex oscillatory behavior and could represent a valuable tool to explore mathematical models of biological rhythms showing sufficiently steep nonlinearities

Leptin and leptin receptor polymorphisms are associated with increased risk and poor prognosis of breast carcinoma

BACKGROUND: Leptin (LEP) has been consistently associated with angiogenesis and tumor growth. Leptin exerts its physiological action through its specific receptor (LEPR). We have investigated whether genetic variations in LEP and LEPR have implications for susceptibility to and prognosis in breast carcinoma. METHODS: We used the polymerase chain reaction and restriction enzyme digestion to characterize the variation of the LEP and LEPR genes in 308 unrelated Tunisian patients with breast carcinoma and 222 healthy control subjects. Associations of the clinicopathologic parameters and these genetic markers with the rates of the breast carcinoma-specific overall survival (OVS) and the disease free survival (DFS) were assessed using univariate and multivariate analyses. RESULTS: A significantly increased risk of breast carcinoma was associated with heterozygous LEP (-2548) GA (OR = 1.45; P = 0.04) and homozygous LEP (-2548) AA (OR = 3.17; P = 0.001) variants. A highly significant association was found between the heterozygous LEPR 223QR genotype (OR = 1.68; P = 0.007) or homozygous LEPR 223RR genotype (OR = 2.26; P = 0.001) and breast carcinoma. Moreover, the presence of the LEP (-2548) A allele showed a significant association with decreased disease-free survival in breast carcinoma patients, and the presence of the LEPR 223R allele showed a significant association with decreased overall survival. CONCLUSION: Our results indicated that the polymorphisms in LEP and LEPR genes are associated with increased breast cancer risk as well as disease progress, supporting our hypothesis for leptin involvement in cancer pathogenesis

A multi-component flood risk assessment in the Maresme coast (NW Mediterranean)

Coastal regions are the areas most threatened by natural hazards, with floods being the most frequent and significant threat in terms of their induced impacts, and therefore, any management scheme requires their evaluation. In coastal areas, flooding is a hazard associated with various processes acting at different scales: coastal storms, flash floods, and sea level rise (SLR). In order to address the problem as a whole, this study presents a methodology to undertake a preliminary integrated risk assessment that determines the magnitude of the different flood processes (flash flood, marine storm, SLR) and their associated consequences, taking into account their temporal and spatial scales. The risk is quantified using specific indicators to assess the magnitude of the hazard (for each component) and the consequences in a common scale. This allows for a robust comparison of the spatial risk distribution along the coast in order to identify both the areas at greatest risk and the risk components that have the greatest impact. This methodology is applied on the Maresme coast (NW Mediterranean, Spain), which can be considered representative of developed areas of the Spanish Mediterranean coast. The results obtained characterise this coastline as an area of relatively low overall risk, although some hot spots have been identified with high-risk values, with flash flooding being the principal risk process