Use of the OLFM4 protein in colorectal cancer diagnosis

The present invention provides a method for diagnosing KRAS mutations in colorectal cancers by measuring the level of OLFM4. In another aspect, the present invention relates a method of predicting the responds to a chemotherapeutic agent of a subject suffering from a colorectal cancer: according to the present invention, the by determining the OLFM4 levels. According to the present invention, the response can be predicted by determining the OLFM4 levels. This result in turn permits the design or the adaptation of a treatment of the said subject with the said chemotherapeutic agent

How should we define STAT3 as an oncogene and as a potential target for therapy?

Aberrant activation of the STAT3 transcription factor has been reported in a large group of tumors and a strong biological basis now defines this protein as an oncogenic driver. Consequently, STAT3 is considered to be a promising target in the field of cancer therapy. For its inhibition to result in a successful therapeutic approach, the definition of a target tumor population identified by specific and detectable alterations is critical. The canonical activation model of STAT3 relies on a constitutive phosphorylation on its 705 tyrosine site, resulting in its dimerization, nuclear translocation, and the consequent activation of cancer genes. Therefore, it is expected that tumors expressing this phosphorylated form are addicted to STAT3 and will be sensitive to existing drugs which are targeting this dimeric form. However, recent results have shown that STAT3 can function as an oncogene in the absence of this tyrosine phosphorylation. This indicates that different forms of the transcription factor also play an important role in tumor growth and chemotherapy resistance. This complicates the definition of STAT3 as an oncogene and as a potential prognosis and predictive biomarker. The obligation to target a defined tumor type implies that future clinical trials should use a precise definition of STAT3 activation. This will allow tumors addicted to this oncogene to be identified correctly, leading to a strong rationale for patient stratification

The cavity method for large deviations

A method is introduced for studying large deviations in the context of statistical physics of disordered systems. The approach, based on an extension of the cavity method to atypical realizations of the quenched disorder, allows us to compute exponentially small probabilities (rate functions) over different classes of random graphs. It is illustrated with two combinatorial optimization problems, the vertex-cover and coloring problems, for which the presence of replica symmetry breaking phases is taken into account. Applications include the analysis of models on adaptive graph structures.Comment: 18 pages, 7 figure

On the inequivalence of statistical ensembles

We investigate the relation between various statistical ensembles of finite systems. If ensembles differ at the level of fluctuations of the order parameter, we show that the equations of states can present major differences. A sufficient condition for this inequivalence to survive at the thermodynamical limit is worked out. If energy consists in a kinetic and a potential part, the microcanonical ensemble does not converge towards the canonical ensemble when the partial heat capacities per particle fulfill the relation $c_{k}^{-1}+c_{p}^{-1}<0$.Comment: 4 pages, 4 figure

Lyapunov exponent of many-particle systems: testing the stochastic approach

The stochastic approach to the determination of the largest Lyapunov exponent of a many-particle system is tested in the so-called mean-field XY-Hamiltonians. In weakly chaotic regimes, the stochastic approach relates the Lyapunov exponent to a few statistical properties of the Hessian matrix of the interaction, which can be calculated as suitable thermal averages. We have verified that there is a satisfactory quantitative agreement between theory and simulations in the disordered phases of the XY models, either with attractive or repulsive interactions. Part of the success of the theory is due to the possibility of predicting the shape of the required correlation functions, because this permits the calculation of correlation times as thermal averages.Comment: 11 pages including 6 figure

Transient backbending behavior in the Ising model with fixed magnetization

The physical origin of the backbendings in the equations of state of finite but not necessarily small systems is studied in the Ising model with fixed magnetization (IMFM) by means of the topological properties of the observable distributions and the analysis of the largest cluster with increasing lattice size. Looking at the convexity anomalies of the IMFM thermodynamic potential, it is shown that the order of the transition at the thermodynamic limit can be recognized in finite systems independently of the lattice size. General statistical mechanics arguments and analytical calculations suggest that the backbending in the caloric curve is a transient behaviour which should not converge to a plateau in the thermodynamic limit, while the first order transition is signalled by a discontinuity in other observables.Comment: 24 pages, 11 figure

Spatial biases reduce the ability of Earth system models to simulate soil heterotrophic respiration fluxes

Heterotrophic respiration (Rh) is, at a global scale, one of the largest CO2 fluxes between the Earth's surface and atmosphere and may increase in the future. The previous generation of Earth system models (ESMs) was able to reproduce global fluxes relatively well, but at that, time no gridded products were available to perform an in-depth evaluation. The capacity of the new generation of ESMs used within the Coupled Model Intercomparison Project Phase 6 (CMIP6) to reproduce this flux has not been evaluated, meaning that the realism of resulting CO2 flux estimates is unclear. In this study, we combine recently released observational data on Rh and ESM simulations to evaluate the ability of 13 ESMs from CMIP6 to reproduce Rh. Only 4 of the 13 tested ESMs were able to reproduce the total Rh flux, but spatial analysis underlined important bias compensation for most of the ESMs, which generally showed an overestimation in tropical regions and an underestimation in arid regions. To identify the main drivers of the bias, we performed an analysis of the residuals and found that mean annual precipitation was the most important driver explaining the difference between ESM simulations and observation-derived products of Rh, with a higher bias between ESM simulations and Rh products where precipitation was high. Based on our results, next-generation ESMs should focus on improving the response of Rh to soil moisture.</p

Singular Cucker-Smale Dynamics

The existing state of the art for singular models of flocking is overviewed, starting from microscopic model of Cucker and Smale with singular communication weight, through its mesoscopic mean-filed limit, up to the corresponding macroscopic regime. For the microscopic Cucker-Smale (CS) model, the collision-avoidance phenomenon is discussed, also in the presence of bonding forces and the decentralized control. For the kinetic mean-field model, the existence of global-in-time measure-valued solutions, with a special emphasis on a weak atomic uniqueness of solutions is sketched. Ultimately, for the macroscopic singular model, the summary of the existence results for the Euler-type alignment system is provided, including existence of strong solutions on one-dimensional torus, and the extension of this result to higher dimensions upon restriction on the smallness of initial data. Additionally, the pressureless Navier-Stokes-type system corresponding to particular choice of alignment kernel is presented, and compared - analytically and numerically - to the porous medium equation

A novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships

<p>Abstract</p> <p>Background</p> <p>Substitution matrices are key parameters for the alignment of two protein sequences, and consequently for most comparative genomics studies. The composition of biological sequences can vary importantly between species and groups of species, and classical matrices such as those in the BLOSUM series fail to accurately estimate alignment scores and statistical significance with sequences sharing marked compositional biases.</p> <p>Results</p> <p>We present a general and simple methodology to build matrices that are especially fitted to the compositional bias of proteins. Our approach is inspired from the one used to build the BLOSUM matrices and is based on learning substitution and amino acid frequencies on real sequences with the corresponding compositional bias. We applied it to the large scale comparison of Mollicute AT-rich genomes. The new matrix, MOLLI60, was used to predict pairwise orthology relationships, as well as homolog families among 24 Mollicute genomes. We show that this new matrix enables to better discriminate between true and false orthologs and improves the clustering of homologous proteins, with respect to the use of the classical matrix BLOSUM62.</p> <p>Conclusions</p> <p>We show in this paper that well-fitted matrices can improve the predictions of orthologous and homologous relationships among proteins with a similar compositional bias. With the ever-increasing number of sequenced genomes, our approach could prove valuable in numerous comparative studies focusing on atypical genomes.</p