On Suicidal punishment among "Acromyrmex Versicolor" Cofoundresses: the Disadvantage in Personal Advantage

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E-cadherin can limit the transforming properties of activating β-catenin mutations

Wnt pathway deregulation is a common characteristic of many cancers. But only Colorectal Cancer predominantly harbours mutations in APC, whereas other cancer types (hepatocellular carcinoma, solid pseudopapillary tumours of pancreas) have activating mutations in β-catenin (CTNNB1). We have compared the dynamics and the potency of β-catenin mutations in vivo. Within the murine small intestine (SI), an activating mutation of β-catenin took much longer to achieve a Wnt deregulation and acquire a crypt-progenitor-cell (CPC) phenotype than Apc or Gsk3 loss. Within the colon, a single activating mutation of β-catenin was unable to drive Wnt deregulation or induce the CPC phenotype. This ability of β-catenin mutation to differentially transform the SI versus the colon correlated with significantly higher expression of the β-catenin binding partner E-cadherin. This increased expression is associated with a higher number of E-cadherin:β-catenin complexes at the membrane. Reduction of E-cadherin synergised with an activating mutation of β-catenin so there was now a rapid CPC phenotype within the colon and SI. Thus there is a threshold of β-catenin that is required to drive transformation and E-cadherin can act as a buffer to prevent β-catenin accumulation

The porin and the permeating antibiotic: A selective diffusion barrier in gram-negative bacteria

Gram-negative bacteria are responsible for a large proportion of antibiotic resistant bacterial diseases. These bacteria have a complex cell envelope that comprises an outer membrane and an inner membrane that delimit the periplasm. The outer membrane contains various protein channels, called porins, which are involved in the influx of various compounds, including several classes of antibiotics. Bacterial adaptation to reduce influx through porins is an increasing problem worldwide that contributes, together with efflux systems, to the emergence and dissemination of antibiotic resistance. An exciting challenge is to decipher the genetic and molecular basis of membrane impermeability as a bacterial resistance mechanism. This Review outlines the bacterial response towards antibiotic stress on altered membrane permeability and discusses recent advances in molecular approaches that are improving our knowledge of the physico-chemical parameters that govern the translocation of antibiotics through porin channel

Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models

The emergence and development of cancer is a consequence of the accumulation over time of genomic mutations involving a specific set of genes, which provides the cancer clones with a functional selective advantage. In this work, we model the order of accumulation of such mutations during the progression, which eventually leads to the disease, by means of probabilistic graphic models, i.e., Bayesian Networks (BNs). We investigate how to perform the task of learning the structure of such BNs, according to experimental evidence, adopting a global optimization meta-heuristics. In particular, in this work we rely on Genetic Algorithms, and to strongly reduce the execution time of the inference -- which can also involve multiple repetitions to collect statistically significant assessments of the data -- we distribute the calculations using both multi-threading and a multi-node architecture. The results show that our approach is characterized by good accuracy and specificity; we also demonstrate its feasibility, thanks to a 84x reduction of the overall execution time with respect to a traditional sequential implementation

Timing of Pathogen Adaptation to a Multicomponent Treatment

The sustainable use of multicomponent treatments such as combination therapies, combination vaccines/chemicals, and plants carrying multigenic resistance requires an understanding of how their population-wide deployment affects the speed of the pathogen adaptation. Here, we develop a stochastic model describing the emergence of a mutant pathogen and its dynamics in a heterogeneous host population split into various types by the management strategy. Based on a multi-type Markov birth and death process, the model can be used to provide a basic understanding of how the life-cycle parameters of the pathogen population, and the controllable parameters of a management strategy affect the speed at which a pathogen adapts to a multicomponent treatment. Our results reveal the importance of coupling stochastic mutation and migration processes, and illustrate how their stochasticity can alter our view of the principles of managing pathogen adaptive dynamics at the population level. In particular, we identify the growth and migration rates that allow pathogens to adapt to a multicomponent treatment even if it is deployed on only small proportions of the host. In contrast to the accepted view, our model suggests that treatment durability should not systematically be identified with mutation cost. We show also that associating a multicomponent treatment with defeated monocomponent treatments can be more durable than associating it with intermediate treatments including only some of the components. We conclude that the explicit modelling of stochastic processes underlying evolutionary dynamics could help to elucidate the principles of the sustainable use of multicomponent treatments in population-wide management strategies intended to impede the evolution of harmful populations.Comment: 3 figure

Improving the Evolutionary Coding for Machine Learning Tasks

The most influential factors in the quality of the solutions found by an evolutionary algorithm are a correct coding of the search space and an appropriate evaluation function of the potential solutions. The coding of the search space for the obtaining of decision rules is approached, i.e., the representation of the individuals of the genetic population. Two new methods for encoding discrete and continuous attributes are presented. Our “natural coding” uses one gene per attribute (continuous or discrete) leading to a reduction in the search space. Genetic operators for this approached natural coding are formally described and the reduction of the size of the search space is analysed for several databases from the UCI machine learning repository.Comisión Interministerial de Ciencia y Tecnología TIC1143–C03–0

Partial response to carboplatin in an RRx-001 pretreated patient with EGFR-inhibitor-resistance and T790M-negative NSCLC.

Few therapeutic options are available for T790M-negative non-small cell lung cancer (NSCLC) after failure of primary epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) and chemotherapy. This report presents the case of a 71-year-old Asian female never smoker with EGFR mutated T790M negative non squamous cell lung cancer (NSCLC) pre-treated with the experimental epi-immunotherapeutic agent, RRx-001, that re-responded to single agent carboplatin after failure of platinum doublets, TKIs, pemetrexed and nivolumab. The management of advanced EGFR mutation-positive NSCLC is briefly reviewed herein and the emerging paradigm of episensitization, which contradicts the long-standing and widely accepted tenet about the immutability of resistance and the futility of therapeutic rechallenge, is introduced as a strategy to avert treatment failure and thereby stave off deterioration and death