Homogenization Model for Aberrant Crypt Foci

Several explanations can be found in the literature about the origin of colorectal cancer. There is however some agreement on the fact that the carcinogenic process is a result of several genetic mutations of normal cells. The colon epithelium is characterized by millions of invaginations, very small cavities, called crypts, where most of the cellular activity occurs. It is consensual in the medical community, that a potential first manifestation of the carcinogenic process, observed in conventional colonoscopy images, is the appearance of Aberrant Crypt Foci (ACF). These are clusters of abnormal crypts, morphologically characterized by an atypical behavior of the cells that populate the crypts. In this work an homogenization model is proposed, for representing the cellular dynamics in the colon epithelium. The goal is to simulate and predict, in silico, the spread and evolution of ACF, as it can be observed in colonoscopy images. By assuming that the colon is an heterogeneous media, exhibiting a periodic distribution of crypts, we start this work by describing a periodic model, that represents the ACF cell-dynamics in a two-dimensional setting. Then, homogenization techniques are applied to this periodic model, to find a simpler model, whose solution symbolizes the averaged behavior of ACF at the tissue level. Some theoretical results concerning the existence of solution of the homogenized model are proven, applying a fixed point theorem. Numerical results showing the convergence of the periodic model to the homogenized model are presented.Comment: 26 pages, 4 figure

A Class of Mathematical Programs with Equilibrium Constraints: A Smooth Algorithm and Applications to Contact Problems

We discuss a special mathematical programming problem with equilibrium constraints (MPEC), that arises in material and shape optimization problems involving the contact of a rod or a plate with a rigid obstacle. This MPEC can be reduced to a nonlinear programming problem with independent variables and some dependent variables implicity defined by the solution of a mixed linear complementarity problem (MLCP). A projected-gradient algorithm including a complementarity method is proposed to solve this optimization problem. Several numerical examples are reported to illustrate the efficiency of this methodology in practice

The root microbiome of Salicornia ramosissima as a seedbank for plant-growth promoting halotolerant bacteria

Root−associated microbial communities play important roles in the process of adaptation of plant hosts to environment stressors, and in this perspective, the microbiome of halophytes represents a valuable model for understanding the contribution of microorganisms to plant tolerance to salt. Although considered as the most promising halophyte candidate to crop cultivation, Salicornia ramosissima is one of the least-studied species in terms of microbiome composition and the effect of sediment properties on the diversity of plant-growth promoting bacteria associated with the roots. In this work, we aimed at isolating and characterizing halotolerant bacteria associated with the rhizosphere and root tissues of S. ramosissima, envisaging their application in saline agriculture. Endophytic and rhizosphere bacteria were isolated from wild and crop cultivated plants, growing in different estuarine conditions. Isolates were identified based on 16S rRNA sequences and screened for plant-growth promotion traits. The subsets of isolates from different sampling sites were very different in terms of composition but consistent in terms of the plant-growth promoting traits represented. Bacillus was the most represented genus and expressed the wider range of extracellular enzymatic activities. Halotolerant strains of Salinicola, Pseudomonas, Oceanobacillus, Halomonas, Providencia, Bacillus, Psychrobacter and Brevibacterium also exhibited several plant-growth promotion traits (e.g., 3-indole acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, siderophores, phosphate solubilization). Considering the taxonomic diversity and the plant-growth promotion potential of the isolates, the collection represents a valuable resource that can be used to optimize the crop cultivation of Salicornia under different environmental conditions and for the attenuation of salt stress in non-halophytes, considering the global threat of arable soil salinization.publishe

Genotypes at the APOE and SCA2 loci do not predict the course of multiple sclerosis in patients of Portuguese origin

Prova tipográfica (In Press)Multiple sclerosis (MS) is a demyelinating disease that affects about one in 500 young Europeans. In order to test the previously proposed influence of the APOE and SCA2 loci on susceptibility to MS, we studied these loci in 243 Portuguese patients and 192 healthy controls and both parents of 92 patients. We did not detect any significant difference when APOE and SCA2 allele frequencies of cases and controls were compared, or when we compared cases with different forms of the disease. Disequilibrium of transmission was tested for both loci in the 92 trios, and we did not observe segregation distortion. To test the influence of the APOE o4 and SCA2 22 CAGs alleles on severity of disease, we compared age at onset and progression rate between groups with and without those alleles. We did not observe an association of the o4 or the 22 CAGs alleles with rate of progression in our total patient population; allele o4 was associated with increased rate of progression of MS in a subset of patients with less than 10 years of the disease. However, globally in the Portuguese population, the APOE and SCA2 genes do not seem to be useful in the clinical context as prognostic markers of this disorder.Fundação para a Ciência e a Tecnologia (FCT) - grant SFRH/BD/9111/2002.Serono Portugal

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

XAF1 as a modifier of p53 function and cancer susceptibility

Cancer risk is highly variable in carriers of the common TP53-R337H founder allele, possibly due to the influence of modifier genes. Whole-genome sequencing identified a variant in the tumor suppressor XAF1 (E134*/Glu134Ter/rs146752602) in a subset of R337H carriers. Haplotype-defining variants were verified in 203 patients with cancer, 582 relatives, and 42,438 newborns. The compound mutant haplotype was enriched in patients with cancer, conferring risk for sarcoma (P = 0.003) and subsequent malignancies (P = 0.006). Functional analyses demonstrated that wild-type XAF1 enhances transactivation of wild-type and hypomorphic TP53 variants, whereas XAF1-E134* is markedly attenuated in this activity. We propose that cosegregation of XAF1-E134* and TP53-R337H mutations leads to a more aggressive cancer phenotype than TP53-R337H alone, with implications for genetic counseling and clinical management of hypomorphic TP53 mutant carriers.Fil: Pinto, Emilia M.. St. Jude Children's Research Hospital; Estados UnidosFil: Figueiredo, Bonald C.. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Chen, Wenan. St. Jude Children's Research Hospital; Estados UnidosFil: Galvao, Henrique C.R.. Hospital de Câncer de Barretos; BrasilFil: Formiga, Maria Nirvana. A.c.camargo Cancer Center; BrasilFil: Fragoso, Maria Candida B.V.. Universidade de Sao Paulo; BrasilFil: Ashton Prolla, Patricia. Universidade Federal do Rio Grande do Sul; BrasilFil: Ribeiro, Enilze M.S.F.. Universidade Federal do Paraná; BrasilFil: Felix, Gabriela. Universidade Federal da Bahia; BrasilFil: Costa, Tatiana E.B.. Hospital Infantil Joana de Gusmao; BrasilFil: Savage, Sharon A.. National Cancer Institute; Estados UnidosFil: Yeager, Meredith. National Cancer Institute; Estados UnidosFil: Palmero, Edenir I.. Hospital de Câncer de Barretos; BrasilFil: Volc, Sahlua. Hospital de Câncer de Barretos; BrasilFil: Salvador, Hector. Hospital Sant Joan de Deu Barcelona; EspañaFil: Fuster Soler, Jose Luis. Hospital Clínico Universitario Virgen de la Arrixaca; EspañaFil: Lavarino, Cinzia. Hospital Sant Joan de Deu Barcelona; EspañaFil: Chantada, Guillermo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. St. Jude Children's Research Hospital; Estados UnidosFil: Vaur, Dominique. Comprehensive Cancer Center François Baclesse; FranciaFil: Odone Filho, Vicente. Universidade de Sao Paulo; BrasilFil: Brugières, Laurence. Institut de Cancerologie Gustave Roussy; FranciaFil: Else, Tobias. University of Michigan; Estados UnidosFil: Stoffel, Elena M.. University of Michigan; Estados UnidosFil: Maxwell, Kara N.. University of Pennsylvania; Estados UnidosFil: Achatz, Maria Isabel. Hospital Sirio-libanês; BrasilFil: Kowalski, Luis. A.c.camargo Cancer Center; BrasilFil: De Andrade, Kelvin C.. National Cancer Institute; Estados UnidosFil: Pappo, Alberto. St. Jude Children's Research Hospital; Estados UnidosFil: Letouze, Eric. Centre de Recherche Des Cordeliers; FranciaFil: Latronico, Ana Claudia. Universidade de Sao Paulo; BrasilFil: Mendonca, Berenice B.. Universidade de Sao Paulo; BrasilFil: Almeida, Madson Q.. Universidade de Sao Paulo; BrasilFil: Brondani, Vania B.. Universidade de Sao Paulo; BrasilFil: Bittar, Camila M.. Universidade Federal do Rio Grande do Sul; BrasilFil: Soares, Emerson W.S.. Hospital Do Câncer de Cascavel; BrasilFil: Mathias, Carolina. Universidade Federal do Paraná; BrasilFil: Ramos, Cintia R.N.. Hospital de Câncer de Barretos; BrasilFil: Machado, Moara. National Cancer Institute; Estados UnidosFil: Zhou, Weiyin. National Cancer Institute; Estados UnidosFil: Jones, Kristine. National Cancer Institute; Estados UnidosFil: Vogt, Aurelie. National Cancer Institute; Estados UnidosFil: Klincha, Payal P.. National Cancer Institute; Estados UnidosFil: Santiago, Karina M.. A.c.camargo Cancer Center; BrasilFil: Komechen, Heloisa. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Paraizo, Mariana M.. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Parise, Ivy Z.S.. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Hamilton, Kayla V.. St. Jude Children's Research Hospital; Estados UnidosFil: Wang, Jinling. St. Jude Children's Research Hospital; Estados UnidosFil: Rampersaud, Evadnie. St. Jude Children's Research Hospital; Estados UnidosFil: Clay, Michael R.. St. Jude Children's Research Hospital; Estados UnidosFil: Murphy, Andrew J.. St. Jude Children's Research Hospital; Estados UnidosFil: Lalli, Enzo. Institut de Pharmacologie Moléculaire et Cellulaire; FranciaFil: Nichols, Kim E.. St. Jude Children's Research Hospital; Estados UnidosFil: Ribeiro, Raul C.. St. Jude Children's Research Hospital; Estados UnidosFil: Rodriguez-Galindo, Carlos. St. Jude Children's Research Hospital; Estados UnidosFil: Korbonits, Marta. Queen Mary University of London; Reino UnidoFil: Zhang, Jinghui. St. Jude Children's Research Hospital; Estados UnidosFil: Thomas, Mark G.. Colegio Universitario de Londres; Reino UnidoFil: Connelly, Jon P.. St. Jude Children's Research Hospital; Estados UnidosFil: Pruett-Miller, Shondra. St. Jude Children's Research Hospital; Estados UnidosFil: Diekmann, Yoan. Colegio Universitario de Londres; Reino UnidoFil: Neale, Geoffrey. St. Jude Children's Research Hospital; Estados UnidosFil: Wu, Gang. St. Jude Children's Research Hospital; Estados UnidosFil: Zambetti, Gerard P.. St. Jude Children's Research Hospital; Estados Unido