Species interactions differ in their genetic robustness

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica. The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.The authors thank reviewers for comments that substantially improved this manuscript. BG and DS were partially supported by grants from the US Department of Energy (DE-SC0004962) and NIH (R01GM089978 and R01GM103502). (DE-SC0004962 - US Department of Energy; R01GM089978 - NIH; R01GM103502 - NIH)Published versio

Competition and Post-Transplant Outcomes in Cadaveric Liver Transplantation under the MELD Scoring System

Previous researchers have modelled the decision to accept a donor organ for transplantation as a Markov decision problem, the solution to which is often a control-limit optimal policy: accept any organ whose match quality exceeds some health-dependent threshold; otherwise, wait for another. When competing transplant centers vie for the same organs, the decision rule changes relative to no competition; the relative size of competing centers affects the decision rules as well. Using center-specific graft and patient survival-rate data for cadaveric adult livers in the United States, we have found empirical evidence supporting these predictions.liver transplantation, competition, optimal stopping

Competition and Post-Transplant Outcomes in Cadaveric Liver Transplantation under the MELD Scoring System

Previous researchers have modelled the decision to accept a donor organ for transplantation as a Markov decision problem, the solution to which is often a control-limit optimal policy: accept any organ whose match quality exceeds some health-dependent threshold; otherwise, wait for another. When competing transplant centers vie for the same organs, the decision rule changes relative to no competition; the relative size of competing centers affects the decision rules as well. Using center-specific graft and patient survival-rate data for cadaveric adult livers in the United States, we have found empirical evidence supporting these predictions.liver transplantation; competition; optimal stopping

Levi umbilical surfaces in complex space

We define a complex connection on a real hypersurface of \C^{n+1} which is naturally inherited from the ambient space. Using a system of Codazzi-type equations, we classify connected real hypersurfaces in \C^{n+1}, $n\ge 2$, which are Levi umbilical and have non zero constant Levi curvature. It turns out that such surfaces are contained either in a sphere or in the boundary of a complex tube domain with spherical section.Comment: 18 page

MLIP: using multiple processors to compute the posterior probability of linkage

<p>Abstract</p> <p>Background</p> <p>Localization of complex traits by genetic linkage analysis may involve exploration of a vast multidimensional parameter space. The posterior probability of linkage (PPL), a class of statistics for complex trait genetic mapping in humans, is designed to model the trait model complexity represented by the multidimensional parameter space in a mathematically rigorous fashion. However, the method requires the evaluation of integrals with no functional form, making it difficult to compute, and thus further test, develop and apply. This paper describes MLIP, a multiprocessor two-point genetic linkage analysis system that supports statistical calculations, such as the PPL, based on the full parameter space implicit in the linkage likelihood.</p> <p>Results</p> <p>The fundamental question we address here is whether the use of additional processors effectively reduces total computation time for a PPL calculation. We use a variety of data – both simulated and real – to explore the question "how close can we get?" to linear speedup. Empirical results of our study show that MLIP does significantly speed up two-point log-likelihood ratio calculations over a grid space of model parameters.</p> <p>Conclusion</p> <p>Observed performance of the program is dependent on characteristics of the data including granularity of the parameter grid space being explored and pedigree size and structure. While work continues to further optimize performance, the current version of the program can already be used to efficiently compute the PPL. Thanks to MLIP, full multidimensional genome scans are now routinely being completed at our centers with runtimes on the order of days, not months or years.</p

Monte-Carlo simulation of events with Drell-Yan lepton pairs from antiproton-proton collisions

The complete knowledge of the nucleon spin structure at leading twist requires also addressing the transverse spin distribution of quarks, or transversity, which is yet unexplored because of its chiral-odd nature. Transversity can be best extracted from single-spin asymmetries in fully polarized Drell-Yan processes with antiprotons, where valence contributions are involved anyway. Alternatively, in single-polarized Drell-Yan the transversity happens convoluted with another chiral-odd function, which is likely to be responsible for the well known (and yet unexplained) violation of the Lam-Tung sum rule in the corresponding unpolarized cross section. We present Monte-Carlo simulations for the unpolarized and single-polarized Drell-Yan $\bar{p} p^{(\uparrow)} \to \mu^+ \mu^- X$ at different center-of-mass energies in both configurations where the antiproton beam hits a fixed proton target or it collides on another proton beam. The goal is to estimate the minimum number of events needed to extract the above chiral-odd distributions from future measurements at the HESR ring at GSI. It is important to study the feasibility of such experiments at HESR in order to demonstrate that interesting spin physics can be explored already using unpolarized antiprotons.Comment: Deeply revised text with improved discussion of kinematics and results; added one table; 12 figures. Accepted for publication in Phys. Rev.

Italian and Argentine olive oils: a NMR and gas chromatographic study

High-field Nuclear Magnetic Resonance (NMR) spectroscopy and Gas Chromatography (GC) were used to analyze 16 monovarietal olive oils obtained from few matched Mediterranean cultivars grown in experimental fields located in Italy and in the Catamarca region of Argentina. The Catamarca region is characterized by extreme pedoclimatic conditions and by a wild spontaneous vegetation. The proposed sampling allows to study the effect of different pedoclimatic conditions on olive oil composition. GC gives the fatty acid profile of olive oil samples. 1H and 13C NMR techniques provide different information: the 1H NMR spectrum allows the measurement of minor components of olive oils such as b-sytosterol, hexanal, trans-2-hexenal, formaldehyde, squalene, cycloartenol and linolenic acid; the 1C NMR spectrum allows to obtain information about glycerol tri-esters of olive oils, i.e., about their acyl composition and positional distribution on glycerol moiety. All the NMR and GC results have been submitted to Linear Discriminant Analysis (LDA) and Tree Cluster Analysis (TCA). A careful analysis of the statistical results allows to select the Mediterranean cultivars less affected by the climatic conditions present in the Catamarca region. The selected cultivars produce olive oils which keep their Mediterranean characteristics and which can be proposed as colonizing plants in this wild Argentine region.La espectroscopía de Resonancia Magnética Nuclear de alta resolución (RMN) y Cromatografía Gaseosa (CG) fueron utilizadas para analizar 16 monovariedades de aceites de oliva, obtenidas de algunos olivares Mediterráneos cultivados contemporáneamente en campos experimentales localizados en Italia y en la región de Catamarca en Argentina. Estas muestras permiten estudiar diferentes condiciones pedoclimáticas en la composición de los aceite de oliva. La CG proporciona el perfil en ácidos grasos de los aceites de oliva y las técnicas RMN 1H y RMN 13C suministran diferentes informaciones: el espectro RMN 1H permite medir los componentes menores del aceite de oliva tales como b-sitoesterol, hexanol, trans - 2 hexanol, formaldehido, escualeno, cicloartenol y ácido linolénico y el espectro RMN 13C da información referente a los triésteres de glicerol de los aceites de oliva, por ejemplo, la composición y distribución de la posición acílica en el glicerol. Los datos de CG y RMN han sido sometidos a un análisis discriminante lineal (LDA) y a un análisis cluster en árbol (TCA). Un minucioso análisis de estos resultados ha permitido seleccionar olivares que han sido menos afectados por las condiciones climáticas presentes en la región de Catamarca. Los olivares seleccionados producen aceites de oliva que pueden mantener sus características Mediterráneas y pueden ser propuestos como plantas colonizantes en esta región silvestre de Argentina

Intrauterine growth curves in a high-income population

OBJECTIVE: growth curves can be used to assess intrauterine growth, to predict diseases in newborns, and to characterize different populations. The objective of this study was to obtain intrauterine growth curves of newborns from the maternity ward of the Hospital Albert Einstein (MAE) and compare them with intrauterine growth curves of a population from California, USA. METHODS: We plotted the growth curves according to weight at birth and gestational age, which was obtained according to information from the mother, after the 32nd week of gestation, between February 1995 and February 1999. We calculated the birth weights for the 10th, 50th, and 90th percentiles of weight at birth for each gestational age and compared them with those of the growth curves from California. RESULTS: The growth curves for the 10th and the 50th percentiles did not differ from the California growth curves. For the 90th percentile, however, the MAE growth curves were lower than those of California. The MAE population presented fewer small-for-gestational age (SGA) and big-for-gestational age (BGA) newborns when assessed according to the California curves. The categories of SGA, normal, and BGA for both male and female newborns indicated a statistically significant relation with the weight gain of mothers. CONCLUSIONS: The two populations assessed in this study were different according to intrauterine growth curves. Further studies should be carried out in order to identify specific factors that may be acting on the MAE population.OBJETIVO: as curvas de percentil constituem uma das formas de avaliação do crescimento intra-uterino e podem predizer doenças do recém-nascido como também caracterizar uma população. Este trabalho teve por objetivo construir as curvas de crescimento intra-uterino dos recém-nascidos da Maternidade do Hospital Albert Einstein (MAE), hospital que atende a uma população de alto nível socioeconômico, e comparar com as curvas de crescimento intra-uterino de uma população norte-americana da Califórnia. MÉTODOS: foram construídas curvas de crescimento intra-uterino a partir do peso do recém-nascido de parto único, tomado logo após o nascimento, e da idade gestacional segundo informações maternas, a partir da 32ª. semana de idade gestacional, abrangendo os nascimentos ocorridos na MAE no período de fevereiro de 1995 a fevereiro de 1999. Foram calculados os percentis 10, 50 e 90 do peso ao nascer para cada idade gestacional e comparados com os das curvas da Califórnia. RESULTADOS: as curvas dos percentis 10 e 50 na população da MAE não diferiram das curvas da Califórnia. Para o percentil 90, a curva da MAE ficou abaixo das curvas da Califórnia. Houve número menor de pequenos e grandes para a idade gestacional (PIG e GIG) quando classificados pelas curvas da Califórnia. A classificação em PIG, AIG, GIG mostrou-se relacionada significantemente com o ganho de peso materno nos dois sexos. CONCLUSÕES: as duas populações analisadas segundo as curvas de crescimento intra-uterino são diferentes entre si; deverão ser identificados fatores específicos que atuem na população da MAE.UNIFESP-EPMSociedade Beneficente Israelita Brasileira Hospital Albert Einstein Instituto de Ensino e PesquisaUSPPrefeitura Municipal de São Paulo Serviços em SaúdeUNIFESP, EPMSciEL