Statistical evaluation of alternative models of human evolution

An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species approximately 141 thousand years ago (Kya), an exit out-of-Africa approximately 51 Kya, and a recent colonization of the Americas approximately 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

The nuclear factor-kappaB and p53 pathways function independently in primary cells and transformed fibroblasts responding to genotoxic damage

With nuclear factor-kappaB (NF-kappaB) and p53 functions generally having disparate outcomes for cell survival and cell division, understanding how these pathways are coordinated following a common activation signal such as DNA damage has important implications for cancer therapy. Conflicting reports concerning NF-kappaB and p53 interplay in different cell line models prompted a reexamination of this issue using mouse primary thymocytes and embryonic fibroblasts, plus fibroblasts transformed by E1A12S. Here, we report that following the treatment of these cells with a range of stress stimuli, p53 and NF-kappaB were found to regulate cell cycling and survival independently.

The Effect of the Japan 2011 Disaster on Nuclear and Alternative Energy Stocks Worldwide: An Event Study

This event study investigates the impact of the Japanese nuclear disaster in Fukushima-Daiichi on the daily stock prices of French, German, Japanese, and U.S. nuclear utility and alternative energy firms. Hypotheses regarding the (cumulative) abnormal returns based on a three-factor model are analyzed through joint tests by multivariate regression models and bootstrapping. Our results show significant abnormal returns for Japanese nuclear utility firms during the one-week event window and the subsequent four-week post-event window. Furthermore, while French and German nuclear utility and alternative energy stocks exhibit significant abnormal returns during the event window, we cannot confirm abnormal returns for U.S. stocks.

Nuclear and plastid markers reveal the persistence of genetic identity: A new perspective on the evolutionary history of Petunia exserta

Recently divergent species that can hybridize are ideal models for investigating the genetic exchanges that can occur while preserving the species boundaries. Petunia exserta is an endemic species from a very limited and specific area that grows exclusively in rocky shelters. These shaded spots are an inhospitable habitat for all other Petunia species, including the closely related and widely distributed species P. axillaris. Individuals with intermediate morphologic characteristics have been found near the rocky shelters and were believed to be putative hybrids between P. exserta and P. axillaris, suggesting a situation where Petunia exserta is losing its genetic identity. In the current study, we analyzed the plastid intergenic spacers trnS/trnG and trnH/psbA and six nuclear CAPS markers in a large sampling design of both species to understand the evolutionary process occurring in this biological system. Bayesian clustering methods, cpDNA haplotype networks, genetic diversity statistics, and coalescence-based analyses support a scenario where hybridization occurs while two genetic clusters corresponding to two species are maintained. Our results reinforce the importance of coupling differentially inherited markers with an extensive geographic sample to assess the evolutionary dynamics of recently diverged species that can hybridize. (C) 2013 Elsevier Inc. All rights reserved.

Nuclear organization in the nematode C. elegans.

With its invariant cell lineage, easy genetics and small genome, the nematode Caenorhabditis elegans has emerged as one of the prime models in developmental biology over the last 50 years. Surprisingly however, until a decade ago very little was known about nuclear organization in worms, even though it is an ideal model system to explore the link between nuclear organization and cell fate determination. Here, we review the latest findings that exploit the repertoire of genetic tools developed in worms, leading to the identification of important sequences and signals governing the changes in chromatin tridimensional architecture. We also highlight parallels and differences to other model systems.

Building silent compartments at the nuclear periphery: a recurrent theme.

In eukaryotes, the genetic material is stored in the nucleus, which is enclosed in a double lipid bilayer, the nuclear envelope (NE). It protects the genome from physical stress and separates it from the rest of the cell. On top of this physical function, growing evidence shows that the nuclear periphery contributes to the 3D organization of the genome. In turn, tridimensional organization of chromatin in the nuclear space influences genome expression. Here we review recent findings on the function of this physical barrier in gene repression and latest models on how silent subnuclear compartments at the NE are built in yeast as well as in the nematode C. elegans and mammalian cells; trying to draw parallels between the three systems.

Repeat length and RNA expression level are not primary determinants in CUG expansion toxicity in Drosophila models.

Evidence for an RNA gain-of-function toxicity has now been provided for an increasing number of human pathologies. Myotonic dystrophies (DM) belong to a class of RNA-dominant diseases that result from RNA repeat expansion toxicity. Specifically, DM of type 1 (DM1), is caused by an expansion of CUG repeats in the 3'UTR of the DMPK protein kinase mRNA, while DM of type 2 (DM2) is linked to an expansion of CCUG repeats in an intron of the ZNF9 transcript (ZNF9 encodes a zinc finger protein). In both pathologies the mutant RNA forms nuclear foci. The mechanisms that underlie the RNA pathogenicity seem to be rather complex and not yet completely understood. Here, we describe Drosophila models that might help unravelling the molecular mechanisms of DM1-associated CUG expansion toxicity. We generated transgenic flies that express inducible repeats of different type (CUG or CAG) and length (16, 240, 480 repeats) and then analyzed transgene localization, RNA expression and toxicity as assessed by induced lethality and eye neurodegeneration. The only line that expressed a toxic RNA has a (CTG)(240) insertion. Moreover our analysis shows that its level of expression cannot account for its toxicity. In this line, (CTG)(240.4), the expansion inserted in the first intron of CG9650, a zinc finger protein encoding gene. Interestingly, CG9650 and (CUG)(240.4) expansion RNAs were found in the same nuclear foci. In conclusion, we suggest that the insertion context is the primary determinant for expansion toxicity in Drosophila models. This finding should contribute to the still open debate on the role of the expansions per se in Drosophila and in human pathogenesis of RNA-dominant diseases.

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Apoptosis of hippocampal neurons in organotypic slice culture models: direct effect of bacteria revisited

Neurons of the hippocampal dentate gyrus selectively undergo programmed cell death in patients suffering from bacterial meningitis and in experimental models of pneumococcal meningitis in infant rats. In the present study, a membrane-based organotypic slice culture system of rat hippocampus was used to test whether this selective vulnerability of neurons of the dentate gyrus could be reproduced in vitro. Apoptosis was assessed by nuclear morphology (condensed and fragmented nuclei), by immunochemistry for active caspase-3 and deltaC-APP, and by proteolytic caspase-3 activity. Co-incubation of the cultures with live pneumococci did not induce neuronal apoptosis unless cultures were kept in partially nutrient-deprived medium. Complete nutrient deprivation alone and staurosporine independently induced significant apoptosis, the latter in a dose-response way. In all experimental settings, apoptosis occurred preferentially in the dentate gyrus. Our data demonstrate that factors released by pneumococci per se failed to induce significant apoptosis in vitro. Thus, these factors appear to contribute to a multifactorial pathway, which ultimately leads to neuronal apoptosis in bacterial meningitis.

Models of hybridization during range expansions and their application to recent human evolution

Several lines of genetic, archeological and paleontological evidence suggest that anatomically modern humans (Homo sapiens) colonized the world in the last 60,000 years by a series of migrations originating from Africa (e.g. Liu et al., 2006; Handley et al., 2007; Prugnolle, Manica, and Balloux, 2005; Ramachandran et al. 2005; Li et al. 2008; Deshpande et al. 2009; Mellars, 2006a, b; Lahr and Foley, 1998; Gravel et al., 2011; Rasmussen et al., 2011). With the progress of ancient DNA analysis, it has been shown that archaic humans hybridized with modern humans outside Africa. Recent direct analyses of fossil nuclear DNA have revealed that 1–4 percent of the genome of Eurasian has been likely introgressed by Neanderthal genes (Green et al., 2010; Reich et al., 2010; Vernot and Akey, 2014; Sankararaman et al., 2014; Prufer et al., 2014; Wall et al., 2013), with Papua New Guineans and Australians showing even larger levels of admixture with Denisovans (Reich et al., 2010; Skoglund and Jakobsson, 2011; Reich et al., 2011; Rasmussen et al., 2011). It thus appears that the past history of our species has been more complex than previously anticipated (Alves et al., 2012), and that modern humans hybridized several times with local hominins during their expansion out of Africa, but the exact mode, time and location of these hybridizations remain to be clarifi ed (Ibid.; Wall et al., 2013). In this context, we review here a general model of admixture during range expansion, which lead to some predictions about expected patterns of introgression that are relevant to modern human evolution.

All-loop anomalous dimensions in integrable λ-deformed σ-models

We calculate the all-loop anomalous dimensions of current operators in λ-deformed σ-models. For the isotropic integrable deformation and for a semi-simple group G we compute the anomalous dimensions using two different methods. In the first we use the all-loop effective action and in the second we employ perturbation theory along with the Callan–Symanzik equation and in conjunction with a duality-type symmetry shared by these models. Furthermore, using CFT techniques we compute the all-loop anomalous dimension of bilinear currents for the isotropic deformation case and a general G . Finally we work out the anomalous dimension matrix for the cases of anisotropic SU(2) and the two couplings, corresponding to the symmetric coset G/H and a subgroup H, splitting of a group G.

Collaboration patterns, external shocks and uncertainty: Swiss nuclear energy politics before and after Fukushima

Energy shocks like the Fukushima accident can have important political consequences. This article examines their impact on collaboration patterns between collective actors in policy processes. It argues that external shocks create both behavioral uncertainty, meaning that actors do not know about other actors' preferences, and policy uncertainty on the choice and consequences of policy instruments. The context of uncertainty interacts with classical drivers of actor collaboration in policy processes. The analysis is based on a dataset comprising interview and survey data on political actors in two subsequent policy processes in Switzerland and Exponential Random Graph Models for network data. Results first show that under uncertainty, collaboration of actors in policy processes is less based on similar preferences than in stable contexts, but trust and knowledge of other actors are more important. Second, under uncertainty, scientific actors are not preferred collaboration partners.

The transcription factor nuclear factor kappa B (NFkappaB) maintains TRAIL resistance in human pancreatic cancer cells

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL/Apo2L) is a member of the TNF family of cytokines that induces apoptosis in a variety of tumor cells while sparing normal cells. However, many human cancer cell lines display resistance to TRAIL-induced apoptosis and the mechanisms contributing to resistance remain controversial. Previous studies have demonstrated that the dimeric transcription factor Nuclear Factor kappa B (NFκB) is constitutively active in a majority of human pancreatic cancer cell lines and primary tumors, and although its role in tumor progression remains unclear it has been suggested that NFκB contributes to TRAIL resistance. Based on this, I examined the effects of NFκB inhibitors on TRAIL sensitivity in a panel of nine pancreatic cancer cell lines. I show here that inhibitors of NFκB, including two inhibitors of the proteasome (bortezomib (Velcade™, PS-341) and NPI-0052), a small molecule inhibitor of IKK (PS1145), and a novel synthetic diterpene NIK inhibitor (NPI-1342) reverse TRAIL resistance in pancreatic cancer cell lines. Further analysis revealed that the expression of the anti-apoptosic proteins BclXL and XIAP was significantly decreased following exposure to these inhibitors alone and in combination with TRAIL. Additionally, treatment with NPI0052 and TRAIL significantly reduced tumor burden relative to the control tumors in an L3.6pl orthotopic pancreatic xenograft model. This was associated with a significant decrease in proliferation and an increase in caspase 3 and 8 cleavage. Combination therapy employing PS1145 or NPI-1342 in combination with TRAIL also resulted in a significant reduction in tumor burden compared to either agent alone in a Panc1 orthotopic xenograft model. My studies show that combination therapy with inhibitors of NFκB alone and TRAIL is effective in pre-clinical models of pancreatic cancer and suggests that the approach should be evaluated in patients. ^

MRI and Bidimensional relaxometry sequences for macro and microstructure assessment in food models.

Physico-chemical and organoleptic characteristics of food depend largely on the microscopic level distribution of gases and water, and connectivity and mobility through the pores. Microstructural characterization of food can be accomplished by Magnetic Resonance Imaging (MRI) and Nuclear Magnetic Spectroscopy (NMR) combined with the application of methods of dissemination and multidimensional relaxometry. In this work, funded by the EC Project InsideFood, several artificial food models, based on foams and gels were studied using MRI and 2D relaxometry. Two different kinds of foams were used: a sugarless and a sugar foam. Then, a half of a syringe was filled with the sugarless foam and the other half with the sugar foam. Then, MRI and NMR experiments were performed and the sample evolution was observed along 3 days in order to quantify macrostructural changes through proton density images and microstructural ones using T1T2 maps, using an inversion CPMG sequence. On the proton density images it may be seen that after 16 hours it was possible to differentiate the macrostructural changes, as the apparition of free water due to a syneresis phenomenon. On the interface it can be seen a brighter area after 16 hours, due to the occurrence of free water. Moreover, thanks to the bidimensional relaxometry (T1-T2) it was possible to differentiate among microscopic changes. Differences between the pores size can be observed as well as the microstructure evolution after 30.5 hours, as a consequence differences are shown on free water redistribution through larger pores and capillarity phenomena between both foams.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.