Use of the frc gene as a molecular marker to characterize oxalate-oxidizing bacterial abundance and diversity structure in soil.

Oxalate catabolism, which can have both medical and environmental implications, is performed by phylogenetically diverse bacteria. The formyl-CoA-transferase gene was chosen as a molecular marker of the oxalotrophic function. Degenerated primers were deduced from an alignment of frc gene sequences available in databases. The specificity of primers was tested on a variety of frc-containing and frc-lacking bacteria. The frc-primers were then used to develop PCR-DGGE and real-time SybrGreen PCR assays in soils containing various amounts of oxalate. Some PCR products from pure cultures and from soil samples were cloned and sequenced. Data were used to generate a phylogenetic tree showing that environmental PCR products belonged to the target physiological group. The extent of diversity visualised on DGGE pattern was higher for soil samples containing carbonate resulting from oxalate catabolism. Moreover, the amount of frc gene copies in the investigated soils was detected in the range of 1.64x10(7) to 1.75x10(8)/g of dry soil under oxalogenic tree (representing 0.5 to 1.2% of total 16S rRNA gene copies), whereas the number of frc gene copies in the reference soil was 6.4x10(6) (or 0.2% of 16S rRNA gene copies). This indicates that oxalotrophic bacteria are numerous and widespread in soils and that a relationship exists between the presence of the oxalogenic trees Milicia excelsa and Afzelia africana and the relative abundance of oxalotrophic guilds in the total bacterial communities. This is obviously related to the accomplishment of the oxalate-carbonate pathway, which explains the alkalinization and calcium carbonate accumulation occurring below these trees in an otherwise acidic soil. The molecular tools developed in this study will allow in-depth understanding of the functional implication of these bacteria on carbonate accumulation as a way of atmospheric CO(2) sequestration.

Y-chromosome diversity in native mexicans reveals continental transition of genetic structure in the Americas

The genetic characterization of Native Mexicans is important to understand multiethnic based features influencing the medical genetics of present Mexican populations, as well as to the reconstruct the peopling of the Americas. We describe the Y-chromosome genetic diversity of 197 Native Mexicans from 11 populations and 1,044 individuals from 44 Native American populations after combining with publicly available data. We found extensive heterogeneity among Native Mexican populations and ample segregation of Q-M242* (46%) and Q-M3 (54%) haplogroups within Mexico. The northernmost sampled populations falling outside Mesoamerica (Pima and Tarahumara) showed a clear differentiation with respect to the other populations, which is in agreement with previous results from mtDNA lineages. However, our results point toward a complex genetic makeup of Native Mexicans whose maternal and paternal lineages reveal different narratives of their population history, with sex-biased continental contributions and different admixture proportions. At a continental scale, we found that Arctic populations and the northernmost groups from North America cluster together, but we did not find a clear differentiation within Mesoamerica and the rest of the continent, which coupled with the fact that the majority of individuals from Central and South American samples are restricted to the Q-M3 branch, supports the notion that most Native Americans from Mesoamerica southwards are descendants from a single wave of migration. This observation is compatible with the idea that present day Mexico might have constituted an area of transition in the diversification of paternal lineages during the colonization of the Americas.

A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations

Studies of large sets of SNP data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2,841 SNPs in 12 Sub-Saharan African populations, including a previously unsampled region of south-eastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1,000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in Sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the south-eastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region.

Supporting the reuse of effective CSCL learning designs through social structure representations

Distance and blended collaborative learning settings are usually characterized by different social structures defined in terms of groups' number, dimension, and composition; these structures are variable and can change within the same activity. This variability poses additional complexity to instructional designers, when they are trying to develop successful experiences from existing designs. This complexity is greatly associated with the fact that learning designs do not render explicit how social structures influenced the decisions of the original designer, and thus whether the social structures of the new setting could preclude the effectiveness of the reused design. This article proposes the usage of new representations (social structure representations, SSRs) able to support unskilled designers in reusing existing learning designs, through the explicit characterization of the social structures and constraints embedded either by the original designers or the reusing teachers, according to well-known principles of good collaborative learning practice. The article also describes an evaluation process that involved university professors, as well as the main findings derived from it. This process supported the initial assumptions about the effectiveness of SSRs, with significant evidence from both qualitative and qualitative data.

Molecular phylogeny and evolution of Sorex shrews (Soricidae: insectivora) inferred from mitochondrial DNA sequence data.

Shrews of the genus Sorex are characterized by a Holarctic distribution, and relationships among extant taxa have never been fully resolved. Phylogenies have been proposed based on morphological, karyological, and biochemical comparisons, but these analyses often produced controversial and contradictory results. Phylogenetic analyses of partial mitochondrial cytochrome b gene sequences (1011 bp) were used to examine the relationships among 27 Sorex species. The molecular data suggest that Sorex comprises two major monophyletic lineages, one restricted mostly to the New World and one with a primarily Palearctic distribution. Furthermore, several sister-species relationships are revealed by the analysis. Based on the split between the Soricinae and Crocidurinae subfamilies, we used a 95% confidence interval for both the calibration of a molecular clock and the subsequent calculation of major diversification events within the genus Sorex. Our analysis does not support an unambiguous acceleration of the molecular clock in shrews, the estimated rate being similar to other estimates of mammalian mitochondrial clocks. In addition, the data presented here indicate that estimates from the fossil record greatly underestimate divergence dates among Sorex taxa.

Structure and expression profile of the Arabidopsis PHO1 gene family indicates a broad role in inorganic phosphate homeostasis.

PHO1 has been recently identified as a protein involved in the loading of inorganic phosphate into the xylem of roots in Arabidopsis. The genome of Arabidopsis contains 11 members of the PHO1 gene family. The cDNAs of all PHO1 homologs have been cloned and sequenced. All proteins have the same topology and harbor a SPX tripartite domain in the N-terminal hydrophilic portion and an EXS domain in the C-terminal hydrophobic portion. The SPX and EXS domains have been identified in yeast (Saccharomyces cerevisiae) proteins involved in either phosphate transport or sensing or in sorting proteins to endomembranes. The Arabidopsis genome contains additional proteins of unknown function containing either a SPX or an EXS domain. Phylogenetic analysis indicated that the PHO1 family is subdivided into at least three clusters. Reverse transcription-PCR revealed a broad pattern of expression in leaves, roots, stems, and flowers for most genes, although two genes are expressed exclusively in flowers. Analysis of the activity of the promoter of all PHO1 homologs using promoter-beta-glucuronidase fusions revealed a predominant expression in the vascular tissues of roots, leaves, stems, or flowers. beta-Glucuronidase expression is also detected for several promoters in nonvascular tissue, including hydathodes, trichomes, root tip, root cortical/epidermal cells, and pollen grains. The expression pattern of PHO1 homologs indicates a likely role of the PHO1 proteins not only in the transfer of phosphate to the vascular cylinder of various tissues but also in the acquisition of phosphate into cells, such as pollen or root epidermal/cortical cells.

Estimating the basic reproductive number from viral sequence data.

Epidemiological processes leave a fingerprint in the pattern of genetic structure of virus populations. Here, we provide a new method to infer epidemiological parameters directly from viral sequence data. The method is based on phylogenetic analysis using a birth-death model (BDM) rather than the commonly used coalescent as the model for the epidemiological transmission of the pathogen. Using the BDM has the advantage that transmission and death rates are estimated independently and therefore enables for the first time the estimation of the basic reproductive number of the pathogen using only sequence data, without further assumptions like the average duration of infection. We apply the method to genetic data of the HIV-1 epidemic in Switzerland.

The interaction of ownership structure and customer satisfaction as determinants of brand equity

In this paper we study the interaction between ownership structure and customer satisfaction, and their impact on a firm's brand equity. We find that customer satisfaction has a positive direct effect on brand equity but an indirect negative one, through reductions in ownership concentration. This latter effect emerges when managers are focused mainly on satisfying customers. It gives out a warning signal that highlights the perverse effect of implementing policies focused excessively on satisfying customers at the expense of shareholders, on a firm's brand equity. We demonstrate our theoretical contention, empirically, making use of an incomplete panel data comprising 69 firms from 11 different nations for the period 2002-2005.

Structural characterization of rockfall sources in Yosemite Valley from remote sensing data and field surveys

Yosemite Valley poses significant rockfall hazard and related risk due to its glacially steepened walls and approximately 4 million visitors annually. To assess rockfall hazard, it is necessary to evaluate the geologic structure that contributes to the destabilization of rockfall sources and locate the most probable future source areas. Coupling new remote sensing techniques (Terrestrial Laser Scanning, Aerial Laser Scanning) and traditional field surveys, we investigated the regional geologic and structural setting, the orientation of the primary discontinuity sets for large areas of Yosemite Valley, and the specific discontinuity sets present at active rockfall sources. This information, combined with better understanding of the geologic processes that contribute to the progressive destabilization and triggering of granitic rock slabs, contributes to a more accurate rockfall susceptibility assessment for Yosemite Valley and elsewhere.

Intégration de méthodes de data mining dans le renseignement criminel : analyse par des structures issues de la théorie des graphes dans le profilage des stupéfiants

Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.

Some last thoughts on compositional data analysis

One of the disadvantages of old age is that there is more past than future: this,however, may be turned into an advantage if the wealth of experience and, hopefully,wisdom gained in the past can be reflected upon and throw some light on possiblefuture trends. To an extent, then, this talk is necessarily personal, certainly nostalgic,but also self critical and inquisitive about our understanding of the discipline ofstatistics. A number of almost philosophical themes will run through the talk: searchfor appropriate modelling in relation to the real problem envisaged, emphasis onsensible balances between simplicity and complexity, the relative roles of theory andpractice, the nature of communication of inferential ideas to the statistical layman, theinter-related roles of teaching, consultation and research. A list of keywords might be:identification of sample space and its mathematical structure, choices betweentransform and stay, the role of parametric modelling, the role of a sample spacemetric, the underused hypothesis lattice, the nature of compositional change,particularly in relation to the modelling of processes. While the main theme will berelevance to compositional data analysis we shall point to substantial implications forgeneral multivariate analysis arising from experience of the development ofcompositional data analysis…

Stepwise multiple testing as formalized data snooping

It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.

Debt and deficit fluctuations and the structure of bond markets

This paper tests for the market environment within which US fiscal policyoperates, that is we test for the incompleteness of the US government bondmarket. We document the stochastic properties of US debt and deficits andthen consider the ability of competing optimal tax models to account forthis behaviour. We show that when a government pursues an optimal taxpolicy and issues a full set of contingent claims, the value of debthas the same or less persistence than other variables in the economyand declines in response to higher deficit shocks. By contrast, ifgovernments only issue one-period risk free bonds (incomplete markets),debt shows more persistence than other variables and it increases inresponse to expenditure shocks. Maintaining the hypothesis of Ramseybehavior, US data conflicts.

Human capital, the structure of production and growth

Do high levels of human capital foster economic growth by facilitating technology adoption? If so, countries with more human capital should have adopted more rapidly the skilled-labor augmenting technologies becoming available since the 1970 s. High human capital levels should therefore have translated into fast growth in more compared to less human-capital-intensive industries in the 1980 s. Theories of international specialization point to human capital accumulation as another important determinant of growth in human-capital-intensive industries. Using data for a large sample of countries, we find significant positive effects of human capital levels and human capital accumulation on output and employment growth in human-capital-intensive industries.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.