The abrupt climate change at the Eocene-Oligocene boundary and the emergence of South-East Asia triggered the spread of sapindaceous lineages.

Background and Aims Paleoclimatic data indicate that an abrupt climate change occurred at the Eocene-Oligocene (E-O) boundary affecting the distribution of tropical forests on Earth. The same period has seen the emergence of South-East (SE) Asia, caused by the collision of the Eurasian and Australian plates. How the combination of these climatic and geomorphological factors affected the spatio-temporal history of angiosperms is little known. This topic is investigated by using the worldwide sapindaceous clade as a case study. Methods Analyses of divergence time inference, diversification and biogeography (constrained by paleogeography) are applied to a combined plastid and nuclear DNA sequence data set. Biogeographical and diversification analyses are performed over a set of trees to take phylogenetic and dating uncertainty into account. Results are analysed in the context of past climatic fluctuations. Key Results An increase in the number of dispersal events at the E-O boundary is recorded, which intensified during the Miocene. This pattern is associated with a higher rate in the emergence of new genera. These results are discussed in light of the geomorphological importance of SE Asia, which acted as a tropical bridge allowing multiple contacts between areas and additional speciation across landmasses derived from Laurasia and Gondwana. Conclusions This study demonstrates the importance of the combined effect of geomorphological (the emergence of most islands in SE Asia approx. 30 million years ago) and climatic (the dramatic E-O climate change that shifted the tropical belt and reduced sea levels) factors in shaping species distribution within the sapindaceous clade.

Evolutionary trajectories of primate genes involved in HIV pathogenesis.

The current availability of five complete genomes of different primate species allows the analysis of genetic divergence over the last 40 million years of evolution. We hypothesized that the interspecies differences observed in susceptibility to HIV-1 would be influenced by the long-range selective pressures on host genes associated with HIV-1 pathogenesis. We established a list of human genes (n = 140) proposed to be involved in HIV-1 biology and pathogenesis and a control set of 100 random genes. We retrieved the orthologous genes from the genome of humans and of four nonhuman primates (Pan troglodytes, Pongo pygmaeus abeli, Macaca mulatta, and Callithrix jacchus) and analyzed the nucleotide substitution patterns of this data set using codon-based maximum likelihood procedures. In addition, we evaluated whether the candidate genes have been targets of recent positive selection in humans by analyzing HapMap Phase 2 single-nucleotide polymorphisms genotyped in a region centered on each candidate gene. A total of 1,064 sequences were used for the analyses. Similar median K(A)/K(S) values were estimated for the set of genes involved in HIV-1 pathogenesis and for control genes, 0.19 and 0.15, respectively. However, genes of the innate immunity had median values of 0.37 (P value = 0.0001, compared with control genes), and genes of intrinsic cellular defense had K(A)/K(S) values around or greater than 1.0 (P value = 0.0002). Detailed assessment allowed the identification of residues under positive selection in 13 proteins: AKT1, APOBEC3G, APOBEC3H, CD4, DEFB1, GML, IL4, IL8RA, L-SIGN/CLEC4M, PTPRC/CD45, Tetherin/BST2, TLR7, and TRIM5alpha. A number of those residues are relevant for HIV-1 biology. The set of 140 genes involved in HIV-1 pathogenesis did not show a significant enrichment in signals of recent positive selection in humans (intraspecies selection). However, we identified within or near these genes 24 polymorphisms showing strong signatures of recent positive selection. Interestingly, the DEFB1 gene presented signatures of both interspecies positive selection in primates and intraspecies recent positive selection in humans. The systematic assessment of long-acting selective pressures on primate genomes is a useful tool to extend our understanding of genetic variation influencing contemporary susceptibility to HIV-1.

Common variants in the ATP2B1 gene are associated with susceptibility to hypertension: the Japanese Millennium Genome Project.

Hypertension is one of the most common complex genetic disorders. We have described previously 38 single nucleotide polymorphisms (SNPs) with suggestive association with hypertension in Japanese individuals. In this study we extend our previous findings by analyzing a large sample of Japanese individuals (n=14 105) for the most associated SNPs. We also conducted replication analyses in Japanese of susceptibility loci for hypertension identified recently from genome-wide association studies of European ancestries. Association analysis revealed significant association of the ATP2B1 rs2070759 polymorphism with hypertension (P=5.3×10(-5); allelic odds ratio: 1.17 [95% CI: 1.09 to 1.26]). Additional SNPs in ATP2B1 were subsequently genotyped, and the most significant association was with rs11105378 (odds ratio: 1.31 [95% CI: 1.21 to 1.42]; P=4.1×10(-11)). Association of rs11105378 with hypertension was cross-validated by replication analysis with the Global Blood Pressure Genetics consortium data set (odds ratio: 1.13 [95% CI: 1.05 to 1.21]; P=5.9×10(-4)). Mean adjusted systolic blood pressure was highly significantly associated with the same SNP in a meta-analysis with individuals of European descent (P=1.4×10(-18)). ATP2B1 mRNA expression levels in umbilical artery smooth muscle cells were found to be significantly different among rs11105378 genotypes. Seven SNPs discovered in published genome-wide association studies were also genotyped in the Japanese population. In the combined analysis with replicated 3 genes, FGF5 rs1458038, CYP17A1, rs1004467, and CSK rs1378942, odds ratio of the highest risk group was 2.27 (95% CI: 1.65 to 3.12; P=4.6×10(-7)) compared with the lower risk group. In summary, this study confirmed common genetic variation in ATP2B1, as well as FGF5, CYP17A1, and CSK, to be associated with blood pressure levels and risk of hypertension.

Breaking the panels: an application to the GDP per capita

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different speci¿cations are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is ¿exible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have an exact limit distribution with a good ¿nite sample performance. Its application to a typical panel data set of real per capita GDP gives support to the trend stationarity of these series

Estimating sex-specific dispersal rates with autosomal markers in hierarchically structured populations.

A recent study suggests that sex-specific dispersal rates can be quantitatively estimated on the basis of sex- and state-specific (pre- vs. postdispersal) F-statistics. In the present paper, we extend this approach to account for the hierarchical structure of natural populations, and we validate it through individual-based simulations. The model is applied to an empirical data set consisting of 536 individuals (males, females, and predispersal juveniles) of greater white-toothed shrews (Crocidura russula), sampled according to a hierarchical design and typed for seven autosomal microsatellite loci. From this dataset, dispersal is significantly female biased at the local scale (breeding-group level), but not at the larger scale (among local populations). We argue that selective pressures on dispersal are likely to depend on the spatial scale considered, and that short-distance dispersal should mainly respond to kin interactions (inbreeding or kin competition avoidance), which exert differential pressure on males and females.

Generational effects on adult height in individual heterogeneity

As adult height is a well-established retrospective measure of health and standard of living, it is important to understand the factors that determine it. Among them, the influence of socio-environmental factors has been subjected to empirical scrutiny. This paper explores the influence of generational (or environmental) effects and individual and gender-specific heterogeneity on adult height. Our data set is from contemporary Spain, a country governed by an authoritarian regime between 1939 and 1977. First, we use normal position and quantile regression analysis to identify the determinants of self-reported adult height and to measure the influence of individual heterogeneity. Second, we use a Blinder-Oaxaca decomposition approach to explain the `gender height gap¿ and its distribution, so as to measure the influence on this gap of individual heterogeneity. Our findings suggest a significant increase in adult height in the generations that benefited from the country¿s economic liberalization in the 1950s, and especially those brought up after the transition to democracy in the 1970s. In contrast, distributional effects on height suggest that only in recent generations has ¿height increased more among the tallest¿. Although the mean gender height gap is 11 cm, generational effects and other controls such as individual capabilities explain on average roughly 5% of this difference, a figure that rises to 10% in the lowest 10% quantile.

The UniProt-GO Annotation database in 2011.

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360,000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.

A theoretical and practical study on linear reforms of dual taxes

[cat] En aquest treball extenem les reformes lineals introduïdes per Pfähler (1984) al cas d’impostos duals. Estudiem l’efecte relatiu que els retalls lineals duals d’un impost dual tenen sobre la distribució de la desigualtat -es pot fer un estudi simètric per al cas d’augments d’impostos-. Tambe introduïm mesures del grau de progressivitat d’impostos duals i mostrem que estan connectades amb el criteri de dominació de Lorenz. Addicionalment, estudiem l’elasticitat de la càrrega fiscal de cadascuna de les reformes proposades. Finalment, gràcies a un model de microsimulació i una gran base de dades que conté informació sobre l’IRPF espanyol de l’any 2004, 1) comparem l’efecte que diferents reformes tindrien sobre l’impost dual espanyol i 2) estudiem quina redistribució de la riquesa va suposar la reforma dual de l’IRPF (Llei ’35/2006’) respecte l’anterior impost.

The determinants of social spending in Spain (1880-1960): Is Lindert right?

[spa] El principal objetivo de este artículo se centra en analizar los orígenes del Estado de Bienestar en España a partir del marco teórico elaborado por Peter Lindert. Con este fin, se ofrece un análisis econométrico de los factores que determinaron la evolución del gasto social público en este país entre 1880 y 1960. Utilizando nueva evidencia cuantitativa, se construyó un panel de datos por quinquenios con el porcentaje de gasto social respecto al PIB desagregado en tres partidas: sanidad, seguridad social y beneficencia. El análisis permite insertar el caso español en el debate internacional y los resultados revelan interesantes singularidades de este país.

Breaking the panels: an application to the GDP per capita

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different speci¿cations are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is ¿exible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have an exact limit distribution with a good ¿nite sample performance. Its application to a typical panel data set of real per capita GDP gives support to the trend stationarity of these series

Sibling competition and the risk of falling out of the nest

In birds, sibling competition encompasses several activities, one of which is jostling for position, that is, competing for the location in the nest where parents predictably deliver food items. We hypothesized that nestlings that compete by jostling for position may fall out of the nest either accidentally or because siblings push each other to reduce brood size. This hypothesis predicts that in a competitive environment needy nestlings trade-off the benefit of being fed against the cost of falling out of the nest. As a first attempt to evaluate this hypothesis, we experimentally manipulated the number of young per brood in the colonial Alpine swift, Apus melba. Nestlings fell out of their colony more frequently when reared in enlarged than in reduced broods. Because brood size manipulation affects not only the number of young per nest but also their body condition, we analysed an extended data set to disentangle these two factors. This analysis showed that, independently of brood size, nestlings in poor condition and those reared in broods where sibling differed markedly in weight were more likely to disappear from the colony. Nestling disappearance also occurred predominantly in nests close to the colony entrances. Although nestling swifts can wander in the colony and become adopted in neighbouring nests, we found no evidence that wandering per se increased the risk of falling out of the colony. Our study therefore highlights a novel cost of scramble competition.

Impacts on the deep-sea ecosystem by a severe coastal storm

Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26th of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem.

Pedotransfer functions to estimate proctor test parameters under different tillage systems

The Proctor test is time-consuming and requires sampling of several kilograms of soil. Proctor test parameters were predicted in Mollisols, Entisols and Vertisols of the Pampean region of Argentina under different management systems. They were estimated from a minimum number of readily available soil properties (soil texture, total organic C) and management (training data set; n = 73). The results were used to generate a soil compaction susceptibility model, which was subsequently validated using a second group of independent data (test data set; n = 24). Soil maximum bulk density was estimated as follows: Maximum bulk density (Mg m-3) = 1.4756 - 0.00599 total organic C (g kg-1) + 0.0000275 sand (g kg-1) + 0.0539 management. Management was equal to 0 for uncropped and untilled soils and 1 for conventionally tilled soils. The established models predicted the Proctor test parameters reasonably well, based on readily available soil properties. Tillage systems induced changes in the maximum bulk density regardless of total organic matter content or soil texture. The lower maximum apparent bulk density values under no-tillage require a revision of the relative compaction thresholds for different no-tillage crops.

Pavement Markings and Safety Final Report, November 2010

Previous research on pavement markings from a safety perspective tackled various issues such as pavement marking retroreflectivity variability, relationship between pavement marking retroreflectivity and driver visibility, or pavement marking improvements and safety. A recent research interest in this area has been to find a correlation between retroreflectivity and crashes, but a significant statistical relationship has not yet been found. This study investigates such a possible statistical relationship by analyzing five years of pavement marking retroreflectivity data collected by the Iowa Department of Transportation (DOT) on all state primary roads and corresponding crash and traffic data. This study developed a spatial-temporal database using measured retroreflectivity data to account for the deterioration of pavement markings over time along with statewide crash data to attempt to quantify a relationship between crash occurrence probability and pavement marking retroreflectivity. First, logistic regression analyses were done for the whole data set to find a statistical relationship between crash occurrence probability and identified variables, which are road type, line type, retroreflectivity, and traffic (vehicle miles traveled). The analysis looked into subsets of the data set such as road type, retroreflectivity measurement source, high crash routes, retroreflectivity range, and line types. Retroreflectivity was found to have a significant effect in crash occurrence probability for four data subsets—interstate, white edge line, yellow edge line, and yellow center line data. For white edge line and yellow center line data, crash occurrence probability was found to increase by decreasing values of retroreflectivity.

Roadway Lighting and Safety: Phase II – Monitoring Quality, Durability and Efficiency, November 2011

This Phase II project follows a previous project titled Strategies to Address Nighttime Crashes at Rural, Unsignalized Intersections. Based on the results of the previous study, the Iowa Highway Research Board (IHRB) indicated interest in pursuing further research to address the quality of lighting, rather than just the presence of light, with respect to safety. The research team supplemented the literature review from the previous study, specifically addressing lighting level in terms of measurement, the relationship between light levels and safety, and lamp durability and efficiency. The Center for Transportation Research and Education (CTRE) teamed with a national research leader in roadway lighting, Virginia Tech Transportation Institute (VTTI) to collect the data. An integral instrument to the data collection efforts was the creation of the Roadway Monitoring System (RMS). The RMS allowed the research team to collect lighting data and approach information for each rural intersection identified in the previous phase. After data cleanup, the final data set contained illuminance data for 101 lighted intersections (of 137 lighted intersections in the first study). Data analysis included a robust statistical analysis based on Bayesian techniques. Average illuminance, average glare, and average uniformity ratio values were used to classify quality of lighting at the intersections.