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The selaginella genome identifies genetic changes associated with the evolution of vascular plants
(2011)
Vascular plants appeared similar to 410 million years ago, then diverged into several lineages of which only two survive: the euphyllophytes (ferns and seed plants) and the lycophytes. We report here the genome sequence of the lycophyte Selaginella moellendorffii (Selaginella), the first nonseed vascular plant genome reported. By comparing gene content in evolutionarily diverse taxa, we found that the transition from a gametophyte- to a sporophyte-dominated life cycle required far fewer new genes than the transition from a nonseed vascular to a flowering plant, whereas secondary metabolic genes expanded extensively and in parallel in the lycophyte and angiosperm lineages. Selaginella differs in posttranscriptional gene regulation, including small RNA regulation of repetitive elements, an absence of the trans-acting small interfering RNA pathway, and extensive RNA editing of organellar genes.
We report the discovery of two new Galactic candidate luminous blue variable (LBV) stars via detection of circular shells (typical of confirmed and candidate LBVs) and follow-up spectroscopy of their central stars. The shells were detected at 22 mu m in the archival data of the Mid-Infrared All Sky Survey carried out with the Wide-field Infrared Survey Explorer (WISE). Follow-up optical spectroscopy of the central stars of the shells conducted with the renewed Southern African Large Telescope (SALT) showed that their spectra are very similar to those of the well-known LBVs P Cygni and AG Car, and the recently discovered candidate LBV MN112, which implies the LBV classification for these stars as well. The LBV classification of both stars is supported by detection of their significant photometric variability: one of them brightened in the R and I bands by 0.68 +/- 0.10 and 0.61 +/- 0.04 mag, respectively, during the last 1318 years, while the second one (known as Hen 3-1383) varies its B, V, R, I and Ks brightnesses by similar or equal to 0.50.9 mag on time-scales from 10 d to decades. We also found significant changes in the spectrum of Hen 3-1383 on a time-scale of similar or equal to 3 months, which provides additional support for the LBV classification of this star. Further spectrophotometric monitoring of both stars is required to firmly prove their LBV status. We discuss a connection between the location of massive stars in the field and their fast rotation, and suggest that the LBV activity of the newly discovered candidate LBVs might be directly related to their possible runaway status.
To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or birth cohorts) and followed up three lead signals in six replication studies (combined N = 19,089). rs7980687 on chromosome 12q24 (P = 8.1 x 10(-9)) and rs1042725 on chromosome 12q15 (P = 2.8 x 10(-10)) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height(1), their effects on infant head circumference were largely independent of height (P = 3.8 x 10(-7) for rs7980687 and P = 1.3 x 10(-7) for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P = 3.9 x 10(-6)). SNPs correlated to the 17q21 signal have shown genome-wide association with adult intracranial volume(2), Parkinson's disease and other neurodegenerative diseases(3-5), indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Femtosecond x-ray laser pulses are used to probe the carbon monoxide (CO) oxidation reaction on ruthenium (Ru) initiated by an optical laser pulse. On a time scale of a few hundred femtoseconds, the optical laser pulse excites motions of CO and oxygen (O) on the surface, allowing the reactants to collide, and, with a transient close to a picosecond (ps), new electronic states appear in the OK-edge x-ray absorption spectrum. Density functional theory calculations indicate that these result from changes in the adsorption site and bond formation between CO and O with a distribution of OC-O bond lengths close to the transition state (TS). After 1 ps, 10% of the CO populate the TS region, which is consistent with predictions based on a quantum oscillator model.
A catalog of genetic loci associated with kidney function from analyses of a million individuals
(2019)
Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
We show that coadsorbed oxygen atoms have a dramatic influence on the CO desorption dynamics from Ru(0001). In contrast to the precursor-mediated desorption mechanism on Ru(0001), the presence of surface oxygen modifies the electronic structure of Ru atoms such that CO desorption occurs predominantly via the direct pathway. This phenomenon is directly observed in an ultrafast pump-probe experiment using a soft x-ray free-electron laser to monitor the dynamic evolution of the valence electronic structure of the surface species. This is supported with the potential of mean force along the CO desorption path obtained from density-functional theory calculations. Charge density distribution and frozen-orbital analysis suggest that the oxygen-induced reduction of the Pauli repulsion, and consequent increase of the dative interaction between the CO 5 sigma and the charged Ru atom, is the electronic origin of the distinct desorption dynamics. Ab initio molecular dynamics simulations of CO desorption from Ru(0001) and oxygen-coadsorbed Ru(0001) provide further insights into the surface bond-breaking process.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Context. Very massive stars pass through the Wolf-Rayet (WR) stage before they finally explode. Details of their evolution have not yet been safely established, and their physics are not well understood. Their spectral analysis requires adequate model atmospheres, which have been developed step by step during the past decades and account in their recent version for line blanketing by the millions of lines from iron and iron-group elements. However, only very few WN stars have been re-analyzed by means of line-blanketed models yet. Aims. The quantitative spectral analysis of a large sample of Galactic WN stars with the most advanced generation of model atmospheres should provide an empirical basis for various studies about the origin, evolution, and physics of the Wolf-Rayet stars and their powerful winds. Methods. We analyze a large sample of Galactic WN stars by means of the Potsdam Wolf-Rayet (PoWR) model atmospheres, which account for iron line blanketing and clumping. The results are compared with a synthetic population, generated from the Geneva tracks for massive star evolution. Results. We obtain a homogeneous set of stellar and atmospheric parameters for the GalacticWN stars, partly revising earlier results. Conclusions. Comparing the results of our spectral analyses of the Galactic WN stars with the predictions of the Geneva evolutionary calculations, we conclude that there is rough qualitative agreement. However, the quantitative discrepancies are still severe, and there is no preference for the tracks that account for the effects of rotation. It seems that the evolution of massive stars is still not satisfactorily understood.