The stellar and sub-stellar IMF of simple and composite populations

The current knowledge on the stellar IMF is documented. It appears to become top-heavy when the star-formation rate density surpasses about 0.1Msun/(yr pc^3) on a pc scale and it may become increasingly bottom-heavy with increasing metallicity and in increasingly massive early-type galaxies. It declines quite steeply below about 0.07Msun with brown dwarfs (BDs) and very low mass stars having their own IMF. The most massive star of mass mmax formed in an embedded cluster with stellar mass Mecl correlates strongly with Mecl being a result of gravitation-driven but resource-limited growth and fragmentation induced starvation. There is no convincing evidence whatsoever that massive stars do form in isolation. Various methods of discretising a stellar population are introduced: optimal sampling leads to a mass distribution that perfectly represents the exact form of the desired IMF and the mmax-to-Mecl relation, while random sampling results in statistical variations of the shape of the IMF. The observed mmax-to-Mecl correlation and the small spread of IMF power-law indices together suggest that optimally sampling the IMF may be the more realistic description of star formation than random sampling from a universal IMF with a constant upper mass limit. Composite populations on galaxy scales, which are formed from many pc scale star formation events, need to be described by the integrated galactic IMF. This IGIMF varies systematically from top-light to top-heavy in dependence of galaxy type and star formation rate, with dramatic implications for theories of galaxy formation and evolution.Comment: 167 pages, 37 figures, 3 tables, published in Stellar Systems and Galactic Structure, Vol.5, Springer. This revised version is consistent with the published version and includes additional references and minor additions to the text as well as a recomputed Table 1. ISBN 978-90-481-8817-

Timeless Links Replication Termination to Mitotic Kinase Activation

The mechanisms that coordinate the termination of DNA replication with progression through mitosis are not completely understood. The human Timeless protein (Tim) associates with S phase replication checkpoint proteins Claspin and Tipin, and plays an important role in maintaining replication fork stability at physical barriers, like centromeres, telomeres and ribosomal DNA repeats, as well as at termination sites. We show here that human Tim can be isolated in a complex with mitotic entry kinases CDK1, Auroras A and B, and Polo-like kinase (Plk1). Plk1 bound Tim directly and colocalized with Tim at a subset of mitotic structures in M phase. Tim depletion caused multiple mitotic defects, including the loss of sister-chromatid cohesion, loss of mitotic spindle architecture, and a failure to exit mitosis. Tim depletion caused a delay in mitotic kinase activity in vivo and in vitro, as well as a reduction in global histone H3 S10 phosphorylation during G2/M phase. Tim was also required for the recruitment of Plk1 to centromeric DNA and formation of catenated DNA structures at human centromere alpha satellite repeats. Taken together, these findings suggest that Tim coordinates mitotic kinase activation with termination of DNA replication

EMF1 and PRC2 Cooperate to Repress Key Regulators of Arabidopsis Development

EMBRYONIC FLOWER1 (EMF1) is a plant-specific gene crucial to Arabidopsis vegetative development. Loss of function mutants in the EMF1 gene mimic the phenotype caused by mutations in Polycomb Group protein (PcG) genes, which encode epigenetic repressors that regulate many aspects of eukaryotic development. In Arabidopsis, Polycomb Repressor Complex 2 (PRC2), made of PcG proteins, catalyzes trimethylation of lysine 27 on histone H3 (H3K27me3) and PRC1-like proteins catalyze H2AK119 ubiquitination. Despite functional similarity to PcG proteins, EMF1 lacks sequence homology with known PcG proteins; thus, its role in the PcG mechanism is unclear. To study the EMF1 functions and its mechanism of action, we performed genome-wide mapping of EMF1 binding and H3K27me3 modification sites in Arabidopsis seedlings. The EMF1 binding pattern is similar to that of H3K27me3 modification on the chromosomal and genic level. ChIPOTLe peak finding and clustering analyses both show that the highly trimethylated genes also have high enrichment levels of EMF1 binding, termed EMF1_K27 genes. EMF1 interacts with regulatory genes, which are silenced to allow vegetative growth, and with genes specifying cell fates during growth and differentiation. H3K27me3 marks not only these genes but also some genes that are involved in endosperm development and maternal effects. Transcriptome analysis, coupled with the H3K27me3 pattern, of EMF1_K27 genes in emf1 and PRC2 mutants showed that EMF1 represses gene activities via diverse mechanisms and plays a novel role in the PcG mechanism

Nicotinic Receptors Underlying Nicotine Dependence: Evidence from Transgenic Mouse Models.

Nicotine underlies the reinforcing properties of tobacco cigarettes and e-cigarettes. After inhalation and absorption, nicotine binds to various nicotinic acetylcholine receptor (nAChR) subtypes localized on the pre- and postsynaptic membranes of cells, which subsequently leads to the modulation of cellular function and neurotransmitter signaling. In this chapter, we begin by briefly reviewing the current understanding of nicotine's actions on nAChRs and highlight considerations regarding nAChR subtype localization and pharmacodynamics. Thereafter, we discuss the seminal discoveries derived from genetically modified mouse models, which have greatly contributed to our understanding of nicotine's effects on the reward-related mesolimbic pathway and the aversion-related habenulo-interpeduncular pathway. Thereafter, emerging areas of research focusing on modulation of nAChR expression and/or function are considered. Taken together, these discoveries have provided a foundational understanding of various genetic, neurobiological, and behavioral factors underlying the motivation to use nicotine and related dependence processes, which are thereby advancing drug discovery efforts to promote long-term abstinence

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions