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The Great Hungarian Plain was a crossroads of cultural transformations that have shaped European prehistory. Here we analyse a 5,000-year transect of human genomes, sampled from petrous bones giving consistently excellent endogenous DNA yields, from 13 Hungarian Neolithic, Copper, Bronze and Iron Age burials including two to high (similar to 22x) and seven to similar to 1x coverage, to investigate the impact of these on Europe's genetic landscape. These data suggest genomic shifts with the advent of the Neolithic, Bronze and Iron Ages, with interleaved periods of genome stability. The earliest Neolithic context genome shows a European hunter-gatherer genetic signature and a restricted ancestral population size, suggesting direct contact between cultures after the arrival of the first farmers into Europe. The latest, Iron Age, sample reveals an eastern genomic influence concordant with introduced Steppe burial rites. We observe transition towards lighter pigmentation and surprisingly, no Neolithic presence of lactase persistence.
1,4-Di(homo)allyl-2,5-diketopiperazines are synthesized and polymerized via ADMET using the Hoveyda-Grubbs 2nd generation catalyst. The but-3-enylated diketopiperazine can be converted into unsaturated tertiary polyamide with molar mass of <3000 g mol(-1), whereas the allylated diketopiperazine cannot. Double-bond isomerization occurs regardless of whether or not benzoquinone is present. A polyesteramide with a higher molar mass of ca. 4800 g mol(-1) is obtained by the alternating copolymerization (ALTMET) of 1,4-di(but-3-enyl)-2,5-di ketopiperazine and ethylene glycol diacrylate. A post-polymerization modification of the poly(ester)amides via radical thiol-ene chemistry, however, fails.
The mid- to late Holocene interval is characterised by a highly variable climate in response to a gradual change in orbital insolation. The seasonal impact of these changes on the Eifel Maar region is not yet well documented largely due to uncertainties about the completeness of this archive ("missing varves" in the well known Lake Holzmaar) and a limited understanding of the factors (e.g. temperature, precipitation) influencing the seasonality archived within the lamination/varves. In this study we approach these challenges from a different perspective. Using detailed microfacies investigations we: (1) demonstrate that the ambiguity about the "missing varves" is related to the climate induced complex biotic and abiotic laminations that led to mis-identification of varves; (2) use a combination of detailed microfacies investigations (varve structure, seasonality of biotic and abiotic signals), lamination quality, varve counts on multiple cores, published and new radiocarbon dates to develop a continuous master chronology based on the Bayesian modelling approach. The dates of major climate, volcanic, and archaeological event(s) determined using our model are in good agreement with the independently determined ages of the same events from other archives, confirming the accuracy of our age model; (3) test the sensitivity of the seasonal proxies to the available data on mid-Holocene changes in temperature and precipitation; (4) demonstrate that the changes in lake eutrophicity are correlative with temperature changes in NW Europe and probably triggered by solar variability; and (5) show that the early Iron Age onset of eutrophication in Lake Holzmaar was climate induced and began several decades before the impact of anthropogenic activity was seen in the form of intensified detrital erosion in the catchment area. Our work has implications for understanding the impact of climate change and anthropogenic activities on limnological systems. (C) 2014 Elsevier B.V. All rights reserved.
Two dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOF-MS) is a promising technique to overcome limits of complex metabolome analysis using one dimensional GC-TOF-MS. Especially at the stage of data export and data mining, however, convenient procedures to cope with the complexity of GCxGC-TOF-MS data are still in development. Here, we present a high sample throughput protocol exploiting first and second retention index for spectral library search and subsequent construction of a high dimensional data matrix useful for statistical analysis. The method was applied to the analysis of 13 C-labelling experiments in the unicellular green alga Chlamydomonas reinhardtii. We developed a rapid sampling and extraction procedure for Chlamydomonas reinhardtii laboratory strain (CC503), a cell wall deficient mutant. By testing all published quenching protocols we observed dramatic metabolite leakage rates for certain metabolites. To circumvent metabolite leakage, samples were directly quenched and analyzed without separation of the medium. The growth medium was adapted to this rapid sampling protocol to avoid interference with GCxGC-TOF-MS analysis. To analyse batches of samples a new software tool, MetMax, was implemented which extracts the isotopomer matrix from stable isotope labelling experiments together with the first and second retention index (RI1 and RI2). To exploit RI1 and RI2 for metabolite identification we used the Golm metabolome database (GMD [1] with RI1/ RI2-reference spectra and new search algorithms. Using those techniques we analysed the dynamics of (CO2)-C-13 and C-13- acetate uptake in Chlamydomonas reinhardtii cells in two different steady states namely photoautotrophic and mixotrophic growth conditions.