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We prove the hitherto hypothesized sequential dissociation of Fe(CO)(5) in the gas phase upon photoexcitation at 266 nm via a singlet pathway with time-resolved valence and core-level photoelectron spectroscopy with an x-ray free-electron laser. Valence photoelectron spectra are used to identify free CO molecules and to determine the time constants of stepwise dissociation to Fe(CO)(4) within the temporal resolution of the experiment and further to Fe(CO)(3) within 3 ps. Fe 3p core-level photoelectron spectra directly reflect the singlet spin state of the Fe center in Fe(CO)(5), Fe(CO)(4), and Fe(CO)(3) showing that the dissociation exclusively occurs along a singlet pathway without triplet-state contribution. Our results are important for assessing intra- and intermolecular relaxation processes in the photodissociation dynamics of the prototypical Fe(CO)(5) complex in the gas phase and in solution, and they establish time-resolved core-level photoelectron spectroscopy as a powerful tool for determining the multiplicity of transition metals in photochemical reactions of coordination complexes. Published by AIP Publishing.
Palaeogenomes of Eurasian straight-tusked elephants challenge the current view of elephant evolution
(2017)
The straight-tusked elephants Palaeoloxodon spp. were widespread across Eurasia during the Pleistocene. Phylogenetic reconstructions using morphological traits have grouped them with Asian elephants (Elephas maximus), and many paleontologists place Palaeoloxodon within Elephas. Here, we report the recovery of full mitochondrial genomes from four and partial nuclear genomes from two P. antiquus fossils. These fossils were collected at two sites in Germany, Neumark-Nord and Weimar-Ehringsdorf, and likely date to interglacial periods similar to 120 and similar to 244 thousand years ago, respectively. Unexpectedly, nuclear and mitochondrial DNA analyses suggest that P. antiquus was a close relative of extant African forest elephants (Loxodonta cyclotis). Species previously referred to Palaeoloxodon are thus most parsimoniously explained as having diverged from the lineage of Loxodonta, indicating that Loxodonta has not been constrained to Africa. Our results demonstrate that the current picture of elephant evolution is in need of substantial revision.
To calibrate delta O-18 time-series from speleothems in the eastern Indian summer monsoon (ISM) region of India, and to understand the moisture regime over the northern Bay of Bengal (BoB) we analyze the delta O-18 and delta D of rainwater, collected in 2007 and 2008 near Cherrapunji, India. delta D values range from + 18.5 parts per thousand to 144.4 parts per thousand, while delta O-18 varies between +0.8 parts per thousand and 18.8 parts per thousand. The Local Meteoric Water Line (LMWL) is found to be indistinguishable from the Global Meteoric Water Line (GMWL). Late ISM (September-October) rainfall exhibits lowest delta O-18 and delta D values, with little relationship to the local precipitation amount. There is a trend to lighter isotope values over the course of the ISM, but it does not correlate with the patterns of temperature and rainfall amount delta O-18 and delta D time-series have to be interpreted with caution in terms of the 'amount effect' in this subtropical region. We find that the temporal trend in delta O-18 reflects increasing transport distance during the ISM, isotopic changes in the northern BoB surface waters during late ISM, and vapor re-equilibration with rain droplets. Using an isotope box model for surface ocean waters, we quantify the potential influence of river runoff on the isotopic composition of the seasonal freshwater plume in the northern BoB. Temporal variations in this source can contribute up to 25% of the observed changes in stable isotopes of precipitation in NE India. To delineate other moisture sources, we use backward trajectory computations and find a strong correlation between source region and isotopic composition. Palaeoclimatic stable isotope time-series from northeast Indian speleothems likely reflect changes in moisture source and transport pathway, as well as the isotopic composition of the BoB surface water, all of which in turn reflect ISM strength. Stalagmite records from the region can therefore be interpreted as integrated measures of the ISM strength.
Arsenic-containing hydrocarbons (AsHCs), natural products found in seafood, have recently been shown to exert toxic effects in human neurons. In this study we assessed the toxicity of three AsHCs in cultured human astrocytes. Due to the high cellular accessibility and substantial toxicity observed astrocytes were identified as further potential brain target cells for arsenolipids. Thereby, the AsHCs exerted a 5-19-fold higher cytotoxicity in astrocytes as compared to arsenite. Next we compared the toxicity of the arsenicals in a co-culture model of the respective human astrocytes and neurons. Notably the AsHCs did not show any substantial toxic effects in the co-culture, while arsenite did. The arsenic accessibility studies indicated that in the co-culture astrocytes protect neurons against cellular arsenic accumulation especially after incubation with arsenolipids. In summary, these data underline the importance of the glial-neuron interaction when assessing the in vitro neurotoxicity of new unclassified metal species.
Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists.
Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs.
Thermal permafrost degradation and coastal erosion in the Arctic remobilize substantial amounts of organic carbon (OC) and nutrients which have accumulated in late Pleistocene and Holocene unconsolidated deposits. Permafrost vulnerability to thaw subsidence, collapsing coastlines and irreversible landscape change are largely due to the presence of large amounts of massive ground ice such as ice wedges. However, ground ice has not, until now, been considered to be a source of dissolved organic carbon (DOC), dissolved inorganic carbon (DIC) and other elements which are important for ecosystems and carbon cycling. Here we show, using biogeochemical data from a large number of different ice bodies throughout the Arctic, that ice wedges have the greatest potential for DOC storage, with a maximum of 28.6 mg L-1 (mean: 9.6 mg L-1). Variation in DOC concentration is positively correlated with and explained by the concentrations and relative amounts of typically terrestrial cations such as Mg2+ and K+. DOC sequestration into ground ice was more effective during the late Pleistocene than during the Holocene, which can be explained by rapid sediment and OC accumulation, the prevalence of more easily degradable vegetation and immediate incorporation into permafrost. We assume that pristine snowmelt is able to leach considerable amounts of well-preserved and highly bioavailable DOC as well as other elements from surface sediments, which are rapidly frozen and stored in ground ice, especially in ice wedges, even before further degradation. We found that ice wedges in the Yedoma region represent a significant DOC (45.2 Tg) and DIC (33.6 Tg) pool in permafrost areas and a freshwater reservoir of 4200 km(2). This study underlines the need to discriminate between particulate OC and DOC to assess the availability and vulnerability of the permafrost car-bon pool for ecosystems and climate feedback upon mobilization.
Although the climate development over the Holocene in the Northern Hemisphere is well known, palaeolimnological climate reconstructions reveal spatiotemporal variability in northern Eurasia. Here we present a multi-proxy study from north-eastern Siberia combining sediment geochemistry, and diatom and pollen data from lake-sediment cores covering the last 38,000 cal. years. Our results show major changes in pyrite content and fragilarioid diatom species distributions, indicating prolonged seasonal lake-ice cover between similar to 13,500 and similar to 8900 cal. years BP and possibly during the 8200 cal. years BP cold event. A pollen-based climate reconstruction generated a mean July temperature of 17.8 degrees C during the Holocene Thermal Maximum (HTM) between similar to 8900 and similar to 4500 cal. years BP. Naviculoid diatoms appear in the late Holocene indicating a shortening of the seasonal ice cover that continues today. Our results reveal a strong correlation between the applied terrestrial and aquatic indicators and natural seasonal climate dynamics in the Holocene. Planktonic diatoms show a strong response to changes in the lake ecosystem due to recent climate warming in the Anthropocene. We assess other palaeolimnological studies to infer the spatiotemporal pattern of the HTM and affirm that the timing of its onset, a difference of up to 3000 years from north to south, can be well explained by climatic teleconnections. The westerlies brought cold air to this part of Siberia until the Laurentide ice sheet vanished 7000 years ago. The apparent delayed ending of the HTM in the central Siberian record can be ascribed to the exceedance of ecological thresholds trailing behind increases in winter temperatures and decreases in contrast in insolation between seasons during the mid to late Holocene as well as lacking differentiation between summer and winter trends in paleolimnological reconstructions. (C) 2015 Elsevier Ltd. All rights reserved.
Background:
COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.
Objective:
The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points.
Methods:
We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.
Results:
Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction.
Conclusions:
We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.