Intramolecular C-13 pattern in hexoses from autotrophic and heterotrophic C-3 plant tissues

The stable carbon isotope 13C is used as a universal tracer in plant eco-physiology and studies of carbon exchange between vegetation and atmosphere. Photosynthesis fractionates against 13CO2 so that source sugars (photosynthates) are on average 13C depleted by 20% compared with atmospheric CO2. The carbon isotope distribution within sugars has been shown to be heterogeneous, with relatively 13C-enriched and 13C-depleted C-atom positions. The 13C pattern within sugars is the cornerstone of 13C distribution in plants, because all metabolites inherit the 13C abundance in their specific precursor C-atom positions. However, the intramolecular isotope pattern in source leaf glucose and the isotope fractionation associated with key enzymes involved in sugar interconversions are currently unknown. To gain insight into these, we have analyzed the intramolecular isotope composition in source leaf transient starch, grain storage starch, and root storage sucrose and measured the site-specific isotope fractionation associated with the invertase (EC 3.2.1.26) and glucose isomerase (EC 5.3.1.5) reactions. When these data are integrated into a simple steady-state model of plant isotopic fluxes, the enzyme-dependent fractionations satisfactorily predict the observed intramolecular patterns. These results demonstrate that glucose and sucrose metabolism is the primary determinant of the 13C abundance in source and sink tissue and is, therefore, of fundamental importance to the interpretation of plant isotopic signals

Factorized Q-Learning for Large-Scale Multi-Agent Systems

Deep Q-learning has achieved significant success in single-agent decision making tasks. However, it is challenging to extend Q-learning to large-scale multi-agent scenarios, due to the explosion of action space resulting from the complex dynamics between the environment and the agents. In this paper, we propose to make the computation of multi-agent Q-learning tractable by treating the Q-function (w.r.t. state and joint-action) as a high-order high-dimensional tensor and then approximate it with factorized pairwise interactions. Furthermore, we utilize a composite deep neural network architecture for computing the factorized Q-function, share the model parameters among all the agents within the same group, and estimate the agents' optimal joint actions through a coordinate descent type algorithm. All these simplifications greatly reduce the model complexity and accelerate the learning process. Extensive experiments on two different multi-agent problems demonstrate the performance gain of our proposed approach in comparison with strong baselines, particularly when there are a large number of agents.Comment: 7 pages, 5 figures, DAI 201

Disentangling multiproxy temperature reconstructions from the subtropical North Atlantic

Reliable reconstruction of past sea surface temperature (SST) is of prime importance for understanding the Earth’s sensitivity to external forcing. Yet, it remains a major challenge in paleoceanography because comparison between SST estimates from different proxies reveals mismatches and raise the question as to what the contrasting proxies actually record. A better understanding of these mismatches in the light of seasonal occurrence of the proxy bearing organisms (archives) and water mass changes help to assess climate models. Here, we analyze data from the last deglaciation using a sediment core site situated at the northern boundary of the North Atlantic subtropical gyre influenced by fast latitudinal migrations of the subtropical Azores Front (AF) and resulting changes in water masses that may affect the SST records. Differences between the SST estimates from different deglacial SST reconstructions obtained from (1) Mg/Ca in planktic foraminifer tests, (2) alkenone UK′37, and (3) planktic foraminifer assemblages (SIMMAX), are assumed to result from the ecology of the proxy bearing organisms, and are assessed for the impact on different SST reconstructions from local seawater δ18O (δ18Ow) reconstructions. The general trends of SSTs from all four proxies confirm the well-known deglacial succession of warm and cold events. Mismatches between amplitudes of temperature changes are explained by differences in the phenology of the proxy-bearing organisms and local changes in hydrography. The combination of δ18O SST from the three different archives of δ18Ow reconstructions may cause offsets that exceed the climate driven signals

Toward System Change to Tackle Antimicrobial Resistance: Improving the Voluntary Stewardship of Antimicrobials in US Agriculture

From Executive Summary:This report presents the details of a research study looking at the potential for improving voluntary stewardship of antimicrobials in US agriculture, in the interests of tackling antimicrobial resistance (AMR). Failure to address AMR could lead to significant impacts on both human and animal health. Voluntary stewardship is an approach that relies on the willingness of food-animal producers and supportive industries (e.g., veterinary services and pharmaceutical companies), as well as broader stakeholders (e.g., public health policymakers and consumer advocates), to ensure the judicious use of antimicrobials without the need for regulation, legislation, mandatory compliance or statutory enforcement

Stellar Astrophysics and Exoplanet Science with the Maunakea Spectroscopic Explorer (MSE)

The Maunakea Spectroscopic Explorer (MSE) is a planned 11.25-m aperture facility with a 1.5 square degree field of view that will be fully dedicated to multi-object spectroscopy. A rebirth of the 3.6m Canada-France-Hawaii Telescope on Maunakea, MSE will use 4332 fibers operating at three different resolving powers (R ~ 2500, 6000, 40000) across a wavelength range of 0.36-1.8mum, with dynamical fiber positioning that allows fibers to match the exposure times of individual objects. MSE will enable spectroscopic surveys with unprecedented scale and sensitivity by collecting millions of spectra per year down to limiting magnitudes of g ~ 20-24 mag, with a nominal velocity precision of ~100 m/s in high-resolution mode. This white paper describes science cases for stellar astrophysics and exoplanet science using MSE, including the discovery and atmospheric characterization of exoplanets and substellar objects, stellar physics with star clusters, asteroseismology of solar-like oscillators and opacity-driven pulsators, studies of stellar rotation, activity, and multiplicity, as well as the chemical characterization of AGB and extremely metal-poor stars.Comment: 31 pages, 11 figures; To appear as a chapter for the Detailed Science Case of the Maunakea Spectroscopic Explore

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Exploring manycore architectures for next-generation HPC systems through the MANGO approach

[EN] The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High-Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit customization to adapt computing resources to reach the desired QoS. For this purpose, it explores different but interrelated mechanisms across the architecture and system software. In particular, in this paper we focus on the runtime resource management, the thermal management, and support provided for parallel programming, as well as introducing three applications on which the project foreground will be validated.This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 671668.Flich Cardo, J.; Agosta, G.; Ampletzer, P.; Atienza-Alonso, D.; Brandolese, C.; Cappe, E.; Cilardo, A.... (2018). Exploring manycore architectures for next-generation HPC systems through the MANGO approach. Microprocessors and Microsystems. 61:154-170. https://doi.org/10.1016/j.micpro.2018.05.011S1541706

Genome Sequencing of SHH Medulloblastoma Predicts Genotype-Related Response to Smoothened Inhibition

SummarySmoothened (SMO) inhibitors recently entered clinical trials for sonic-hedgehog-driven medulloblastoma (SHH-MB). Clinical response is highly variable. To understand the mechanism(s) of primary resistance and identify pathways cooperating with aberrant SHH signaling, we sequenced and profiled a large cohort of SHH-MBs (n = 133). SHH pathway mutations involved PTCH1 (across all age groups), SUFU (infants, including germline), and SMO (adults). Children >3 years old harbored an excess of downstream MYCN and GLI2 amplifications and frequent TP53 mutations, often in the germline, all of which were rare in infants and adults. Functional assays in different SHH-MB xenograft models demonstrated that SHH-MBs harboring a PTCH1 mutation were responsive to SMO inhibition, whereas tumors harboring an SUFU mutation or MYCN amplification were primarily resistant