Global Carbon Budget 2018

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018

Cyr61 and YB-1 are novel interacting partners of uPAR and elevate the malignancy of triple-negative breast cancer.

The triple-negative breast cancer (TNBC) is a very aggressive tumor type often occurring in young women and is associated with a bad prognosis for the patients. TNBC lacks established targets for breast cancer therapy, such as the estrogen receptor (ER), progesterone receptor (PR) and the human epidermal growth factor receptor 2 (HER2). Therefore, novel therapeutic targets and strategies are needed for an improved treatment of this breast cancer subtype. TNBC and respective cell lines often overexpress proteins of the urokinase plasminogen activator system (uPAS) including uPA, its receptor uPAR and inhibitor PAI-1, which together with co-factors contribute to the malignancy of TNBC. Here, two novel interacting partners of uPAR, the cysteine-rich angiogenic inducer 61 (Cyr61) and the Y-box-binding protein 1 (YB-1) were identified and their differential expression demonstrated in TNBC cells as well as in tumors. In the TNBC cohort, both interactors significantly correlated with expression levels of cathepsin B, c-Met and the tumor grade. In addition, expression levels of Cyr61 significantly correlated with cathepsin D (p=0.03), insulin receptor (p≤0.001), insulin-like growth factor receptor 1 (IGF1R, p=0.015) and also with YB-1 (p=0.0004) levels. The interactions of uPAR with Cyr61 significantly correlated with expression levels of tumor-promoting biomarkers including plasminogen (p=0.0014), cathepsin B (p=0.032), c-Met (p=0.0192) as well as with the tumor grade (p=0.02). In multivariate survival analysis, YB-1 showed independent prognostic value (p=0.01). As the novel interacting partners, also together with uPAR, contribute to tumor progression and metastasis, both may be potential therapeutic targets in breast cancer

High-resolution metabolite imaging of light and dark treated retina using MALDI-FTICR mass spectrometry.

Mass spectrometry imaging (MSI) is a valuable tool for diagnostics and systems biology studies, being a highly sensitive, label-free technique capable of providing comprehensive spatial distribution of different classes of biomolecules. The application of MSI to the study of endogenous compounds has received considerable attention because metabolites are the result of the interactions of a biosystem with its environment. MSI can therefore enhance understanding of disease mechanisms and elucidate mechanisms for biological variation. Here we present the in situ comparative metabolomics imaging data for analyses of light- and dark-treated retina. A wide variety of tissue metabolites were imaged at a high spatial resolution. These include nucleotides, central carbon metabolism pathway intermediates, 2-oxocarboxylic acid metabolism, oxidative phosphorylation, glycerophospholipid metabolism, and cysteine and methionine metabolites. The high lateral resolution enabled the differentiation of retinal layers, allowing determination of the spatial distributions of different endogenous compounds. A number of metabolites demonstrated differences between light and dark conditions. These findings add to the understanding of metabolic activity in the retina. This article is protected by copyright. All rights reserved

A novel approach of MALDI drug imaging, immunohistochemistry, and digital image analysis for drug distribution studies in tissues.

Drug efficacy strongly depends on the presence of the drug substance at the target site. As vascularization is an important factor for the distribution of drugs in tissues, we analyzed drug distribution as a function of blood vessel localization in tumor tissue. In order to explore distribution of the anti-cancer drugs afatinib, erlotinib, and sorafenib, a combined approach of matrix-assisted laser desorption/ionization (MALDI) drug imaging and immunohistochemical vessel staining was applied and examined by digital image analysis. Two xenograft models were investigated: (1) mice carrying squamous cell carcinoma (FaDu) xenografts (ntumor=13) were treated with afatinib or erlotinib, and (2) sarcoma (A673) xenograft bearing mice (ntumor=8) received sorafenib treatment. MALDI drug imaging revealed a heterogeneous distribution of all anti-cancer drugs. The tumor regions containing high drug levels were associated with a higher degree of vascularization than the regions without drug signals (p<0.05). When correlating the impact of blood vessel size to drug abundance in the sarcoma model, a higher amount of small vessels was detected in the tumor regions with high drug levels compared to the tumor regions with low drug levels (p<0.05). With the analysis of co-registered MALDI imaging and CD31 immunohistochemical data by digital image analysis, we demonstrate for the first time the potential of correlating MALDI drug imaging and immunohistochemistry. Here we describe a specific and precise approach for correlating histological features and pharmacokinetic properties of drugs at microscopic level, that will provide information for the improvement of drug design, administration formula or treatment schemes

Lessons Learnt From Linking Global Recommendations With Localized Marine Restoration Schemes and Policy Options by Using Mixed Methods

In order to advance ongoing efforts in the (still emerging) field of marine restoration, different forms of knowledge must be combined: not only the biological and technical aspects, but also the social and cultural dimensions of marine restoration efforts. This calls for a newly combined array of methods that allows for a bridging of these different knowledge dimensions. Drawing on our experiences from the ongoing knowledge transfer processes of the INTERNAS project (Scientific Transfer of the results of INTERNational Assessments in the field of Earth and Environmental Research into the German policy context), we provide an overview of methods that were used to link global recommendations with localized marine restoration schemes and policy options. Using a mixed methods approach, we were able to capture and understand the pathways of knowledge transfer from globally synthesized scientific knowledge to local realities related to protecting and enhancing marine biodiversity in Germany. With this structured knowledge transfer approach, actionable solutions for marine conservation and restoration activities could be tailored to the specific national and regional circumstances. Using participatory methods, framework conditions like ecological, social, legal, and sectoral value judgment dimensions can be identified. This allows for the development of concerted solutions and creates a common ground for good governance towards marine restoration. When scientists engage not only as experts but also as reflexive facilitators in such participatory processes, it is ensured that more inclusive forms of knowledge are fostered that are necessary to better anticipate the potentials and likely pitfalls that marine restoration efforts may encounter. We conclude that existing knowledge on ecosystems, their goods and services as well as societal expectations need to be understood from the onset in any kind of marine restoration effort

Correction to: In vitro cellular and proteome assays identify Wnt pathway and CDKN2A-regulated senescence affected in mesenchymal stem cells from mice after a chronic LD gamma irradiation in utero.

Authors would like to correct the typo in author name of the co-author. The author name is corrected from "Ann Karin Olson" to "Ann Karin Olsen" in the original publication. The original article has been corrected

A rapid <em>ex vivo</em> tissue model for optimising drug detection and ionisation in MALDI imaging studies.

The aim of this study was to establish an ex vivo model for a faster optimisation of sample preparation procedures, for example matrix choice, in matrix-assisted laser desorption/ionisation (MALDI) drug imaging studies. The ionisation properties of four drugs, afatinib, erlotinib, irinotecan and pirfenidone, were determined in an ex vivo tissue experiment by spotting decreasing dilution series onto liver sections. Hereby, the drug signals were distinctly detectable using different matrix compounds, which allowed the selection of the optimal matrix for each drug. The analysis of afatinib and erlotinib yielded high drug signals with &alpha;-cyano-4-hydroxycinnamic acid matrix, whereas 2,3-dihydroxybenzoic acid was identified as optimal matrix for irinotecan and pirfenidone detection. Our method was validated by a MALDI drug imaging approach of in vivo treated mouse tissue resulting in corresponding findings, indicating the spotting method as an appropriate approach to determine the matrix of choice. The present study shows the accordance between the detection of ex vivo spotted drugs and in vivo administered drugs by MALDI-TOF and MALDI-FT-ICR imaging, which has not been demonstrated so far. Our data suggest the ex vivo tissue spotting method as an easy and reliable model to optimise MALDI imaging measurements and to predict drug detection in tissue sections derived from treated mice prior to the recruitment of laboratory animals, which helps to save animals, time and costs