dataesr/scientific-paragraphs-categorization huggingface dataset:
However, here we focus on the northern Eurasian region, in particular on the territory corresponding to LU NEW (figure  S1 ). To test the sensitivity of E LUC to the two LUC datasets, we ran three additional simulations: one with fixed pre-industrial (1860) land-cover map from LU NEW , i. e. no land-use (S noLUC ), and other two simulations where cropland is prescribed from LU NEW. We define two extreme scenarios for the range of forest vs. grassland trajectories following land-abandonment: FOR and GRA, corresponding to forest or grass-land PFTs being preferentially assigned to the fraction of cropland removed (figure  S3 , S FOR and S GRA , respectively). All three simulations were forced with historical climate. To evaluate the contribution of climate anomalies to the simulated CO 2 fluxes, an additional simulation was performed with 1901-1910 cyclic climate (S Clim ).
On the contrary, LU REF does not capture these short-term variations, reporting an increase in cropland extent during the 1920s and 1930s, and only a slight decrease during the 1940s. This implies that using total population to extrapolate countrylevel crop area (as used in  [19] ) may miss important LUC changes, by not reflecting the effects of migratory fluxes between rural and urban areas (which are highly relevant in the early 20 C), nor variations in active work force due to war (or other disrupting events), nor the mobilization of labour to other sectors of the economy  [24]. Nevertheless, it should be noted that using total population data may still be the best variable to consistently harmonize country-level data at global scale for earlier periods in history, when other indicators may not be available.
Conclusions Here, we simulate CO 2 fluxes in northern Eurasia using a model specifically developed for high-latitudes, in order to evaluate two hypothesis to explain the differences between observations and reconstructions of the GCB in the early 20th century  [2]. The high-latitude warming during the 1930s and 1940s is a consistent feature in observation-based and proxy data  [13, 17, 47]. Our simulations indicate very strong enhancement of net CO 2 uptake in northern Eurasia by 0. 4 PgC. yr -1 , vegetation growth and accumulation of carbon in soils in the high-latitudes coinciding with spring warming, which is supported by tree-ring data  [4]. The fact that state-of-the-art LSMs from TRENDYv4 do not capture such response highlights the importance of correctly representing and parametrizing high-latitude processes to capture the effects of warming on boreal vegetation.
The climateinduced enhancement of NBP in northern Eurasia could potentially explain 60% of the 1940s' global sink gap found in  [2]. Massive and abrupt land-abandonment in the 1920s and 1940s in the FSU and subsequent recovery of C-stocks could result in increased terrestrial uptake. Such short-term fluctuations are not represented in the LUC datasets used to force LSMs, as their main purpose is to estimate E LUC over centuries  [26]. We compiled a new dataset of cropland area in the FSU based on annual official stastistics from GOSKOMSTAT collected between 1913 until 1961. Our dataset is consistent with other social and economical statistics, indicating that the changes in cropland area reported in our dataset are realistic. Here we show that extreme but relatively short LUC events may result in decadal E LUC variability and contribute to the discrepancies found in  [2].
On the one hand, we show the importance of representing specific high-latitude processes to better simulate the terrestrial sink response to arctic warming. On the other hand, we show the relevance of using LUC datasets with finer temporal resolution during periods of drastic demographic and economic transitions, to estimate resulting LUC emissions and their variability. Still, our results point to key processes that may need to be improved in land-surface models and LUC datasets in order to better represent decadal variability in the land CO 2 sink.
Acknowledgments The work is supported by the Commissariat à l'énergie atomique et aux énergies alternatives (CEA). The authors would like to thank the TRENDY modelling teams and  S Sitch  and  P Friedlingstein  for providing and maintaining the TRENDYv4 outputs. Above-ground biomass C stocks from [45] were downloaded from www. wenfo. org/wald/global-biomass/. We thank the valuable help of  Dan Zhu ,  Fabienne Maignan ,  Shushi Peng & Albert Jornet  during the development of this study.
The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1-3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme and (ii) the measurement and modelling activities performed as part of it.
3 Research themes and integration within the APHH-Beijing programme The APHH-Beijing programme has four themes to address the specific objectives outlined in Sect. 2 and is delivered through five inter-related research projects: - During the intensive campaigns, the project measured the fluxes of particulate and gaseous air pollutants from groundlevel sources by sampling on the meteorological tower (325 m) at the IAP site, which is compared with emissions estimates taken from the inventory for Beijing. This was complemented by top-down fluxes inferred from satellite data for nitrogen dioxide, sulfur dioxide and formaldehyde, the latter indicative of volatile organic compound (VOC) oxidation processes  (Palmer et al. , 2003; Fu et al. , 2007). Through these means, the emissions inventory is being tested, allowing revisions which are being incorporated into the atmospheric modelling work.
These data are being brought together for use in receptor modelling of PM sources, which are compared with other estimates of source contributions to PM concentrations. Measured ground-level concentrations both from our campaign sites and the Beijing monitoring network, together with vertical gradient observations at the tower and source apportionment results, are compared with the predictions of a chemistry-transport model and used to provide a clear distinction between advected regional pollution and the impact of local sources. Divergences between measured and modelled pollutant concentrations will be used to provide critical evaluation of emissions inventories, which will be enhanced iteratively to improve knowledge of the sources and emissions of pollutants affecting air quality in Beijing.
The IAP tower allowed vertical profiles of key pollutants up to 320 m to be obtained and, with additional remote sensing of composition and meteorology, provided insight into boundary layer stability and evolution over the diurnal cycle. Quantification of shallow mixed layers proved to be vital for explaining local surface in situ chemical processing and also street-level concentrations of relevance to exposure. The potentially significant vertical gradients anticipated in some chemicals and PM properties were further quantified using instruments installed on the tall tower and via profiling gondola measurements. The combined datasets, surface and profiles provide the basis for evaluation of model performance and notably comparisons for those intermediates that provide indicators of whether secondary pollution production is being correctly simulated.
Outcomes of Themes 1, 2 and 3 help to provide Theme 4 with a more accurate estimate of pollution costs and to develop cost-effective air pollution control measures in Beijing. The third stream of integration activities involves regular APHH-Beijing programme science and stakeholder engagement meetings to stimulate collaboration and knowledge transfer between different themes and stakeholders. Furthermore, sharing of data was made available via a dedicated depository in Centre for Environmental Data Analysis (http://catalogue. ceda. ac. uk/ uuid/7ed9d8a288814b8b85433b0d3fec0300, last access: 20 May 2019). All data in the depository will be made publicly available by the end of 2022. Together, this interdisciplinary APHH-Beijing programme delivers key scientific values and innovation, including 1.
Synoptic-scale meteorology during the field campaigns Synoptic circulation patterns (e. g. horizontal advection and wet deposition) play a key role in the variations of air quality in Beijing  (Miao et al. , 2017; Wu et al. , 2017; Zhang et al. , 2012). To provide the synoptic context of the APHH-Beijing observations, the daily mesoscale flow patterns have been classified and put into context using a 30-year climatology (Sect. 5. 4). Circulation types (CTs) are classified using the software produced by the COST Action 733 "Harmonisation and Applications of Weather Type Classifications for European regions"  (Philipp et al. , 2010)  with (ECMWF reanalysis) ERA-Interim 6 h 925 hPa geopotential reanalysis data  (Dee et al. , 2011)   (Huth et al. , 2008; Philipp et al. , 2010 Philipp et al. , , 2016;; Tveito and Huth, 2016) , two are used: T-Mode PCA (principal component analysis) and SANDRA (simulated annealing and diversified randomisation clustering).
Meteorological conditions during the field campaigns To assess how local-scale flow related to ERA-Interim fields (Sect. 4. 3) compared to local conditions, the link between the coarse gridded data and tower-based sonic anemometer observations is explored based on wind roses (Fig. 4 ). The 30-year climatology (Fig. 4a, d ) confirms the clear seasonality in wind direction affecting the occurrence of CTs discussed (Sect. 4. 3); i. e. during the winter intensive campaign period (10 November-10 December), north-easterly flow clearly dominates, while southerly wind directions are most common during the summer campaign period (20 May-22 June). The wind roses for winter 2016 and summer 2017 (Fig. 4b, e ) are slightly noisier but show similar tendencies to the climatology. The general large-scale patterns are consistent with the in situ wind measurements (Fig.
We also investigated how representative the campaign periods were of the selected seasons in Beijing by comparing pollutant levels with those from the same period each year over the 2013-2017 period. The NAQPMS model was run for the full 5-year period driven by NCEP meteorology and using temporally varying emissions for a single year that is broadly representative of 2013 conditions. The same emissions were used each year so that the meteorological contribution to pollutant levels could be assessed. This provides important information that cannot be obtained from the monitoring data (as emission varies year by year). The frequency distribution of PM 2. 5 over each campaign period for each year is shown in Fig. 12. Winter 2016 was broadly typical of the 5-year period, with similar characteristics to winter 2014, but both years show higher PM 2.
Summary APHH-Beijing is an integrated and multidisciplinary research programme conducted by leading UK and Chinese researchers to (1) quantify sources and emissions of urban atmospheric pollutants; (2) elucidate processes affecting urban atmospheric pollution events; (3) estimate the personal exposure and impacts of air pollution on human health and (4) develop intervention strategies to improve air quality and reduce health impacts in the Beijing megacity. This introduction paper outlines the motivation of the APHH-Beijing programme and provides the background air quality and meteorological conditions during the two intensive field campaigns that form the basis of data interpretation for campaign observations. APHH-Beijing has measured the fluxes of key air pollutants, including NO x , CO, BC, VOCs and speciated particulate matter, applied a suite of traditional and modern techniques to apportion the sources of particulate matter, determined a wide range of pulmonary and cardiovascular biomarkers linking to direct personal exposure and extensive fixed-station monitoring as well as source apportionment re-sults and has evaluated the effectiveness of Beijing's air pollution control policies using both chemical transport models and novel machine learning techniques.
Acknowledgements. Funding is provided by  UK Natural Environment Research Council, Medical Research Council and Natural Science Foundation of China  under the framework of  Newton Innovation Fund  ( NE/N007190/1  ( Roy M. Harrison ,  Zongbo Shi ,  William J. Bloss );  NE/N007077/1  ( William J. Bloss ));  NE/N00700X/1  ( Sue Grimmond ),  NE/N007018/1  ( Frank J. Kelly );  NSFC  Grant  81571130100  ( Tong Zhu ),  NE/N007115/1  ( Alastair C. Lewis ,  Andrew R. Rickard ,  David C. Carslaw );  NE/N006917/1  ( James Lee ,  Jacqueline F. Hamilton ,  Rachel E. Dunmore );  NE/N007123/1  ( James Allan ,  Carl Percival ,  Gordon McFiggans ,  Hugh Coe );  NE/N00695X/1  ( Carl Percival ,  Hugh Coe ,  Gordon McFiggans ,  James Allan) ;  NE/N006976/1  ( C. Nicholas Hewitt ,  Oliver Wild );  NE/N006925/1  ( Oliver Wild );  NE/N006895/1  ( Dwayne Heard ,  Lisa Whalley );  NE/N00714X/1  ( Daobo Guan ),  NE/N007182/1  ( Miranda Loh );  NSFC 41571130024 (Pingqing Fu)  and  NE/N006879/1  ( Paul I.
Financial support. This research has been supported by the  Natural Environment Research Council  (grant nos. NE/N007190/1 ,  NE/N007077/1 ,  NE/N00700X/1 ,  NE/N007018/1 ,  NE/N007115/1 ,  NE/N006917/1 ,  NE/N007123/1 ,  NE/N00695X/1 ,  NE/N006976/1 ,  NE/N006895/1 ,  NE/N00714X/1 ,  NE/N007182/1 ,  NE/N006925/1 ,  NE/N006879/1 ,  NE/R005281/1 , and  NE/N006879/1 ), the  National Natural Science Foundation of China  (grant nos. 81571130100  and  41571130024 ) and the  Royal Society  (grant no. CHG/R1/17003 ). Review statement. This paper was edited by  Delphine Farmer  and reviewed by three anonymous referees.
In this study, we aimed to decipher the respective contributions of type I and type II IFNs to shed light on their respective influence in HIV/SIV infection and pathogenesis. We analyzed IFN and ISG transcriptomic profiles and their associated functional signatures in the cynomolgus macaque (macaca fascicularis) pathogenic model of SIV infection, taking advantage of longitudinal access to blood and lymphoid tissues. We elucidated the respective contribution of type I and type II IFNs in determining ISG expression levels, patterns, and associated functions in both acute and chronic SIV infection, by classifying the ISGs into either type I or type II, based on information obtained from the Interferome database  [48]  or by using an innovative approach to classify ISGs based on the presence of ISRE or GAS conserved consensus sequences in their respective promoters.
The Agilent One-Color Microarray-Based Gene Expression Analysis Protocol was followed for hybridization and array washing. Arrays were scanned with an Agilent microarray G2505C scanner and image analysis was performed using Agilent Feature Extraction 11. 0. 1 Software. Raw images were analyzed using Agilent Feature Extraction software (version 9. 5. 3. 1) and the GE1_1100_Jul11 extraction protocol. All arrays were required to pass Agilent QC flags.
Transcriptomic analysis Microarray data were processed using R/Bioconductor. Gene expression values were scaled and normalized using the limma package. Differentially expressed genes were identified using two-sample t-tests (p < 0. 05) and based on a 2-fold-change (FC) threshold. Functional Enrichment analysis was performed using Ingenuity1 Pathway Analysis (IPA, version n˚31813283) and the right tailed-Fisher Exact test. P-values were corrected for multiple comparisons using the Benjamini-Hochberg Multiple Testing Correction. Genes were annotated using DAVID Bioinformatics Resources 6. 8 (NIAID/NIH, USA). Raw and normalized microarray expression data are publicly available on the ArrayExpress database (ID: E-MTAB-6068).
ISG annotations Differentially expressed interferon-induced genes were annotated using two approaches as described in S1 Fig. The first approach was based on the Interferome database (http://www. interferome. org) [48] , an open-access database of type I, II, and III Interferon-regulated genes collected from analyzing expression datasets of cells and organisms treated with IFNs. We used this database to identify and classify genes depending on their expression following induction by either type I IFN, type II IFN, or both IFN species. We also used a complementary approach in which the genes were annotated depending on the presence of either GAS, ISRE, or both consensus sequence motifs in gene promoters within the 2,000 bp upstream of the 5'UTR after locating them using Geneious software (http://www.
SIVmac251 infection induces both type I and Type II ISGs during both phases of infection in PLNs We previously showed early trafficking of pDC in PLNs and their contribution to massive IFN-α production during acute infection  [25, 31]. We focused our ISG analysis on PLNs, because we previously observed that IFN-α production is followed by high ISG expression in this tissue, and because IFNs were mainly produced in PLNs in the present study. We excluded the controller macaque #30742 from the data set for ISG analyses to avoid a confounding factor by including an animal with a different disease outcome. We identified 278 ISGs among 1,638 up-regulated genes in PLNs. A total of 169 ISGs were specifically induced during the acute phase, but not the chronic phase (D9-ISGs), and 58 were specifically induced during the chronic phase, but not the acute phase (M3-ISGs), whereas 51 were induced at both time points (D9&M3-ISGs) ( We annotated the ISGs using the Interferome database  [48]  to understand the contribution of type I IFNs, type II IFN, or both to the ISG expression pattern and identified type-I ISGs (inducible by type I IFNs but not type II IFN), type II ISGs (inducible by type II IFN but not  We then used the GAS/ISRE annotation to investigate the respective roles of the targeting of these sequences in the signaling pathways leading to ISG expression.
Activation of pDC in lymph nodes  [25]  may also contribute to CCL3 expression, further increasing the attraction of pDCs and other CCR5 + cells. Increased expression of CCL3 may be a beneficial response of the host against HIV/SIV infection, due to its ability to block HIV entry into CCR5 + T cells  [74] , but it can also be deleterious, through the recruitment of new target cells to inflamed lymph nodes. The CCL3 gene is reported to be type I IFN-inducible in the Interferome database. However, it bears a GAS sequence, but no ISRE, in its promoter and could thus be sustained by IFN-γ during the chronic phase or low undetectable type I IFN expression through alternative type I IFN signaling. We observed a significant decline in the number of CD4 T cells, a signature of SIV and HIV pathogenesis that drives disease progression  [75] , below baseline levels.
This work was supported by the  Agence Nationale de Recherches sur le SIDA  et les hepatites virales (www. anrs. fr). NE, SD and CPBP benefited from  ANRS  post-doctoral fellowships. This work was also supported by  Agence Nationale de Recherches sur le SIDA et les hepatites virales (ANRS)  through research project grant  11360  attributed to BV, by the  agence Nationale de la Recherche  (http://www. agence-nationalerecherche. fr)" Programme d'Investissements d'Avenir" (PIA)  under Grant  ANR-11-INBS-0008 , that funds the  Infectious Disease Models and Innovative Therapies (IDMIT, Fontenay-aux-Roses, France)  infrastructure, and  PIA  grant  ANR-10-EQPX-02-01  that funds the  FlowCyTech facility  (project investigator RLG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
4 ). Altogether, these data suggest an ongoing MBD4-related mutagenic process during tumor progression, as has been observed with APOBEC in other cancers  14. MBD4 germline mutations in UM and glioblastoma. To investigate the frequency of MBD4 and hypermutation in an independent UM cohort, we analyzed the TCGA UM dataset (N = 80 patients). This identified an additional hypermutated UM case (patient UVM_1; Fig. 2a ). This tumor was carrying a BAP1 mutation and monosomy 3 as well as 474 SNVs (305 nonsynonymous SNVs) corresponding to a 36-fold increase of SNVs as compared to the overall TCGA UM series. Again, the SNVs were predominantly CpG>TpG (460/474; 97% of SNVs). This patient furthermore carried a germline c. 1562-1G>T:p. D521Pfs*4 MBD4 splice-site variant and somatic loss of the wild-type allele due to tumor monosomy 3.
UVM_1 is a 41-year-old woman without past medical history of cancer, diagnosed with a stage IIIA UM localized to the choroid. No metastatic recurrence was reported after a follow-up of 39 months. The tumor showed focal lymphocytic infiltration with low CD8A and moderate CD274 (which codes for PD-L1) RNA expression. GBM_4 presented a glioblastoma at age 48. No other details are available. Sample collection. Several non-interventional cohorts have been proposed in Institut Curie to metastatic UM patients. In ctDNA R0 (ClinicalTrials. gov, NCT02849145) patients provided written informed consent to perform ctDNA monitoring, germline, and somatic genetic analyses of resected metastases/archived primary tumors. In ALCINA (NCT02866149), patients provided written informed consent to perform blood-borne biological markers and correlation with clinical/ pathological characteristics.
WES depth was a priori settled up to sequence germline DNA at 30× and somatic DNA at 100×. The library from UVM_IC primary tumor was prepared using the Agilent SureSelectXT HS kit (Agilent Technologies) from 20 ng of DNA isolated initial libraries with median insert size of 300 bp according to the manufacturers' protocols. Libraries were 100 bp paired-end multiplex sequenced on the Illumina HiSeq 2000 (Illumina). WES depth was a priori settled up at 100×. Mutation calling. Sequencing quality was assessed by FastQC. WES reads were aligned to the human genome (hg19) with Bowtie2 2. 1. 0  21. PCR duplicates were removed using Picard Tool MarkDuplicates v1. 97. WES data underwent variant calling for SNP and indels using the combination of three variant callers: Haplo-typeCaller, MuTect2, and SAMtools mpileup  [22] [23] [24].
Union of variants detected with these three algorithms were annotated using ANNOVAR  25  with the following databases: ensGene, avsnp147  26  , cosmic80  27  , popfreq_all_20150413, and dbnsfp33a. Somatic variants with <10 reads of position depth (DP) in germline and/or <10 reads of somatic DP and/or <6 reads of allele depth (AD) and/or an AD/DP ratio of <0. 05 and/or a population frequency higher than 1% (popfreq_all >0. 01) were filtered out. All somatic mutations called by this procedure were controlled manually using the Integrative Genomics Viewer (IGV). Sashimi plots were generated with the R software version 3. 4. 2 and its packages GenomicAlignments (1. 12. 2) and GenomicRanges (1. 28. 4) from data downloaded through the GDC portal. Expression data of the tumors from UVM_1 and GBM_4 was explored through the cbioportal.