dataesr/scientific-paragraphs-categorization huggingface dataset:
We used the ECMWF operational analysis at 0. 5 • × 0. 5 • resolution. Within the coarsest two model grids we enabled the parameterisations for shallow cumulus convection and for deep convection. We used the deep convection parameterisation from  Grell and Dévényi (2002)  as implemented in CATT-BRAMS in  Freitas et al. (2009). We allowed the model to resolve clouds and convective processes directly for the finestresolution grid. The topography used in the model has a 10 km resolution within the coarsest two grids and a 1 km resolution within the finest grid. Sea surface temperatures (SSTs) were initialised using the satellite observed weekly average SSTs  (Reynolds et al. , 2002). To describe CHBr 3 emissions, we have implemented the emission inventory of  Ziska et al. (2013). This is a bottom-up inventory based on the atmospheric and oceanic measurements of the HalOcAt (Halocarbons in the Ocean and Atmosphere) database project (https://halocat.
Code availability. As a third-party user of the open-source model C-CATT-BRAMS, we cannot grant access to the model code directly ourselves. However, the C-CATT-BRAMS code package is available upon request by email at gmai@cptec. inpe. br (Longo et al. , 2013). Modifications to the chemical mechanism specific to bromine chemistry are available upon request by email (paul. hamer@nilu. no). Data availability. The model datasets produced by the C-CATT-BRAMS model are available on request by email from the corresponding author (paul. hamer@nilu. no). For access to all other datasets produced by the co-authors, i. e. , TOMCAT model output, SPIRIT and GHOST-MS instrument data, and the bromoform emissions, please contact the corresponding author (paul. hamer@nilu. no), who can then forward requests to data owners.
Other data used in the paper are available from external links, i. e. , MTSAT-2 data (http://database. rish. kyoto-u. ac. jp/arch/ ctop/index_e. html, last access: 15 November 2021; CEReS, 2015) and NDVI data (https://modis. gsfc. nasa. gov/data/dataprod/mod13. php, last access: 15 November 2021; NASA, 2021). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/acp-21-16955-2021-supplement. Author contributions. PDH co-designed the study, wrote the main text of the paper, ran the model, analysed the model results, and created many of the figures; VM co-designed the study, helped develop this version of C-CATT-BRAMS, wrote some of the text, and created some of the figures; RH ran the TOMCAT simulations and helped edit the manuscript; MP co-designed the chemical mechanism and the study and helped develop this version of C-CATT-BRAMS; GK co-designed the chemical mechanism, helped develop this version of C-CATT-BRAMS, and edited the manuscript; FZ de-.
The disulfide bonds are indicated with yellow numbers, and N-linked glycosylation sites with hexagons (green with black border-built in our structure; green with gray border-built in the PBD accession code 7CZF  [34] ; white, with black borders-the remaining predicted sites). Signal peptides at the start of each protein are represented as white boxes with gray lines, transmembrane anchor domains in EphA2 and gH as dark gray boxes, and double strep tag for affinity purification on gL and EphA2 LBD as half circles. (B) The structure of the tertiary complex is represented as molecular surface and cartoon model (EphA2 LBD in purple, gL in blue, and gH in gray). The N and C termini of each protein are labeled with letters "N" and "C," respectively. The 4 domains of gH are marked with roman numbers on the left side, and putative locations of the viral and cellular membranes with dashed arrows (black and purple, respectively).
e. , domains II, III, and the membrane-proximal domain IV (Fig  1B ). The HHV-8 gH/gL resembles the most its EBV counterpart, consistent with the highest sequence conservation between the two, followed by the β-herpesvirus CMV gH/gL complex and less so the α-herpesvirus complexes (S5 Fig). The RMSD values and Z-scores calculated from the superimposition of individual gH domains and gL are given in S5B Fig (superimposing the entire gH/gL ectodomains is not informative because of the different orientations of the domains with respect to each other). Su and colleagues reported the crystal structure of the same tertiary complex (PDB accession code 7CZF)  [34]  while we were preparing our manuscript. The 2 structures are very similar, with the RMSD value of 6. 4 Å for the superimposition of the 2 tertiary complexes.
The relatively high RMSD value stems from the disposition of gH in respect to the EphA2 LBD and gL end of the molecule that align very well (RMSD <1 Å) (S5B Fig). These movements are likely a consequence of the flexible hinge helix connecting domains I and II of gH (Fig  1B ) and could also be influenced by the different packing of molecules within the 2 crystal lattices (P2 1 2 1 2 1 and C222 1 for the PDB: 7CZF  [34]  and our structure PDB: 7B7N, respectively).
The same type of EphA2 dimer stabilized via the DIN is supported by our crystal structure and the data from the FSI-FRET experiments (Figs  5  and S2 ). Based on what is known about the ephrin ligand-induced clustering of EphA2 receptors, the gH/gL-induced EphA2 dimerization would presume ligand-driven stabilization resembling the formation of the Eph-ephrin tetramers (S2 Fig). Analyses of the contacts in our structure show, however, that the gH/gL molecules do not make contacts with the second EphA2 from the DIN-stabilized tetramer, but rather with an EphA2 from the neighboring EphA2 tetramer (S12 Fig). This poses question of how the gH/gL-induced EphA2 dimers are stabilized, and why CIN-stabilized EphA2 dimers bound to gH/gL are not observed on the cell surface instead. We analyzed the DINs in unliganded EphA2 receptor and in complex with ephrin ligands and HHV-8 gH/gL.
Crystallization, data collection, and structure determination Crystals grew in 0. 1 M Na-malonate (pH 5), 14. 2% PEG 3350 in the presence of 14 mM adenosine-5 0 -triphosphate disodium salt hydrate diffracted to 2. 7 Å. They were transferred into the crystallization solution supplemented by 20% ethylene glycol as a cryo-protectant and flashfrozen in liquid nitrogen. The details of data collection, processing, and structure determination are given in S1 Table and S1 Text. The tertiary complex crystallized in an orthorhombic space group (C222 1 ) and the crystals, which contained 1 molecule per asymmetric unit, diffracted to 2. 7 Å. The initial phases were calculated by molecular replacement using the EphA2 LBD (PDB: 3HEI) and a HHV-8 gH/gL theoretical model derived from the EBV gH/gL X-ray structure (PDB: 3PHF) using the Phyre2 program for protein modeling and structure prediction  [56].
Then, the cells were stained for actin using rhodamine-conjugated phalloidin (Thermo Fisher Scientific; R415) for 90 minutes at room temperature. The cells were washed twice with PBS in between each step. Finally, starvation media was added to each well prior to imaging. Actin-stained fixed cells were imaged with a Leica TCS SP8 confocal microscope equipped with a HyD hybrid detector and a 63x objective. The measurements were performed with a 552-nm excitation diode laser at 0. 5% power using the dsRed setting, which measures the fluorescence between wavelengths of 562 and 700 nm. The scanning speed was at 200 Hz, the pixel depth at 12-bits, the zoom factor at 1, and the image size at 1024 × 1024 pixels. Cell area was determined using the ImageJ software (NIH, Bethesda, MD) by drawing a polygon around the membrane of the cells.
LBD binds to HHV-8 gH/gL in 1:1 stoichiometry. SEC-MALS traces are shown for HHV-8 gH/gL alone (blue curve), EphA2 ectodomain or LBD alone (red curves), and gH/gL mixed with EphA2 (purple, dashed curve). Molecular weights are indicated on the chromatograms, demonstrating that the tertiary complexes are composed of 1 molecule of HHV-8 gH/gL bound to 1 molecule of EphA2 ectodomain or EphA2 LBD. The underlying data can be found in S2 Data. gH/gL, glycoproteins H and L; HHV-8, human herpesvirus 8; LBD, ligand-binding domain; SEC-MALS, size exclusion chromatography coupled with multi-angle light scattering. (PDF) S5 Fig. Structural comparison of gH/gL from gamma-(HHV-8, EBV), beta-(CMV), and alpha-herpesviruses (HSV-2 and VZV). (A) Available structures of the gH/gL complexes are shown, with the corresponding PBD access numbers indicated below.
This project has been supported via the recurrent funding from  Institut Pasteur (FR) ,  CNRS (FR)  and  ANR  proposal # ANR-10-IHUB-0002  (FR), and grants from  National Institute of Health   GM068619  (KH) and  National Science Foundation MCB 1712740 (KH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This method allows the comparison of heterogenous datasets to find commonly regulated genes among all studies  78. The genes with an adjusted p-value < 0. 05 and the same expression trend (up or down regulated) for all the comparisons were considered as differentially expressed metaDEGs for Abiotic (A-metaDEGs) or Biotic (B-metaDEGs) stresses. The overlapping of A-and B-metaDEGs was conducted using the graphical representation of the common genes by the Eulerr on-line software (http:// eulerr. co) and genes found in common between A-and B-metaDEGs were considered as core-metaDEGs, regardless of their expression trend (Supplementary Figure  S3 ). The scripts used in this analysis are available in https:// github. com/ lbi-cenar gen/ MetaA nalys is/. Functional annotation and heatmaps. Genes identified as DEGs were functionally annotated by Mercator  79  , using default parameters and used as input for the boxplot in the ggplot2 package in R  80.
Visualization of commonly expressed genes among the 16 RNA-Seq libraries was conducted by InteractiVenn (http:// www. inter activ enn. net/). Heatmaps showing the expression profile of DEGs were made in gplots package  81  using average expression values for genes in the biotic and abiotic treatments  11. For dotplot, we used the expression values from the core-metaDEG and crossDEG as input for ggplot package  80. Arachis stenosperma cross-stress assays and library sequencing. Plant materials and bioassays. Six-week-old A. stenosperma (accession V10309) plants grown at 70% of field capacity (FC) under greenhouse conditions were submitted to four treatments (well-irrigated control, cross-stress, nematode infection and drought), with each treatment comprising three sets (biological replicates) of 20 plants.
arenaria and submitted to water withdrawal for seven days. At the 7th day plants were collected and stored as above. Cross-stress RNA-Seq sequencing and analysis. Total RNA was extracted from roots of the three biological replicates from each treatment (cross-stress, nematode, drought, and control) using a modified lithium chloride protocol  83  and further purified with Invisorb Plant RNA Mini Kit (Invitek, Berlin, Germany). RNA was reverse transcribed and analyzed according to Morgante et al. , (2013). In total, 12 paired-end cDNA libraries were constructed using the TruSeq™ Stranded Total RNA LT Sample Prep Kit from Illumima (Illumina Inc. , San Diego, CA, USA) and sequenced by Macrogen (Seoul, Korea) using HiSeq-4000, 150 bp (Illumina Inc. , San Diego, CA, USA). Illumina raw reads were analyzed and quantified as before  43  (PRJNA284674).
Tularemia is a highly dangerous zoonotic infection due to the bacteria Francisella tularensis. Low genetic diversity promoted the use of polymorphic tandem repeats (MLVA) as first-line assay for genetic description. Whole genome sequencing (WGS) is becoming increasingly accessible, opening the perspective of a time when WGS might become the universal genotyping assay. The main goal of this study was to describe F. tularensis strains circulating in Kazakhstan based on WGS data and develop a MLVA assay compatible with in vitro and in silico analysis. In vitro MLVA genotyping and WGS were performed for the vaccine strain and for 38 strains isolated in Kazakhstan from natural water bodies, ticks, rodents, carnivores, and from one migratory bird, an Isabellina wheatear captured in a rodent burrow.
tularensis or Neisseria meningitidis  [9] [10] [11] [12]. Carrying out in silico MLST on WGS data is not difficult owing to the availability of appropriate algorithms and allows comparing the results obtained previously  [13]. Obtaining a relevant in silico MLVA profile is a more challenging task due to the occurrence of errors in the assembly of short reads and contig breaks in VNTR locations  [14]. Nevertheless, the use of appropriate sequencing reads length allows to conduct in silico MLVA with high reliability. It has been established for Brucella that read sizes of 200 base-pairs or more allow to correctly assemble tandem repeat arrays for most loci used in the MLVA assay and to produce a reliable MLVA profile  [15]. Simple scripts have been developed to run in silico MLVA (https://github.
Genome sequencing, single nucleotide polymorphism (SNP) calling and canSNP assignment Sequencing libraries were prepared using Nextera XT DNA Library Preparation Kit (Illumina, USA). Sequencing was performed using MiSeq Reagent Kit v3 (600 cycles) on the Illumina MiSeq platform. Sequencing quality was checked using FastQC v0. 11. 15  [38]. High-quality sequence selection was performed using MultiQC v3  [39]. Raw reads can be accessed from the European Nucleotide Archive  [7]  under study accession PRJNA639508 (https://www. ebi. ac. uk/ena/browser/view/PRJNA639508; run accessions SRR13617503-SRR13617541). SNPs were called by mapping raw sequencing reads on a reference genome using BioNumerics version 7. 6. 3 (Applied-Maths, Laethem-Saint-Martin, Belgium) with default parameters as previously described except when mapping Ion Torrent PGM sequence data for which the "allow gapped alignment" option was activated  [22].
Publicly available assemblies and raw reads were downloaded via EBI-ENA (last download on August 25 th 2020). The list of public assemblies and sequence reads archives evaluated for this report is provided in S1 Table, as well as the list of accessions used for each figure. Assemblies were split into 50 bp long artificial reads with a 10X cover and no error model. These artificial reads were then mapped on the reference genome for SNP calling as done with raw sequencing reads. BioNumerics was used with default parameters (no resampling) for Maximum Parsimony analysis  [40]  and dendrogram drawing. Raw reads datasets were assembled using SPAdes  [41]  version 3. 13. 1 and SKESA  [42]  version 2. 3. 0. The canSNP assignment of each strain was deduced from genome assemblies using CanSNPer2 (https://github.
In vitro MLVA typing In vitro MLVA genotyping was performed with the previously described 25 VNTR loci  [4]. The ten most variable loci (Ft-M02, Ft-M03, Ft-M04, Ft-M05, Ft-M06, Ft-M10, Ft-M20, Ft-M22, Ft-M23 and Ft-M24) were analysed using capillary electrophoresis with fluorescent primers (Applied Biosystems genetic analyzers)  [18]. The remaining 15 loci (Ft-M01, Ft-M07, Ft-M08, Ft-M09, Ft-M11, Ft-M12, Ft-M13, Ft-M14, Ft-M15, Ft-M16, Ft-M17, Ft-M18, Ft-M19, Ft-M21 and Ft-M25) were typed using monoplex PCR and agarose gel electrophoresis  [22]. The resulting MLVA data were deposited in the public Francisella tularensis MLVA database accessible at https://microbesgenotyping. i2bc. paris-saclay. fr/.
In silico MLVA on genome assemblies and on raw sequence reads In silico MLVA was run on genome assemblies by applying the MLVA_finder. py script with default settings (https://github. com/i2bc/MLVA_finder) and primers listed in S2 Table. The size of the polymorphic VNTR arrays being smaller than the 300 bp reads produced here, we also typed raw reads data. A simple script based on bbduk (BBTools, https:// sourceforge. net/projects/bbmap/) was developed to identify reads containing VNTRs and both flanking sequences (https://github. com/Vladislav-Shevtsov/search-primers-in-reads/). Primers were selected that were located as close as possible to the VNTR loci (S2 Table ). When selecting primers for in silico instead of in vitro detection, attention was paid only to uniqueness and to the formation of only the target fragment.
The analyses required the reculturing of the strains to prepare new DNA extractions. One cannot formally exclude cross-contaminations and additional studies will be required to confirm the present observations. In particular, it would be highly recommended to prepare a DNA batch for later sequencing purposes at the time of the very first isolation and growth of the pathogen. This DNA batch could be validated by MLVA7 in vitro genotyping and the resulting data could be archived in an online F. tularensis MLVA database. This initial genotype could serve as a DNA identification control of the eventual WGS data which could be in silico genotyped at least if sequencing reads are longer than 300 bp. Interestingly, owing to the extensive field sampling in natural foci regularly done in Kazakhstan, a strain was recovered from an Isabellina wheatear incidentally trapped out of a rodent burrow in West Kazakhstan  [49].
Iceberg Trajectories and Deep Hydrography The Agulhas Plateau is situated at the southern boundary of the Indian-Atlantic Ocean Gateway (Figure  1a ); the upper water column is dominated by eastward flowing Indian Ocean surface waters retroflected as the Agulhas Return Current (i. e. not 'leaked' into the South Atlantic). To the south, the relatively cold and fresh waters of the SAZ meet their northern limit, forming steep hydrographic gradients at the subtropical frontal zone (STFZ; Figure  1 ). Iceberg presence (and subsequently IRD deposition) at this location can therefore be influenced by regional hydrography (i. e shifts in the STFZ) as well as the export, survivability, and transport of icebergs into and across the SO. To aid in our interpretation of the IRD MAR proxy, we perform iceberg trajectory modelling experiments using Pyberg, an offline implementation of the Finite Element Sea Ice-Ocean Model (FESOM-IB)  14  iceberg drift and decay module.
Surface-Deep Phasing The glacial AP comp is characterised by generally higher IRD MAR and lower δ  13  C benthic (shaded bars in Figure  2 ) compared to interglacials, reflecting the increased presence of Antarctic icebergs and the reduced presence of NSW, respectively. A significant negative correlation is present between IRD MAR and δ 13 C benthic (r 2 = -0. 39), becoming stronger still when IRD MAR is log-transformed (r 2 = -0. 54). The reason for log-transforming the IRD MAR data is twofold: firstly, it has a strongly skewed distribution with a small number of very high values. Secondly, we consider log-IRD MAR a more sensitive indicator of paleoiceberg drift, for example the probability of iceberg presence in the SO decreases by orders of magnitude with distance north of the main iceberg belt in the Weddell Sea sector  21.
Regardless, the southern escape of freshwater (IRD MAR ) into the SAZ appears to scale with the magnitude of glacial AMOC perturbations as indicated by δ 13 C benthic minima; notably, the IRD MAR maximum (and δ 13 C benthic minimum) at ∼0. 9 Ma coincides with the implied collapse in AMOC as recorded in the nearby deep Cape Basin  50. 15% concentration contour for September) is shown for PI and LGM. Surface ocean circulation is modified from  3  ; AR = Agulhas Retroflection, AL = Agulhas Leakage, ARC = Agulhas Return Current. The shaded grey band represents the Subtropical Frontal Zone (STFZ)  51. b. 0-50 • E zonal mean of mean SST under PI (pink) and LGM (blue) conditions. SST proxy data are from MARGO  26  (blue symbols; triangle = diatom, circle = radiolarian, square = alkenone). Model SST data are from COSMOS experiments (see online methods).
57): No quantitative distinction is presented between mineralogies of phenocrysts present, however grains that were clearly of volcanic (e. g. tephra) or authigenic (e. g. pyrite) were excluded from the IRD counts. Energy Dispersive X-Ray Spectrometry (EDS) point analysis was used to identify the mineralogy of several grains from a selection of samples (total grains = 31). Of the 31 measured, 23 were quartz (mostly 'clean' quartz with some Fe-K and Fe members), 7 were orthoclase (K-feldspar), and 1 was garnet (Almandine member) (Extended Data Figure  3 ). The origin of ice-rafted minerals in the Atlantic SO has been the topic of some discussion, as the presence of sea-ice rafted volcanic and mafic material in sediment cores close to volcanic Subantarctic islands can complicate the interpretation of IRD records  58, 59.
In this study, to investigate responses of Antarctic iceberg transport to different climate backgrounds of the Southern Ocean, we utilized published equilibrium experiments under Pre-industrial (PI) and Last Glacial Maximum (LGM) boundary conditions  15. To further assess roles of a lower-than-LGM obliquity (i. e. additional cooling on the glacial Southern Ocean), we further conducted one LGM sensitivity experiment with 27ka obliquity (22. 25 • ) that is lower than the LGM value (22. 949 • ). The three experiments are integrated to quasi-equilibrium and the average of the last 100 years is calculated to represent the corresponding climatology and used for modelling iceberg trajectory. The simulated climatological SO conditions of these runs can be found in Extended Data Figure  6.
Iceberg Trajectory Model We use Pyberg (https://github. com/trackow/pyberg), an offline Python implementation of the FESOM-IB iceberg drift and decay module  14. The model simulates iceberg trajectories and alongtrack rates of melting using established iceberg physics  [68] [69] [70]. Pyberg reads monthly forcing data from different climates as simulated by the COSMOS climate model (10m winds and ocean currents for atmospheric and oceanic drags, sea surface height for the surface slope term, sea surface temperature for melting parameterizations). Monthly sea ice fields are also read and allow to lock icebergs into the sea ice when ice concentrations exceed 86%  29, 70. In that case, icebergs are advected along with the sea ice velocity field. Erosion of icebergs by surface waves is damped at high ice concentrations  69.
Along-track melt-rates are gridded and summed on a 1 • x1 • regular grid to produce the meltwater distribution. The modelled PI trajectories are consistent with modern observational datasets  29, 30  (Extended Data 7). The LGM results are broadly consistent with the previously published results from the Fine ResolUtion Greenland And Labrador (FRUGAL) intermediate complexity climate model iceberg module  16  , with an equatorward shift and lengthening of trajectories in the Atlantic-Indian Southern Ocean Sector, however discrepancies are apparent such as the more extreme equatorward spread of LGM trajectories in the FRUGAL model compared to Pyberg. This is the result of different iceberg seeding configurations (i. e. we introduce icebergs only in the 'iceberg alley' region and neglect possible Subantarctic sources) and variations in the forcing provided by the underlying climate models.
We manually add a peak interglacial marker at 506 ka (based on Northern Hemisphere perihelion) to include the 'cool' interglacial MIS 13a. Within each interval we calculate the cumulative integral of IRD MAR and δ  18  O benthic , before normalizing the to percentages of total 'accumulation' for that interval (Extended Data figure  5d ). Finally, for the phase wheels in figure  3 , we use the Blackman-Tukey method with a Bartlett window (using the Analyseries software  89  ) after linearly interpolating (dt=1. 5 kyrs) and standardizing (mean = 0, standard deviation = 1) the data.