dataesr/scientific-paragraphs-categorization huggingface dataset:
The BA. 2. 75. 2, BQ. 1. 1, XBB. 1, and XBB. 1. 5 RBD constructs containing an N-terminal BM40 secretion tag and a C-terminal octa-histidine tag followed by flexible linker and Avi tag were codon optimized, synthesized, and inserted into the pcDNA3. 1(+) vector by Genscript. The boundaries of the construct are N-328RFPN331 and 528KKST531-C. The monomeric human ACE2 ectodomain (residues 19-615) construct used for BLI contains an N-terminal signal peptide and a 10x His tag and was synthesized and inserted into pTwist-CMV by Twist Bioscience. For SPR, SARS-CoV-2 RBD plasmids encoding residues 328-531 of the S protein from GenBank NC_045512. 2 with an N-terminal signal peptide and a C-terminal 8×His-Avi Tag or thrombin cleavage site-8×His-Avi tag. The ACE2 construct used for SPR and cryo-EM, encodes for residues 19-615 from Uniprot entry Q9BYF1 with a C-terminal thrombin cleavage site-TwinStrep-10×His-GGG tag, and N-terminal signal peptide.
1. 5 (GISAID ID: EPI_ISL_16353849, kindly provided by O. Schwartz and colleagues) was then administered intranasally to each animal (50 µl per nostril). Mock-infected animals received the physiological solution only. Infected and mock-infected hamsters were housed in separated isolators and were followed-up daily, for four days, when the body weight and the clinical score were noted. At day 4 post-inoculation, the animals were euthanized with an excess of anaesthetics (ketamine and xylazine) and exsanguination. Blood samples were collected by cardiac puncture; after coagulation, the tubes were centrifuged at 2,000g during 10 min at 4 °C, the serum was collected and frozen at -80 °C until further analyses. The lungs were collected, weighted and frozen at -80 °C until further analyses.
Transient expression of recombinant SARS-CoV-2 S and flow cytometry ExpiCHO-S cells were seeded at 6 × 10 6 cells per ml in a volume of 5 ml in a 50-ml bioreactor. The following day, cells were transfected with SARS-CoV-2 S glycoprotein-encoding pcDNA3. 1(+) plasmids (Beta-CoV/Wuhan-Hu-1/2019, accession number MN908947, Wu-D614; Omicron BA. 2, BQ. 1. 1, XBB. 1, XBB. 1. 5, BN. 1 or BA. 2-E340A generated by overlap PCR mutagenesis of the Wu-D614 plasmid) harbouring the Δ19 C-terminal truncation. S-encoding plasmids were diluted in cold OptiPRO SFM (Life Technologies, 12309-050), mixed with Expi-Fectamine CHO Reagent (Life Technologies, A29130) and added to cells. Transfected cells were then incubated at 37 °C with 8% CO 2 with an orbital shaking speed of 250 rpm (orbital diameter of 25 mm) for 24 to 48 h.
Transiently transfected ExpiCHO-S cells were harvested and washed twice in wash buffer (PBS 2% FBS, 2mM EDTA). Cells were counted and distributed into round bottom 96-well plates (Corning, 3799) and incubated with serial dilutions of mAb starting at 10 µg ml -1. Alexa Fluor 647-labelled Goat anti-human IgG secondary antibody ( Jackson ImmunoResearch, 109-606-098) was prepared at 2 µg ml -1 and added onto cells after two washing steps. Cells were then washed twice and resuspended in wash buffer for data acquisition at Ze5 cytometer (Bio-Rad).
PMBCs from healthy donors were labelled with CellTrace Violet (Invitrogen) and used as source of phagocytic effector cells. Target cells (10,000 per well) were incubated with titrated concentrations of monoclonal antibody for 10 min and then mixed with PBMCs (200,000 per well). The next day, cells were stained with APC-labelled anti-CD14 antibody (BD Pharmingen), BV605-labelled anti-CD16 antibody (Biolegend), BV711-labelled anti-CD19 antibody (Biolegend), PerCP/Cy5. 5-labelled anti-CD3 antibody (Biolegend), APC/ Cy7-labelled anti-CD56 antibody (Biolegend) for the identification of CD14 + monocytes. After 20 min, cells were washed and fixed with 4% paraformaldehyde before acquisition on a ZE5 Cell Analyzer (Bio-Rad). Data were analysed using FlowJo software (v10. 8. 1). The percentage ADCP was calculated as the percentage of monocytes (CD3 -CD19 -CD14 + cells) positive for PKH67.
Intact mass spectrometry analysis and liquid chromatographymass spectrometry analysis Four micrograms of PNGase F-treated BN. 1 RBD was used for each injection on the liquid chromatography-mass spectrometry (LC-MS) system to acquire intact mass spectrometry signal after separation of protease and protein by liquid chromatography (Agilent PLRP-S reversed phase column). Thermo MS (Q Exactive Plus Orbitrap) was used to acquire intact protein mass under denaturing conditions. BioPharma Finder 3. 2 software was used to deconvolute the raw m/z data to protein average mass. Peptide mapping with LC-MS was used to profile the site-specific glycosylation sites on BN. 1 RBD. Glycopeptides containing only one specific glycan were achieved by selectively digesting with chymotrypsin protease. Twenty micrograms of each digest product (peptide with a single glycan) was analysed by LC-MS (Agilent AdvanceBio peptide mapping column and Thermo Q Exactive Plus Orbitrap MS).
SPR assays to measure binding of ACE2 and S309 Fab to RBDs Measurements were performed using a Biacore T200 instrument or a Biacore 8k instrument using the Biacore Evaluation software (v. 3. 2. 1). CM5 chips with covalently immobilized anti-Avi polyclonal antibody diluted to a final concentration of 25 µg ml -1 (GenScript, A00674-40) were used for surface capture of His-Avi tag containing RBDs. Running buffer was HBS-EP+ pH 7. 4 (Cytiva) and measurements were performed at 25 °C. Experiments were performed with a fourfold dilution series of monomeric S309 Fab or ACE2 at 300, 75, 18. 8 and 4. 7 nM and were run as single-cycle kinetics. Data were double reference-subtracted and fit to a binding model using Biacore Insight software (v4. 0. 8. 20368). The 1:1 binding model was used to determine the kinetic parameters.
The cells were incubated at 37 °C and 5% CO 2 in a Cytation 7 plate Imager (BioTek) and both bright-field and GFP images were collected every 30 min for 18 h. Fusogenicity was assessed by measuring the area showing GFP fluorescence for each image using Gen5 Image Prime v3. 11 software. To measure surface expression of the variant SARS-CoV-2 S protein, 1 × 10 6 transiently transfected BHK-21-GFP 1-10 cells were collected by centrifugation at 1,000g for 5 min. The cells were washed once with PBS and fixed with 2% paraformaldehyde. The cells were washed twice with flow staining buffer (1% BSA, 1 mM EDTA, 0. 1% NaN 3 in PBS) and labelled with 25 µg ml -1 S2L20, an NTD-directed antibody that recognizes all currently and previously circulating SARS-CoV-2 variants, for 45 min. The cells were washed three times with flow staining buffer and labelled with a PE-conjugated anti-human IgG Fc antibody (Thermo Fisher) for 30 min.
Cryo-EM sample preparation, data collection and data processing Cryo-EM grids of BQ. 1. 1 RBD-ACE2-S309, XBB. 1 RBD-ACE2-S309 or BN. 1 RBD-ACE2-S309 complex were prepared fresh after purification by size-exclusion chromatography. For BQ. 1. 1 RBD-ACE2-S309 complex, 3 µl of 0. 25 mg ml -1 BQ. 1. 1 RBD-ACE2-S309 were loaded onto freshly glow-discharged R 2/2 UltrAuFoil grids  62  , prior to plunge freezing using a vitrobot Mark IV (Thermo Fisher Scientific) with a blot force of 0 and 6 s blot time at 100% humidity and 22 °C. Data were acquired using an FEI Titan Krios transmission electron microscope operated at 300 kV and equipped with a Gatan K3 direct detector and Gatan Quantum GIF energy filter, operated in zero-loss mode with a slit width of 20 eV. For BQ. 1. 1 RBD-ACE2-S309 data set, automated data collection was carried out using Leginon v3.
4  63  at a nominal magnification of 105,000× with a pixel size of 0. 843 Å and stage tilt angle of 0° and 30°. 6,487 micrographs were collected with a defocus range comprised between -0. 5 and -2. 5 µm. For XBB. 1 RBD-ACE2-S309 complex, samples were prepared using a Vitrobot Mark IV (Thermo Fisher Scientific) with R 2/2 UltrAuFoil grids and a Chameleon (SPT Labtech) with self-wicking nanowire Cu R1. 2/0. 8 holey carbon grids. For XBB. 1 RBD-ACE2-S309 data set, 6,355 micrographs from UltrAuFoil grids were collected with a defocus range comprised between -0. 2 and -3 µm and stage tilt angle of 0° and 30° and 2,889 micrographs from chameleon grids were collected with a defocus range comprised between -0. 2 and -3 µm without tilting the stage. For BN. 1 RBD-ACE2-S309 complex, samples were prepared using a Vitrobot Mark IV (Thermo Fisher Scientific) with R 2/2 UltrAuFoil grids, manual blotting/plunging with C-flat holey thick carbon grids and Chameleon (SPT Labtech) with self-wicking nanowire Cu R1.
2/0. 8 holey carbon grids. For BN. 1 RBD-ACE2-S309 data set, 3,822 micrographs from UltrAuFoil grids, 2,000, micrographs from chameleon grids and 1,915 micrographs from C-flat holey thick carbon grids were collected with a defocus range comprised between -0. 2 and -3. 5 µm and stage tilt angle of 0° and 30°. The dose rate was adjusted to 15 counts per pixel per s, and each movie was acquired in super-resolution mode fractionated in 75 frames of 40 ms. Movie frame alignment, estimation of the microscope contrast transfer function parameters, particle picking, and extraction were carried out using Warp 64 (v1. 0. 9). Two rounds of reference-free 2D classification were performed using cryoSPARC  65  (v4. 2. 2) to select well-defined particle images. These selected particles were subjected to two rounds of 3D classification with 50 iterations each (angular sampling 7.
Statistical analysis All statistical tests were performed as described in the indicated figure legends using Prism v9. 1. 0. The number of independent experiments performed are indicated in the relevant figure legends. Comparisons of means between multiple groups of unpaired data were made with Kruskal-Wallis rank test and corrected with Dunn's test. Statistical significance is set as P < 0. 05, and P values are indicated with: NS, not significant; *P < 0. 05; **P < 0. 01; ***P < 0. 001, ****P < 0. 0001. ED 50 , 80% of the maximum binding response (BD 80 ), ID 50 and IC 50 titres were calculated from the interpolated value from the log(agonist) and the log(inhibitor), versus response using variable slope (four parameters) non-linear regression. Data were plotted and analysed with GraphPad Prism software (version 9.
Acknowledgements The authors thank  A. E. Powell ,  Y. M. DaCosta ,  J. M. Errico  and  A. Lin  for assistance with protein production. This study was supported by the  National Institute of Allergy and Infectious Diseases  ( DP1AI158186 ,  P01AI167966  and  75N93022C00036  to D. V. ), the  National Institute of Health Cellular and   Molecular Biology Training Grant  ( T32GM007270  to A. A. ), a  Pew Biomedical Scholars Award  (D. V. ), an Investigators in the  Pathogenesis of Infectious Disease Awards  from the  Burroughs Wellcome Fund  (D. V. ),  Fast Grants  (D. V. ), the  University of Washington Arnold  and  Mabel Beckman Cryo-EM Center  and the  National Institute of Health  grant  S10OD032290  (to D. V. ). D. V. is an Investigator of the  Howard Hughes Medical Institute  and the  Hans Neurath Endowed Chair  in Biochemistry at the  University of Washington.
O. G. is funded by the  Swiss Kidney Foundation. A. L. is supported by the  European Research Council  ( ERC  grant no. 885539 ENGRAB ). We acknowledge the  Research Council of Cantonal Hospital Aarau  for the financial support (to M. J. K. ). The  SARS-CoV-2 Omicron/XBB. 1. 5 isolate used for hamster challenge experiment was supplied by  O. Schwartz  and colleagues.
Data availability The cryo-EM maps and atomic coordinates were deposited to the Electron Microscopy Data Bank (EMDB) and the PDB with accession numbers EMD-29531 and 8FXC (BQ. 1. 1 RBD-ACE2-S309), EMD-29530 and 8FXB (XBB. 1 RBD-ACE2-S309), and EMD-40240 and PDB 8S9G (BN. 1 RBD-ACE2-S309), respectively. All datasets generated and information presented in the study are available from the corresponding authors on reasonable request. Materials generated in this study can be available on request and may require a material transfer agreement. Source data are provided with this paper.
Data Collection and Definitions Patient demographic characteristics and comorbidities were recorded, as well as the occurrence of a TEE, defined by a diagnosis of PE confirmed by a thoracic CT scan or a diagnosis of deep vein thrombosis (DVT) confirmed using venous echo-Doppler. We defined the day of admission to the ICU (D1) as the first day of hospitalization in the ICU of one of the two centers of the study. Further data about the infection (vaccination status, PE or DVT at admission, variant) and about the therapeutics initiated in the first 48 h and during the ICU stay were also recorded. Blood samples were collected at baseline and on day 3 (D3). All biomarkers were assessed using automated standard methods. Endocan assays were performed on EDTA plasma or on citrated plasma. A correction factor was applied for assays on a citrate tube to take into account the underestimation found with this type of matrix based on previously published pre-analytical data  [13]  according to the following rule: ×2 if the endocan us less than 3 ng/mL, ×1.
Conversely, however, only one patient showed a transition from high thromboembolic risk at admission (CALT 1 greater than or equal to four) to low at the reassessment at D3 (CALT 2 less than zero). Our study has several strengths. It is a bicentric study covering a large period over several epidemic waves during which practices evolved. Most of the parameters evaluated are used in common practice. We extended our investigations to factors that are less widely used but of potential interest in view of the pathophysiology of the coagulopathy observed during severe SARS-CoV-2 infections. We also propose a practical algorithm for routine clinical practice based on a two-stage decision score that can be used on patients on whom CT scans cannot be performed. One of the main limitations of our study is the absence of data before the current hospitalization.
We included a heterogeneous population, including subjects coming from home, from conventional hospitalization, or from another ICU, most often in order to benefit from ECMO. As such, we could not collect reliable data on the existence of previous thromboprophylaxis or therapeutic anticoagulation. This limitation can be analyzed in light of the data reported by Battistoni et al. , who showed that the use of chronic anticoagulation was not associated with an overall increase in ICU mortality or morbidity  [29]. However, in the adjusted survival analysis of this study, in-hospital anticoagulation was associated with higher survival compared with no anticoagulation, supporting the hypothesis that anticoagulation started during hospitalization has a benefit. Notably, we were only able, in our study, to collect data regarding the prophylactic or therapeutic nature of anticoagulation for the first 48 h in the ICU and found, as expected, that all patients with PE upon admission to the ICU initially received therapeutic anticoagulation.
Flow-cytometry Staining was performed for 30 minutes at 4°C in PBS. All antibodies were purchased from Biolegend and were used in 1:50-1:100 dilutions. The complete list of antibodies is shown in Supplementary Table  1. The compensation control was performed using single color staining. Unstained controls and Fluorescence minus one (FMO) control were utilized to establish baseline gate settings for each respective antibody-fluorophore combination used in individual experiments. Stained cells were analyzed with CytoFLEX Cytometer (Beckman Coulter). Data analysis was performed using the Cytexpert software (Beckman Coulter).
Tumor experiments AB12 cells (1 × 10 5 ) were injected to the peritoneum of BALB/c mice (at least 7 mice per group). To determine survival, mice were routinely monitored and when they developed significant ascites or their general condition deteriorated, they were euthanized. Tumor tissue was collected from the peritoneal cavity immediately after the mice were anesthetized. The percentage of necrotic area out of entire tumor area was determined in hematoxylin and eosin stained tumor section based on morphology using the ImageJ software. CTLA-4, PD-1, LAG-3 and TIM-3 blockade and cisplatin treatment 200µg of anti CTLA-4 (clone 9D9), anti PD-1 (clone RPMI-14) anti LAG-3 (clone C9B7W) or anti TIM-3 (RMT3-23) blocking antibodies (BioXcell) were injected to the peritoneum of tumor-bearing mice at the indicated time points.
RNA sequencing RNA-Seq was performed on AB12 tumors from at least 3 independent mice per group at the indicated time points. Libraries were prepared using the KAPA RNA HyperPrep kit (Roche), according to the manufacturer instructions. Paired-end 75 or 100 base massively parallel sequencing was then carried out on an Illumina NextSeq500 or NovaSeq6000, respectively. FASTQ files were aligned to the mouse reference genome GRCm38/mm10 using TopHat2 (v2. 0. 14). Uniquely mapped reads were kept and BAM files were indexed and sorted using Sambamba (v0. 6. 5). We used HTSeq to obtain the number of reads associated with each gene in the Gencode vM21 transcriptome indexes. The Bioconductor DESeq2 package was used to import raw HTSeq counts for each sample into R statistical software and to apply variance stabilizing transformation to the raw count matrix to obtain an expression matrix without variance-mean dependence (DESeq2-normalized counts).
Human-mouse transcriptomic integrative analysis A total of 306 samples from 3 different RNA-sequencing datasets were used for the comparative transcriptomic analysis, including 295 hMPM (from 2 different datasets: 209 and 86 hMPM from the Bueno and TCGA series, respectively)  (26, 27)  and 11 mouse AB12 samples. First, common genes that are 1:1 orthologs in human and mouse were selected using the list of mouse-human 1:1 orthologous genes from MGI (http://www. informatics. jax. org). Then, we filtered out most of the genes by keeping only the 2000 mouse-human 1:1 orthologous genes with the highest variance in human datasets. Finally, we standardized gene expression in each dataset to have mean 0 and standard deviation 1 per gene just before the three datasets were integrated. Unsupervised hierarchical clustering of the integrated data was performed using cosine distance and Ward's linkage method on the 2000 most variant orthologous genes with ComplexHeatmap package in R statistical software.
Pathway enrichment analysis Differentially expressed protein coding genes between groups were determined using the DESeq2 package in R. Only genes with an adjusted p-value below 0. 05 and a fold-change higher than 2 were considered. The hypergeometric test was used on overexpressed and underexpressed genes separately to identify enriched mouse Molecular Signatures Database gene sets (MSigDB v7. 2. 1 obtained using msigdb in R) in the list of differentially expressed genes. Over-representation analyses were performed using the Hallmark, KEGG, Reactome and GeneOntology databases. The over-represented signal pathways over-represented in several of the databases were grouped into families and sub-families, which are highlighted in Supplementary Table  3.
Molecular classification and histomolecular score predictions Expression data from RNA sequencing (FPKM scores) were used to predict Thorsson subgroups  (28). In particular, an ensemble classifier based on XGBoost was implemented to classify tumor samples into one of six immune subtypes using the "ImmuneSubtypeClassifier'' package in R. Histo-molecular scores in human tumor samples were previously predicted  (17). Only samples with a cumulated E. score and S. score higher than 50% were taken into account to ensure sufficient tumor content for correct estimation.
Tumor microenvironment cell content The human microenvironment cell population counter (MCP-counter) or mouse dedicated (mMCP-counter) methods were used to compute scores of infiltration for different immune and stromal cell populations from DESeq2-normalized RNA-seq data. MCP-counter scores were calculated using the MCPcounter method  (29)  previously validated in hMPM tumor samples  (17)  and adapted to RNAseq data using genes filtered on hMPM cell lines (30) whereas mMCP-counter scores were obtained using the mMCPcounter package in R  (31). The list of specific genes used for each population is available in Supplementary Table  4. Infiltrations were determined using the scores of MCP-counter for hMPM and mMCP-counter for AB12 tumors and matching of the cell populations between the two predictive tools.
A total of 295 human tumor samples from two different series of RNAseq were combined in the integrated analysis with public datasets, including the 209 samples from Bueno et al. (26)  and 86 samples from TCGA  (27). Then, we standardized gene expression separately to have a mean of 0 and a standard deviation of 1 per gene in each dataset. Statistical analysis and data visualization were performed using R software. Unsupervised hierarchical clustering was performed using cosine distance and Ward's linkage method.
1 ) which forms part of the ROMARIN network (https://erddap. osupytheas. fr, last access: 14 February 2023). Atmospheric pCO2 is recorded at the terrestrial station of Cinq Avenue (CAV, Fig. 1 ) by the AtmoSud regional atmospheric survey network (https://www. atmosud. org, last access: 14 February 2023), and AMC project (Aix-Marseille Carbon Pilot Study, https://www. otmed. fr/research-projects-andresults/result-2449, last access 14 February 2023). CAV station is located in the city Marseille and, the recorded pCO2 values are representative of a highly urbanized environment, exhibiting strong maxima and large variations. Solar irradiance and wind speed were extracted from the WRF meteorological model  (Yohia, 2017)  for SOLEMIO station (Fig. 1 ). To evaluate our model results, we compared the modelled total chlorophyll concentration to in situ measurements by using a dataset from the Service d'Observation en Milieu LITtoral (SOMLIT, https://www.
Typical vs limited conditions We simulated three types of light and nutrient regimes: typical, nutrient limited, and light limited (Table  4 ). Simulations are run for 2017, at SOLEMIO station. For the typical scenario, light was modelled using the solar irradiance from the WRF meteorological model for SOLEMIO station (Table  1 ) and NO3 -, NH4 + , and PO4 3-concentrations were based on in situ observations at SOLEMIO during 2017 (values from SOMLIT) using a linear interpolation between fortnightly data points (Fig  3 ). In the nutrient limited scenario the ecosystem is limited by DIN and DIP concentrations only, using values 10 times lower than the minima observed at SOLEMIO, keeping both DIN (sum of NO3 -and NH4 + , 6. 75×10 -3 mmol m -3 and 7. 5×10 -4 mmol m -3 , respectively) and DIP constant for the duration of the simulation.
Acknowledgements We thank the  National Service d'Observation en MILieu Littoral (SOMLIT)  for its permission to use SOLEMIO data. We would like to thank the crew members of the  RV Antedon II , operated by the  DT-INSU , for making these samplings possible, the team of the SAM platform ( Service Atmosphère Mer)  of the  MIO  for help with the field work. We also thank  Michel Lafont  and  Véronique Lagadec  of the  PACEM  ( Plateforme Analytique de Chimie des Environnements Marins ) platform of the MIO. We acknowledge the  TMEDNet team  for its permission to use the Planier-Souquet temperature data. We thank the  ROMARIN network team  for its permission to use the salinity data from Carry buoy. We thank the  observatoire de la qualité de l'air en Région Sud Provence-Alpes-Côte d'Azur (ATMOSUD)  in particular,  Alexandre Armengaud , and the  AMC (Aix-Marseille Carbon Pilot Study)  project leaders,  Irène Xueref-Remy  and  Dominique Lefèvre  for providing the atmospheric CO2 data at the  Cinq Avenue  station.