dataesr/scientific-paragraphs-categorization huggingface dataset:
Liquid The 1 H NMR analysis of the liquid samples was performed in a Bruker AVANCE 400 MHZ spectrometer and analyzed using the software TopSpin 3. 0. The measurements were performed at room temperature with an accumulation of 64 scans. The samples (≈20 mg) were diluted with deuterated DMSO (DMSO-d 6 ) (0. 6 mL). The liquid product was completely soluble in the DMSO solution. The NMR spectra are shown in Fig. S6. Comprehensive GC × GC/TOF-MS and GC × GC/FID were used to, respectively, identify and quantify the compounds in the pyrolysis liquid product. The GC × GC/TOF-MS system was equipped with a cryogenic modulator from Zoex Corporation (USA) and a BenchTOF 2 TI spectrometer from Sepsolve. The GC × GC/FID was equipped with a switch valve modulator (Agilent G3486A CFT modulator). The chromatograph and TOF parameters are described in Tables S1.
For analysis, the liquid product was solubilized in THF using a concentration of ≈1 wt%. Before the analysis, any unsoluble products were filtered using a 45 µm PTFE syringe filter. The data obtained from comprehensive GCxGC-FID was also used to provide the distillation curve of the compound families in the pyrolysis liquid products by using a mixture of n-alkanes (C 7 to C 40 ) as a reference.
Details about the market and case selection are discussed in Section III-C, showing, also, how data were collected and analyzed. Through an interpretative study of the literature results, together with interactive analysis of the interviews, a six-phase model was created in the theory-building and model conceptualization stage (which corresponds to the prescriptive study phase of DRM). Finally, in the validation phase (which corresponds to the descriptive study II phase of DRM), this model was tested by interpreting the data from the application case and verifying and triangulating them with the theory on DS and BMI. The outcome of the entire research process is the design of a validated model, showing a six-phase journey for DS supporting BMI.
D. Data From Application Case Collection and Analysis Data were primarily collected through the analysis of primary and secondary data. Table  III  presents some details about this. The interviewees were mainly managers who were responsible for the successful implementation of the DS processes. This was because, in small enterprises, strategy and decision making are concerted among a few informants  [73]. The interviews were conducted separately with the company and the start-up, mainly through phone calls. Open-ended questions were asked and notes were taken. The respondents had an engineering or informatics background. Furthermore, the firm managers boasted several years of professional experience, while the start-up workers were young. Therefore, based on the above-mentioned criteria, the chosen interviewees were considered appropriate informants for the study.
Following this, the second set of questions, connected to DS, were asked to explore and describe the phases incurred by the firm, including questions, such as "Why did you decide to include services in your value offering?," "How did you get to the deliverable solution?," and "What challenges did you have to cope with?. " Last, the third set of questions looked at BMI. Therefore, questions, such as "What are the main changes to your way of creating, delivering, and capturing value?," were asked. The secondary data included all relevant notes, reports, market forecasts, and detailed specifications and descriptions of the different technologies. To avoid any bias, the presented research was designed with special attention to the context and to the selection of interviewees, data collection, and analysis.
Finally, in this phase, based on an understanding of the goals and investment possibilities, the managers allocated funds for the developing, implementing, and selling of the digital servitized solutions. 3) Phase 3. Solution Conceptualization: Once the SME was reorganized, Start-up B and the team of engineers from Company A started collaborating to make the idea a reality. Combining the software and hardware capabilities, they first created a simple sensor and the related software, where data were collected for the provision of basic monitoring and controlling services. With this first concept solution, the firms asked its suppliers and some potential customers in the region for feedback and suggestions to, first, test if the solution was of interest and then to understand which specific digital services could be added.
This project received funding from the  Innovative Medicines Initiative 2 Joint Undertaking  under grant agreement  EBOVAC1  (grant nr. 115854 ),  EBOVAC2  (grant nr. 115861 ) and  EBOVAC3  (grant nr. 800176 ). This Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation programme  and the  EFPIA.
( ClinicalTrials. gov Identifier: NCT02416453 and EudraCT 2015-000596-27), 18 to 65 years old healthy adults were included in the United Kingdom and France. The EBL2002 study (ClinicalTrials. gov Identifier: NCT02564523) was conducted in Burkina Faso, Cote d'Ivoire, Kenya and Uganda and enrolled three cohorts; 18 to 70 years old healthy adults, HIV infected adults, 12 to 17 years old adolescents and 6 to 11 years old children. The EBL3001 (ClinicalTrials. gov Identifier: NCT02509494) was a phase 3 double-blinded study which evaluated the safety and immunogenicity of the Ad26. ZEBOV (at day 0) and MVA-BN-Filo (at day 56) vaccine regimen in healthy adults, adolescents, children and toddlers in Sierra Leone. The Phase 2 UK/France study (EBL2001) protocol and study documents were approved by the French national Ethics Committee (CPP Ile de France III; 3287), the French Medicine Agency (150646A-61), the UK Medicines and Healthcare Products Regulatory Agency (MHRA), and the UK National Research Ethics Service (South Central, Oxford; A 15/SC/0211).
MS scans (m/z 375-1500) were recorded at a resolution of R = 120000 (@ m/z 200), a standard AGC target and an injection time in automatic mode, followed by a top speed duty cycle of up to 3 seconds for MS/MS acquisition. Precursor ions (2 to 7 charge states) were isolated in the quadrupole with a mass window of 1. 6 Th and fragmented with HCD@28% normalized collision energy. MS/MS data was acquired in the ion trap with rapid scan mode, a 20% normalized AGC target and a maximum injection time in dynamic mode. Selected precursors were excluded for 60 seconds. Protein identification was done in Proteome Discoverer 2. 5. Mascot 2. 5 algorithm was used for protein identification in batch mode by searching against a UniProt Homo sapiens protein database (75796 entries, release September 3, 2020; https://www.
The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository  (33)  with the dataset identifier PXD043640. Immunohistochemistry on HCC samples. Mouse HCC samples were from Hep3B xenografts previously described  (20). This model consisted of subcutaneous inoculation of Hep3B-shCtrl or Hep3B-shRnd3 cells in immunodeficient NOG mice treated with doxycycline to induce or not Rnd3 knockdown. The analysis of entosis was performed on tumor sections stained with hematoxylin to mark cytoplasm and nuclei of cells. Human samples came from resected or explanted livers with HCC of patients treated in Bordeaux from 1992-2005. The characteristics of HCCs used for the IHC analysis (10 HCCs) are indicated in Table  1. Formalin-fixed, paraffin-embedded sections of human or mouse HCC samples were used for Hematoxylin-Eosin or immunohistochemical staining.
Acknowledgments We thank  V. Pitard  and  N. Dugot-Senant  from the  FACSility and Histopathology platform  respectively ( TBMCore, UMS005, Bordeaux ). Electron and photonic microscopy was done in the  Bordeaux Imaging Center , a service unit of the  CNRS-INSERM and Bordeaux University , member of the national infrastructure  France Bio Imaging , with the help of  Dr Etienne Gontier  and  Isabelle Svahn. We express our gratitude to  Paul Divet ,  Cyril Dourthe  and  Clotilde Billottet  for their help, with, respectively, evaluation of entotic cells, bubble plot representation of proteomic data and collecting of patient tumor data.
00 18. 33 12. 43 4. 58 1,75E-06 1,72E-04 1,32E-05 4,84E-07 4,53E-04 6,53E-04 3,03E-02 1,77E-03 3,95E-05 1,32E-02 upload_1 (Homo sapiens) Reference List: 2. 79 3. 85 3. 23 1. 98 3. 40 2,16E-06 1,70E-04 1,43E-05 5,86E-07 4,77E-04 7,87E-04 3,03E-02 1,87E-03 4,61E-05 1,33E-02 Homo sapiens (all genes in database) Test Type: 2. 15 10. 21 4. 82 15. 64 95. 32 2,23E-06 1,76E-04 2,43E-05 6,18E-07 4,73E-04 7,95E-04 3,07E-02 3,10E-03 4,68E-05 1,34E-02 FISHER Correction: 2. 73 3. 81 15. 21 13. 71 7. 77 3,09E-06 1,88E-04 3,01E-05 1,40E-06 5,82E-04 1,08E-03 3,25E-02 3,66E-03 1,02E-04 1,61E-02 FDR upload_1 (fold Enrichment) upload_1 (raw P-value) upload_1 (FDR) 11. 91 3,35E-06 1,14E-03 30. 64 2,08E-04 3,54E-02 15. 21 3,01E-05 3,75E-03 2. 57 1,67E-06 1,18E-04 11. 00 6,19E-04 1,64E-02 2. 44 7. 66 3. 48 3. 32 4.
Of which, 560 upregulated and 1308 downregulated are significantly different only in the 1° infection in comparison to uninfected cells (green bars), and 376 downregulated and 928 upregulated are specific of the 2° infection (purple bars). These results show that the 1° infection is dominated by downregulated DEGs, while upregulated DEGs prevail during the 2° infection, and highlight the observation that cells following 1° infection respond differently to a 2° infection. By performing Gene Set Enrichment Analysis (GSEA), we obtained a functional description of the transcriptome using the gene sets reported in the Reactome database (Figure  1E  and Table  S1 ). A normalized enrichment score (NES) is calculated for each significatively enriched pathway (FDR>0. 05) and indicates expression levels.
A549 cells are terminally differentiated type II pneumocytes with little potential to transmit epigenetic changes in a physiological setting. Therefore, we performed infections of undifferentiated nasal cells, RPMI 2650, and measured levels of H3K4me2 by immunofluorescence. Similarly to A549 cells, we observe a strong increase in the level of H3K4me2 after 48 h of infection (1°) (MOI 10) compared to uninfected cells (UI) (Figure  4D ). In these cells, we also confirmed the specificity of our antibody by performing the same immunofluorescence experiments with another H3K4me2 antibody cataloged in the Histone Specificity Database (http://www. histoneantibodies. com). Similarly, we were observed a strong increase in the level of H3K4me2 after 48 h of infection (1°) compared to uninfected cells (UI) (Figure  S4C ), independently of the antibody used.
Amongst these, only 9 were linked with a gain in methylation, which is we decided was not sufficient to further our analysis. Therefore, we extended our study to include regions of methylation and genes that displayed a upwards trend even though they were not statistically significant (black dotted lines in Figure  S5B ). Using this method, we predicted 3845 regulatory links between H3K4me2 regions and genes. Together with the above 29, we analyzed 3874 associations from a global perspective, using a Multiple Factor Analysis (MFA)  (21). This factorial method is aimed at uncovering the main sources of variability that characterize a dataset among multiple sets of quantitative and qualitative variables. To perform this method, we used both transcriptome and methylome, more precisely: the complete transcriptome dataset of the UI cells, post 1° infection, PI and post 2° infection (TOME); the H3K4me2 log fold change of PI vs UI and the average H3K4me2 level of the 1° infection time course (METH).
We added the epigenome profile of the UI cells (EPIG) described by six key histone marks symptomatic of the main active and repressive chromatin states (CS). We retrieved ten ENCODE samples H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K79me2 and H3K27me3 from the ENCODE database for A549 cells  (22). Finally, we considered two additional variables that describe the regulatory links between genes and H3K4me2 peaks, as estimated by the T-Gene tool of the MEME suite  (23) : the distance in bp separating each gene-peak pair (DIST) and the correlation between chromatin and gene expression changes in an independent tissue panel (CORR) (Figures S6A). Factors resulting from the MFA summarize the structure of the joint groups of variables, as shown by the cumulative percentage of variance associated to the first 5 factors/dimension (Dim) and the correlation coefficients of groups of variables with each factor (Figure  S6B ).
e. UI, 1°, 2° infections and PI in triplicates, was measured using the Affymetrix Human Gene array 2. 1 microarray. Data were deposited into the Gene Expression Omnibus (GEO) repository of the National Center for Biotechnology Information under accession number GSE230142. Expression signal was normalized using the Robust Multichip Average (RMA) method, from the affy R package (doi: 10. 1093/bioinformatics/btg405). Control and lowly express probes were filtered out and the replicate effect was removed using the ComBat approach implemented in the sva R package  (52). Replicate 3 from 1° infection was filter out after principal component analysis. Differential expression analysis was performed using the limma method (  53 ) and the following comparison evaluated: 1° infection vs UI cells, 2° infections vs PI and (2° vs PI) vs (1° vs UI), i.
e. 2° infection vs 1° infection. Genes with an adjusted p-value < 0. 05 were defined as differentially expressed (DEGs). For the functional characterization, we performed a Gene Set Enrichment Analysis (GSEA) for each comparison, by ranking the genes with the t-statistic, which is the log2 fold change divided by its standard error. We used the Reactome database gene sets and the GSEA implementation in https://gitlab. pasteur. fr/hvaret/fgsa_scripts.
Methylome analysis. H3K4me3 and H3K4me2 were profiled using ChIPseq for the UI cells, 1° infection (3h) and PI (7d) in duplicates. Complete analysis from the raw sequencing data to the differential marking analysis was done following the ePeak approach  (54). Default parameters were used for the filtering, mapping of reads and for narrow peak calling. For H3K4me2, reproducible peaks were determined using the intersection approach, requiring at least 40% length overlap between replicates. For H3K4me3, reproducible peaks were determined using the IDR method. Data were deposited into the Gene Expression Omnibus (GEO) repository of the National Center for Biotechnology Information under accession number GSE230142. Differential analysis was performed using the limma method (  53 ) with a model considering the biological factor of interest, i.
Coverage over peaks was normalized by length and scaled. Peaks with similar epigenomic profiles were clustered using the Euclidean distance and the Ward agglomerating method. Integrative analysis. Joint analysis of the complete dataset was performed by Multiple factor analysis (MFA)  (21). Firstly, we predicted the regulatory links between DEs and DMs using T-gene (23) and selected the most significant links (distance < 500Kb and correlation p-value < 0. 05). The joint dataset contains the 3874 links holding either a differentially expressed gene (DEs) and/or a dynamically marked region (DMs) and either a not DMs and/or a not DEs. For each link we defined five groups of continuous variables: • Transcriptome (TOME) consisting of the gene expression over the four time points (UI, 1°, 2° infections and PI) in triplicates; • H3K4me2 methylome (METH) measured by the average methylation over le three time points (UI, 1°, PI) and the log fold change between PI and UI cells; • Epigenome of the UI condition (EPIG) including the coverage of the above-mentioned histone modifications over the H3K4me2 regions; • Distance (DIST) and correlation (CORR) of the regulatory link between genes and regions; and two groups of categorical variables: • DEG kind and sing, describing whether genes are specific of the 1° or 2° infection, or Not specific; and whether genes are going Up, Down, UpDown or DownUp along the time course; • DMR kind and sing, indicating whether regions are DM or NotDM; and whether regions belong to the Gain or Loss of H3K4me2 profile along the 1° infection time course.
For each peak, 500bp were extracted around the summit and then used as input for MEME-chip V5. 1. 1  (56). For the analysis, the HOCOMOCO v11 was used as target database for the motifs and the parameter ccut (maximum size of a sequence before it is cut down to a centered section) was set to 0. All the other parameters were the default parameters of the MEME-chip web version.
Acknowledgements We would like to thank  Tiphaine Marie-Noelle Camarasa  for her help with the acquisition of the samples performed on MACSQuant flow-cytometer. We thank the  Biomics platform ,  C2RT ,  Institut Pasteur  in particular  Juliana Pipoli Da Fonseca  for processing the libraries and the sequencing of ChIP-seq. We were thankful to all members of the  Chromatin and Infection Unit  and the  GORE expertise group of the Hub  for their precious advice throughout the project and for critical reading of this manuscript. We thank the  UTechS PBI platform ,  C2RT ,  Institut Pasteur , for giving us access to the LSM780 confocal microscopy driven by  Zen software (Zeiss)  to acquire some images. We would like to thank  Thomas Kohler  for providing of Streptococcus pneumoniae TIGR4 strain used in this study.
Work in the Chromatin and Infection Unit (headed by  Melanie Hamon ) is supported by the  Institut Pasteur , the  Agence Nationale de la Recherche  ( ANR 17 CE12 0007 01 EPIBACTIN ), the  Fondation pour la Recherche Médicale  ( FRM608 EQU202003010152 ), the  Fondation iXCore-iXLife , the  Don Prix CANETTI 2020 , the  EMBO   Young Investigator Program. M. A. H. is a member of the  Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases" Agence Nationale de la Recherche  ( ANR-10-LABX-62-IBEID ). M. G. C. is supported by a Springboard to Independence grant (AirwayStasis) from the  French Government 's  Investissement d'Avenir program , the  Laboratoire d'Excellence ''Integrative Biology of Emerging Infectious Diseases"  ( ANR-10-LABX-62-605IBEID ) and  Pasteur-Weizmann research fund.
Complement proteins are highly conserved in Humans and Rhesus The complement system is comprised of a series of activating and suppressing proteins, expressed in soluble form as well as an on cellular membranes that interact and catalyze transformations that can either negatively regulate or result in loss of membrane integrity (Figure  1A ). We wished to explore the conservation of human and rhesus proteins at the level of primary structure and obtained the sequences of complement proteins from humans and rhesus from the uniprot database (UniProt, 2021) (Table  1 ). Because Complement Component 7, Factor H and Factor I proteins of rhesus were not annotated, sequences for these proteins were obtained by applying BLAST (Basic Local Alignment Search Tool) algorithm  (Altschul, Gish et al. , 1990)  using human sequences as a query on the Macaca mulatta proteome.
Acknowledgements HIVIG was obtained through  NIH   HIV Reagent Program ,  Division of AIDS, NIAID ,  NIH :  Polyclonal Anti-Human Immunodeficiency Virus Immune Globulin, Pooled Inactivated Human Sera ,  ARP -3957, contributed by  NABI  and  National Heart Lung and Blood Institute  ( Dr. Luiz Barbosa ). VRC01 heavy and light chain in expression vector plasmids (ARP-12035,12036) were also obtained through  NIH HIV reagents program : contributed by  Josh Mascola. Some of the HIV-1 gp140 antigens produced in CHO cells lines ( ARP -12063, 12064, 12065, 12066) were obtained from  NIH  HIV reagent program: contributed by  DAIDS/NIAID ; produced by  Polymun Scientific Inc. A few other HIV-1 gp140 antigens produced in HEK 293F cells ( ARP-12572 ,  12573 ,  12575 ,  12577 ,  12581 ) were obtained from  NIH   HIV reagent program : contributed by  Dr.
Funding These studies were supported in part by  NIAID   P01AI162242 ,  R01AI129801 ,  Institut Pasteur  funds,  Fondation pour la Recherche Médicale (FRM) ,  ANRS-MIE , the  Vaccine Research Institute  ( ANR-10-LABX-77 ),  HERA European program  ( DURABLE consortium ),  Labex IBEID  ( ANR-10-LABX-62-IBEID ),  ANR  and  ANR/FRM Flash Covid  grants.
Gene relative expression was calculated in two steps: First, the comparison ratio of a target cDNA sequence to a reference DNA sequence (mean of two housekeeping genes, Cg-RPL40 for ribosomal protein L40, Genbank AN FP004478; Cg-EF1 for elongation factor 1α, Genbank AN AB122066) was realized automatically by LightCycler® 480 Software (Version 1. 5). Then, normalized ratio was calculated by dividing the ratio of selected condition with the ratio of control condition according to  Pfaffl, 2001 (37) : Normalized ratio = ([target]/[reference]) selected condition/([target]/[reference]) control condition. For every condition, each of the 10 individuals at time T0 was compared to the 10 individuals at time T1 that generated 100 values/condition/gene.
Acknowledgments We acknowledge the support of the  Ifremer facilities of La Tremblade ,  Bouin  and  Argenton (ASIM-"Adaption et Santé des Invertébrés Marins " , " Atlantic Marine Molluscs Experimental" -EMMA and PHYTNESS units, France ). Authors also thank the  FINA Ifremer program  and the  DECICOMP  project ( Guillaume Mitta ,  ANR-19-CE20-0004 ) for  01/2020  and F15 oyster production, respectively. We are grateful to  Philippe Clair  from the  qPHD-Montpellier GenomiX  platform for useful advice.
Funding This work was supported by the project " STAR" ( Ifremer Innovation program) ,  EU  project  VIVALDI  ( H2020 program , no. 678589 ) and the " Primoyster " funded by the  French Research Agency  ( ANR-22-CE20-0017 ) and the  DECICOMP  project ( ANR-19-CE20-0004 ). MM funding was supported by  Ifremer. These results are protected under patent supported by  Ifremer , application number  WOEP2021/062895 , " composition for the treatment  and/or  prevention of marine mollusc viral infection ".
The spatial resolution varied from locality to country scale, with more often province chosen as sampling location. Fieldwork areas were described with environmental characteristic or administrative nomenclature. Inconstance came from different focus either on a local targeted area or on over a broader-scale exposure to the pathogens. Sizes of datasets were often small. The median sample size was 40 and the maximum sample size was 3186 rock doves (Columbia livia) from an urban setting in Italy for B. anserina detection 136. A total of 41 publications tagged captured individuals. But tags were not always specific and trustable, some authors simply relying on scars made by biopsy or on feather clipping. The aim of marking was sometimes only to avoid resampling, with immediate release in case of recapture.
(B) Distribution of the study years of fieldwork effort. From data on start and end dates, a count of publications putting fieldwork effort was implemented by year. Unfortunately, 20 publications did not inform their time period of fieldwork. (C) Detection methodologies. PCR = Polymerase in Chain Reaction; ELISA = Enzyme-Linked Immunosorbent Assay; IFA = Immunofluorescence Assay; µ = microscopy; HA = Hemagglutination Assay; SNT = Serum Neutralisation Titer; SNAP = commercial veterinary Ig detection kit; WB = Western Blot; IP = Indirect Immunoperoxidase; NI = Not Informed; SB = Southern Blot; seq = Sequencing; SIA = Strip Immunoblot Assay; CFR = Complement Fixation Reaction; eph = electrophoresis; inj = Injection in mice. Data are available in Supplementary Dataset 1.