dataesr/scientific-paragraphs-categorization huggingface dataset:
Background Influenza surveillance is essential for tracking and controlling influenza infections and for assessing influenza vaccine effectiveness (IVE). Since 2012, the Global Influenza Hospital Surveillance Network (GIHSN) has run an annual prospective, active-surveillance, hospital-based study to collect epidemiological and virological data on influenza  [1]. The aim of the GIHSN is to improve understanding of influenza epidemiology to better inform public health policy decisions. During the 2015-2016 influenza season, the GIHSN included 11 coordinating sites and 27 hospitals in nine countries (St. Petersburg and Moscow, Russian Federation; Prague, Czech Republic; Ankara, Turkey; Paris, France; Beijing, China; Valencia, Spain; Tlalpan, Mexico; Jammu and Kashmir, India; and Fortaleza and Curitiba, Brazil).
Admission with influenza according to pregnancy A total of 1051 women 15-45 years old were included in the study, of whom 615 were pregnant (596 in Moscow, 2 in the Czech Republic, 2 in Turkey, 4 in France, 3 in Valencia, 4 in India, and 4 in Curitiba; data not shown). The probability of laboratory-confirmed influenza was significantly higher (P < 0. 001) in included pregnant women (45. 2%) than non-pregnant women in this age range (23. 8%) (data not shown). After considering site as a random effect and excluding data from St. Petersburg, Beijing, and Mexico (where no pregnant women were enrolled), the crude OR of admission with influenza was 2. 82 (95% CI, 1. 90 to 4. 19)  for pregnant women (data not shown). When considering pregnant women with no comorbidities, the crude OR was 2. 64 (95% CI, 1.
In addition, different sources of data were used to ensure complete case ascertainment, including data from clinical records, health registries, and information provided by the patient and attending nurses and doctors. Influenza vaccination status was obtained by asking the patient (or representative) if they had received the current season's influenza vaccine, the date of vaccination, and if the vaccine had been administered at least 2 weeks before the onset of symptoms. Additionally, when records existed, this information was validated by existing registers, vaccination cards, or through contacting the clinic where the vaccine was administered. To describe heterogeneity we reported the I 2 parameter. Finally, we used random effects to account for variability by site. From 2014-2015 to 2015-2016, the GIHSN expanded from seven coordinating sites in six countries to 11 coordinating sites in nine countries.
Acknowledgements Medical editing was provided by  Drs. Phillip Leventhal  and  Jonathan Pitt  (4Clinics, Paris, France) and paid for by  Sanofi Pasteur. The GIHSN members include:  O. Afanasieva ,  Research Institute of Influenza, St. Petersburg, Russian Federation ;  M. Akcay Ciblak ,  Sanofi Pasteur, Istanbul, Turkey ;  A. Bagci Bosi ,  Hacettepe University, Faculty of Medicine, Ankara, Turkey ;  V. Baselga-Moreno ,  FISABIO-Public Health, Valencia, Spain ;  E. Burtseva ,  D. I. Ivanovsky Institute of Virology FSBI "N. F. Gamaleya NRCEM", Moscow, Russian Federation ;  M. Carballido-Fernández ,  Hospital General de Castellón, Castellón, Spain ;  P. Cervantes ,  Sanofi Pasteur, France ;  B. Costa-Caetano ,  Foundation Oswaldo Cruz Foundation (FIOCRUZ) ,  Rio de Janeiro , Brazil;  B. Cowling ,  School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China ;  M.
Quantifications of tract size and feather follicles/dot number Tract size. Feather-containing surfaces normalised by that of the whole dorsum were measured using Fiji software on pictures of flat skins at developmental stages corresponding to tract completion (E11 for the domestic chicken, n = 2; E10 for the Japanese quail, n = 3, E12. 5 for the common pheasant, n = 3, E26 for the emu, n = 2, approximately E25 for the gentoo penguin, n = 1) and at hatching for the zebra finch (the relative surface of the completed tract being conserved during development, follicles are best visualised at P0; n = 2). Follicle/Dot number. To quantify feather follicles or dot number (F) respectively on pictures of flat skins or model simulations in a time-efficient and consistent manner (i. e. , across species and at different stages), we developed a custom Matlab program.
The algorithm follows three steps: first, a gaussian filter reduces optical noise through image smoothing (Matlab function 'imfilter'; filters were obtained with the function 'fspecial'). Second, morphological operations are applied (i. e. , closing followed by opening of the image with a disk of radius 1 pixel using functions 'imopen' and 'imclose'; the disk was constructed using the strel function). Third, feather follicles/dots are detected as connected components of the image and their properties (centroid, bounding box, surface, etc. ) stored. Because background levels on skin images can fluctuate, the algorithm contains a set of linearly spaced thresholds to (1) produce a binary image through a detection threshold of the pretreated image, (2) identify the connected components of the binary image (Matlab function 'bwconncomp'), and (3) repeat the second step if the maximal value in a given component is above the next threshold.
The resulting feather/dot locations are presented in a Matlab interface (S1 Fig) allowing adjustment of thresholds, filtering of properties, and correction for undetected follicles or false positives (needed for less than 5% of the total follicle number). Locations are processed to identify rows by segmenting the set of feathers/dots according to their location along the xaxis (and corrected by hand in the cases of Japanese quail and zebra finch, for which fr# is shifted laterally, and in the emu, for which counting was performed along six virtual lines). Program code and interface (Dotfinder) are available upon request.
Modelling All simulations were performed using FreeFem++  [41]  software (specifically designed to compute numerical solutions of partial differential equations) with no flux (Neumann) boundary conditions (i. e. , cells or molecules are free to diffuse outside of the tract). Spatial and temporal discretisation parameters were chosen as a compromise between accuracy and efficiency (n x between 120 and 160, dt between 0. 01 and 0. 1). Size of simulations frames. For comparison of pattern dynamics relative to tract size, the width (l s ) and length (L s ) of simulation frames have been set for each species according to developmental landmarks: we measured widths (i. e. , l, in mm, distance between wings) and lengths (i. e. , L, in mm, distance between tails and a medial point between wings; Fig 3A  , S3  Table, and S5 Data).
Immunohistological stains and quantifications Embryonic specimens were embedded in gelatin/sucrose, sectioned using a CM 3050S cryostat (Leica), treated with HCl 2N for 20 minutes (for BrdU stains), rinsed, and stained using a rat primary antibody directed against BrdU (Abcam; 1:200) or β-catenin (Abcam; 1/100) and goat anti-rat Alexa 488 or goat anti-rabbit Alexa 568 secondary antibodies (Abcam; 1:500). Cell nuclei were revealed using DAPI (Southern Biotech). Slides were mounted in Fluoromount (Southern Biotech) prior to imaging. For quantifications of cell density or proliferation, the number of DAPI + or BrdU + cells in both epidermal and dermal layers was counted in 10 sections of confocal images (dividing the dorsal skin from the midline to the ventral limit of the feather field using Fiji software; a in Homogeneity of cell proliferation along the mediolateral axis at stage 0 in the Japanese quail (n = 8) and emu (n = 4) was assessed using a Friedman test on 10 sections of identical lengths dividing the whole feather field, and the significance of differences of cell density or proliferation rates from stages 0 to 3 in the Japanese quail was assessed using Student t tests on the 120μm-long sections.
Acknowledgments We thank  B. Perthame  for help with project conception and analyses;  T. Lecuit  and  A. Planques  for helpful discussion on the manuscript;  E. Bouvet ,  M. Ladner ,  N. Haupaix , and  P. Galipot  for help with the collection of Galliformes, zebra finch, and emu specimens; H. and  M. P. Delignières  as well as the  Falkland Islands Government  for landowner and collection permits for the collection of gentoo penguin specimens; and  N. Quenech'Du  and the  Collège de France imaging facility  for help with image processing and analysis.
In Archaea and Bacteria, the arrays called CRISPRs for 'clustered regularly interspaced short palindromic repeats' and the CRISPR associated genes or cas provide adaptive immunity against viruses, plasmids and transposable elements. Short sequences called spacers, corresponding to fragments of invading DNA, are stored in-between repeated sequences. The CRISPR-Cas systems target sequences homologous to spacers leading to their degradation. To facilitate investigations of CRISPRs, we developed 12 years ago a website holding the CRISPRdb. We now propose CRISPRCasdb, a completely new version giving access to both CRISPRs and cas genes. We used CRISPRCasFinder, a program that identifies CRISPR arrays and cas genes and determine the system's type and subtype, to process public whole genome assemblies.
Strains are displayed either in an alphabetic list or in taxonomic order. The database is part of the CRISPR-Cas ++ website which also offers the possibility to analyse submitted sequences and to download programs. A BLAST search against lists of repeats and spacers extracted from the database is proposed. To date, 16 990 complete prokaryote genomes (16 650 bacteria from 2973 species and 340 archaea from 300 species) are included. CRISPR-Cas systems were found in 36% of Bacteria and 75% of Archaea strains.
CRISPR-Cas systems can be found on plasmids and are D536 Nucleic Acids Research, 2020, Vol. 48, Database issue often associated with transposable elements allowing their transfer between strains and species  (16). Dedicated software have been developed to detect CRISPR arrays, the most used being PILER-CR  (17) , CRT  (18) , CRISPRFinder  (19)  and MinCED (https://github. com/ctSkennerton/minced). Detection of Cas proteins is performed either by BLAST or by Hidden Markov Model (HMM) search such as in CasFinder, a development of MacSyFinder  (20)  and HMMCAS  (21) , using a set of reference Cas from well-known systems. Defining accurately the CRISPR-Cas systems remains a challenge when new genomes are analysed, particularly for the detection of Cas9-like proteins which show a high degree of diversity  (22) (23) (24).
HMM protein profiles such as those available at TIGRFAM  (25)  or Pfam sites  (26)  need to be improved when new sequences become available. Databases that can be queried online are valuable tools to investigate the diversity of the CRISPR-Cas systems, if they are regularly updated. Following the development of the CRISPRFinder program, we launched the first website dedicated to these structures and holding a database called CRISPRdb  (27). Recently we created a new website and developed a tool called CRISPRCas-Finder which associates CRISPRFinder and CasFinder to identify both CRISPR arrays and cas genes in submitted sequences  (28). Other databases were created such as CRISPI  (29) , CRISPRBank  (30) , CRISPRone  (31)  and CRISPRminer  (32). CRISPRDetect is a program that can be used locally or online to analyse genome sequences  (30) , whereas CRISPRdisco allows the discovery and analysis of CRISPR-Cas systems by installing the program locally  (33).
Database and software design and implementation CRISPRCasdb and associated services are implemented in Microsoft. Net Core 2. 2 (multiplatform web application framework), PostgreSQL 9. 5 (RDBMS) and Python (database feeding and updates, BLAST jobs management). Both database and web server run on a single 4-cores virtual machine, while a physical server with 64 cores and 128Gb of memory provides the calculation part for CRISPR and Cas detection and BLAST jobs  (34). Both machines run in a Linux environment (Ubuntu 16. 04). The core application consists of two main programs: CRISPRCasFinder to detect CRISPRs and cas genes and extract them from a genomic sequence, and 'Database Tools' for downloading prokaryotic genomes, metadata and taxonomy from the NCBI ftp site, running CRISPRs and Cas detection scripts on downloaded sequences, storing results, and allowing BLAST searches on DRs and spacers stored in the database.
CRISPRCasFinder is a full command line tool written in-house in Perl. It is used to process published genome sequences and to feed the CRISPRCas database. It can also be run interactively through the web interface for submission and analysis of users sequence data  (28). 'Database Tools' are a set of Python and Perl scripts (the workflow is shown in Supplementary Figure  S1 ). Downloading of genomic sequences, CRISPRs and Cas detection, and motifs extraction are fully automated. The. Net Core Framework, providing a set of tools for object-oriented web programming and an integrated web server is used to build a web resource on top of these programs. This preserves platform independence across multiple operating systems and allows the user to interact with the different CRISPR tools programs without computer programming or (shell) scripting skills.
The database (CRISPRCasdb) CRISPRCasdb is a relational database implemented using postsgreSQL 9. 5. The flowchart on Figure  1A  summarizes the different steps of the database constitution. Supplementary Figure  S2  shows the Unified Modeling Language (UML) class diagram, and Supplementary Figure  S3  shows the tables interactions. Currently, CRISPRCasdb is composed of 15 tables. A BLAST search against lists of repeats and spacers has been implemented (Figure  1B ). The database is regularly updated by adding newly available genomes, and a version of the updater scripts allowing weekly update is being developped. If a major evolution of the CRISPRCasFinder program or associated HMM profiles is released, all the available genomes are downloaded and re-analysed when updating the database. This allows regularly improving the definition of structures when new Cas types and subtypes are defined.
In June 2019, all 'complete genome' and 'chromosome' publicly available in GenBank were recovered from NCBI  (35)  together with taxonomy information  (36) , and the database was built using CRISPRCasFinder v4. 2. 19 program. The selected criteria require that the minimal structure of a putative CRISPR should consist in at least two successive direct repeats with a maximum of one mismatch, separated by one spacer. Tests are performed to classify the putative CRISPRs arrays with evidence level 1 to 4. CRISPRs of less than 4 spacers with three or more perfect repeats are assigned the lowest evidence level. The other CRISPRs are classified based on the conservation of repeats which must be high in a real CRISPR array, and on the similarity between spacers which must be low. We measure CRISPR repeat conservation based on Shannon's entropy and produce an EBcons (entropy-based conservation) index  (28).
RESULTS The CRISPR-Cas++ website which holds the CRISPRCasdb and associated tools was designed to allow fast analyses and updates of the site. In the current version of the database, only complete genomes of bacteria and archaea strains were analysed. Downloading of the genomes and metadata from 16 990 strains (available on June 2019), and CRISPRCasFinder calculation were achieved in 150 h.
CRISPRCasdb: display and query The strains can be displayed as an alphabetical list or by taxonomy, allowing observation of CRISPR-Cas systems in phylogenetically related species, and search can be performed by strain name or GenBank/RefSeq accession number. 'Metrics' provides the date of the last update and global statistics on the number of Cas clusters and level 4 CRISPR arrays. The list of strains can be filtered on the basis of CRISPR or cas number or on the presence of CRISPRs with evidence levels 1 to 4, species Taxid, Cas name and CRISPR-Cas type. Figure  2  details some of the pages which can be viewed when selecting a strain within the alphabetical order view. After clicking on the strain name (step 1), a table on the right appears, showing for each genome present in the strain (chromosome or plasmid) the CRISPRs and cas genes clusters that have been found.
Authorizing small CRISPR-like structures in the database sometimes leads to an important amount of evidence level 1 arrays. For convenience they can be hidden to facilitate observation of the most interesting structures. The CRISPR-Cas type and subtype is indicated together with the cas genes cluster position on the genome, the number of spacers or cas genes and the consensus repeat sequence. An indication of the repeat orientation (when known) and of the CRISPR evidence level is shown. On top of the page, a schematic representation of the genome displays the positions of the CRISPR arrays and cas genes. An arrow appears when an element is selected. Querying a CRISPR locus (step 2) leads to a.
The repeats and spacers lists Repeat sequences of all the evidence level 4 CRISPRs from the database are listed and can be downloaded as a fasta file. Presently they amount to 19 321 sequences. For each repeat the id of the CRISPR in which the sequence was observed is indicated. Similarly, a list of 211 397 spacers encountered in level 4 CRISPRs is available. A dedicated page called 'search DR/spacers' allows running a BLAST (blastn) using selected spacers or repeats against these lists with a default cutoff E-value of 0. 1 and a matching length of at least 70% the queried sequence size. A maximum of 200 results per sequence queried is displayed and the mismatches are shown in red (Figure  2 , bottom panel). Clicking anywhere on a line showing the alignment leads to the name of the target genome in which it is present and display of the corresponding CRISPR.
In total, 123 out of 142 type III-B systems are associated with a type I-A, type I-B or type I-C system. Such associations are also observed in bacteria not only with type I systems but also with other Cas types (Supplementary Table  S1 ). It was proposed that type I and type III cooperate to counteract viral escape in Marinomonas mediterranea  (38). The analysis of large numbers of strains from a single species confirms that some species or genus seem to be completely or mostly devoid of CRISPR-Cas systems. For example in Staphylococcus aureus only five strains out of 449 possess a type III-A system. In the genus Bordetella with a total of 637 strains analysed in the database, only three possess a CRISPR-Cas system. Intracellular organisms such as Chlamydia, Rickettsia and Brucella have no CRISPR-Cas systems.
Comparison with other databases We could identify four additional web-based databases for CRISPR arrays and cas genes (Table  2 ). CRISPI (https://crispi. genouest. org/) is mostly dedicated to the identification of CRISPR arrays whereas CRISPRBank, CRISPRone and CRISPRminer use different programs to define CRISPR and cas clusters, which results in a number of differences with CRISPRCasdb. We previously discussed the performances of the CRISPR and cas genes identification tools in the different programs and concluded that none achieved a perfect identification of both  (28). Accordingly when comparing the databases we could observe a number of discrepancies in characterization of CRISPR arrays and definition of cas gene clusters, although overall these databases can be complementary in providing a thorough investigation of CRISPR-Cas systems.
Improvements of CRISPRFinder are regularly made to obtain a more accurate definition, the last version including the possibility to validate small CRISPRs when their repeat belongs to a level 4 CRISPR. Such small CRISPRs are not taken into account in the other databases. The web sites also differ in the interface and tools offered. CRISPRBank (http://bioanalysis. otago. ac. nz/CRISPRBank/) possesses CRISPR arrays and cas genes from 2733 strains and can be accessed by querying repeats and spacers. CRISPRminer (http://www. microbiome-bigdata. com/CRISPRminer) provides a database of CRISPR and cas genes from complete and draft prokaryote genomes, and additional D540 Nucleic Acids Research, 2020, Vol. 48, Database issue  information on self-targeting, anti-CRISPR genes and the nature of protospacers.
Genomes can be browsed by providing the name of a strain or RefSeq ID or using taxonomic classification. CRISPRone provides a long list of 'mock CRISPRs', most of which are not detected by CRISPRFinder or by Tandem Repeat Finder (TRF)  (39) , which raises questions on their relevance. CRISPRone (http://omics. informatics. indiana. edu/CRISPRone/), like CRISPRminer displays CRISPR arrays and cas genes in a graphical fashion and provides different files with details on repeats and spacers. Presentation in CRISPRCasdb of analysed genomes in the form of an alphabetical list of strains or taxonomic classification is particularly useful to browse the database and discover potentially interesting CRISPR-Cas systems. This interface is not proposed in the other databases available on the web as one must indicate the name or accession number of the organism to query.
DISCUSSION AND FUTURE PROSPECTS CRISPRCasdb by allowing the identification of both CRISPRs and cas genes is a major improvement over CRISPRdb and will replace it once users are fully aware of the new database. We first chose to analyse only complete genomes because we were concerned by the correct identification of CRISPR-Cas systems, which requires that the full cas gene cluster be present on a single sequence. In the future, data extracted from draft or large contigs will be included with an indication of their nature. Following the first analyses by Banfield's group (40) detection of CRISPR arrays in metagenomics data has been performed by different teams and specific tools were developed such as Crass  (41) , MinCED (https://github. com/ctSkennerton/ minced) and MetaCRAST  (42). It will be an interesting challenge to propose such tools on CRISPR-Cas++ owing to the considerable size of data to be processed and required calculation time.
Some functions offered together with CRISPRdb will be implemented, such as a tool to compare alleles of a given CRISPR array among strains, and classify the spacers. Several programs are available such as CRISPRtionary  (43) , CRISPR Visualizer  (44)  and CRISPRStudio  (45)  for comparative visualization of CRISPR content. The new CRISPR-Cas++ website has high performances and flexibility which will allow further evolutions. Its architecture was designed to allow additional developments and in particular the possibility to evolve toward a real webserver by proposing an Application Programming Interface (API). This will give the possibility to interact programmatically with the database and the different applications. We performed some analyses on the database content to illustrate its potential use but more need to be done to understand the distribution of CRISPR-Cas systems in prokaryotic genomes.
Protective effect of divalent ions chelators Divalent ions have been described as common key players in the main proposed modes of action of Bt toxins  (Zhang et al. , 2006). To investigate their contribution to Cry1Ca toxicity, we carried out Sf9 cells intoxication during 18 h with different concentrations of toxin in the presence of 5 mM EDTA or 5 mM EGTA and we evaluated cell viability. EDTA chelates Mg 2+ and Ca 2+ , whereas EGTA preferentially chelates Ca 2+. No detectable mortality was observed when Sf9wt or Sf9-LD 80 cells were incubated with chelators only (data not shown). As shown in Fig. 4A , both EDTA and EGTA displayed a protective effect regarding toxin action when compared to Sf9 cells intoxicated without ion chelators in the media. The LD 50 s measured for Sf9wt (black circles), Sf9wt with EDTA (black triangles) and Sf9wt with EGTA (white circles) were 2.