dataesr/scientific-paragraphs-categorization huggingface dataset:
Thematic analysis is a method used in qualitative research to identify, analyse and report on themes and trends in qualitative data  [14]. To apply this method, we followed the four steps described by  Yin (2011)   [15] : compilation, disassembly, reassembly and interpretation of the data. First, we transcribed all interview recordings and coded them according to the informant's sector, occupation and level of action. Then, using the computerassisted qualitative data analysis software Atlas. ti, we identified in the informants' narratives words or phrases that could constitute an influential factor in the implementation of an integrated surveillance system for zoonoses in Burkina Faso, which we sorted according to the themes, concepts or ideas to which they referred. This coding was done inductively and iteratively.
Organization and functioning of the anthrax surveillance system in Burkina Faso Surveillance of anthrax in Burkina Faso includes three surveillance programmes, the characteristics of which are presented in Table  1. In livestock, surveillance is event-based (i. e. passive) and coordinated by the general directorate of the veterinary services (DGSV) of the MARF through the epidemiological surveillance network for animal diseases (called RESUREP). Data collection and sampling are carried out by the veterinary posts under the DGSV. They are assisted in this task by the volunteer extension workers at the village level, who are under their direct responsibility, and the heads of the zones for technical support to livestock, who are under the hierarchical responsibility of the provincial and regional directorates of the MARF.
The samples are sent to the regional livestock laboratories, which are responsible for packaging and shipping them to the national livestock laboratory, which is in charge of testing them. The heads of the veterinary posts notify suspected cases on a weekly basis to the epidemiology department of the DGSV's Animal Health Directorate, which centralizes all surveillance data. The data are analysed weekly and the results recorded in epidemiological bulletins, which are sent to the DGSV, the TFPs and also to the heads of the veterinary posts. Notification of positive cases is made to the OIE and WAHO. In the human sector, there is an event-based surveillance programme supervised by the MOH. This surveillance is coordinated by the national committee in charge of outbreak management, whose executive body is the epidemiological surveillance service of the directorate in charge of population health protection (DPSP).
The data are collected and reported by the health facilities consisting of the centres in charge of health and social promotion, the regional hospitals, the university hospitals and the hospitals. Additionally, there is a network of community-based health workers who report health events to the centres in charge of health and social promotion. Each week, the health facilities summarize the diseases and events under surveillance in the weekly official letter telegram notebooks. The summary of surveillance data is transmitted by telephone to the district level, then from the district to the regional level and finally from the region to the DPSP, which processes and analyses the surveillance data. The results are transmitted to the WHO country office and WAHO, using an electronicbased reporting tool called District Health Information System 2.
Forestry officers are currently being trained by the veterinary services to take samples themselves. Collaboration also exists between the animal-health and human-health sectors. Transfers of skills and the sharing of technical equipment and reagents can occur on an ad hoc basis. There are also several initiatives led by TFPs to harmonize the packaging and routing of samples to the laboratories and to establish a common information system for surveillance results using DHIS2. Surveillance data on priority zoonoses collected at pilot sites were centralized until 2020 in a common database, set up by the Measure Evaluation project  [15]. However, those initiatives have been struggling to keep up their maintenance with domestic funding, since external sources of fund have stopped. In the event of a suspected case of anthrax in one sector or another, joint investigations between the animal and human health authorities are conducted.
The major advantage of qualitative research lies in the richness of the data produced, which is specific to the context of implementation. It allows for the exploration of actors' beliefs, values and motivations and sheds light on certain behaviours  [20]. This approach was therefore well suited to the objective of our study, as it allowed us to explore the perception and posture of the different categories of actor towards integrated surveillance from a One Health perspective. It led to a deeper and richer understanding of the technical, cultural and socio-political factors that hamper the operationalization of integrated surveillance. Interviews were conducted with all categories of actor involved in surveillance, whether they act directly in the surveillance process or have a technical and financial support role.
Determination of the Optimal Sampling Method Several conditions of VOC collection were assessed and large amounts of data were generated (detailed in the Section 7 and Table  S2 ). To validate our approach for measuring VOCs in the field, we first compared the profiles of the VOCs surrounding the grapevine foliage with those at the edge of the plot (Ext) in 2017 and 2018. A principal component analysis (PCA) of the data collected during the growing season showed specific grapevine VOCs emitted by the foliage whatever the treatment (control, elicitor) (Figure  S2 ). VOCs are emitted as a mixture and diluted in the canopy atmosphere. Therefore, technical optimisation was necessary to capture them. Three methods of passive VOC collection using SBSE Twister™ in a tea ball were assessed: OA, OA-CUMUL and BAG (Figure  2 ).
Bastid ® -Induced VOCs The 2019 dataset was used to select Bastid ® -induced VOCs when fit to the following parameters; i. e. , when FC > 1 (Bastid ® vs. H 2 O-treatment calculated at each time point of each phenological stage) was observed for at least half of the sample sets. From this, the lists composed of 15 and 11 Bastid ® -induced VOCs were obtained for the Burgundy and Bordeaux vineyards, respectively (Table  2 ). Among them, 9/15 and 7/11 (ca. 60%) were terpenoids. They were mainly monoterpenes, including pinenes (α-and β-pinenes, αand γ-terpinene), and ocimenes isomers (cis-β-, trans-βand allo-ocimenes). Only EZ-alloocimene was in common between the two lists, but not systematically induced at all stages. Some of the listed compounds were already induced in the 2018-BAG experiment, e.
VOCs were retained when fold change (FC) > 1 at least 4 times out of the 6 time point datasets (ca. > 50% of the collected samples). *: Significant t-test (FDR < 0. 05) vs. H 2 O control samples. n. i. : not induced. Phenological stages of grapevine: pre-blossom: PB; fruit-set: FS and bunch-closure: BC. Time points: three-and five-days post treatment (D3 and D5). Phenological stages are indicated in the last column when VOCs were induced in the same vineyard in 2018-BAG (FC > 1). The three elicitors induced VOCs with emission profiles depending on the time point of sampling, the vineyard and the elicitor. The most common elicitor-induced VOCs were α-and β-pinenes, cis-β-, trans-β-, EE-and EZ-allo-ocimenes, limonene, isocaryophyllene and DMNT. Bastid ® and CuSO 4 (ca. 1 < FCm < 2) were weak VOC inducers, whereas MeJA was a stronger one (FCm > 4).
The tubes were incubated in the dark at ambient temperature for 4h, then analyzed using a Tri-Carb 3110 TR Liquid Scintillation Analyzer with QuantaSmart TriCarb LCS 3. 00 software. 3  H was measured in the range 2. 0-18. 6 keV for 5 minutes on the high sensitivity setting. Synovial uids from patients: Collection of synovial uids were performed in the framework of a clinical study (ClinicalTrials. gov Identi er: NCT04460144) in accordance with relevant national guidelines and regulations. Patients were informed of the anonymous data collection in this study and were given the opportunity to express their opposition to participation. All study protocols and procedures involving patients were approved by a national ethics committee (07/03/2020, Comité de Protection des Personnes Nord Ouest III, registration number 2019-A02427-50).
Author Contributions: UM conceptualized the study. Methodology and Investigation were performed by JP, RW, CD, BB, GD, DB, BP, MR, MT, EV, JPH, IGB, UM. Funding was acquired by UM and JPH. The project administration was done by JP, MR and UM. The study was supervised by IGB and UM. JP, UM, JPH, EV wrote the initial draft. All authors participated to reviewing and editing of the manuscript. Financial support: This work was supported by the Agence National de Recherche (ANR-16-CE17-0009), the Direction de la Recherche Clinique et de l'Innovation (CRC TDR-Arthrite), the KOURIR patient association, the Societé Française de Rhumatologie, the Fondation du Judaïsme Français and the Fondation Arthritis (grants to UM). JPH received a grant from the Association François Aupetit. JP received a fellowship (Année Médaille) from the Assistance Publique-Hôpitaux de Paris (AP-HP) and a grant from the Fonds d'Etudes et de Recherche du Corps Médical (FERCM).
CD and BB received a fellowship from the Societé Française de Pédiatrie. UM is a member of the Paris Center for Microbiome Medicine (PaCeMM) FHU, AP-HP, Paris, Île-de-France, France. Ethical All experiments involving animals were performed according to French national laws and regulations for use of animals in research. The study protocols were approved by the ethics committee on animal experimentation and the French Ministry of Research (10/02/2019 registration number APAFIS#15436 and 09/05/2019 registration number APAFIS#20501). Collection of synovial uids were performed in the framework of a clinical study (ClinicalTrials. gov Identi er: NCT04460144) in accordance with relevant national guidelines and regulations. All study protocols and procedures involving patients were approved by a national ethics committee (07/03/2020, Comité de Protection des Personnes Nord Ouest III, registration number 2019-A02427-50).
The photographs of the habitus and internal structures were taken using a stereo microscope Leica MZ 16 with IC3D camera. Final images were adjusted using Helicon ver. 5. 0 software and Adobe Photoshop (ver. 7. 0). The SEM photographs of uncoated specimens were taken in the Laboratory of Scanning Microscopy, MIZ PAS (Warsaw), using a scanning electron microscope HITACHI S-3400N under low vacuum conditions. The diff erent proposed taxonomic rearrangements are displayed according to standardized models proposed by  Bourgoin (2022) ,  Bourgoin et al. (2015)  and in other tropiduchid papers:  Gnezdilov et al. (2016) ,  Bourgoin et al. (2019 Bourgoin et al. ( , 2021)) ,  Bourgoin & Wang M. (2020).
Although Lactobacilli or Clostridiales may have an influence on the development of the gastrointestinal tract just by passing through it, the beneficial effect of probiotics on gut health will most likely prevail when probiotic bacteria are able to implant and colonize the gut successfully. Given its biological and economic implications, it is surprising that GM transfer between hens and chicks has not been studied in more depth, especially given the recent advances in next-generation sequencing which now allows past technical challenges to be readily addressed. The 16S rRNA gene is commonly used to identify and compare bacteria present in a given sample  (70). Accessible bacterial databases, such as Greengenes  (71)  and Silva  (72) , in addition to well-developed bioinformatics pipelines are available to facilitate these analyses  (73) (74) (75).
Acknowledgments We thank  Vanaique Guillory  ( ISP, INRAE) , the staff from the  Plate-forme d'Infectiologie Expeŕimentale (PFIE, INRAE) , and our colleagues from the  Centre International de Ressources Microbiennes -Bacteŕies Pathogènes  ( CIRM-BP, ISP, INRAE ) for providing technical support, animals and sterility checks, respectively.
Database To gain a quantitative understanding of the potential of every residue management measure to mitigate N 2 O emissions from crop residues, we conducted a meta-analysis using an extended version (as described below) of the database compiled by  Rittl et al. (2022). Briefly, this database contains data from field studies across the world investigating the impact of crop residues on N 2 O emissions. Crop residues are considered as any aboveground plant component of a crop returned to the soil. The database consisted of 367 selected pairwise comparisons reported in 78 studies, which met predetermined quality criteria (only studies with replication, with detailed information, and performed under realistic field conditions)  (Rittl et al. , 2022). Pairwise comparisons only included observations where a treatment (i.
e. , with crop residue retention) and a control (i. e. , with crop residue removal) could be compared with all other factors unchanged. The database provides information about the management, site, and experimental factors from each study, which allowed us to test the effect of several mitigation measures identified through the literature review. To do so, we extended the database in this study creating additional variables that categorize the available information into moderators for a metaanalysis. For example, according to the crop residue application method, observations were categorized as incorporated (when crop residues were mechanically incorporated into the soil) or surface applied (when residues were retained at the soil surface without incorporation, e. g. , via mulching). The specific information about crop residue incorporation depth was categorized into deep (≥15 cm) and shallow (<15 cm).
Information about fertilisation at the time when the residues were incorporated was coded as in combination with and without fertiliser application. Moreover, for studies assessing residue management in combination with fertiliser applications, we categorized studies according to the type of fertiliser applied (synthetic, organic, or combination of synthetic and organic). The timing of residue incorporation was grouped as autumn incorporation versus spring incorporation. For the measures that could not be analysed with the database, the quantitative N 2 O mitigation potential was derived from a literature review based on individual studies for novel measures such as anaerobic digestion of crop residues or crop residue mixtures, for which the empirical evidence is more limited (Table  1 ). Certain management strategies, such as liming in combination with residue application were not included because there were not enough observations in the database, and because the available information did not attribute the effect of the mitigation measure to N 2 O emissions from crop residues (most available strategies are focused on fertiliser-derived N 2 O emissions).
However, it is also possible that this result is due to a confounding effect between fertiliser type and residue type, since most crop residues linked to organic fertiliser application in our database were immature crops (grasslands, vegetables and cover crops), which induce higher N 2 O emissions. Even if organic fertilisers increase N 2 O emissions from crop residues, their use is crucial for the delivery of other agroecosystem services. This is because organic fertilisers provide several nutrients (e. g. , P, K) in addition to N, and may increase SOC and yield in poor soils. Using organic fertilisers avoids energy consumption and emissions of GHGs during the industrial Haber-Bosch process of N-fixation for synthetic fertiliser production and promotes circularity of nutrients at farm to regional scale.
Acknowledgements This study was supported by the  FACCE ERA-GAS Cofund (European Research Areafor mitigation of Greenhouse gases from Agri-and Silvi-culture ; id number:  696356 ), project  ResidueGas  (https:// projects. au. dk/residuegas/). The Danish funding was received from  Innovation Fund Denmark  (project  7108-00005B ). The French funding was received from the  Agence Nationale de la Recherche  ( ANR-17-EGAS-0003 ) and the  National Institute for Food, Agriculture and the Environment (INRAE). The authors acknowledge funding in the UK from the  Department for Environment, Food and Rural Affairs (Defra)  and the  Scottish Government's Strategic Research Programme , and in Germany from the  German Federal Ministry for Food and Agriculture (BMEL)  [grant number  744 2817ERA08C ]. The authors acknowledge funding in Norway from the  Research Council of Norway  (Project No.
A comparative analysis of the riparian vegetation dominated by Alnus glutinosa in Italy and Tyrrhenian islands, based on literature data and unpublished relevés, is presented. A total of 456 phytosociological relevés were processed. For the definition of plant communities and alliances, hierarchical clustering was performed by using Bray-Curtis coefficient and Detrended Correspondence Analysis ordination methods. Identification of diagnostic species of the vegetation units was performed by means of the phi fidelity index. Quantum GIS software version 3. 6 was used for the interpolation of the bioclimatic variables and A. glutinosa communities. Overall, a total of 18 A. glutinosa-riparian wood communities were distinguished for Italy and Tyrrhenian islands, of which two new associations and one new subassassociation are described.
Statistical Analysis A multivariate analysis (Linkage method: Ward's, Distance measure: Bray-Curtis) was applied  [30, 31]. The optimal number of clusters was identified using the Silhouette index by means of the cluster package in R software  [32]. Cluster analysis and ordination of the dataset were performed using PC-ORD 6 software  [33]. Ordination (DCA) took into account the bioclimatic variables at 30 s resolution from WorldClim  [34]. Quantum GIS software version 3. 6 was used for the interpolation of the bioclimatic variables and A. glutinosa communities. Diagnostic species of the vegetation units (partitions) was performed by software JUICE  [35]. It was determined by means of their fidelity (phi coefficient), and each group was standardized in order to remove dependence of the phi coefficient on unequal sizes; non-significant phi values at p > 0.
Introduction The investigation of genetic markers or genome relationships between different pathogens and microorganisms requires good-quality genomes. A large panel of good-quality genomes makes it possible to study chromosome rearrangements in more detail, identify sequences of interest and improve the identification of genetic clustering. Among the most frequently consulted sequence databases for collecting genomes is the open-access GenBank database, housed by the National Centre for Biotechnology Information (NCBI). GenBank annotates a collection of all publicly available nucleotide sequences generated by laboratories throughout the world from more than 100,000 distinct organisms. Release 242. 0, produced in February 2021, contained over 12 trillion nucleotide bases in more than 2 billion sequences.
1 To facilitate the retrieval of genomes of interest from the GenBank database, we designed a workflow (called SalmoDEST) to search and download genomes with a coverage greater than 50x. The options of this tool make it possible to download either complete genomes or contigs. It is possible to choose to download protein fasta files, if desired, and an output directory where all the selected fasta files are kept. The SalmoDEST tool was developed for Salmonella, a well-known and widely distributed foodborne pathogen. Salmonella enterica is regulated in the European Union (EU) and monitored in the United States (US) and many other countries. In the US, the economic burden due to salmonellosis is estimated to be US$3. 66 billion per year. In 2016, the incidences of culture-confirmed cases of salmonellosis were 14.
ABSTRACT: With the advent of next-generation whole-genome sequencing (WGS), the need for good-quality and well-characterised Salmonella genomes has increased over the past years. Good-quality complete genomes are often required for assembly reference mapping or phylogenetic single nucleotide polymorphism (SNP) analysis. Complete genomes or contigs from specific sources or serovars are also searched for clustering analysis or source attribution studies. Therefore, new bioinformatics tools are needed for the extraction of good-quality and well-characterised genomes from public databases. Here, we developed SalmoDEST, an open-source Python tool capable of extracting Salmonella genomes with a coverage higher than 50x and genome length over 4Mb from the GenBank database in the form of complete genomes or contigs, with verification of the serovar to which they belong and identification of the corresponding multi locus sequence type (MLST) profile.
To validate the ability to SalmoDEST to screen for and retrieve genomes of good quality, we compared our results for S. Typhi complete genome with those available in the literature and extracted Salmonella genomes from bovine sources strains isolated worldwide. Finally, we provide in this study a list of 239 complete genomes for 123 serovars of Salmonella of high quality. SalmoDEST is a handy and easy-to-use open-source tool to extract complete genomes or contigs that can be routinely used in public health, food safety and research laboratories. SalmoDEST (SALMOnella Download gEnome Serotype sT) is available at https://github. com/I-Guy/SalmoDEST.
Bioinformatics and Biology Insights SalmoDEST is a workflow designed to search and download Salmonella genomes from the NCBI GenBank database using either the ncbi-acc-download 4 tool for complete genomes or ncbi-genome-download  5  for contigs. Using these tools, the first Python script 'Get_HQ_Genome_1. py' in SalmoDEST automatically downloads the genome fasta files of the strains for which accession numbers are present in the input text file. Then, the serovar and MLST profile predictions of the downloaded genomes is carried out with a Bash process using SeqSero,  6  MLSTseeman tool  7  and Quast, 8 respectively. The second Python script 'Get_HQ_Genome2. py' renames the downloaded fasta files, adding the accession number, the serovar and the MLST profile predictions as follows: antigenic formula or serovar name_ST_ID_Accession number (eg, Montevideo_81_42N_CP037893.
1). The Python script 'Get_ HQ_Genome2. py' also downloads the gff and gbk files and checks the quality of each genome. It retains only those with coverage greater than 50x and a genome length longer than 4 Mb, and removes the others. Finally, this Python script compresses (zips) all files. Optionally, it is possible to choose to download fasta protein files, if desired, and, in addition, choose an output directory in which all the selected fasta files are stored. Get_HQ_Genome_1. py script. The input file of SalmoDEST and the 'Get_HQ_Genome1. py' script is a text file, obtained from an NCBI Nucleotide database query (https://www. ncbi. nlm. nih. gov/nuccore) or compiled by the user, listing the accession numbers of the complete genomes or contigs to download. If an NCBI Nucleotide database query is used, the 'Complete Record' must be exported into a destination 'File' in the 'Accession List' format sorted by 'Default order'.