dataesr/scientific-paragraphs-categorization huggingface dataset:
DNA Extraction And Quantitative Real-time PCR In the ENVT laboratory, DNA was extracted from tissue biopsies using a commercial kit (QIAmp® DNA Mini Kit, Qiagen, Courtaboeuf, France). Following the manufacturer's recommendations, 50 mg aliquots of tissue biopsies were processed after an over-night incubation with proteinase K. Besnoitia spp. internal transcribed spacer 1 (ITS-1) ampli cation was performed with the commercial PCR kit AdiaVetTM Besnoitia (AES Chemunex, Bruz, France). The quantitative PCR was performed with the Stratagene MX3005P thermal cycler (Agilent Technologies, La Jolla, CA, USA). Positive and negative controls were provided by the manufacturer. Results were analyzed using the MxPro QPCR version 4. 10 software (Agilent Technologies). When the Ct value was inferior or equal to 36, the parasite DNA was considered detected and the animal was deemed to be a super-spreader, when Ct values ranged between 36 and 40, parasite DNA was at the limit of detection, and a Ct superior to 40 was considered as a negative real-time PCR result.
Data collection Dead broilers were removed at the carousel table and accounted by batch or consignment (load) immediately after slaughter and checked by the official veterinarian. The same official veterinarian recorded from 700 carcasses per batch (total 44. 800) the number of bruises on wings, legs and breast and from 1. 400 carcasses per batch (total 89. 600) the number of carcasses condemned by dehydration. Bruises were classified according to the approximate age using visual and objective color assessment standards  (Northcutt et al. , 2000)  so as to consider only those which had occurred during the pre-slaughter period. Dehydrated carcasses were recognised during post mortem inspection by being dry, tacky and badly bled  (Butterworth & Niebuhr, 2009). Information regarding age at slaughter (d); mean body weight (kg); batch size (number of broilers per vehicle); time of catching (before/ after midnight); team for catching and vehicle; time of arrival at the slaughterhouse; duration of transport (min); distance of transport (km); crate floor area (cm 2 /kg); density per crate (kg/m 2 ); number of birds/ crate; lairage duration (min) and water withdrawal duration (min) was collected for the 64 batches.
GzLM model was not found for dehydration and data was analysed thought univariate chi-square for categorical variables: catching period in a binary scale (before/after 00h); lairage duration and withdrawal duration in a 3-point scale (< 8h; > 8h and < 12h; > 12h) and Mann-Whitney for numeric variables: body weight and transport duration. Chi-square and Mann-Whitney tests were performed using SPSS 25. 0. GzLM was performed using R. 3. 52 version Packages MASS.
We collected epidemiological data from the weekly numbers of suspected cases and deaths reported in the DRC national Integrated Diseases Surveillance System (IDSR) collected by the national health system from the Ministry of Health, between 2000 and 2018 (S1 Data), at the health zone area scale. Meningitis suspected cases were defined according to the WHO guidelines  [27]. The cases were notified to the hierarchic level by the health structures (hospital and health centers) in the 515 different health zones and from sentinel health zone sites, attached to health areas in the provinces of Haut Katanga (Lubumbashi) and the city-province of Kinshasa (Lingwala, Kalembelembe and Kingasani). Patients with suspected meningitis who were evaluated at reference centers or at sentinel sites structures had a lumbar puncture performed to collect cerebrospinal (CSF) fluid for laboratory testing by Gram stain and culture or latex agglutination, when available, or by Polymerase Chain Reaction (PCR) at the Institut National de Recherche Biomedicale (INRB), Kinshasa.
Between 2008 to 2012, patients were primarily infected by S. pneumoniae (50%), N. meningitidis (13%), H. influenzae (2%) or other pathogens (35%) identified by CSF culture or PCRs performed. 486 CSF samples were tested via culture (100%) and 267 via PCR (54. 93%)  [28]. Population data. Population sizes of health areas were collected from the Expanded Programme on Immunization (EPI), program of Public Health Ministry. They correspond to estimations based on the last census performed in 1984 with a calculated annual growth rate of 1. 03% applied for the following years. Shapefile data. Issued from WHO Healthmapper (a WHO information and mapping application for public health). Socio-environmental data. Climate data has been downloaded from WorldClim-Global Climate Data  [29]. They concern 30-years average monthly rainfall and temperature data.
The variables are collected at the scale of 30 arc seconds (~1km 2 ). Each zip file contains 12 GeoTiff (. tif) files, 1 per month (January = 1, December = 12). The raster image was superimposed on the DRC 515 health zones Shapefile, and we extracted the average, minimum, maximum, and mean temperature (in ˚C) and precipitation data (in mm) for each health zones using ArcGIS (ver 10. 6. 1). F r all these data we used the average values. The altitude data for health zones are from the Shuttle Radar Topography Mission (SRTM) in the European soil data center (ESDAC)  [30]. Outside the USA and their associated territories, an altitude measurement is taken every 90 m. This makes it possible to draw quite high accuracy isolines of altitudes throughout the DRC. Information is available in the form of rasters, and backgrounds were obtained from SRTM 90m Digital Elevation Database v4.
1 site h  [31]. In order to cover the entire territory of the DRC, 19 raster images have been downloaded. These were subsequently mosaic into a single image. The raster image was superimposed on the 515 health zones shapefile of the DRC, and the average altitude data extraction for each health zone was performed using ArcGIS. The latitude and longitude data of the health zones were extracted from the shapefile of the 515 health zones using the R software. Bushfire data by health zone are dated and geo-localized from MODIS images provided by NASA site  [32, 33]. Livestock rearing activity in the health zone (1 = Health zone without livestock breeding activities, 2 = HZ with small-scale livestock activities, 3 = HZ with large livestock activities). The Index of Economic Well-being (IEW) was estimated during the second Demographic and Health Survey conducted (DHS) in the DRC between 2013 and 2014  [34].
The  NGO « Organisation pour le Developpement Durable de Mai-ndombe » (NGO ODDM) , the  URF-ECMI (Training and Research Unit in Ecology of infectious diseases ,  Medicine Faculty ,  University of Kinshasa, DRC ) and  IRD/ MIVEGEC, UMR CNRS IRD UM, Montpellier ,  France. Jean-Franc  ¸ois Guegan is supported by an " Investissement d'Avenir " grant managed by  Agence Nationale de la Recherche  ( LABEX CEBA :  ANR-10-LABX-25-01 ), and is also supported by  Institut de recherche pour le developpement (IRD) ,  Institut national de recherche pour l'agriculture , l'alimentation et l'environnement (INRAE),  Universitede Montpellier and Ecole des Hautes Etudes en SantePublique (EHESP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
1 ). But how many molecules of solutes cross the PM and VM during stomata opening/closure? To estimate this, we used data from Vicia faba. To drive stomata opening a net raise of 4-5 pmol of ionic solutes per guard cell, mainly K + , Cl -, NO 3 - or malate 2-, is necessary  (Allaway & Hsiao, 1973). This raise of solutes induces an increase of the total intracellular concentration between 0. 8 and 1 M in open stomata. Considering an opening time of 60 minutes and a V. faba guard cell surface of 1899 µm 2  (Meckel et al. , 2007) , a net entry of up to ~7×10 8 molecules•s -1 /GC across the PM and then across the VM can be calculated (Fig. 1a ). When stomata close, ionic solutes leave the cell in about 20 minutes generating a net flux of ~2×10 9 molecules•s -1 /GC firstly across the VM and then across the PM (Fig.
Otherwise, the transport processes occurring in the VM and in other membranes, such as the PM, have been considered separately. Compared with the PM, only a restricted number of regulatory mechanisms targeting the VM transport systems is known. An integrative perspective on the intracellular transport reactions comes from in silico modelling, but only few data are available in vivo. Recently, in vivo data demonstrated the impact of ion transport on cytosolic conditions and connected it with stomatal aperture  (Demes et al. , 2020). Therefore, a future challenge will be to visualise and decipher, in living cells, the connection between transport systems residing in different membranes during cellular responses. and SLAC1 in the PM. ATP is the substrate for the pumping activity of the H + ATPases and is a negative regulator of anion channels in the PM and VM.
Different potentials of limonene-1-OOH and limonene-2-OOH in 3D models First, we determined the amounts that lead to DC activation after topical application of the two compounds on RHE (SkinEthic), thereby giving a clearer image of what may happen in vivo. To achieve this, we placed THP-1 cells under the RHE (Fig. 2a , for details see  23  ). As recommended, we tested RHE covering three donors  35. Data presented in Fig. 2b  show clear upregulation of CD86 and CD54 on THP-1 when 120 µg/cm² (1. 2%) limonene-1-OOH or 200 µg/cm² limonene-2-OOH was applied, while no or only marginal upregulation was observed for 20 µg/cm² (0. 2%). An EPR-ST methodology was developed to study radical intermediates of the limonene-OOHs (Fig. 2c-d ). First, studies in solution were performed to define the radical landscape in a simple system (i.
Acknowledgements This work was part of the  DEFCHEMSKALL Franco-German Collaborative International Research Project  financially supported by the  ANR (Agence Nationale de la Recherche ; project no. ANR-15-CE15-0023-01 ) and the  DFG (Deutsche Forschungsgemeinschaft ; project no. DFG ,  BL340/6-1 ). The  Réseau NAtional de Rpe interDisciplinaire (RENARD, Fédération IR-RPE CNRS  # 3443 ) is also acknowledged. We thank  Prof. Dr. Claudia Traidl-Hoffmann  ( University Center for Health Sciences Accepted Article.
Acknowledgements Authors thank  Jessee J. Smith  for copy-editing and reviewing the manuscript before submission. The assistance of  Nathan Renfro  (GIA) has been appreciated. Authors are thankful to the team "Minéralogie et environement" of ISTerre, with a special thanks to  Laurent Truche  (head of team) for providing funding and assistance for this research. We thank  Fanny Gangloff  for designing and drawing the final figure. Authors are thankful to  Nick Arndt  for his useful comments.
X-ray microtomography. 3D images have been acquired by x-ray microtomography on RX-Solutions EasyTom XL Nano equipment using a Hamamatsu L8121 sealed tube and a Paxscan 2520DX flat panel from VAREX Imaging. A source tension of 100 kV with a current of 80 µA was combined with a 0. 25 mm thick aluminum filter. The magnification was set to 25. 4 resulting in a voxel size of 5 µm. 1984 projections were acquired over one turn. Each project is the average of 6 images exposed during 0. 5 s each. A classical filtered back projection algorithm was used for 3D reconstruction. In order to reveal fine details on forelegs, the reconstruction has been segmented slice by slice by manual border selection using the open software ImageJ. 3D renderings are obtained with the ThermoFicher Scientific Avizo software.
53 N, 1. 58 E), Southwestern France, from late May to late June (Fig. 1 ). Our data suggest no statistically significant differences between the day and night soil moisture at these soil horizons (Table  1 ). In contrast, the average seedbed temperatures across these soil horizons during the day time were significantly higher than those registered during the night-time (Fig. 1 ). However, late spring season is not the hot and dry period of the year in Southwestern France or southern Europe in general. Therefore, the same variables of the seedbed weather should be measured during hot and dry periods of the year (i. e. summer) across these regions. The moisture level has been reported to affect seed reserve utilization and seedling growth in wheat  [6]  that may have an important impact on emergence of crops sown during summer across dry summer regions.
De novo assembly pipeline The bioinformatics pipeline was slightly different for the six samples because of the variations in sequence protocols (as described above). However, the pre-processing of the reads was similar for both Illumina and PacBio data. The Illumina reads were filtered using the wrapper Trim Galore! (https://www. bioinformatics. babraham. ac. uk/projects/trim_galore/). For PacBio, circular consensus sequences (CCS) were generated using the SMRT® pipe RS_ReadsOfInsert Protocol (PacBio) with a minimum of three full passes and minimum predicted accuracy greater than 90%. The adapter and potential chimeric reads were removed using seqkt (github. com/lh3/seqtk) as described by Lefoulon et al. (50)  (analyses were performed with an in-house shell script). When sufficient PacBio reads were obtained, a de novo long-read assembly was done using canu  (56)  according to Lefoulon et al.
KEGG Orthology (KO) assignments were generated using KASS (KEGG Automatic Annotation Server)  (73). KASS assigned orthologous genes by a BLAST comparison against the KEGG genes database using the BBH (bi-directional best hit) method. The same assignment analysis was performed for the newly produced genomes and the set of 15 Wolbachia genomes from the NCBI database. The assigned KO were ordered in 160 different KEGG pathways (Table  S2 ). Several pathways which showed differences in the number of assigned genes between Wolbachia genomes were selected. A list of genes assigned to these pathways was compiled to study potential losses/acquisitions of these genes across the various Wolbachia (Table  S3 ).
The phylogenetic trees were edited in FigTree (https://github. com/rambaut/figtree/) and Inkscape (https://inkscape. org/). To study the evolution of the filarial hosts infected with Wolbachia, the same workflow was applied to the amino-acid files previously produced by the BUSCO analysis (Augustus implemented as functionality) based on the set of 982 orthologue genes common among nematodes (nematoda_odb9) (Table  S4 ). The six produced filarial nematode draft genomes were analyzed with five draft genomes available in the database (AAQA00000000 for B. malayi; JRWH00000000 for B. pahangi; CAWC010000000 for O. ochengi, CBVM000000000 for O. volvulus, LAQH01000000 for W. bancrofti).
Interestingly, the ftsZ gene used in these MLST studies could not be detected in the wDcau and wCtub genomes. In addition, some multi-locus studies had observed PCR amplification of this gene to be unsuccessful within supergroup J Wolbachia  (36, 84)  while other studies included an ftsZ sequence from Wolbachia from D. gracile  (34). To resolve this contradiction, we compared the 33 sequences of Wolbachia from D. gracile available on the NCBI database and our complete wDcau genome, which should be closely related, using nblast. For six of these 33 sequences, from the ftsZ gene, it appears unlikely that they belong to Wolbachia from D. gracile, only having between 72. 37% to 89. 91% identity with wDcau (while all other PCR sequences show 95. 36-99. 98% identity) (Table  S5 ). Four of these six sequences are identical to genes of Wolbachia from Drosophila spp.
Discussion The LEFT-SEQ method was applied to four invertebrate DNA samples, enabling us to produce four complete Wolbachia genomes: wLsig, wDimm, wDcau and wCtub. For wLsig and wDimm, draft genomes had previously been sequenced and analyzed  (26, 90)  but not submitted to the NCBI database. The complete genomes of wDcau and wCtub are, so far, the smallest Wolbachia genomes. Using the enrichment method associated with Illumina sequencing  (52) , two draft genomes were sequenced, a 41-contig wLbra draft genome and a 208-contig wMhie draft genome. Our data confirmed that wLsig and wLbra belong to supergroup D, wDimm resides in supergroup C, wMhie belongs to supergroup F, and wDcau and wCtub form a well-supported clade, supergroup J. Thus, wDcau and wCtub are now the first representative genomes of supergroup J, while wMhie constitutes the first representative genome of supergroup F from a filarial nematode.
The latter phylogenetic position of this Wolbachia has been questioned by some authors and is often retained as belonging to supergroup C  (35, 82, 83). More recently, using a concatenation of seven genes and newly studied Wolbachia, Lefoulon et al. (36) , demonstrated the validity of supergroup J, as distinct from supergroup C; a phylogenetic position confirmed by the present study (Figure  2 ). Our analyses show that the ftsZ gene is not present (or is highly degenerate) in the wDcau and wCtub genomes, while previous Wolbachia phylogenies have been based on this marker. Our analyses (Table  S5 ) suggest that the variable position of Wolbachia from D. gracile in some phylogenetic analyses is linked to the fact that some database sequences likely do not belong to this strain. The two complete genomes, wDcau and wCtub, are divergent from supergroup C Wolbachia.
In addition, they are highly divergent from each other, with an ANI of 81%, despite the fact they form their own clade (Figure  1 ). These divergences have been suggested by earlier multi-locus phylogenies with Wolbachia from Cruorifilaria and Yatesia species forming one subgroup and Wolbachia from Dipetalonema spp. forming another subgroup within supergroup J  (36). Our data suggest that the use of the ftsZ gene for MLST studies is not appropriate for Wolbachia that are highly divergent. The fact that the MLST system was designed on the basis of supergroups A and B Wolbachia  (48) , which have low genetic diversity  (30) , is a source of concern for its general use when studying divergent phylogenies. Moreover, the risk of erroneous data finding their way into databases (e. g. through contamination, misidentification), combined with the fact that sequences used to build concatenated matrices very often do not originate from the same specimen, weakens multi-locus phylogenies, unless potential confounding factors are taken into consideration.
Along with the assembly of the Wolbachia genome, draft genomes of the nematode hosts were produced (Table3): a 1,888-contig draft genome of C. tuberocauda, nCtub, of 75,522,022 bp total BUSCO database), the draft genome of D. caudispina shows the highest level of completeness with 959 genes detected (97. 7%). The draft genomes of C. tuberocauda and L. brasiliensis show similar results with 939 (95. 6%) and 917 (93. 4%) genes detected. The draft genome of M. hiepei has the lowest level of completeness with 849 (86. 4%) genes identified (TableS4). Draft genomes of nDimm and nLsig have previously been published.
Along with the assembly of the Wolbachia genome, draft genomes of the nematode hosts were produced (Table3): a 1,888-contig draft genome of C. tuberocauda, nCtub, of 75,522,022 bp total BUSCO database), the draft genome of D. caudispina shows the highest level of completeness with 959 genes detected (97. 7%). The draft genomes of C. tuberocauda and L. brasiliensis show similar results with 939 (95. 6%) and 917 (93. 4%) genes detected. The draft genome of M. hiepei has the lowest level of completeness with 849 (86. 4%) genes identified (TableS4). Draft genomes of nDimm and nLsig have previously been published length; an 839-contig draft genome of L. sigmodontis, nLsig, of 64,161,459 bp total length; a 1,026-contig draft genome of L. brasiliensis, nLbra, of 65,202,511 bp total length; a 1,294-contig draft genome of D.
(D. ) immitis, nDimm, of 83,711,400 bp total length, a 2,615-contig draft Among 221 single-copy orthologous genes conserved among proteobacteria (BUSCO database), 171 and 162 are present in the wCtub and wDcau complete genomes, respectively, suggesting 77. 4% and 73. 4% BUSCO completeness (Table3, TableS4). The other two complete genomes, wLsig and wDimm, have 76. 1% and 76% BUSCOs completeness with 168 genes identified. The draft genome wLbra has 76. 5% complete BUSCOs with 169 genes identified. The draft genome of wMhie has 75. 6%BUSCO completeness with 167 genes identified. These levels of completeness are similar to most Wolbachia genomes from filarial nematodes. For example, Wolbachia from B. malayi, wBm, has a higher level with 175 complete genes identified (79. 2%) and Wolbachia from O.
UAVs are alternatives to quickly recording data (images) to compute a 3D model of a small area. In fact, UAVs show the advantage of being inexpensive, whether in financial or human terms, and their size and weight make them easy to deploy and implement. Considering these advantages, a photogrammetric monitoring using UAV was carried out along the concave bank of the most active meander of the Moselle River in order to better understand and model the lateral migration of the river. In order to survey this fluvial morphodynamic process more closely, a 4D GIS has been established along the meander bend. The objective of this monitoring is to assess the bank erosion rates according to hydrodynamic parameters (discharges, water levels, flow velocities, shear stresses, etc. ) and geotechnical properties of the eroded bank (rest angle, bank sediment stratigraphy, vegetation, etc.
, 2011) , a typical image-based surveying with UAV systems requires a mission planning, GCPs measurement for geo-referencing, image recording, camera calibration, and image orientation, image processing for 3D modeling and information extraction. The first date was an experimental operation to define the first state of the meander and to calibrate the field operations. More than 1,000 images (Table  1 ) were recorded during each mission, whether in nadiral or oblique views (Figure  2 ). On some of them, coded circular targets are visible. These were used to materialize GCPs (Figure  3 ): the GCP coordinates were then measured with a geodetic GNSS receiver. The measured and automatically extracted points using Agisoft Metashape software are in the centre of the targets and their coordinates have been determined in the French RGF93-CC49 system.
Generation of point clouds. Large quantities of images were therefore acquired by drone for each measurement campaign. Among this mass of data for each campaign, a sorting was carried out, to preserve only images with a good quality. Two selection methods were applied: (i) a qualitative selection apparent to a visual analysis of the images to eliminate the unusable images (duplicates, under or overexposed images). In this first method, the operator's analysis is heavily used to make a manual selection; (ii) a quantitative selection using the Metashape software to estimate the quality of an image, by means of a coefficient. A blurry image, therefore unusable, will have a coefficient of 0. 50. To maintain only good quality images, the acceptability threshold for this coefficient has been set at 0.
The realization of cross-sections is an interesting option, but only with a 2D view (in this case x and z). Metashape does not offer tools to directly calculate profiles. For this reason the data were exported and superimposed in 3DReshaper software package. The realization of cross-sections required the definition of an axis according to which these were to be calculated. For such needs, all point clouds have to rasterized in CloudCompare with a grid size of 1 m, when local slopes were calculated using ArcGIS package. Based on slope discontinuity, a line was drawn along the river banktop for each campaign, from the limnimeter to the downstream opposite side. Considering that profiles were built perpendicularly to the banktop line, this line was smoothed using Bezier curves tools, in order to estimate as far as possible vertical profiles.