dataesr/scientific-paragraphs-categorization huggingface dataset:
0 × planapochromatic objective (10447243) was used, equipped with a Digital Color Camera Leica DFC310 FX (Software LAS 4. 13). Filter sets were GFP 10446222 in case of compound FAMA, dSRED 10447079 in case of S-CY3A, CY3A and TAMRA, and CY5 10446366 in case of S-CY5. 5A and S-CY5A. After manual delineation of the whole body (WB) contours of the zebrafish eleuthero-embryos using MetaMorph (Microscopy Automation & Image Analysis Software V. 7. 8. 00), the fluorescence in the selected area was quantified as integrated fluorescence intensity (RFU) that adds up all fluorescence intensity values of the individual pixels. In case of the combination treatment the same correction factor for exposure time from the camera setting was applied in the case of FAMA and TAMRA, to avoid saturation of the images (Supplementary information.
Acknowledgements We thank  G. van der Star  and  J. Castillejos  for their advice during the mathematical modelling. This research was funded by  Fundación CeiBA -Colombia  " Rodolfo Llinás para la promoción de la formación avanzada y el espíritu científico en Bogotá " (M. G. ),  MarPipe , a fellowship from  H2020-Marie Skłodowska-Curie Innovative Training Networks  PhD, proposal number: 721421 (A. G. ) and by  L'Oréal  (contract  C150353 ).
Data Analysis Microsatellite genotype distances were calculated using Bruvo's distance  (Bruvo et al. , 2004). The analyses were done in three steps. Firstly, all susceptible and resistant isolates from the mycology team of Besancon were used. Genotypic richness was assessed by the total number of unique multilocus genotypes (MLGs) or expected MLGs (eMLGs), which approximates the number of genotypes that would be expected at the largest, shared sample size based on rarefaction. Diversity (Simpson's, Shannon-Wiener, or Stoddart and Taylor's Indexes) and evenness were also calculated for each type of isolate (azole susceptible and resistant) with the R package poppr  (Kamvar et al. , 2015). Secondly, only local TR 34 /L98H isolates were analyzed in order to see the proximity according to their origin.
Thirdly, we compared our local TR 34 /L98H isolates to those with available data worldwide. For this, we used a global dataset housed within the online AfumID application (https://afumid. shinyapps. io/ afumID/)  (Sewell et al. , 2019). We thus included a further 194 isolates that had previously been isolated and genotyped from 16 countries. In order to ensure harmonization, the number of alleles was recalibrated between the two databases using the reference strain Af293. Data were represented by circular genetic tree build by a Neighbor-Joining method clustering from a matrix of bruvo distance  (Bruvo et al. , 2004)  using ape library (Paradis and PA5 5′-TCTCTGCACGCAAAGAAGAAC-3′ PA7 5′-TCATATGTTGCTCAGCGG-3′ Set 2 AF306F 5′-CACTGCAACTCTAATCCTCG-3′ AF855R 5′-TAACGCAGACTGAGTCAAGC-3′ Set 3 AF766F 5′-TTCGGATCGGACGTGGTGTA-3′ AF1330R 5′-CGCTGATGGACGAAGACGAA-3′ Set 4 AF1179F 5′-TGACGGTGACAAGGACTCTC-3′ AF1709R 5′-ACAACCTCGTCGTTCTCCTG-3′ Set 5 AF1426F 5′ AGTCTTCCTCCGCTCCAGTA-3′ AF2025R 5′-ACACCTATTCCGATCACACC-3′ Schliep, 2019) and interactive tree of life (iTOL) software (https://itol.
Genotyping Results for TR 34 /L98H Isolates: Global Scale A subset of the dominant MLGs in the Franche-Comtéarea were commonly shared with isolates found worldwide: MLG B (found in CF patients, hospital air, sawmills, and market gardens) was also detected in Australia and Ireland and MLG E (detected in market gardens and sawmills) was also isolated in Denmark (Figure  4 ). In comparison, MLG A, C, and D, while common in our dataset, were not observed in the global dataset, suggesting that they are geographically spatially constrained. Other MLGs found in Eastern France were also closely related to those occurring more widely including those found in the Netherlands (links between the MLG on the Figure  4 ). One MLG was shared by four isolates in Besancon (a sawmill, twice in hospital air and once in a CF patient) and one isolate in the Netherlands.
Equids are chronically infected with parasitic strongyle nematodes. There is a rich literature on horse strongyles, but they are difficult to identify morphologically and genetic studies on strongyles infecting other equid species are few, hampering studies of host specificity. We sequenced expelled worms from two sympatric zebra species in central Kenya to expand the strongyle phylogeny and used DNA metabarcoding on faecal samples to genetically characterize zebra nemabiomes for the first time. We generated sequences for several species new to public genetic reference databases, all of which are typical strongyles in wild zebras (i. e. , the three species of Cylindropharynx and Cyathostomum montgomeryi), and identified their closest relatives. We also discovered an apparent fungus infecting a quarter of the expelled Crossocephalus viviparus worms, a hyperabundant nematode species in the family Atractidae, hinting at the possibility that zebra host-parasite dynamics may involve a zebrafungus mutualism.
In this study, our objectives were to (1) build upon genetic reference databases for equid nematodes and generate an updated strongyle phylogeny integrating the species that infect zebras; (2) genetically characterize the nemabiomes of plains and Grevy's zebras for the first time, using DNA metabarcoding; and (3) determine the extent to which wild plains and Grevy's zebras host the same strongyle species, and thus their potential for cross-infection.
Phylogeny building We used Geneious 11. 0. 4 (https://www. geneious. com) to align forward and reverse reads and generate the consensus sequences for each nematode reference sample. Each of these sequences was run through BLASTn to find the closest matches in GenBank and confirm morphological identification. Any worm for which morphological identification was uncertain was identified to species level if >98% similar to a Gen-Bank reference and to genus level if >95% similar to a GenBank reference along the entire sequence. We chose these thresholds based on inter-and intraspecific sequence similarity (inferred using the European Bioinformatics Institute, or 'EMBL-EBI', MUSCLE algorithm;  Madeira et al. , 2019)  between worms that we could confidently identify morphologically. We then conducted a multiple sequence alignment using MUSCLE  (Edgar, 2004)  and used MEGA-X (version 10.
2. 6;  Kumar et al. , 2018; Stecher et al. , 2020)  to test models for estimating evolutionary distance by maximum likelihood with default parameters. The model with the lowest Bayesian information criterion (BIC) score (the Tamura 3-parameter model with gamma-distributed substitution rates, γ = 0. 45) was selected to build a phylogenetic tree with the neighbour-joining method  (Saitou and Nei, 1987). The tree robustness was assessed using the bootstrap test (2000 replicates) and we plotted the consensus tree using the R package ggtree, labelling nodes that were highly supported with bootstrap values (i. e. , the percentage of the replicate trees that had the same branch tips cluster together) (R version 4. 0. 0; R Core Team, 2019; Yu et al. , 2017). In addition to generating a phylogeny from our reference worms, we integrated the reference worms that we could identify to species level into a broader phylogenetic tree that included all sequenced strongyles with species-level identification extracted from the 'Nemabiome' nematode ITS2 database (version 1.
2. 0; www. nemabiome. ca), which draws data from GenBank and which included sequences contributed from the present study  (Avramenko et al. , 2015 (Avramenko et al. , , 2017)). In addition to the 329 Strongylidae sequences extracted from the database, we manually added the only available sequence for Strongylus asini (entered only as S. asini in GenBank) and our Caenorhabditis elegans positive control to serve as the outgroup. A sequence from one of the Coronocyclus labiatus references (MG738707) was excluded after it appeared as an outgroup in the phylogeny instead of C. elegans in an initial tree construction. We then processed the sequences as above (using the Tamura 3-parameter model with γ = 1. 11). In addition, we pruned the tree by merging all immediate sister taxa with identical species assignments or synonymous assignments (i.
e. , Cylicodontophorus mettami and Parapoteriostomum mettami, Petrovinema poculatum and Cylicostephanus poculatus;  Lichtenfels et al. , 2008)  in R with the 'drop. tip' function from the package ape  (Paradis and Schliep, 2019)  before visualizing the tree with ggtree.
Output sequences were run through the obitools workflow  (Boyer et al. , 2016)  to (1) align paired-end reads, (2) demultiplex sequences for each sample, (3) dereplicate the sequences, (4) identify sequences that were likely to be derived from PCR/sequencing errors, and (5) assign sequences to a taxon against both a global database (derived from the EMBL database) and the local database we created from the nematode reference samples that we morphologically identified (see details in SI1)  (Pansu et al. , 2019). Preference was given to the local database in the case of a discrepancy and equal match scores. Additional filtering steps were conducted in R (SI1). All samples were rarefied to 1000 reads based on rarefaction curves constructed with the vegan package  (Oksanen et al. , 2019)  to standardize library sizes and enable cross-sample comparison.
Prior to analyses, the 224 unique sequences that remained were grouped into clusters approximating species, called molecular operational taxonomic units (mOTUs), using the SUMATRA algorithm for sequence alignment  (Mercier et al. , 2013)  and MCL for clustering  (van Dongen, 2008). For our analyses, we used a 98% similarity threshold between sequences to define clusters. Interspecific differentiation in nemabiome communities was visualized using non-metric multidimensional scaling (NMDS) ordinations based on Jaccard distances  (Jaccard, 1901)  calculated with the package vegan  (Oksanen et al. , 2019)  and using bipartite networks (constructed with the package bipartite;  Dormann et al. , 2008). Because of possible amplification biases between nematode taxa, the potentially misleading skew in egg shedding between taxa  (Kuzmina et al.
Results The expelled worms we found in zebra faeces that were successfully sequenced belonged to five genera and 18 species or mOTUs. Most of the collected worms were Parapoteriostomum species, followed by Crossocephalus viviparus (the only species collected from the family Atractidae), and only one was a strongylin (Craterostomum acuticaudatum). Four species were new to public genetic reference databases (Cylindropharynx brevicauda, C. intermedia, C. longicauda, and Cyathostomum montgomeryi). Our study also provided new information on withinspecies genetic variation in strongyles: out of the 91 worms sequenced, only three, all of which were identified as Cylicostephanus minutus, had species-level matches (>98% similarity) to existing Gen-Bank entries, and these matches were only partial (85-90% of the sequence length).
In our broader phylogeny of strongyles integrating sequences from the Nemabiome database, the immediate relatives of the newlysequenced strongyles could be confidently identified. The closest relatives of Cylindropharynx were Skrjabinodentus caragandicus, a cyathostomin, and Bidentosomum ivashkini, a strongylin (Fig. 1 ). The optimal tree further placed the three Triodontophorus species and Craterostomum acuticaudatumwhich are all also strongylins (but see  Hung et al. , 2000)  as the next clade to branch from this cluster. The closest relative of Cyathostomum montgomeryi was identified with high confidence as Cyathostomum tetracanthum, and unlike the phylogeny of our reference worms, Cylicostephanus bidentatus was placed far from these species and in a basal position within the broader phylogeny, potentially because of the addition of many more taxa in this phylogeny.
Parapoteriostomum and Poteriostomum were shown to be closely-related genera, and non-equid strongyles (Tziminema, Khalilia, Kiluluma, Quilonia, and Murshidia speciesmembers of the Strongylidae family that infect tapirs, rhinoceroses, and elephants) formed a cluster with several well-supported internal nodes. Much uncertainty remains in the relationships between most cyathostomin genera, with Cylicostephanus, Cylicocyclus, Coronocyclus, and Cyathostomum species widely distributed throughout the phylogeny. All nematode mOTUs were found in both host species. Nemabiome community composition differed slightly by host species as evidenced by some weak but statistically significant clustering in ordination plots (SI3, SI4). However, the ANOSIM revealed an overall R value of 0. 013 (p 1. Phylogeny of all sequenced Strongylidae with species-level taxon assignments from GenBank and the present study, coloured by genus (the same colour code is used across all figures in this paper).
02; Fig. 2b ). The most prevalent nematodes -'Unknown 2' (which had no reference matches >95% in public genetic databases), Cylicostephanus bidentatus, Cyathostomum montgomeryi, and Cylicostephanus sp. Bwere equally prevalent in the two host zebra species (upper right corner of Fig. 2b ). Potential weak host preferences as suggested by skew in prevalence were apparent in some nematode clades. For example, among Cylindropharynx, C. intermedia was more prevalent in Grevy's zebras (prevalence in Grevy's: 69. 9%, in plains: 52. 0%) and C. brevicauda in plains zebras (80. 1% in Grevy's, 90. 1% in plains; Fig. 2 ). While none of our zebra hosts carried the three principal strongylins of domestic horses (Strongylus vulgaris, S. edentatus, and S. equinus, each of which has ITS2 references in GenBank), an unknown mOTU likely to be in the Strongylus genus was prevalent in both zebra species, as were other strongylins such as S.
Discussion Our sequenced reference samples provided many new contributions to public genetic databases. Four of the seven strongyle taxa that we could confidently identify to species-level had not previously been sequencedthese were all strongyles common in wild zebras (the three Cylindropharynx species and Cyathostomum montgomeryi;  Krecek et al. , 1987b; Matthee et al. , 2004; Round, 1968; Scialdo-Krecek et al. , 1983). We were further able to identify the closest relatives for each of these taxa, and the proximity of Cylindropharynx species with strongylins in our broad phylogeny indicates that their pathogenicity may be a worthwhile target for future research. The high uncertainty of many phylogenetic nodes and the scattered distribution of many cyathostomin genera in the tree highlight the need to further resolve the strongyle phylogeny.
Conclusions This study revealed an absence of strict host specificity among gastrointestinal nematodes infecting sympatric plains and Grevy's zebras in central Kenya, suggesting that the two species have high potential for cross-infecting one another. Cumulative zebra dung density on the landscape is thus likely a determinant of the exposure risk of both zebra species to these faecal-orally transmitted nematodes. We also found their nemabiomes to be highly similar in terms of the prevalence of the various nematode taxa. Several prevalent sequences from the metabarcoding analyses matched publicly available reference sequences only to genus level or broader. Given the absence of reference sequences in public databases for many nematodes infecting wildlife, and the wealth of information such databases provide for phylogenetic and DNA metabarcoding studies, we suggest that the development of extensive taxonomically verified reference libraries is a high priority for future research  (Pringle and Hutchinson, 2020).
Acknowledgments This work was funded by the  National Science Foundation  ( IBN-0309233 ,  CNS-025214 ,  IOB-9874523 ,  IIS-0705822 ,  IIS-0747369 ,  IOS-1656527 ) and the  High Meadows Environmental Institute and Department of Ecology and Evolutionary Biology at Princeton University. Sequence alignment, filtering, and taxonomic assignment were performed on computational resources managed and supported by  Princeton Research Computing , a consortium of groups including the  Princeton Institute for Computational Science and Engineering (PICS-ciE)  and the  Office of Information Technology's High Performance Computing Centre and Visualization Laboratory at Princeton University. We thank  Mpala Research Centre ,  Kenya Wildlife Services  (permit number  KWS/BRM/5001 ), the  National Environment Management Authority  ( NEMA/AGR/107/2018 ), and the  National Commission for Science and Technology  ( A10450 ) for permission to conduct our research and for logistical support, as well as the  United States Department of Agriculture  for permission to transport the samples into and within the  United States (USDA APHIS permits 130123 ,  137202 , and  137555 ).
8S-ITS2) of ribosomal DNA by PCR using ITS4 and ITS6 primers  [26, 27]. Amplified samples were purified with the EZNA Cycle Pure Kit (Omega Bio-Tek, Norcross, GA, USA) and sequenced by Source Bioscience Lifesciences or Macrogen Europe. Sequencing results were analysed with CLC Main Workbench (Qiagen, San Diego, CA, USA) by comparison against two different databases to identify each isolate: GenBank, using the BLAST tool with the algorithm "blastn"; if the result suggested a Phytophthora species, the sequence was compared against accessions in the Phytophthora Database (http://www. phytophthoradb. org/).
1 µ M each TaqMan probe, 1 µL undiluted eDNA, 0. 6 µ M each internal control primer, 0. 13 µ M internal control probe, 0. 1 ng µL -1 plasmid PLRV DNA and Milli-Q water to a final reaction volume of 25 µL. For the trnM and atp9 probes the amplification mixture was the same but the IPC primers, probe and plasmid DNA were excluded and 2 µL of undiluted eDNA added. Negative controls were included using Milli-Q water as template in all PCRs for all plant composts (ITS, trnM and atp9 with the plasmid PLRV DNA). Cycling conditions were 95 °C for 2 min; 50 cycles of 95 °C at each specific annealing temperature for 1 min. Data were collected in the last holding stage of each cycle. Results were analysed using 7500 Software v2. 3 (Applied Biosystems, Thermo Fisher Scientific, Waltham, MI, USA) and exported to an Excel template to determine eDNA concentrations.
Of the plants sampled here, only 12 of 99 included information on the country of origin (China and Germany). Such data would be of great value in the development of contingency measures following a disease outbreak once plants are planted  [5, 6]. Internet plant sales and rapid postal deliveries might also be speeding up the spread and establishment of potentially harmful pathogens, reducing the time plants spend in transit and delivering viable pathogens along with the plants. During this work, there were no differences in detection of oomycete species in plants obtained online and from physical retailers. A major review published recently illustrated the high incidence of Phytophthora infestations in plant nurseries and the movement of these potentially damaging pathogens to gardens, forests and natural ecosystems  [3].
Supplementary Materials: The following are available online at www. mdpi. com/2309-608X/7/2/87/s1, Table  S1 : Genbank accession numbers for the ITS region of oomycete isolates, MF115150-MF115524. Table  S2 : eDNA quantification with ITS, trnM-trnP-trnM and atp9-nad9 probes (in ng g -1 of plant compost, roots or crushed filters), and list of oomycete species isolated on each plant using classical methods. Author Contributions: Conceptualization, S. W. , P. J. M. B. and E. B. ; methodology, A. P. , S. W. and P. J. M. B. ; formal analysis, A. P. , S. W. , P. J. M. B. ; investigation, A. P. ; writing-original draft preparation, A. P. and S. W. ; writing-review and editing, A. P. , S. W. , P. J. M. B. , E. B. ; funding acquisition, S. W. , P. J. M. B. and E. B. All authors have read and agreed to the published version of the manuscript.
Effect of the Pandemic on International Cooperation and on Various Development Projects International travel restrictions seriously impacted ongoing and future international technical and scientific cooperation. Most of the camel countries belong to the group of developing states and some are among the poorest in the world, especially Sahelian countries, which represent 78% of the world camel population  (Faye, 2020). The development of the camel sector in those countries is depending on financial support from different projects supported by international organizations, such as FAO (e. g. , in Chad or in Mauritania) or on EU (projects such as CARAVAN, CAMELMILK, and CAMELSHIELD) or some NGOs. In most of the cases, the COVID-19 pandemic has postponed expected activities (training, experiments, capacity building, and support for inputs) and sometimes delayed financial supports.
Statistical Analyses Survival analyses were performed with R 3. 6. 2 and its packages survival and survminer. The effects of early spaying and MTs on survival were analyzed with log-rank tests (for categorical variables) and Cox proportional-hazards regression models (for continuous variables). The proportional hazard assumption was checked graphically with graphics of the scaled Schoenfeld residuals against time. Kaplan-Meier curves were drawn using Medcalc®statistical software (MedCalc Software Ltd. , Ostend, Belgium). When required, normality was assessed with Shapiro-Wilk's test. Student's t-test was used to compare numerical variables between groups and help identify possible confounding factors. A logistic model approach was used to evaluate the relationship between the spaying status (intact, ES, and LS) and urinary incontinence.
Jitpean reported on the rate of MTs at the age of 10, and probably underestimated the percentage of females affected by MTs during their lifespan  [25]. Salas reported that adult female dogs (9 to 12 years old) were most frequently involved  [26]. Indeed, Vascellari reported that MTs accounted for 54% of all tumors in female dogs  [27]. The present study was retrospective. The most critical bias in such studies is the selection bias. As we enrolled all of the female dogs born between 2000 and 2003 that were recorded in our database, under the condition that at least one complete physical examination was available from 6 years of age, with known sterilization status, such a bias is unlikely to have occurred. Other sources of bias such as a relationship between owner decision regarding spaying or MT surgery and specific profiles of dogs may have been present.
Bovine respiratory disease (BRD) is one of the most common calfhood diseases in dairy cattle. Unfortunately, published data on the short-and long-term effects of calfhood BRD on health and performance are scarce and, when available, often conflicting and uncertain. The objective of this study was therefore to review the scientific literature on the effects of calfhood BRD on health and performance of dairy cattle and summarize the research findings using a meta-analysis approach. The systematic review and meta-analysis were performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed and CAB Abstract databases were screened for relevant studies that were published in English (until February 3, 2020). Only studies reporting naturally occurring BRD cases from birth to 12 mo of age in dairy calves in Europe and North America were considered eligible.