dataesr/scientific-paragraphs-categorization huggingface dataset:
This estimation, without any published references, seems quite unlikely to entomologists studying the French Guianan fauna. However, it highlighted the fact that no global checklist was available to provide an accurate account of what was known so far. French Guiana, with its rich diversity, became a popular destination for entomologists worldwide and therefore is assumed to be better studied than some other tropical countries. Unfortunately, faunal lists are only available for a restricted number of groups (e. g. Coleoptera: Cerambycidae, Tavakilian and Chevillotte 2012). There are at least three important objectives for this work on the compilation of regional species databases: 1) To enable data exchange, which makes data sharing possible between observational or collection databases from different users, as long as they use the same taxonomic list.
For these reasons, we launched this project as a part of the national taxonomic database (TAXREF:  Gargominy et al. 2013 ) on behalf of the natural heritage inventory of France (MNHN, online). The database will be available online (see Suppl. material 1) and will be updated on a yearly basis. This publication provides descriptive analysis of what is known so far, quantifies the description rates, discusses who supports the faunistic and taxonomic progress, which are the most and least studied orders, and tries to extrapolate a rough figure of the total species richness of insects in French Guiana.
Elaboration of the checklist of known species Except for a few families that recently benefited from a regional checklist (e. g. Heiss and Moragues 2009 , Faynel 2010 , Brûlé 2011 , Pauly et al. 2013)  and some global species databases (e. g. Tavakilian and Chevillotte 2012) , no list of species was available for French Guiana. In 2008, we started the French Guiana list, as a part of the French national taxonomic database (TAXREF:  Gargominy et al. 2013) , with the help of all our colleagues working on specimens collected by SEAG (Société entomologique Antilles-Guyane -Entomological Society of French Guiana and West Indies). At the end of 2012, we asked those experts to compile and transmit lists in their taxonomic groups of study, taking into account only published records for French Guiana up to the beginning of 2013.
2013 ) in order to integrate the species database. This includes a "biogeographic status" field regarding the occurrence of the species in French Guiana. The following codes were used: P: taxa present in French Guiana (default status); G: taxa described and only known (so far) from French Guiana; E: endemic taxa (used only for well-known groups, otherwise G); S: sub-endemic taxa (well-known taxa ranging only in the Guiana Shield region); I: introduced taxa; J: introduced and invasive; B: vagrant; Q: taxa recorded from French Guiana in error.
Other insect baselines for comparison To compare and extrapolate the total diversity of French Guiana, we first sought published checklists or available online databases for very well-known fauna, in all orders and families, in as close a biogeographical context (tropical America) as possible. We found no convincing resources corresponding to these criteria. We finally used for comparison three faunal references: total species richness of the global, Nearctic and French faunas. The total number of known species per order worldwide  (Zhang 2013 ) cannot be used to extrapolate total diversity, as it is dependent on the level of the taxonomic knowledge. However, it can be used to identify major gaps, by comparing the number of species known worldwide per order with the same figure from French Guiana.
The figures for the North American fauna from the Nomina Insecta Nearctica series  (Poole and Gentili 1996)  were used at the family level. Although compiled 15 years ago, this series provides a comprehensive reference for all orders. Knowing the total figure for North America (ca. 95 000 species), it was possible to estimate the diversity in French Guiana using cross-multiplication from a sample of well-known families. These figures are useful, but we assume that the total richness based on this projection is surely underestimated. The Fauna Europeae project is a continent-wide data basing effort  (De Jong 2013). Additional faunistic and taxonomic updates have been conducted on a subset of the TAXREF data limited to France and Corsica. The French fauna is one of the longest studied, and estimated to contain 36 000 insect species.
We consider the building and maintenance of a regional species database for insects as an opportunity to raise awareness of insect diversity and to measure the taxonomic gap. The initial checklist analyzed in this paper will be regularly supplemented and corrected, with updates made available from an online downloadable database (MNHN, online). Finally, we invite all our taxonomist colleagues to contribute to the insect list any missing taxa already described, corrections to existing records and to publish any new taxa and new records for French Guiana.
Acknowledgments We wish to thank our friends and colleagues of the SEAG, for hundreds of hours spent on the ground and sorting the samples collected during this study. We also wish to thank all fellow entomologists who compiled species lists and who agreed to receive (or received) and study (or studied) the entomological material and to participate in the various entomological works done in French Guiana, without whom our knowledge would not have increased in recent years:  Alexandre Aguiar ,  Angélico Asenjo ,  Alberto Ballerio ,  Max Barclay ,  Paula Batista dos Santos ,  Frédéric Bénéluz ,  Jean-Michel Bérenger ,  Paul Beuk ,  Svatopluk Bily ,  Denis Blanchet ,  Olivier Boilly ,  Stéphane Boucher ,  Volker Brachat ,  Yves Braet ,  Harry Brailovksy ,  Boris Büche ,  Fabio Cassola ,  Jacques Chassain ,  Andrew Cline ,  Philippe Collet ,  Oskar Conle ,  Robert Constantin ,  Geovan Corrêa ,  Gianfranco Curletti ,  Mauro Daccordi ,  Pierre-Henri Dalens ,  Nicolas Degallier ,  Gérard Delvare ,  Thierry Deuve ,  Benoit Dodelin ,  Frédéric Durand ,  Marc Epstein ,  Terry Erwin ,  Christophe Faynel ,  François Feer ,  Rodrigo Feitosa ,  Serge Fernandez ,  Julio Ferrer ,  Eric Fisher ,  Carlos Flechtmann ,  Antoine Foucard ,  Alexandre François ,  Steve Gaimari ,  David Gibbs ,  Jessica Gillung ,  Christophe Girod ,  David Gonzales ,  Eric Guilbert ,  Grey Gustafson ,  Esteban Guttierez ,  Martin Hauser ,  Ernst Heiss ,  Daniel Herbin ,  Bernard Hermier ,  Andreas Herrmann ,  Gary Hevel ,  Mary Liz Jameson ,  Laurent Juillerat ,  Bruno Kneubühler ,  Olavi Kurina ,  Fabrice Lavalette ,  Gérard Le Goff ,  Pascal Leblanc ,  Daniel Lohez ,  Roland Lupoli ,  Daiara Manfio ,  Antoine Mantilleri ,  Lubomir Masner ,  Lucia Massutti de Almeida ,  Erica Mc Alister ,  Charyn Micheli ,  Olaf Mielke ,  Didier Morin ,  Miguel Angel Moron Rios ,  Massimo Olmi ,  Ivan Paulmier ,  Eddy Poirier ,  Alain Pauly ,  Yannig Ponchel ,  Adrian Pont ,  Pierre Queney ,  Chris Raper ,  Brett Ratcliffe ,  Joachim Rheinheimer ,  Menno Reemer ,  Albino Sakakibara ,  Floyd Shockley ,  John Smit ,  Villu Soon ,  Marc Soula †  ,  Adeline Soulier-Perkins ,  Cibele Stramare Ribeiro-Costa ,  Daniela Takyia ,  Paul Thiaucourt ,  Alain Thomas ,  Marc Thouvenot ,  Guy Tomasovic ,  José Fernandez Triana ,  Marc Tussac ,  Lars Vilhelmsen ,  Monty Wood ,  Franz Wachtel ,  Jean-Hervé Yvinec  and  Theo Zeegers.
Differentiation Studies Before each experiment, af-MSCs were seeded (1 3 10 6 cells per well in 1 ml of AmnioChrome II medium) in six-well plates, as previously described  [19]. For adipogenic differentiation, af-MSCs were cultured for 3 weeks using the human MSC (hMSC) Adipogenic BulletKit (Lonza), following the manufacturer's protocol. Oil Red O staining was used to detect adipocytes. For osteogenic differentiation, af-MSCs were cultured for 3 weeks using the hMSC Osteogenic BulletKit (Lonza), following the manufacturer's protocol. Differentiation was assessed by alizarin red S staining. Differentiation experiments were performed twice on two af-MSC lines. For each differentiation protocol, negative control conditions were achieved by culturing cells in AmnioChrome II medium. Supplemental data are available online.
We then used the XTT kit (Roche Applied Science, Indianapolis, IN, https://www. roche-applied-science. com) to assess cell viability, following the manufacturer's protocol. Results are expressed as percentage ratios of the absorbance (XTT) obtained in HR cells over absorbance of the same cells cultivated in control conditions. Cells were also stained for viability using the 7-AAD dye (BD Biosciences) and analyzed by flow cytometry. Data are from three independent experiments (three af-MSC lines).
ACKNOWLEDGMENTS We are grateful to  Nicolas Chatauret ,  Raphael Thuillier , and  Sebastien Giraud  for their guidance and advice;  Sandrine Joffrion  and  Marie-Laure Bonnet  for their excellent technical assistance with the in vitro experiments;  Pierre-Olivier Delpech ,  William Hebrard , and  Thibaud Saint-Yves  for their efficient implementation of surgery procedures; and  Tackwa Khalifeh  and  Paul Roblot  for their helpful work performed during the course of their master's studies. This work has benefited from the facilities and expertise of the  ImageUP platform (Institut de Physiologie et Biologie Cellulaires-University of Poitiers ).
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Reference formatting There are no strict requirements on reference formatting at submission. References can be in any style or format as long as the style is consistent. Where applicable, author(s) name(s), journal title/ book title, chapter title/article title, year of publication, volume number/book chapter and the article number or pagination must be present. Use of DOI is highly encouraged. The reference style used by the journal will be applied to the accepted article by Elsevier at the proof stage. Note that missing data will be highlighted at proof stage for the author to correct. If you do wish to format the references yourself they should be arranged according to the following examples:.
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S. Jones, R. Z. Smith (Eds. ), Introduction to the Electronic Age, E-Publishing Inc. , New York, 2009, pp. 281-304. Reference to a website: [5] Cancer Research UK, Cancer statistics reports for the UK. http://www. cancerresearchuk. org/ aboutcancer/statistics/cancerstatsreport/, 2003 (accessed 13 March 2003). Reference to a dataset: [dataset] [6] M. Oguro, S. Imahiro, S. Saito, T. Nakashizuka, Mortality data for Japanese oak wilt disease and surrounding forest compositions, Mendeley Data, v1, 2015. https://doi. org/10. 17632/ xwj98nb39r. 1. Reference to software: [7] E. Coon, M. Berndt, A. Jan, D. Svyatsky, A. Atchley, E. Kikinzon, D. Harp, G. Manzini, E. Shelef, K. Lipnikov, R. Garimella, C. Xu, D. Moulton, S. Karra, S. Painter, E. Jafarov, S. Molins, Advanced Terrestrial Simulator (ATS) v0.
It was later complemented by a larger set of 99 new SSRs, derived from an EST database  [22] , and used at least in one study  [23]. SSRs are of particular value for population studies, since they are co-dominant, easy to use, and highly polymorphic markers. As diversity in Z. tritici is unanimously considered high, a reduced panel of adapted SSRs should suffice to analyze population genetic structure  [17]. Ideally, such markers should be genetically independent, i. e. , reside on different chromosomes, and selectively neutral to avoid bias in subsequent population genetic analyses  [24]. Moreover, multiplex PCR, i. e. , the simultaneous amplification of several markers within a single reaction, is a good way to improve the SSR genotyping efficiency and to considerably reduce cost and labour  [25].
Additionally, in order to increase the number of available SSRs from which to choose markers to constitute the panels, microsatellites were mined from the fastaformatted genome of strain IPO-323 using the same pipeline of Perl scripts and C++ program that has been used to obtain microsatellites from EST sequences of higher plants  [26]. This pipeline output primer sequences, motifs and repeat counts of simple and compound microsatellites, primer annealing temperatures, and primer locations in the genome. It searched for motifs of one to four nucleotides, with respective minimum repeat counts of 12, 6, 4, and 3. Up to 10 percent of mismatching positions were allowed, and the maximum distance between consecutive repeat blocks was five nucleotides in compound microsatellites. Primers were chosen to amplify products 100 to 500 nucleotides long, and to anneal at 60 ± 1.
2°C, with preference to annealing temperatures in the interval 60. 0 ± 0. 2°C. In addition to the assembled genome of IPO-323, 86,776,768 short (45-base) reads were available for strain IPO-94269 (unpublished data). Reads with sufficiently high quality scores were mapped to the genome of IPO-323 by blastn, and a Perl-collated consensus of these reads provided an approximate assembly of the genome of IPO-94269. IPO-94269 lacks the accessory chromosomes 18 and 20, present in IPO-323  [5]. Otherwise, it was assumed for the sake of tractability that the two strains differed only in substitutions, and not in indels. Another Perl script blast-aligned the microsatellite primers from above to the IPO-323 and IPO-94269 genomes, and selected the primer pairs that hit each genome exactly once. For chromosomes 18 and 20, we selected the primer pairs that hit the genome of IPO-323 exactly once.
The marker ST1E7  [20]  was included in multiplex 2 to allow comparison with previously published datasets  [10]. Finally, primers amplifying a 108 bp fragment from the housekeeping gene ILV5, keto-acid reductoisomerase (Chromosome 1, Protein ID 102127), and a 96 bp fragment from the housekeeping gene SOD, superoxide dismutase (Chromosome 1, Protein ID 102956), were introduced in the multiplexes to serve as amplification controls. This is particularly important for multiplex 3, since isolates without any accessory chromosome may be detected in field populations. Once the three panels were optimized on the limited number of samples, the procedure was automatized for high-throughput routine work. Fresh sporidia, collected from 5 day-old mono-pycnidia cultures on malt-yeast agar MYA (20 g. l -1 malt extract, 5 g.
Panel composition is detailed in Table  1. PCR conditions were identical for all multiplexes, with preheating   [20, 22]. The graphical representation of the map was constructed using the software MAPCHART  [33]. The microsatellites used in the three multiplexes are represented in larger font and in bold with their new name (correspondence to the previously published name can be found in Table  1 ). The colour of a microsatellite locus indicates in which multiplex the marker is integrated: red for multiplex 1, blue for multiplex 2 and green for multiplex 3. An asterisk indicates that the marker is reported for the first time. The positions of the housekeeping genes ILV5 (ID 102127) and SOD (ID 102956) are also indicated on chromosome 1. Proposed name of microsatellite loci starting with the fungus initials and followed by the chromosome number on which the microsatellite is located (except for ST1E7).
i Frequency of missing data or null alleles (no amplification) in the total population. j Unbiased gene diversity H E calculated as the probability that two individuals taken at random have different genotypes (excluding null alleles)  [31]. at 95°C for 5 mn, followed by 30 cycles of 95°C for 30 s, 57°C for 90 s and 72°C for 30 s, with a final extension step of 60°C for 30 mn, using a MJ research PTC-200 thermocycler. The PCR products were run on a 2% agarose gel to check for amplification products. Sequencing reactions were prepared as follows: for multiplexes 1 and 2, 0. 8 μl PCR product, 40 μl Sample Loading Solution (SLS) and 0. 5 μl 400 bp size standard (red dye); the mix for multiplex 3 was the same, with the exception that 0. 5 μl 600 bp size standard was used instead of the previous one.
Binned alleles were finally assigned a definitive name (generally derived from the mean allele size) and allele size ranges were established (Table  1 ). The generated binning files could be used to annotate allele peaks from new data in any laboratory using a Beckman Coulter DNA Analyzer, and are described in Additional file 3 and provided as Additional file 4 or upon request to the authors. The alleles' sizes of IPO-323 and other 100 reference isolates are provided as examples of this procedure (Additional file 3) to help further assignment by other operators. Resequencing data of all these reference isolates will be soon released on the JGI Genome Portal website (http://genome. jgi-psf. org/). This procedure assures reliable and accurate allele scoring, even when different or inexperienced operators manipulate the data, increasing the reproducibility between distinct datasets generated over time.
Checking the quality of the multiplexed SSR panels Frequency parameters were calculated for the 166 individuals (see below for the description of the populations) with the software GENALEX 6. 4  [28]. For each marker, the number of SSR repeats present in the isolate IPO-323 was determined according to its genome sequence and used to infer the number of repeats from all the other alleles. In a few cases, fewer than 0 repeats were deduced for alleles present in never more than one to three individuals; such alleles were coded as missing alleles and were not considered further. Excluding those, a total of 204 alleles were detected. The number of alleles per SSR ranged from 2 to 16 for panels 1 and 2 on the core chromosomes (Table  1 ). Markers on the accessory chromosomes 14 and 20 had particularly numerous alleles with 36 and 20 detected alleles, respectively.
For further index calculations, missing data were coded as missing alleles for multiplexes 1 and 2, and as null alleles for multiplex 3. Gene diversity, estimated as the mean expected heterozygoty H e over the loci  [31] , and clonal richness (G/N; number of unique genotypes compared to the number of individuals) were plotted against the number of loci used to calculate these indexes in the three multiplexes and for all of them (Figure  3 ), using the MULTILOCUS program  [32]. As expected, gene diversity was similarly high in the two populations, and exceeded 0. 95 after 4 loci were included in calculation for multiplexes 1 and 2, and after two loci were included for multiplex 3, probably because null alleles are considered as distinct alleles for markers located on the dispensome. The 24 SSR loci present in the three panels are then sufficient to saturate the whole gene diversity, at a local and a larger scale.
Figure1Position of 80 published microsatellite loci on the genome of Zymoseptoria tritici (scale of the chromosomes is in base pairs) [20, 22]. The graphical representation of the map was constructed using the software MAPCHART [33]. The microsatellites used in the three multiplexes are represented in larger font and in bold with their new name (correspondence to the previously published name can be found in Table1). The colour of a microsatellite locus indicates in which multiplex the marker is integrated: red for multiplex 1, blue for multiplex 2 and green for multiplex 3. An asterisk indicates that the marker is reported for the first time. The positions of the housekeeping genes ILV5 (ID 102127) and SOD (ID 102956) are also indicated on chromosome 1.
The indirect labeling consisted of successive incubations of 1 × 10 6 cells with anti γδTCR (1/100 dilution), anti-mouse IgG (1/1000 dilution) and anti-CD3 (1/100 dilution) antibodies in a final volume of 100 µl. All incubations lasted 30 min and were carried out at 4°C. After each staining step, cells were washed twice in 250 µl PBS. Cells were suspended in 400 µl of fluorescence-activated cell sorter buffer before analysis. Analysis of PBMC was performed using a Macs Quant Analyzer (Miltenyi Biotec, Bergisch Gladbach, Germany) with MacsQuant Quantify software. The strategy of gating for the analysis is presented in Figure  1.
Statistical analysis Analysis of variance was performed using the mixed procedure of SAS (version 8. 1, 2000, SAS Institute Inc. , Cary, NC, USA). The fixed factors of the analysis were the treatment and replicate. Normality of the data was checked on residuals with the Shapiro-Wilk test. For blood leukocyte counts and cytometry, data from experiments A and B were analyzed together with experiment B declared as a 5th replicate. Because the disequilibrium owing to the lack of IC pigs in experiment B could have biased the analysis, those results were compared with those of an analysis, taking into account only the repetitions from experiment A. The means that were statistically different when pooling experiment A + B were also significant (% CD3 + CD4 + CD8 + at 5 months of age, blood lymphocyte numbers at 4 months), close to statistical difference (% γδT cells at 5 months) or at least in the same numerical order (blood total leukocyte and lymphocyte counts at 5 months, γδT and CD3 + CD4 + CD8 + % at 4 months) in experiment A alone.