dataesr/scientific-paragraphs-categorization huggingface dataset:
The PCR products were separated on 2% agarose gels in tris-acetate-ethylenediaminetetraacetic acid (TAE buffer) and were visualized under ultraviolet light after staining with ethidium bromide. A 100-bp DNA ladder was used as a standard marker. Strong positive samples were purified and directly sequenced using an Applied Biosystems model 3730XL (Fisher Scientific S. A. S. , Illkirch-Graffenstaden, France). The newly generated sequences were aligned using Mega X  [44]. All sequences were assembled and compared with similar sequences retrieved from the GenBank nucleotide database using BLASTn  [45]. Phylogenetic analyses were inferred using the maximum-likelihood method implemented in the Mega X program  [44].
Availability of Data and Materials The GenBank accession numbers obtained in this study were MK608560-MK608588; MK608594-MK608637; MK608656-MK608660; MK624992-MK624999; MK652441-MK652442 for gltA gene (n = 91) and MK608589-MK608593; MK608638-MK608655; MK618727-MK618732; MK609661; MK600862; MK608661-MK608662 and MK618727-MK618732 for ompA gene (n = 33). For tick identification (16S rDNA) the GenBank accession numbers obtained were: MK620874-MK620878 (Dermacantor marginatus), MK620873 (R. bursa), MH663977 for (H. marginatum) MK620872 (I. ricinus) and MK761069-MK761072 (R. sanguineus s. l. ). All other relevant data are included in the article.
gltA], MG920564 (Turkey) [ompA]). Cluster II represented the Candidatus Ri. barbariae group. Our sequences were 99-100% identical to each other and to the Candidatus Ri. barbariae detected in Sardinia (EU272185 [gltA] and MF002506 [ompA]). Cluster III represented Ri. slovaca; sequences were 100% identical to each other and showed 99. 9% identity with that in GenBank (MF002529 (China) [gltA] and MF379311 (Turkey) [ompA]). Cluster four corresponded to the Ri. monacensis sequences group (100% identical to Ri. monacensis MH18982 (Poland) [gltA] and MG32690 (Italy) [ompA]). Cluster five included Ri. massiliae sequences and displayed 99. 8% identity with Ri. massiliae (MH990860 (Pakistan) [gltA] and MH990860 (Pakistan) [ompA]). Pathogens 2019, 8, x FOR PEER REVIEW 9 of 18 2. 5. Phylogenetic Analysis The results of phylogenetic trees based on gltA and ompA sequences are illustrated in Figure 2 A,B).
Cluster I corresponded to Ri. aeschlimanii: the sequences were 100% identical to each other and to the Ri. aeschlimanii sequences deposited in GenBank (KU961540 (Russia) [gltA], MG920564 (Turkey) [ompA]). Cluster II represented the Candidatus Ri. barbariae group. Our sequences were 99-100% identical to each other and to the Candidatus Ri. barbariae detected in Sardinia (EU272185 [gltA] and MF002506 [ompA]). Cluster III represented Ri. slovaca; sequences were 100% identical to each other and showed 99. 9% identity with that in GenBank (MF002529 (China) [gltA] and MF379311 (Turkey) [ompA]). Cluster four corresponded to the Ri. monacensis sequences group (100% identical to Ri. monacensis MH18982 (Poland) [gltA] and MG32690 (Italy) [ompA]). Cluster five included Ri. massiliae sequences and displayed 99.
2. 4 Revised). The effect of cultivar and shoot type (proleptic or sylleptic) on the number of phytomers per shoot and the number of central and associated floral buds were tested by two-way ANOVA with interaction after checking the normality of residuals with a Shapiro-Wilk test. The analysis was followed by Tukey's honest significant difference test for pairwise comparison considering all the shoot type and cultivar combinations. The effect of each shoot and cultivar combination on proportions of central bud fates and proportions of buds with associated floral buds was assessed with a χ 2 test  (Siegel and Castellan, 1988; Sharpe, 2015). The analysis was followed by a post hoc test considering all the shoot type and cultivar combinations using the chisq. post. hoc function of the fifer package of R software.
Organization of bud fates along shoots To determine the sequence of bud fates along shoots, hidden semi-Markov models (HSMMs) were built for all shoot types and cultivars  (Costes and Guédon, 1997, 2002; Renton et al. , 2006) , using the V-Plants software (release 0. 9) of the OpenAlea platform  (Pradal et al. , 2008). Shoot structure information was represented in these models with the estimation of the following parameter subsets: (1) initial probabilities for delineating the first zone at the base of the shoot; (2) transition probabilities determining the succession of zones along the shoot; (3) occupancy distributions representing the length of each zone (in number of phytomers); and (4) observation distributions representing the mixture of observations in each zone for the two observed variables (central bud fate and number of associated floral buds)  (Costes and Guédon, 1997, 2002; Renton et al.
Number of phytomers There was a significant cultivar effect on the number of phytomers per shoot (Table  1 ). Similarly, there was a significant shoot type effect that was mainly associated with fewer phytomers on Shoot type and cultivar effects were assessed by a two-way ANOVA with interaction. This analysis was followed by a post hoc Tukey's honest significant difference test considering the complete dataset. Values with different superscript letters are significantly different (P < 0. 05). ***P < 0. 001; ns, not significant. sylleptic compared with proleptic shoots for all cultivars. There were no significant interactions between cultivar and shoot type on the mean number of phytomers (Table  1 ). Based on the post hoc analysis, the number of phytomers in proleptic shoots was similar among cultivars, except for 'O'Henry', having fewer phytomers than the other cultivars (Table  1 ).
Production and purification of the casposases Production, purification and removal of the His-tag by Tev protease from recombinant A. boonei casposase were performed as described previously (26) (Supplementary Figure  S2A ). A codon-optimized version of the coding sequence of the Ca. Nitrosopumilus koreensis AR1 casposase (Gen-Bank protein accession number: AFS80663; coded by CP003842. 1: 655943. 656986) was ordered from GenArt™ (a subsidiary of Thermo Scientific). The gene, including the stop codon, was excised with PagI and XhoI and recloned between the NcoI and XhoI sites of the pETM-11 vector (EMBL Protein Expression and Purification facility). Thus, the casposase was flanked at the NH 2 terminus by the sequence MKHHHHHHPMSDYDIPTTENLYFQ, which provided a His 6 affinity tag followed by a recognition site for Tev protease that enabled removal of the affinity tag (Figure  1B ).
After completion of electrophoresis, the gels were scanned for 6-FAM fluorescence on a GE Typhoon FLA950 imager as described previously  (26). We then determined the ratio of the relative intensities of the bands corresponding to integration into the relaxed or linear form of the plasmid using the ImageJ32 software  (28). Results from at least three incubations were then processed using Kaleidagraph ® to yield the average ratio ± standard deviation of the two species. The incorporation of various 6-FAM-labelled singlestranded oligonucleotides was performed similarly. Restriction mapping of the concerted integration catalyzed by the casposase of Ca. N. koreensis was performed by digesting the pEX-A2-TSD-NitAR1 plasmid with ScaI (Thermo Fisher) or PagI (New England Biolabs). The mixture of fragments was column-purified using the Macherey Nagel Gel and PCR Clean-up kit, reacted with Ca.
Sequencing PCR products were purified using the NucleoSpin®Gel and PCR Clean-up kit (Macherey-Nagel, Düren, Germany) following the manufacturer's instructions. Purified products were quantified with a Qubit® 2. 0 fluorometer (ThermoFisher Scientific, Waltham, CA). The PCR primers and 10 ng of DNA were used for sequencing in both directions using a Big Dye Terminator v. 3. 1 cycle sequencing kit (Applied Biosystems) on a capillary sequencer (model 3100, Applied Biosystems). In case of nucleotide ambiguity, sequencing was repeated. Sequences generated in the present study were submitted to the EMBL/GenBank database under the accession numbers LT599493 to LT599497.
Data analysis and phylogeny Assembly and analysis of sequence data were conducted using the BioEdit Software version 5. 0. 9  [44]. Additionally, the software was used to read the sequencing electrophoregrams and to exclude nucleotide ambiguity. To ensure the reliability of sequences, forward and reverse sequences were aligned with ClustalW  [45]. Phylogenetic analyses were performed using the maximum likelihood method, the Tamura-Nei model (gamma distributed), with 500 bootstrap replicates and pairwise deletion using MEGA software Version 6. 06  [46]. For reference, bootstrap values above 50 were labelled on major tree branches. The nucleotide sequences of partial segments of the S1, G, HA, and F genes of IBV, aMPV, AIV and AAVV-1, respectively, were compared with the first 10 blast hit sequences and reference sequences of the same genes from GenBank.
Acknowledgements The authors express special thanks to the participating farmers in Pakistan. We also thank the  Plateau de Génomique GeT-Purpan ,  UDEAR UMR 5165 CNRS/UPS ,  CHU PURPAN, Toulouse, France , for the sequencing;  Angelina Gorrill  for editorial assistance; and  Maxime Fusade-Boyer  for his help with cartography.
All these proposals were collected in a database. Each card played was discussed among the farmers in groups. Following this phase, the farmers collectively built a cropping strategy combining several practice cards to develop a mycorrhizal network among the crops using the board game (Fig. 1 ). The second step was an on-farm survey based on semistructured questionnaires carried out 2 months later with all the farmers who attended the first workshop. The objectives were to assess knowledge retention, to continue proposal collection, and to identify the different types of constraints to mycorrhizal mobilization. The fifteen questions used to identify constraints focused on five aspects: (i) Farmers' level of environmental concern. (ii) Knowledge acquired about mycorrhizae. (iii) Agronomic constraints and implications of mycorrhizal mobilization in terms of inputs, soil tillage, crop rotations, etc.
The database of proposals was enriched through this stage. The third step was the second half-day collaborative workshop held to combine the proposals into a design strategy. This workshop was organized in two phases: (i) a presentation of the results of the survey and a debate on recent experimentation, and (ii) a prospective evaluation to orient collective creativity for the future for mycorrhizal enhancement. All steps were implemented in every study area over a period of 3 to 4 months.
These claims agree with the proposals of  Rillig et al. (2016) , which advocated database creation and adaptation of plant breeding strategies to the local needs of farmers. Although limited to small groups of farmers, the MYMYX approach has allowed (i) the appropriation of the mycorrhizal stakes by different stakeholders and (ii) the initiation and development of knowledge exchange tools. These results will likely support the establishment of new learning communities able to develop practices that are adapted to local constraints and challenges, which these communities could disseminate to the larger public.
Acknowledgments The authors would like to thank  Amélie Lefèvre ,  Jean-Louis Diman ,  Arnaud Dufils , and  Arnaud Larade  and the technical teams of the  INRA units Alénya, Peyi and ASTRO  for their contributions to the workshops,  Anne-Charlotte Harter  for the experiments, and  Mireille Navarrete  for her comments on the manuscript.
For Arabidopsis samples the Message AmpII aRNA amplification kit (Ambion) (Thermo fisher scientific, San Jose, CA, USA) and for apple samples the Low Input Quick Amp Labeling Kit, two-color (Agilent, Foster City, CA, USA) was used for cDNA synthesis and hybridization. The hybridizations were performed on a NimbleGen Hybridization System 4 (mix mode B) at 42 • C overnight. Afterwards, the slides were washed, dried, and scanned at 2 µm resolution. NimbleGen MS 200 v1. 2 software was used for microarray scans, and the Agilent Feature Extraction 11. 5 software was used to extract pair-data files from the scanned images. Statistical analysis was based on a dye switch approach as described in  [61]. All statistical analyses were performed using the R language (R Development Core Team, 2009); data were normalized with the lowess method, and differential expression analyses were performed using the lmFit function and the Bayes moderated t test using the package LIMMA  [62]  from the Bioconductor project.
Acknowledgments: K. G. and E. B. were funded by the  EPICENTER ConnecTalent  grant of the Pays-de-la-Loire. The authors are grateful to  Daniel Sochard  (Phenotic,  IRHS-UMR 1345 ) for growth chamber maintenance,  Fabienne Simonneau  for microscopy facilities (IMAC, SFR QuaSaV), and  Muriel Bahut for Transcriptomic facility  ( ANAN, SFR QuaSaV ).
In vitro inhibition The concentration of inhibitor that inhibited 50% of enzyme activity (IC50) under our specific experimental conditions (pH, temperature, time, protein concentration) was calculated using the logistic curve from the library of non-linear regressions of the XLSTAT software: y=E0. e (-b x [I]) +Eres where E0 is the total activity, Eres the residual activity, b=ki x t (ki inhibition kinetic constant, t the time in min) and IC50=ln(2)b -1.
Mortality and activities tests The significance of all results was tested using permutation tests due to non-respect of normality and homoscedasticity (Software; R version 3. 4. 3 and RStudio version 1. 1. 423). We used the package 'lmPerm'  (Wheeler and Torchiano, 2016)  and the function aovp combined with the function pairwise. perm. t. test from RVAideMemoir package. "Fdr" adjust of p-value were used due to risk of multiple comparison.
g. an increase in forage intake per animal contributes to a decrease in the forage biomass stock and vice versa). The figure was designed with Vensim software  (Ventana Systems, 2017). A detailed description of the herd and forage components of the model, as well as underlying differential equations, are presented in Appendix S1) conditions that are not onerous which, in effect, confers private ownership of pastoral operations. Properties are usually family or company owned and can be held for many generations within family structures. Given this security of tenure, most operations aim for long-term sustainability, although the challenges in matching forage supply and forage demand in a highly variable climate with frequent droughts can lead to cycles of degradation and recovery. Total standing dry matter (TSDM) forage levels for the Wambiana region are around 2,000 kg/ha, and if conservative grazing management is practised, moderate stocking rates are around 0.
Climate data from  Jones, Wang, and Fawcett (2009 ) (mean over years 1981 -2012). Cattle numbers in million head (M) from the Australian Bureau of Statistics (  2016 ) representation of the model key dynamics). Forage availability and quality as well as herd fertility, liveweight gains, mortality and sales rates determine the size of these flows, and therefore, the size of the cattle stock at any given point in time. When the model is in equilibrium, the inflows (births) and outflows (deaths and sales) are equal and the population is steady. The model was programmed using Stella Architect software v1. 5. 1 (isee systems, 2017).
Enteric methane emissions We estimated methane emissions from grazing cattle enteric fermentation (excluding calves) based on  Charmley et al. (2015)  study who reported a close relationship between dry matter intake and methane production. This relationship was derived from an analysis of Australian data of dairy and beef cattle fed diets of over 70% forage. We considered methane from manure in grazing systems as negligible due to aerobic conditions (Commonwealth of Australia, 2016a). Biogenic methane emissions were expressed as CO 2 -eq using the 100-year Global Warming Potential value 34 from the IPCC Fifth Assessment Report and include climate carbon feedbacks, feedbacks which measure the indirect effects of changes in natural carbon reservoirs (e. g. ocean, atmosphere) due to changes in climate (IPCC, 2014).
| Model evaluation Key forage and herd outputs of the model were evaluated by comparing the results from a baseline model simulation with a set of measured data for Wambiana and northern Queensland (see Figure  3  and Appendix S1 for evaluation results,  Hunt et al. , 2014; McGowan et al. , 2014; O'Reagain & Bushell, 2011). Due to the limited amount of long-term forage and herd measurements available in the literature, we also compared our model outputs with the ones from the GRASP model, which has been extensively used for northern Queensland including Wambiana  (Ash et al. , 2015; McKeon et al. , 2000; Scanlan, Macleod, & O'Reagain, 2013). Key outputs included temporal variations in forage growth, TSDM and stocking rates, as well as mean stocking rates, TSDM, fertility, mortality, calving and weaning rates, forage utilization rates, forage intake as a function of forage availability, animal liveweight gains and total methane emissions over the relevant time periods.
We then selected years from this data set to generate 13 time series of 30 years. The baseline scenario included non-dry years only and was only used to estimate herd recovery times after drought events (see section 'Proxies to characterize the herd dynamics2. 7'). The other scenarios included varying numbers of consecutive dry and very dry years ('drought period') which were imposed from year 6. The non-dry years in these other scenarios were the same as in the baseline. Figure  4  shows the list of these 13 scenarios. The 432 mm/year precipitation threshold that differentiated 'nondry' and 'dry' years was relatively consistent with the years considered in the region as drought years for livestock production. Indeed, the 'Queensland 1990s drought  ' (1992-1996)  was associated with precipitations below 437 mm/year in the Wambiana region  (Stehlik, Gray, & Lawrence, 1999)   2007).
Image Conversion to Darter Color Space For all images, RAW files were converted to 16-bit tiff files using the rawpy python API. We converted RAW files to RGB triplets without any spatial interpolation, gamma correction or white-balance to maintain linearity. Images were then converted into a darter colorspace. The generation of the darter colorspace was done by first characterizing the sensitivity functions of our camera, and then using known darter visual sensitivities to generate a mapping from camera space to darter space  55. The sensitivity functions for the camera were estimated using a monochrometer and a calibrated spectrometer, which ensured that each color channel was linear  56. To model darter color vision, we generated a dichromatic model using cone sensitivities peaking at 525nm and 603nm (darters lack a short wavelength sensitive cone class).
Statistical Analysis To ensure that images of species-typical habitat were representative of their class, we pooled images of each habitat class across multiple sites. We then compared the Fourier slope across habitat classes and across darter species (males and females analyzed separately) using ANOVAs. To examine the relationship between the Fourier slope of habitats and that of darter patterns, we used generalized linear mixed models. We computed this model using the R package MCMCglmm  59, 60. Our model predicted the value of the Fourier slope of each individual fish based on the slope of their habitat. Capture site and phylogeny were included as random effects. The phylogenetic tree of the ten studied species was inferred from a previously published molecular phylogeny (accessed via TreeBASE)  30, 61.
Four cases were undecided (i. e. , investigators could not be decided which wound or wound half showed faster reepithelization than the other). Measurements of wound size showed a trend toward accelerated wound healing with Oleogel-S10 but this was not statistically significant. Touch sensitivity, itching, exudation, and efficacy as rated by investigators and patients were comparable for both treatments. These results indicate a potential for faster reepithelialization of wounds in patients with dystrophic EB when treated with Oleogel-S10 but larger studies are needed to confirm the significance of these findings  (Schwieger-Briel et al. , 2017). A global Phase 3 trial of Oleogel-S10 in EB is currently ongoing. Efficacy And Safety of Oleogel S10 in patients with EB (EASE) (NCT03068780; EudraCT No.
ACKNOWLEDGEMENTS The authors would like to thank  Felicity Leigh  and  Nigel Eastmond  of  Eastmond Medicomm Ltd  for medical writing support that was funded by  Amryt Pharmaceuticals DAC. DISCLOSURES A. S. B. , H. O. , D. K. , and C. B. confirm that their contribution to the manuscript is entirely independent of economic, research, or other relations to the sponsor. M. L. L. is an employee of Amryt AG, part of the  Amryt Pharmaceuticals DAC group.
Measurements Raw materials and diets were analyzed for dry matter (AFNOR methods V18-109), N content (ISO 16634-1, Kjeldahl method) and AA content (ISO 13903; analyzed by Ajinomoto Eurolysine SAS laboratory, Amiens, France). Growth performance was recorded throughout the rearing period and calculated for each pen. All birds were weighed individually at day 21 and day 36 after 4 h fasting. Feed intake was recorded per pen from day 21 to day 36. The feed conversion ratio (FCR) was calculated between day 21 and day 36. At day 36, four birds representing the average and the variability of the pen were selected to be slaughtered (32 birds per treatment). They were slaughtered at the experimental processing plant of the experimental poultry unit (PEAT, INRA Nouzilly, France) after 8 h of feed withdrawal.
Statistical analyses All data were analyzed using SAS (SAS Institute Inc. , Cary, NC, USA). The type I error accepted was 5%. The respective effects of levels of dietary Lys and AA were analyzed by twoway ANOVA with the AA × Lys interaction (GLM procedure). Pairwise comparisons of means for each significant effect were performed by Scheffe test using the Lsmeans statement of the GLM procedure. Values were expressed as Lsmeans and SEM. When the AA × Lys interaction was significant, effects of diet were analyzed by one-way ANOVA (GLM procedure) and the respective effects of levels of dietary Lys and AA were also presented as response surfaces (Minitab 16 statistical software). Pearson correlation coefficients were analyzed with the procedure CORR of SAS to assess the relationship between traits.
Acknowledgments The authors thank  Fréderic Mercerand  ( PEAT, INRA, Nouzilly, France ),  Jean-Marc Hallouis ,  Sabine Crochet ,  Thierry Bordeau  and  Estelle Cailleau-Audouin  ( BOA, INRA, Tours University, Nouzilly, France ),  Yvan Primot  and  Marcelle Eudaimon  ( Ajinomoto Eurolysine s. a. s. laboratory, Amiens, France ) for their collaboration in this study. They are also grateful to  Doreen Raine  ( Surrey, UK ) for editing the English language. This study received financial support from  INRA  and  Ajinomoto Eurolysine S. A. S. P. Belloir  is supported in part by  Ajinomoto-Eurolysine S. A. S. Research Grants.
A P35S:GFP::T'NOS construct was also used as a control (Figure  1B ). T'NOS is the 3 UTR of the agrobacterial nopaline synthetase gene. For this construct, a modified NOS terminator (T'NOS) without any putative PUF-binding motif was used (Figure  1A ). The transformed calluses were first selected based on antibiotic resistance, and the presence of the targeted 3 UTR was confirmed by PCR-mediated DNA amplification. The transformed calluses were then transferred to the incubation medium containing different concentrations of sugars ranging from 10 to 200 mM, and fluorescence intensity was assessed using ImageJ software after 8 h incubation. The 3 UTR RhBRC1 -transformed calluses (P35S:GFP::3 UTR RhBRC1 ) were incubated on a medium containing a soluble sugar (sucrose or glucose) for 8 h, and fluorescence strongly decreased as sugar concentrations increased (Figure  2B ).