dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors would like to thank  Mikhail Klimov  at the  Material Characterization Facility (MCF)  at  UCF  for conducting the SIMS measurements. The authors gratefully acknowledge for financial support:  IdEx Bordeaux  (Cluster of Excellence LAPHIA and the allocated grant referred to as  ANR-10-IDEX-03-03 ) and the  CNRS  project  EMERGENCE @INC2019. This project has received funding from the  European Union 's  Horizon 202 research program  under the  Marie Skłodowska-Curie  grant agreement no. 823941  (FUNGLASS).
Acknowledgements We acknowledge funding from the  European Commission  through the  Marie Sklodowska-Curie  project  ULTIMATE  ( GA-813036 ), the  Agence Nationale de la Recherche  through the  Labex projects CSC  ( ANR-10-LABX-0026 CSC ) and  NIE  ( ANR-11-LABX-0058 NIE ) within the  Investissement d'Avenir program  ( ANR-10-120 IDEX-0002-02 ), the  International Center for Frontier Research in Chemistry (icFRC) , the  Chinese Scholarship Council ,  S. Ippolito ,  F. Urban ,  N. Turetta  for the helpful discussions and  S. Gullace  for the graphical suggestions. Keywords: covalent organic frameworks • imines • dynamic covalent chemistry • post-synthetic modification.
However, it should be noted that some phases (Ettringite, C-S-H) start dehydroxylation at a lower temperature than 105 • C  [11]. In addition, we chose to compare the experimental quantities of Ca(OH) 2 to evaluate the methods' relevance in our study because Ca(OH) 2 is a relatively easy data set to determine thanks to TGA analysis. The SEM-BSE image analysis presents the volume of Ca(OH) 2 over time of hydration. We convert from volume fraction to mass fraction using a Ca(OH) 2 density of 2. 24 (g/cm 3 ). The Ca(OH) 2 / initial cement mass ratio measured by the SEM-BSE images analysis method is calculated according to the following equation (Eq. (  22 )):   3. Cement density: 3. 15 g/cm 3 (Table  5 ). The result of three methods is presented in the Table  15. Ca(OH)2 (t) mass initial cement mass = V Ca(OH)2 (t) V anhydrous cement (t = 0) * 2.
However, it also confirms that neat synthesis protocols and control experiments are mandatory when ligand-capped QDs are operated at the industrial level. Besides, in these extreme conditions, 2C-SFG spectroscopy revealed its potential to be used as an analytical probe for biosensing applications at the nanoscale level. Such an optical technique could therefore be used in the future for any type of sensor based on metal, semiconductor, or hybrid nanocrystals. Funding: Research leading to these results has received funding from the International Scientific Cooperation Program of the CNRS (Centre National de la Recherche Scientifique) under Grant agreement number PICS07339.
Two samples have been subjected to Cu oxidation by annealing in air after growth of graphene ("with post ox-sample1" and "with post ox-sample2"); and two additional samples without any post-growth treatment ("Pristine-sample1" and "Pristine-sample2") were measured. The Raman analysis alone is not sufficient to identify the type of doping (n or p). The literature suggests that graphene transferred on SiO 2 is p-doped  [32] , and hence, it is reasonable to assume that our samples are p-doped as well. Raman measurements have been obtained on different zones for each sample. The data (illustrated in Figure  6b ) shows an evolution close to the orange line which represents a prediction of (ν G , ν 2D ) for strain-free graphene with p doping in the range 0 < p < 4 × 10 12 cm -2. Moreover, it can be seen that the graphene biaxial strain is almost completely relaxed after transfer onto Si/SiO 2 as shown in Figure  6b : the residual strain stands between -0.
The Sanger sequencing reactions were performed by MWG Eurofin Operon (Ebersberg, Germany) using the primer 907r. All the sequences were identified using the nucleotide BLAST program  (Altschul, 1997). Sequence alignment and distance tree were constructed using SeaView (version 4. 7)  (Gouy et al. , 2010)  and by using neighbor-joining algorithms with the Kimura two-parameter correction. Distance trees were constructed and bootstrap values were obtained using 1,000 replicates. Trees were generated using the Dendroscope 3 software (version 3. 6. 3) (Huson and Scornavacca, 2012). The 16S rRNA Sanger sequences generated for this study were submitted to the Genbank database of NCBI under the accession numbers MN193104 -MN193411.
, 2011). The sample multiplexing, the paired-end Illumina sequencing using 2x250 bp Miseq v3 and the de-multiplexing of the sequences were performed at GeT-PlaGe (Genotoul, Toulouse, France) according to the manufacturer's instructions. Raw sequences processing was performed using FROGS (Find Rapidly OTU with Galaxy Solution) pipeline  (Escudié et al. , 2018). Paired sequences were merged into contigs with flash  (Magoc and Salzberg, 2011) , cleaned with cutadapt  (Martin, 2011)  and chimeras were removed with VSEARCH  (Rognes et al. , 2016). The clustering to generate Operational Taxonomic Units (OTU) was then performed with SWARM algorithm  (Mahé et al. , 2014)  using a local clustering threshold (97% similarity) and the taxonomic affiliation of each OTU was based on the reference databases NCBI Blast+ on SILVA123 16S  (Camacho et al.
, 2009 , Quast et al. , 2013). Finally, a table presenting the number of 16S rRNA sequences assigned to each OTU as well as their taxonomic affiliation was generated. OTUs belonging to Eukaryota or Archaea, chloroplasts or mitochondria were discarded as well as contaminant OTUs generated by the extraction and amplification steps. All the singletons were removed for the OTUs analyses. Finally, the number of sequences per sample ranged from 17,806 to 39,132 giving a total of 334,380 sequences and 3,079 OTUs. OTU analyses were then performed using packages in R with a random subsampling to normalize each sample with the smallest number of sequences. The bacterial richness and alphadiversity (Chao1, ACE, Shannon and inverse Simpson indexes) were calculated based on OTU relative abundance. The Illumina 16S rRNA sequences generated for this study were submitted to the Sequence Read Archive (SRA) of NCBI under the accession number PRJNA55031.
To determine both sequence homology and the relative environmental representativeness of the bacterial isolates recovered in our study, the Sanger 16S rRNA gene sequences were compared to the Illumina 16S rRNA gene sequences using the Basic Local Alignment Search Tool (BLAST) algorithm  (Altschul et al. , 1990). The Illumina 16S rRNA gene sequences of each compartment were used as database and an alignment of the Sanger 16S rRNA gene sequences was performed with NCBI-Blast+ using an e-value cutoff of 1 e-5. This analysis was done on the 253 bp overlapping between the Sanger and Illumina 16S rRNA gene sequences.
Statistical analyses All statistical analyses were performed using R 3. 2. 3 software (R Core  Team, 2015). The effect of the compartment (i. e. , BS vs HW vs SW) was tested on the chemistry data and the bioassay data using an analysis of variance (one-way ANOVA, P<0. 05), followed by a Tukey test. Wood density differences between the two oak wood compartments (SW and HW) was determined by a t-test. For the culture-dependent approaches, a Chi 2 test (P<0. 05) analysis was performed to determine whether the frequency of distribution of the bacterial isolates according to their efficacy depended on their ecological origin. For the Illumina 16S rRNA gene sequences and the related OTUs, the analyses were performed using R packages: phyloseq (McMurdie and Holmes, 2013), ape  (Paradis et al. , 2004)  and vegan  (Oksanen et al.
, 2007). The data were visualized using ggplot 2  (Wickham, 2009). The distribution of the bacterial communities according to their compartments was analyzed by performing multidimensional scaling (MDS) ordination using Bray Curtis matrix distance. Permutational multivariate analysis of variance (PERMANOVA) based on Bray-Curtis distances with 999 permutations were performed on the OTU table using the vegan package and the Adonis command. Analysis of variance and subsequent post-hoc Tukey's tests to compare taxonomic and functional differences between the compartments were also performed. Relative abundance values at all taxonomic levels (phylum, class, order, family, genus, OTU) were compared for taxa or OTUs presenting a minimum of 100 sequences. These values were transformed using the arcsine square root to achieve a normal distribution.
Comparison of the Sanger and Illumina 16S RNA gene sequences This analysis highlighted that all the 308 bacterial isolates of our collection had a minimum of 97% of sequence homology with at least one OTU of the Illumina sequence dataset. When the highest homology was considered, this analysis revealed that the bacterial isolates corresponded to 65 OTUs identified in the Illumina dataset. These OTUs represented 55. 4% of the total number of Illumina 16S rRNA sequences. Interestingly, the most represented bacterial isolates in our collection (at the genus level) were also among the dominant in the OTUs (Rank in the collection / rank in the OTU table; Paraburkholderia (1/1), Acidisoma (2/5), Dyella (3/12), Acidocella (6/4) and more distantly Pseudomonas (7/114) (data not shown).
Acknowledgments This work was supported by the Laboratory of Excellence Arbre (ANR-11-LABX-0002-01; DivBacto project) and by the EFABA project (SF 4242; Al-16-3). The UMR1136 is supported by the French Agency through the Laboratory of Excellence Arbre (ANR-11-LABX-0002-01). We would like also to thank A. Deveau for her help concerning the analysis of the Illumina Miseq 16S rRNA sequences. Picture of an oak disc after 9 months of in situ decay (T9 months) showing the side in direct contact with the soil. C. Mean percentage of the penetration depth for the sapwood (SW) and heartwood (HW) compartments assessed using a Pilodyn penetrometer at T0 (n=3) and T3, T6 and T9 months (n=20 per time point). Significant differences between the two wood compartments for each time point are presented using a star (P<0.
Bioinformatic Analyses Samples from Madagascar, Mayotte and Reunion: Following demultiplexing and quality trimming, reads were assembled into contig using CLC Genomic Workbench 8. 5. 1 and following versions. Contigs were annotated by BLASTx analysis against the GenBank protein database. Contigs were then manually assembled into scaffolds, which were consolidated and extended by several rounds of mapping of reads to yield the finalized scaffolds sequences. For two of the isolates (RE-Ljv and MY-Ren), reads corresponding to deletion events generating defective molecules were identified during this assembly process and scaffolds corresponding to these DI RNAs were therefore also reconstructed. Samples from DR Congo: Sequence analyses were done using the Geneious 11. 1. 3 environment (www. geneious.
com and embedded plugins). Data were submitted to a preprocessing step consisting of setting paired reads, and trimming adaptor sequences and low-quality reads (by BBDUK). Unique sequences were generated as clean reads by merging paired reads (by BBMerge) and removing duplicate reads (Dedupe). SPADES was used for de novo assembly. Reconstructed contigs were screened against the Refseq viral database retrieved from NCBI (12 October 2018) using BLASTn and BLASTx searches and annotated through tBLASTx. Viral contigs were further analyzed directly on the NCBI site using a BLASTn and BLASTx search with standard parameters. Identification of functional gene domains for all samples was done by submitting predicted open reading frames (ORFs) directly on the NCBI's conserved domain search tool (https://www.
ncbi. nlm. nih. gov/Structure/cdd/wrpsb. cgi) (accessed from October to December 2018). Multiple sequence alignments were built with ClustalW embedded in Mega X. Maximum likelihood phylogenetic trees were reconstructed in Mega X using the GTR+GI model for the alignment of nucleotide sequences and a Poisson model with uniform distribution for amino acid sequence alignments. Bootstrap analysis (100 replicates) was performed in order to evaluate the stability and significance of branches. Phylogenetic trees of amino acid sequences were reconstructed using only isolates for which the amino acid sequence of the analyzed protein was complete or nearly complete. Putative recombination events were detected and evaluated using the RDP4 program (version 4. 99)  [19]  and a ClustalW-built multiple alignment of the complete genome sequences.
Identification of Closteroviridae Members in Cassava Thirteen contigs or scaffolds of more than 10 kilobases of Closteroviridae isolates could be reconstructed using the sequencing reads from the seven analyzed landraces (Table  4 ). The lengths of the contigs, which represent large parts of the corresponding genomes, ranged from 10,417 to 13,770 nucleotides (nt). Some of the analyzed plants contained multiple contigs corresponding to different isolates (Table  4 ). Thorough screening of these reconstructed contigs against viral reference databases revealed nucleotide and amino acid sequence homologies with members of the family Closteroviridae and, in particular, with the genus Ampelovirus. In addition to these previously unknown viruses, the results further indicated the presence of CBSVs and/or CMGs in three cassava samples (Table  1 ).
It has been shown that downstream of the coat protein, some members of the family Closteroviridae have a variable number of ORFs encoding accessory proteins, some of which may have functional conserved domain  [24] , while others show no or only very limited identity to any other proteins. The translated amino acid sequences of the protein encoded by the ORF6 have shown similarity with the p24 protein of the pineapple mealybug wilt-associated virus-1 (25. 1%) and the minor coat protein (CPd) of the grapevine leafroll-associated virus-5 (20. 8%) from the TrEMBL database of UniProt. This suggests that, although they share <20% identity with their respective, the proteins coded by the ORF6 could be considered as minor coat proteins. This ORF6 overlaps partially with the 3 -proximal region of ORF5.
All of the isolates sequenced share the same genome organization, although the contigs obtained for the isolates MG-Mia-403 and MG-Mian-2-2 were incomplete, missing ORF5 and ORF6. The reads belonging to four defective RNA (D-RNAs) molecules were identified (Figure  1 ). Three of them were detected in the long Java accession (RE-Ljv) originating from the Reunion island (two for MEaV-1 (RE-Ljv-D-RNA-1 and RE-Ljv-D-RNA-2, accession numbers MW306827 and MW306828, respectively), one for MEaV-2 (RE-Ljv-D-RNA-3, accession number MW306829) and the remaining one in the Menatana accession originating from Madagascar (MG-Men-D-RNA-4 belonging to MEaV-2, accession number MW306830)). The deleted zones cover different genome regions and consist of most of the ORF5 and the ORF6 for the RE-Ljv-D-RNA-1, most of ORF3, ORF4, ORF5 and the start of ORF6 for the RE-Ljv-D-RNA-2, and most of the ORF3 and ORF4 for the RE-Ljv-D-RNA-3.
Fit ancestral data only Because the ancestral datasets do not have replicate evolution popultions we need to take care in applying the "random effects" of replicate population. Even coding them as having a single replicate population poses a problem, as the binomial parameter will be the sum of the strain intercept and the inferred replicate population effect. If we use the whole dataset to do this, then the SD of the replicate pop effect comes from the whole dataset and gives a false view of way more variance in the strains. We can get around this by fitting the ancestral data separately and then later combining the posterior samples for our plotting and analysis. This works because our full model has the full combinatorial effect of strainXtreatmentXassay time. Ancestral Model: Counts of sporulated cells (out of total cells counted) are binomially distrubted with a mean value that depends on the strain type by time of the assay (2.
Bacillus subtilis PTA-271 Bacillus subtilis PTA-271 (GenBank Nucleotide EMBL Accession No. AM293677 for 16S rRNA and DDBJ/ENA/GenBank Accession No. JACERQ000000000 for the whole genome) was isolated in 2001 from the rhizosphere of healthy Chardonnay grapevines (V. vinifera L. cv. Chardonnay) from a vineyard located in Champagne (Marne, France)  (Trotel-Aziz et al. , 2008; Leal et al. , 2021). Bacterial growth started by adding 100 µl of glycerol stock suspension to sterile Luria Bertani (LB) medium and incubating at 28 • C with agitation (100 rpm). Experiments were performed when the bacterial culture is at the exponential growth phase. After centrifugation (5,000 g, 10 min), the pellet was washed once with a sterile 10 mM MgSO 4 medium and resuspended in a same MgSO 4 medium. Bacterial density was measured by spectrophotometry at 450 and 650 nm, and the mean density was adjusted with a sterile MgSO 4 medium before treatment according to  Trotel-Aziz et al.
Controls containing one single isolate (Bs PTA-271, Ta SC1, or Np-Bt67) were also made, either on the side of the plate or at the center. All plates were incubated in the dark at 28 • C for at least 11 days and photographed daily. Antagonistic effect was characterized by an inhibition zone around the BCA and/or the pathogen. Since the first kind of confrontation (A) added no more information compared to the others (B and C), it was not shown in this study. The experiment was conducted twice with three replicate plates per treatment, and the area occupied by each microorganism was measured daily using ImageJ software  (Rueden et al. , 2017) , based on a reference distance common to all images.
First-strand cDNA was synthesized from 150 ng of total RNA using the Verso cDNA synthesis kit (Thermo Fisher Scientific, Inc. , Waltham, MA, United States). Polymerase chain reaction (PCR) conditions were the ones described by  Gruau et al. (2015). Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed with Absolute Blue qPCR SYBR Green ROX Mix according to manufacturer instructions (Thermo Fisher Scientific, Inc. , Waltham, MA, United States), in a BioRad C1000 thermocycler using the Bio-Rad manager software CFX96 Real-Time PCR (BioRad, Hercules, CA, United States). A set of six defense-related genes, selected for their responsiveness to pathogen or priming state induced by beneficial microorganisms  (Trotel-Aziz et al. , 2019) , was tracked by qRT-PCR using specific primers (Table  1 ).
Integration of the formula was performed by the CFX Manager 3. 1 software (Bio-Rad). Although the genes analyzed were considered significantly up-or downregulated when changes in their expression were >2-fold or <0. 5-fold, respectively, we still performed a statistical analysis. Control samples for the rootlings model are cDNA from leaves of rootlings untreated with BCA and inoculated with sterile PDA plugs (1× expression level).
Statistical Analysis Data of canker area and length of external and internal necrosis of the stems were obtained by the analysis of photos using ImageJ software  (Rueden et al. , 2017). Statistical analyses were carried out using all the vines of three replicates among five for each modality with RStudio software  (Horton and Kleinman, 2015). For modality significance, mean values were compared by Tukey's test (p < 0. 05). Results of confrontation tests are from one representative repetition out of two showing the same trends. Statistical analyses were carried out using the SigmaStat 3. 5 software. For treatment effect, mean values were compared by Tukey's test (p < 0. 05). Results of gene expression by qRT-PCR analysis correspond to means ± SEM deviation from three representative repetitions out of five showing the same trends.
0 transferase PAL Phenylalanine XM_003635637 1 TCCTCCCGGAAAACAGCTG TCCTCCAAATGCCTCAAATCA 60 101 92. 9 ammonia lyase STS Stilbene synthase NM_001281117 1 AGGAAGCAGCATTGAAGGCTC TGCACCAGGCATTTCTACACC 60 101 94. 3 1 NCBI accession number.
Sample size: n = 44. Comparison of microbial community composition across compartments. The comparison of microbial community composition across compartments of the sequence soil-phyllosphere-teat-milk was performed at the farm network level based on genera relative abundance data, farms being considered as replicates. Microbial communities of each compartment in the sequence soil-phyllosphere-teat-milk were compared to each other according to their composition and their richness in terms of prokaryotic and fungal genera. Finally, co-occurrence of genera between the compartments of the sequence soil-phyllosphere-teat-milk was evaluated by merging lists of observed genera per compartment among farms. Nevertheless, information on the frequency at which genera co-occurred at the farm level are also provided (Supplementary Data 2).
Prokaryotic and fungal communities across farm compartments. Microbial communities were compared for their composition (i. e. relative abundance) at the genus level across the four farm compartments of the sequence by means of a Non-Metric Multidimensional Scaling (NMDS) approach. Mean relative abundance of observed genera per compartment (soil, phyllosphere, cow-teat, milk) are provided in Supplementary Data 1. Results are presented in Fig. 1  in which the four farm compartments are compared for their prokaryotic or fungal community composition (Fig. 1A ,B, respectively). Prokaryotic communities were discriminated from one another according to the farm compartment (Fig. 1A ). According to centroids position, prokaryotic communities from soil and phyllosphere were discriminated from those of milk and cow-teat along NMDS1 axis.
Farm network and sampling design. A farm network was constituted based on volunteer farms across the PDO Comté cheese area, the most important PDO cheese in France by its tonnage. This network was constituted of 44 farms distributed all along the French Jura Mountains across an elevation gradient ranging from 328 to 1238 m a. s. l. (Fig. 4A, B ) with warm temperate climates at the lowest elevation to boreal climates at the highest elevations  51, 52. The maps presented in Fig. 4A, B  were generated by the authors under QGIS 3. 12 (https:// www. qgis. org)  53. Background in each map is based respectively on administrative limits of countries (https:// ec. europa. eu/ euros tat/ fr/ web/ gisco/ geoda ta/ refer ence-data/ admin istra tive-units-stati stical-units/ count ries; Fig. 4A ) or RGE Alti 75 m database (https:// geose rvices.
ign. fr/ rgeal ti; Fig. 4B ), both databases being open access. The area of the French Jura Mountains is characterized by high soil variability with a predominance of cambisols and a relatively high plant diversity in permanent grasslands. In each farm, four compartments were considered: grassland soil, grassland phyllosphere, cow-teat surface and milk. For this, each farm gave an individual permission for sample collection. First, a parcel of permanent grassland grazed by dairy cows was selected. Within this parcel, a sampling plot of 60 m × 2 m was delimited, located on the flattest area of the parcel far from its margin and georeferenced. Within this sampling plot, two parallel series of five sub-plots (area: 0. 25 m 2 ) were distributed every 10 m to account for grassland variability (Fig.
First, the 16S and 18S raw reads (15 881 872 and 15 723 864 raw reads; respectively) were sorted according to each sample using multiplex identifiers. Low quality reads were then deleted based on their length (less than 350-bp for 16S reads and less than 300-bp for 18S reads), their number of ambiguities and their primer(s) sequence(s). Microbial data are accessible on EBI (PRJEB47150). Then, a PERL program was then applied for rigorous dereplication (i. e. clustering of strictly identical sequences). Dereplicated reads were aligned using Infernal alignment  60  and the number of sequences per sample was normalized (i. e. 10,000 high-quality reads for each sample) by random selection to allow efficient comparison of the data sets and avoid biased community comparisons. Nevertheless, two samples had only 3746 and 9379 high-quality reads and therefore, all high-quality reads were kept for further analyses.