dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements ERGA Infrastructure: We acknowledge access to the storage resources at  Barcelona Supercomputing Center , which are partially funded from  European Union   H2020-INFRAEOSC-2018-2020  programme through the  DICE  project (Grant Agreement no. 101017207 ), RES ( Spanish Supercomputing Network) ,  INB (Spanish National Bioinformatics Institute). We would like to thank  Alisha Ahamed ,  Josephine Burgin ,  Joana Paupério ,  Jeena Rajan  and  Guy Cochrane  from the  European Nucleotide Archive  (ENA) for their support PhD fellowship  1156622N ), S. P is supported by the  Icelandic Research Council , grant nr. 173908-05 ; S. V is supported by the  Department of Agricultural and Environmental Sciences (DiSAA), University of Milan , both with her PhD scholarship and with the project " SPEED: Species distribution modelling and population genomics to calculate extinction risk in a changing climate", Piano di Sostegno alla Ricerca 2019  ( PSR2019_DIP_014SPIER ), awarded to the team member  Simon Pierce ; J.
H is supported by VR,  Formas  and BGE;S. G is supported by the  Novo Nordisk Foundation  ( NNF20CC0035580  and  NNF210C0069089 ); G. M. H is supported by  University College Dublin Ad Astra  grant; The  Royal Swedish Academy of Sciences  provided funding for the reference genome of Stylops ater to  Johannes Bergsten  (Grant  BS2022-0020 );  Portuguese National Funds  through  FCT (Fundação para a Ciência e a Tecnologia)  support the research contract to  AC [2020. 00823. CEECIND/CP1601/CT0003 ]; this study was partly supported by the  Slovenian Research Agency  through research core funding No. P1-0403  for F. J. ; IRA funded by  Portuguese  funds through  FCT -Fundação para a Ciência e a Tecnologia , I. P. , under the  Norma Transitória   -DL57/2016/CP1375/CT0003 ; A Böhne received support from the  German Research Foundation DFG  (grant numbers  DFG 497674620  and  DFG 492407022 ) and the  Leibniz Association ,  A Böhne  and  R.
Fernandez  were funded by  Horizon Europe  under the  Biodiversity, Circular Economy and Environment  (REA. B. 3); co-funded by the  Swiss State Secretariat for Education, Research and Innovation (SERI)  under contract number  22. 00173 ; and by the  UK Research and Innovation (UKRI)  under the  Department for Business, Energy and Industrial Strategy 's  Horizon Europe Guarantee Scheme ; Z. O. J is supported by  University of Iceland  research fund; P. C. W is supported by the  Academy of Finland  ( 324602 ); C. V would like to thanks  COST  Action  CA 18134  G-BiKE; Sampling and shipping for H. B was funded under  HUNVIPHAB LIFE- project ( LIFE18NAT/HU/000799 );  J. Höglund  would like to thank the  Faculty of Sciences of Uppsala University (Sweden)  for its generous contribution, which guaranteed the inclusion of all the Swedish species in the ERGA pilot project ; RJL was supported by the  Fundação para a Ciência e Tecnologia (FCT)  through a  Transitory Norm  contract [ DL57/2016/CP1440/CT0006 ]; The tissue sample for the European mink has been taken from a male mink in Dordogne (France) in 2006 by  Pascal Fournier  and  Christine Fournier-Chambrillon  ( GREGE , sample collectors), in the framework of the first National Action Plan for the conservation of the European mink, and sent to a collection of cryopreserved cells (managed by  Vitaly Volobouev ) at  MNHN  ( National Museum of Natural History ).
The study of plant-microbe interactions and the characterization of plant-associated microbiota has been the focus of plant researchers in the last decades due to its importance for plant health in natural conditions. Here, I explore the persistent core microbiota associated with different plant species and across different environments by performing a meta-analysis of publicly available datasets. Intra-specific analyses revealed that diverse plant genotypes growing in similar habitats interact with a common set of microbial groups but that some of these core groups are species-or environment-specific. Furthermore, interspecific meta-analysis demonstrates the conservation of seven bacterial orders across diverse photosynthetic organisms, including microalgae, suggesting a conserved capacity for interaction with these core microbes throughout evolutionary history.
Also, it is possible that with evolutionary distance, there may be Intraspecific persistent bacterial and fungal orders across published datasets. a) Bacterial orders that are found across 70% of the samples of a given genotype within each study, with an abundance of at least 0. 05% across the dataset. Symbol sizes represent the average relative abundance across the dataset and are color-coded based on their taxonomic assignment at the phylum level. Symbol shapes represent the microhabitat that was analyzed in each study. The upper panel represents the number of bacterial persistent groups found across different types of approaches (sample number: n = 992 P. virgatum samples in Ref. [22] ; n = 137 H. vulgare samples in Ref. [23] ; n = 379 Zea samples in Ref. [6] ; n = 198 A. thaliana samples in Ref.
[25] ; n = 208 A. thaliana samples in Ref. [4] ; n = 108 Capsella samples in Ref. [25] ). b) Fungal orders that are found across 70% of the samples of a given genotype within each study, with an abundance of at least 0. 05% across the dataset. Symbol sizes represent the average relative abundance across the dataset and are color-coded based on their taxonomic assignment at the phylum level. Symbol shapes represent the microhabitat that was analyzed in each study. The upper panel represents the number of fungal persistent groups found across different types of approaches (sample number: n = 387 Zea samples in Ref. [6] ; n = 216 A. thaliana samples in Ref. [4] ). The core microbiota across the green lineage  Durán 3  an increase and diversification of exudates and anatomical complexes, and more microbial members are capable of associating with these photosynthetic hosts.
Meta-analysis of intraspecific and interspecific overlap of microbial communities For the meta-analysis of host-associated bacterial and fungal communities, data from previous studies were retrieved directly as processed operational taxonomic units or amplicon sequence variants tables from their respective publications (Tables  1  and 2 ). Given that these studies used nonoverlapping sequencing primers, all datasets were combined after aggregating relative abundances at the bacterial order taxonomic level. The persistent and core groups of the host-associated microbiota were determined by identifying bacterial orders Core microbiota across the green lineage. a) Phylogenetic tree of photosynthetic organisms used in this meta-analysis. In shaded gray and green are highlighted the domains to which each species belongs, and the leaves of each domain are collapsed for easier visualization.
Acknowledgements I thank  Fabrice Roux ,  Fabienne Vailleau  and two anonymous reviewers for constructive comments on the manuscript. P. D. is member of the " Laboratoires d'Excellences (LABEX)" TULIP  ( ANR-10-LABX-41 ) and of the " E ´cole Universitaire de Recherche (EUR) "  TULIP-GS  ( ANR-18-EURE-0019 ).
Methods The analyses presented here were performed using data from the Multidomain Alzheimer Prevention Trial (MAPT) (clinicaltrials. gov: NCT00672685). This 3-year placebocontrolled interventional study assessed the effects of isolated multidomain intervention (consisting of cognitive stimulation as well as nutritional and PA counseling), isolated supplementation with omega-3 fatty acids, or the combination of both multidomain intervention and omega-3 supplementation on cognitive trajectories in older adults. 26  Briefly, the MAPT study demonstrated no significant effect of the interventions on cognitive decline, but subgroup analyses indicated that the multidomain intervention slowed down the rate of cognitive decline in individuals who had high dementia risk (based on cardiovascular risk factors-the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) score) and in amyloid-positive participants (based on positron emission tomography scans).
Statistical analyses The characteristics of the participants were computed using data obtained at the 1-year visit of the MAPT (i. e. , the time point when the IF1 concentration was measured). Means and SDs were used for normally distributed continuous variables, while medians with first (Q1) and third (Q3) quartiles were provided for skewed continuous variables. Categorical outcomes were presented as numbers and percentages. The sample was also divided into 4 groups according to the IF1 quartiles in order to provide subject characteristics according to each quartile. The differences between the quartiles were examined using analysis of variance and independent t tests for normally distributed continuous variables. Non-parametric KruskalÀWallis and WilcoxonÀMannÀWhitney tests were used to examine skewed continuous variables, and x 2 tests were performed for categorical variables.
Supplementary longitudinal analyses were performed using the 5-times sit-to-stand test instead of MVPA as the outcome. Since data for this test were available until the 5-year visit of MAPT, the analyses were performed over the entire period from the 1-year to the 5 year-visit. However, since PA data were available only until the 3-year visit of the MAPT, 2 distinct models were performed: one with and one without the use of MVPA as a covariate. For each regression model and at each step of the mediation analyses, the normality and homoscedasticity of the residuals were examined visually, and multicollinearity was checked using the variance inflation factor. For the analyses, a square root transformation was applied to the continuous variables IF1, apoA-I, apoA-II, apoB100, mMVPA, and MVPA in order to obtain a normal distribution of the residuals and to avoid heteroscedasticity.
Moreover, outliers (defined as values below or above 4 SD from the mean) were removed before the analyses, which led to the exclusion of 1 and 4 subjects from the square root-transformed variables IF1 and apoA-II, respectively. The statistical analyses were conducted with IBM SPSS statistics Version 23 (IBM Corp. , Armonk, NY, USA) and R Version 4. 1. 3 (R Foundation for Statistical Computing, Vienna, Austria) software. Analyses of mediation were carried out with SPSS using the PROCESS macro Version 3. 5. 3 from Andrew F. Hayes (https://www. afhayes. com). The analyses were undertaken using an alpha risk of 5%. For the mediation analyses, the significance of the indirect effects was concluded based on the 95% bootstrap confidence intervals rather than on p values, as suggested by Hayes. 39.
Acknowledgments The present work was performed in the context of the  Inspire Program , a research platform supported by grants from the  Region Occitanie/Pyr en ees-M editerran ee  (Grant No. 1901175 ) and the  European Regional Development Fund (ERDF)  (Grant No. MP0022856 ). This study received funding from  la F ed eration Française de Cardiologie" (FFC, Dotation Recherche) ,  Alzheimer Prevention in Occitania and Catalonia  ( APOC Chair of Excellence -Inspire Program ) and  Saint Louis University. The MAPT study was supported by grants from the  G erontopôle of Toulouse , the  French Ministry of Health  ( PHRC 2008 (PHRC , 2009)),  Pierre Fabre Research Institute  (manufacturer of the omega-3 supplement),  ExonHit Therapeutics SA , and  Avid Radiopharmaceuticals, Inc. The.
Human tumor samples Melanoma tumor samples were obtained through the Biological Resource Center of the Lyon Sud Hospital (Hospices Civils de Lyon) and were used with the patient's written informed consent. This study was approved by a regional review board (Comité de Protection des Personnes Ile de France XI, Saint-Germain-en-Laye, France, number 12027) and is registered in ClinicalTrial. gov (MelBase, NCT02828202). 30 cutaneous melanoma patients were used for multi-immunofluorescence analyses. All melanoma biopsies were cutaneous, either primary melanoma or cutaneous metastases (Supplementary Table  1 ).
1B ), except for ZEB2 mRNA which was not modified, consistent with previous reports  (20). We confirmed in the RNA-seq dataset from Tsoi et al. the progressive increase in ZEB1 expression in the NCL and undifferentiated states, while ZEB2 was strongly expressed in the melanocytic state and gradually decreased during dedifferentiation (Supp. Fig. 1A ). Importantly, this switch was reversible, since the withdrawal of TNF promoted the return to baseline expression levels (Supp. Fig. 1B ). In C-09. 10 cells, TNF was combined with TGF in order to ensure an efficient phenotype switching, evidenced by decreased MITF expression (Supp. Fig. 1C ). Drastic upregulation of ZEB1 expression was associated with progressive ZEB2 protein level downregulation upon TNF + TGF treatment (Supp. Fig. 2A-B ).
5D-E ). Interestingly, similarly to TNF + TGF treatment, overexpression of ZEB1 was sufficient to induce decreased activity of MITF TF, as well as increased activity of RELA and FOS/JUN (Fig  5F ). Altogether, these results further support the conclusion that a major part of TNF-mediated transition towards a more invasive/NCSC-like state is regulated by ZEB1. Interestingly, beyond well-described phenotypic markers from Figure  4 , ZEB1 binding peaks were found in other major markers of melanoma cell identity, namely BIRC3, ITGA2 and EGFR, which are up-regulated upon phenotype switching towards the ZEB1 high state as confirmed by RT-qPCR (Supp. Fig. 6B-C ). ZEB1 binding on the promoters of these genes could also be confirmed by ChIP-qPCR (Supp. Fig. 6D ). Finally, in order to analyze the lineage specificity of ZEB1 binding compared to carcinoma models, we performed a comparative analysis with a previously published ZEB1 ChIP-seq dataset performed in the MDA-MB-231 breast cancer cell line  (23).
Single-cell and spatial analyses of ZEB1 intra-tumor heterogeneity in melanoma patient samples To further investigate the correlation between the expression of ZEB1 and markers of melanoma cell states at the single-cell level, we first used publicly available single-cell RNAseq datasets. In the panel of 10 melanoma cell lines from Wouters et al. (37) , including the A375 cell line, ZEB1 was preferentially expressed in mesenchymal-like cells, while ZEB2 was found in melanocyte-like cells (Fig. 6A ). We observed ZEB1 co-expression at the single-cell level with markers of the NCSC or the undifferentiated phenotype, NGFR and SOX9, respectively, and confirmed its antagonistic expression pattern with MITF and SOX10, markers of the melanocytic/proliferative phenotype. In addition, in the scRNA-seq dataset of melanoma PDX tumors from Rambow et al.
Acknowledgments preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The authors would like to thank  Brigitte Manship  for critical reading as well as  Irwin Davidson  lab for helpful discussions. YT was supported by a fellowship from  Ligue Nationale contre le Cancer  and SD by a fellowship from the  Association pour la Recherche contre le Cancer (ARC).
This work was funded by the  Ligue Nationale contre le Cancer (Comité de l'Ain) , the  Lyon Integrated Research Institute in Cancer  ( SIRIC LYriCAN INCa -DGOS-Inserm_12563 ), the  Institut Convergence PLAsCAN  ( ANR-17-CONV-0002 ), the  ERiCAN program of Fondation MSD-Avenir  (Reference  DS-2018-0015 ), the  Institut National contre le Cancer (INCA-DGOS PRTK) , the  Société Française de Dermatologie (SFD) , the association  Melarnaud and Vaincre le Mélanome. MelBase is sponsored by the  French National Cancer Institute (INCa).
RNA libraries were prepared with the TrueSeq poly-A+ kit from Illumina and sequenced on the genomic platform of the CRCL, on an Illumina NovaSeq 6000 sequencing machine with a paired-end protocol (2x75bp, 32Mp reads). Raw sequencing reads were aligned on the human genome (GRCh38) with STAR (v2. 7. 8a), with the annotation of known genes from gencode v37. Gene expression was quantified using Salmon (1. 4. 0) and the annotation of protein-coding genes from gencode v37. Bulk RNA-seq data of melanoma cell lines from Tsoi et al. (29)  was retrieved from GEO, with accession number GSE80829. Single-cell RNAseq data of patient derived xenograft from Rambow et al. (15)  were obtained from GEO with accession number GSE116237. Single-cell RNAseq data of melanoma cell lines from Wouters et al. (37)  were analysed and visualized using Scope (https://scope.
RNA-seq analyses confirmed that C-09. 10 cells display a more melanocytic phenotype than GLO cells, but similar pathways and signatures were consistently altered in this model (Fig. 1Gand Supp. Fig. 3B, D-E). Computational inference of transcription factor (TF) activity, with the VIPER algorithm, confirmed MITF and SOX10 TF decreased activity (Fig 1H & Supp. Fig. 3F). Moreover, the activity of the Activator Protein-1 (AP-1) complex members JUN and FOS, the major regulators of the mesenchymal state (32) , was induced upon TNF treatment in both GLO and C-09. 10 cells, as well as that of the NF-κB subunits (RELA and NFKB1) (Fig1H& Supp. Fig. 3F). Of note, ZEB1 and ZEB2 TF activity could not be reliably assessed based on DoRothEA pancancer database, because of melanoma cell-type specificities.
Amplified fragments were Sangersequenced with F-and R-primers, and, in addition with MF-and MR-primers for Psyr3208 (Genoscreen, France). Geneious version 9. 1. 7 software was used to assemble, align, orientate, and trim sequences according to the reading frame. Sequences of partial CDSs were deposited in Genbank under the accession numbers MW892843-MW892968 and were 825-bp (Psyr3208), 318-bp (Psyr3420) et 309-bp (Psyr4880) long. Genes were amplified in strains whose genome sequence was not available. Homologous sequences retrieved from genome sequences (Table  2 ) were added to the data set.
Genome sequencing and analyses. The genomes of strains P129 2d and P135 2d belonging to the clade 2d were sequenced. Their DNA was extracted using the Wizard Genomic DNA Purification Kit (Promega) and was paired-end sequenced (2 × 150 bp) using the Illumina HiSeq X-Ten at Beijing Genomics Institute (China). Genome assembly was performed with SOAPdenovo version 2. 04, SOAPGapCloser version  1. 12 (Luo et al. 2012) , and Velvet version  1. 2. 02. (Zerbino and Birney 2008). Fasta-formatted assemblies were deposited in NCBI with accession numbers SAMN18647612 and SAMN186476113. Phylogenic position of clade-2d strains was determined by the percentage of shared 15-mers  (Briand et al. 2019 ) on the dataset of 118 genomes (Supplementary Table  1 ). Percentage of shared k-mers and distance matrix were calculated with Ki-S as were dendrograms (https://iris.
angers. inra. fr/galaxypub-cfbp)  (Briand et al. 2019). T3E repertoire of each strain was predicted through tBLASTN search (identity higher than 80% on at least 80% of CDS length) on 138 amino acid sequences of T3Es (Hopsdatabase at http://www. pseudomonas-syringae. org/). Putative frameshift mutations Caroline Lacault 9 were checked by aligning each T3E sequence with the corresponding curated reference sequence with MultAlin (http://multalin. toulouse. inra. fr/multalin/)  (Corpet 1988).
Caroline Lacault 10 SkIf_with_DSK identifies specific k-mers within a group of genome sequences (in-group) that are absent in the other genome sequences (out-group). It also provides their precise locations on a reference genome and uses the positions to concatenate the overlapping k-mers into long-mers  (Denancé et al. 2019). A k-mer size of 22 was used to search for specific sequences using the dataset of 118 genome sequences (Supplementary Table  1 ). Specific long-mers were searched for in clusters 2ba-A, 2ba-B, 2ba-C, 2a-D and 2a-E, in larger groups 2ba-ABC and 2a-DE encompassing the clusters of VCZ strains, and in clades 2b and 2d (Figure  2  and Supplementary Table  1 ). Different tree nodes were tested to isolate long-mers specific of clade-2b strains including or not pathovar pisi or the clade 2ba (Figure  2 ).
Caroline Lacault 11 Specificity of primers and associated probes was tested in silico using PrimerSearch (Val Curwen, Human Genome Mapping Project, Cambridge, UK), first, on our collection of 121 genomic sequences, and second, on the 194,438 whole Genome Shotgun (WGS) sequences of Bacteria and Archae available in the NCBI database (03/2019 release). When necessary, phylogenetic position of strains was checked using KISonWGS  (Briand et al. 2020)  (https://iris. angers. inra. fr/galaxypub-cfbp). KISonWGS identifies WGS neighbor genome sequences of query input genome file. For multiplex qPCRs, sets of primers and probe and combinations of primers and probes were tested on the genomes of P99 2ba-A , P12857 2ba-B , ZUM3584 2ba-C , P77 2a-D , P66 2a-E , 13-139B 2a-F , P108 2b and P135 2d using AmplifX version 2.
Several of these cross reactions involved strains with in-between genotypes, revealing a greater diversity than expected within 2ba clade. For the test targeting 2ba-A cluster, strain 1188-1 (SAMN03976479) isolated from zucchini, classified in clade 2b on the basis of its whole genome sequence, was positive in silico with the 2ba-A test (Table  4 ). This genome was positive for other PCR tests targeting cluster 2ba-A such as 2ba-ABC, 4Ba, and Rpt2 (targeting avrRpt2) PCR tests and matched also primers and probe for clade 2b (Supplementary Table  2 ). Similarly, positive reactions with 2ba-A and Rpt2 primers were observed in silico or in vitro for three strains belonging to clusters 2ba-B and 2ba-C2 (Supplementary Table  2  and Table 4 ). For the PCR test dedicated to cluster 2ba-B strains, three cross-reactions were observed in silico for P.
coronafaciens genomes (PG4, Table  4 ), that were confirmed in vitro by a positive signal for the type strain of P. coronafaciens (Table  1 ). For cluster 2ba-C, primers annealed with 4 mismatches in silico with Caroline Lacault 15 a strain of clade 2a and gave a band at the wrong size in vitro for one clade-2b strain. Two genomes of P. coronafaciens perfectly matched with 2a-D primers. Primers for group 2ba-ABC annealed in silico with mismatches on two strains, of which strain 1188-1. Primers for group 2a-DE annealed the two cluster 2a-F genome sequences with three mismatches. Concerning 2b* PCR test, the clade-2b genome sequence of strain ICMP 4917 (SAMN03976350) did not match in silico. Numerous in silico unperfect matches were obtained for primers and probe targeting clade 2b* on non-targeted genomes but they were not confirmed in vitro on representative strains.
Genome sequence of strain ICMP 4996 (SAMN03976403), named P. coronafaciens pv. striafaciens in the NCBI database, was classified in the 2b clade according to our KISonWGS assignation and to Dillon and colleagues  (Dillon et al. 2019b)  and not in PG4 as expected by its taxonomic assignation. This genomic sequence perfectly matched the 2b* primers and probe. This result was confirmed in vitro with the synonymous strain CFBP 1750 that gave a positive signal with this test. This particular case was considered a problem of misclassification and not a real cross reaction. Primers and probe dedicated to clade-2d strains gave one cross reaction in silico with the clade-2b strain 3023 (SAMN05861187). In silico and in vitro testing 4Ba qPCR test confirmed that this test was 100% inclusive of VCZ strains but detected also some other PG2 strains despite mismatches in the primers (Table  1  and Supplementary Table 2 ).