dataesr/scientific-paragraphs-categorization huggingface dataset:
A 323. 5 kb sequence was identified within a 6987 kb contig of Anso77 (Data S2), while a 347. 5 kb sequence was identified within a 6871 kb contig of Doublon (Data S2), and both genomes were obtained by long-read assembly (Methods S1). For the four other lines we retrieved M5-M4 sequences of 337. 6 and 376. 7 kb (Data S2), from public databases. M5-M4 sequences in PI 161375, Anso77, Doublon, HS, and Harukei-3 were fully syntenic, with a subtelomeric region of chromosome 5 in DHL92 but with the opposite arm of chromosome 5 in Payzawat (Fig. S2 ), suggesting pericentric inversion between DHL92 and Payzawat lines. Then we checked the long-read coverage at the putative inversion breakpoints. For Payzawat, no long reads overlapped the breakpoints (along 300 bp) and conversely for DHL92 many long reads overlapped the breakpoints.
We investigated microsynteny within and between the seven M5-M4 regions. Dot plots highlighted several duplications within each M5-M4 region except DHL92 (Fig. S3-A ) with small palindromic sequences in most of them, thus suggesting that repeat elements were present. We designed six markers in the M5-M4 region of PI 161375 (Fig. S1 ) and located them by alignment (blastn) in the seven melon lines (Data S1)-they mapped in the same order in all lines. Syntenic analyses carried with DHL92 as reference, actually revealed different indels between the M5-M4 regions (Fig. S3-B ). All accessions shared large syntenic blocks downstream M5 (almost 60 kb) and upstream M4 (about 100 kb). The most compact M5-M4 region was in PI 161375, and remarkably large insertions occurred in HS, DHL92, and Anso77. DHL92 was derived from a cross between Piel de Sapo and PI 161375-because of the differences we observed in the M5-M4 region between DHL92 and PI 161375, we concluded that the M5-M4 region in DHL92 corresponded to the M5-M4 region in Piel de Sapo.
The sequences were obtained from public databases for Cucumis melo DHL92 (https://www. melonomics. net/), Payzawat, Harukei-3, HS, and Cucumis sativus, Citrullus lanatus, Benincasa hispida (http://cucurbitgenomics. org/), and Momordica charantia. In the seven melon lines, three genetic markers, i. e. , V432, V681, and M7, and three specific markers, i. e. , Z5182, Z5184, and Z5257, were positioned. The colored boxes correspond to the main collinear blocks shown in Fig. S3  melon lines. These Vat-1 contained three, four, five, or seven R65aa motifs in the LRR2 part. We called the second Vat homologs Vat2, located 77. 5-137. 4 kb from M5 and they contained one, two, three, or seven R65aa motifs in the LRR2 part. We kept this Vatx nomenclature for all Vat homologs identified on that strand. They were located within the first 188 kb of the M5-M4 regions.
Downstream of the VatRev locus, up to M4, the region also exhibited highly conserved gene organization, with five genes (Fig. 1 ). The annotations and positions for all genes in the M5-M4 region are presented in Data S3 and S4 and the transcripts are presented in Data S2. In order to investigate the Vat cluster organization in the cucurbit family, we sought to retrieve the M5-M4 region in genomes available in public databases. We focused on seven genomes obtained from long-read sequences of other cucurbit species: Cucumis sativus cv 9930 and Gy14 (n = 7), Citrullus lanatus cv 97103 (n = 11), Benincasa hispida cv B227 (n = 12), Cucurbita argyrosperma subsp. argyrosperma (n = 20), Luffa cylindrica (n = 23), and Momordica charantia cv Dali 11 (n = 11). We searched for the highly conserved genes identified on both extremities of the M5-M4 region in melon (STK, CGN, ERAD-associated E3 ubiquitin-protein ligase, 50S ribosomal protein L18, manganese-transporting ATPase, vesicle-associated protein 2-2) and the first exon of Vat-1, all from PI 161375, in the full genome of each cucurbit (Data S5).
Unraveling SNPs in Vat CDSs of 21 melon accessions We gathered 44 CDSs to investigate the sequence diversity of the Vat homologs. First CDSs from the 19 Vatx and VatRev genes identified in the clusters described above for the five melon lines. We obtained 25 additional CDSs from 16 other melon lines (Methods S2 and Data S9). Overall, the three genetic groups of melon identified by Bayesian clustering were represented among the 21 accessions (Table  S3 ). The 44 CDSs had 1 to 7 R65aa motifs in LRR2. Three parts, pre-LRR2/LRR2/post LRR2, were independently aligned (Fig. 4 ), and then the phylogeny was reconstructed. The phylogenetic tree highlighted strong differentiation between the Vat homologs with a single R65aa motif, which have a common ancestral gene, and all others. Homologs with a single R65aa motif had a 522-525 bp insertion at the end of the LRR1 part compared to other Vat homologs (Fig.
We built virtual CDSs without any R65aa parts to facilitate   1. The MegaX software suite  43  was then used to infer the evolutionary histories. The percentage of trees in which the associated CDSs clustered is shown next to the branches (500 replications). The tree is drawn to scale, with branch lengths measured according to the number of substitutions per site breakpoint detection in LRR2 (Fig. 5 ). If unequal crossover was the main process involved in inflating the R65aa motif, then we would expect to obtain evidence of a breakpoint at the junction between LRR1 and LRR3 parts. Among the 39 CDS, we used GARD to analyze the alignment of 31 virtual polymorphic CDS with the 2442 bp pre-LRR2 part and 1212 bp post-LRR2 part. The algorithm revealed up to 10 recombination breakpoints among 548 potential breakpoints, with a median distance of 359 bp.
The baseline indicated the geographical origin of the accession. The upper line gives information obtained from amplicons of the LRR2 domain: the number of digits gives an estimate of the number of homologs in the accession, each digit gives the number of R65aa estimated in each homolog. Twenty SSRs distributed over the 12 chromosomes were amplified and their diversity analyzed by Bayesian clustering  26. The allele size at the eight microsatellite loci and probabilities of assignation at the three genetic clusters are given in the Table  S3  annotated as repetitive sequences  14. Automatic annotation of Vat-related sequences in C. lanatus exemplified this problem: in both assemblies in public databases, cv Charleston gray and 97103, the genomic sequences were 100% identical but automatic annotation identified either one or two genes, but none complete Vat-related sequence.
B The MegaX software suite  43  was then used to infer the evolutionary histories. The percentage of trees in which the associated CDSs clustered is shown next to the branches (500 replications). The tree is drawn to scale, with branch lengths measured according to the number of substitutions per site chromosome, R genes should subsequently be subject to transposition and clusterization. According to that scheme, a Vat-related gene should be present in a cucurbit protochromosome. In an older cucurbit, i. e. , M. charantia that diverged from other lineages more than 50 mya (Fig. 6 ), we spotted two sequences related to the first exon of Vat between an STK and a manganese-transporting ATPase followed by a vesicleassociated protein. The presence of these two sequences in M. charantia suggested that a Vat-related gene was present in the ancestral cucurbit older than 60 my, lost in Luffa and Cucurbita lineages but conserved in the Benincasae lineage.
Characteristics of the melon accessions Eighty-six melon lines were used and are listed in Table  S3  with their geographic origins and botanical groups. Genomic DNA was isolated from fresh young leaves using the DNeasy Plant Mini Kit (QIAGEN, www. qiagen. com). Twenty microsatellite loci distributed in the 12 linkage groups of melon  25  were amplified at the Gentyane platform and the allele sizes were inferred by GeneMapper v3. 7 software (APPLIED BIOSYSTEMS, Foster City, California, USA). The lines were assigned to genetic clusters by Bayesian clustering  26. For 1-10 clusters, we compared 10 replicate runs (admixture model with a burn-in of 250,000 iterations and a subsequent Markov chain of 500,000 iterations) and, according to the Evanno method  27  , the most likely number of genetic clusters was three.
Retrieving and annotating the genomic region spanning the Vat cluster in cucurbits We retrieved nucleic sequences between the M5-M4 markers from the Anso77 and Doublon genome assemblies we produced, and from public databases for DHL92, Payzawat, Harukei-3, and HS genomes (FTP1, FTP2, FTP3, FTP4)  17, [28] [29] [30]. To that end, we used informations from PI 161375: eight markers (M5, Z5182, V432, V681, Z5184, M7, Z5257, M4), exon 1 sequence from Vat-1 and a set of six gene sequences (STK, CGN, ERAD-associated E3 ubiquitin-protein ligase, 50S ribosomal protein L18, manganese-transporting ATPase, vesicle-associated protein 2-2). Using blastn (NOBLAST version 2. 1, blastall with E-value < 1E10 -5 ) we examined sequences with a percentage score, i. e. , either higher than 30 queries or a target alignment, and an identity of > 40  31.
Moreover, nucleic sequence sets were mapped against the genome assemblies using the Minimap2 alignment program for genomic DNA  32. According to the analyses conducted for C. melo, we used the same set of sequences to search similar regions in public genomes of Cucumis sativus cv 9930 and Gy14 (FTP5, FTP6)  33  , Citrullus lanatus cv 97103 (FTP7)  34  , Benincasa hispida cv B227 (FTP8)  35  , Cucurbita argyrosperma (FTP9)  36  , Luffa cylindrica (FTP10)  37  , and Momordica charantia (FTP11)  38. Mapping and BLAST parameters were the same as in the previous step. Genome assemblies from public databases, annotation sets, and fasta files for protein and cDNA were downloaded from the Genbank NIH genetic sequence database, Melonet DB (https:// melonet-db. dna. affrc. go. jp) and from the International Cucurbits Genomics Initiative (ICUGI) server CuGenDB (http://cucurbitgenomics.
org/). We retrieved genomic sequences spanning all or at least some of these genes. The genomic sequences were exported to CLC Main workbench software (V 8. 1. 2, QIAGEN Aarhus A/S, www. qiagenbioinformatics. com) for manual annotations of Vatrelated sequences. The Vat-1 gene from PI 161375 was used as a reference sequence to find the set of Vat-related sequences using the BLASTn-NCBI Basic Local Alignment Search Tool (https://blast. ncbi. nlm. nih. gov). BLAST queries with the first and third exon, corresponding respectively to the CC-NBS-ARC-LRR1 and LRR3 domains, revealed Vatrelated sequences which were manually annotated for exons, introns, and LRR2 characteristics in reference to Vat-1 from PI 161375. In addition, an automatic annotation was carried on (Methods S3).
CDSs retrieved from Vat-related sequences in several cucurbit genomes were aligned with the MUSCLE algorithm in Seaview software  42. For melon, only CDSs from Vat homologs with one R65aa were introduced in the alignment. The MegaX software suite  43  was then used to infer the evolutionary histories. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Tamura-Nei model for CDSs of Vat-related sequences (with one R65aa for C. melo) retrieved for cucurbit species and using the JTT model for Vat homologs obtained from 21 melon accessions. The topology with highest log-likelihood value was selected. CDSs retrieved from Vat-related sequences in melon were aligned while considering three independent blocks -pre-LRR2/LLR2/post LRR2-with the MUSCLE algorithm in the Seaview software package  42.
Acknowledgements We thank  Sandrine Arribat  ( CNRGV ) for furnishing high-quality HMW DNA for Anso77 and  Doublon and INRAe-URGV  for providing the PI 161375 BACs. We thank the EPGV staff,  Aurélie Chauveau , and  Isabelle Le Clainche  for library preparation and sequencing,  Elodie Marquand  and  Aurélie Canaguier  for data management and the  CEA-IbFj/Genoscope  sequencing platform staff for their help, as well as  Vincent Rittener  for all DNA/RNA preparation and sequence analyses. We thank  Zhang Hong  ( Hami Melon Research Center, Xinjiang Academy of Agricultural Sciences, China)  for providing C. melo cv Payzawat seeds as well as  Seminis vegetable Seeds (St Louis, Missouri, USA)  for providing C. sativus cv Chinese Long 9930 and  Gy14. Moreover , we are grateful to  Bernard Caromel  for advice concerning the manuscript.
Data availability Sequencing data for genome assemblies and contigs sequences were deposited in the NCBI database under the following numbers: Bioprojects PRJNA662717 and GenBank MW591952 for Anso77, BioProject PRJNA662721 and GenBank MW591951 for Doublon, and BioProject PRJNA664659 and GenBank MW591953, MW591954, MW591955 for PI 161375.
Upon single-stranded RNA-binding, the basic finger changes its conformation such that the NTD grabs the RNA molecule (Figure  1b   [12] ) and the single-stranded RNA-bounded form (right; PDB ID: 7ACT  [13] ) are shown in light sea green and magenta, respectively. In the right panel of (b), RNA is denoted in orange and the RNAunbounded form of the NTD is superimposed for structural comparison. The direction of the movement of the basic finger upon RNA-binding is shown by a black arrow; (c) CTD dimer interface. The CTD monomers (PDB ID: 6WZO  [15] ) are shown in orange and marine blue, respectively. In (b,c), the residue numbers at both termini of the structures that are visible in the crystal structures are denoted. All the models are depicted using UCSF Chimera  [16]. The crystal structures of the CTD have been solved at 1.
According to hydrogen/deuterium exchange measurements on dimers of N CoV2 CTD  [15] , this region is exposed to the solvent, suggesting that this region is not involved in dimer formation. So far, it is unclear what role this long insertion observed in N MERS CTD plays in the function of the protein. The fact that other regions of the CTD possess common structural features among three coronaviruses displayed here suggests that dimer formation of the nucleocapsid protein through its CTD is essential for formation of RNP complexes and hence RNA genome packaging, which is the fundamental function of the nucleocapsid protein. [12] ) and the single-stranded RNA-bounded form (right; PDB ID: 7ACT  [13] ) are shown in light sea green and magenta, respectively. In the right panel of (b), RNA is denoted in orange and the RNA-unbounded form of the NTD is superimposed for structural comparison.
The direction of the movement of the basic finger upon RNA-binding is shown by a black arrow; (c) CTD dimer interface. The CTD monomers (PDB ID: 6WZO  [15] ) are shown in orange and marine blue, respectively. In (b,c), the residue numbers at both termini of the structures that are visible in the crystal structures are denoted. All the models are depicted using UCSF Chimera  [16]. The crystal structures of the CTD have been solved at 1. 4 Å  [15, 17]  and 2. 0 Å  [18]  resolutions. It has been shown that the dimer interface consists of two β-strands and one α-helix (Figure  1c ), which is similar to that of the nucleocapsid protein of SARS-CoV  [19]. In solution, the N CoV2 molecules have been shown to exist in dimers by small-angle X-ray scattering  [20]. Note that, however, N CoV2 can also form tetramers  [15] , suggesting that its solution structure is sensitive to the solvent conditions.
NTD and the NTD of the nucleocapsid protein of MERS-CoV (N MERS ; PDB ID: 4UD1  [22] ) shown in orange. Note that N CoV2 NTD in the left and right panels are displayed at slightly different angles to focus on the structural differences from the N SARS and N MERS counterparts; (b) (left) Comparison of the CTD structures of N CoV2 (PDB ID: 7C22  [18] ) and of N SARS (PDB ID: 2CJR  [23] ), which are shown in marine blue and magenta, respectively. (right) Comparison of N CoV2 CTD and the CTD structure of N MERS (PDB ID: 6G13  [24] ) shown in orange. In both (a,b), the major structural differences are shown by grey arrows. All the models are depicted using UCSF Chimera  [16].
From these data, the scattering data arising from each protein can be extracted, leading to the elucidation of its conformation together with how each protein is arranged inside the droplets. The structural fluctuation of the molecules in the droplets are obtained by incoherent neutron scattering (iNS). This technique measures the intensity of neutron scattered by the samples as a function of the momentum and energy change of the neutron, from which the amplitude, the frequency and their distribution of atomic motions at pico-to nanosecond timescale at ångström length scale are estimated  [57]. The values of incoherent scattering cross-section of atoms found in biomolecules are shown in Figure  6b. It is found that the scattering cross-section of hydrogen atoms is much larger than any other atom and deuterium, meaning that iNS provides information of the motions of hydrogen atoms.
Deff denotes the efficient diffusion coefficient of the NTDs/CTDs and/or of the N CoV2 molecules. In the lower panel, τ, D, and a denote the residence time, the diffusion coefficient, and the amplitude of amino acid side chains and/or backbones, respectively. Hydrogen atoms are shown in red. p and (1-p) show the immobile and mobile fractions of atoms in proteins; (b) N CoV2 in an isolated state (dimer). Each monomer is shown in sea green and forest green, respectively. The central linker was modelled using the Ranch program  [93] ; (c) a model of nucleocapsid complex for SARS-CoV  [8]. Only CTDs are displayed because NTD positions are unknown. Possible locations of RNA molecules are depicted by brown line. One CTD monomer is shown in marine blue The models in sphere or ribbon representation are depicted using UCSF Chimera  [16].
Background: The aim of this ancillary study of the SARAH trial is to compare health-related quality of life (HRQoL) in patients with locally advanced or inoperable hepatocellular carcinoma (HCC) treated with transarterial radioembolisation (TARE) or sorafenib. Methods: This study included randomised patients who received either TARE or at least one dose of sorafenib with no major deviation in the protocol and who had at least one QoL follow-up assessment in addition to the baseline evaluation. QoL was assessed from the date of randomisation using the European Organisation for Research and Treatment of Cancer QLQ-C30 questionnaire, until disease progression or other reasons for stopping study participation. Data were analysed using linear mixed and time-dependent models. Results: A total of 285 patients were included (122 and 163, in the TARE and sorafenib groups, respectively).
Patients SARAH is a multicentre RCT performed in 25 centres in France (ClinicalTrials. gov: NCT01482442) between 2011 and 2015. The study was performed in accordance with the Declaration of Helsinki, approved by an ethics committee and complied with the provisions of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use guidelines for Good Clinical Practice. All patients provided written informed consent. The protocol and main results have been published  [7]. The present study reports the detailed results of HRQoL, a secondary end-point, in the SARAH trial. The main inclusion criteria for SARAH were a diagnosis of either locally advanced HCC (BCLC stage C) with no extrahepatic disease  [7] , new HCC not eligible for surgical resection, liver transplantation, or thermal ablation following previously cured hepatocellular carcinoma, or HCC that failed to respond to two unsuccessful rounds of transarterial chemoembolisation.
Statistical analysis Analyses were performed in the QoL population. Baseline characteristics were compared between the TARE and sorafenib groups using the Student's t-test for continuous variables and the chi-squared test or Fisher's test for categorical variables. A response analysis was performed between the two groups using the chi-squared test to compare the distribution of data in the three categories (improved, worsened and stable domain/item). A linear mixed model was used to explore the overall impact of time and the potential interaction between treatment allocation and time (at inclusion and 1, 3, 6, 9 and 12 months after treatment initiation). Time-to-deterioration analyses were performed for the global QoL scale and function domains (physical functioning, role functioning, emotional functioning, cognitive functioning and social functioning).
Treatment effect was estimated with the Fine and Gray model  [15]. Results are presented as sub-distribution HRs and their 95% CIs. A post hoc subgroup analysis was performed in patients with macroscopic vascular invasion. SAS software version 9. 4 was used for all analyses. A p value <0. 05 was considered to be significant. No formal adjustment of p-values was made for the multiple testing. The two groups were well-balanced at baseline and no clinically relevant differences were observed between the groups (Table  1 ). There were statistically significant differences between patients excluded from the perprotocol population and those in our study sample for some known prognostic factors such ChildePugh liver function (p Z 0. 045), tumour burden >25% (p Z 0. 012) and albumin-bilirubin (ALBI) grade (p Z 0.
Acknowledgements We would like to thank  Pascaline Aucouturier  and  Aurelia Dinut  at the  Clinical Research Unit, Hopital Europeen Georges-Pompidou , for their help in managing the study. We would also like to thank all clinical research associates for data monitoring and data collection and to the clinical research technicians and nurses from each centre. We thank the patients, their caregivers, and the investigators who participated in this study. The SARAH investigators are listed in the Supplementary Materials.
Image acquisition and averaging All eyes were imaged using the OptoVue HD OCTA device (AngioVue model, manufactured by OptoVue, 2800 Bayview Drive, Fremont, CA 94538, USA) always by the same technician, and with a limited time between each acquisition. The OptoVue HD OCTA is part of routine care in eyes with macular oedema. A total of five sequential 3x3-mm and five sequential 6x6-mm scans centered on the fovea were obtained for each eye. The number of 5 sequential scans was chosen for the averaging because no significant difference in vessel length density (VLD) has been reported after averaging 5 images by Uji et al  [13]. We used the terminology proposed by Campbell et al  [16]  to name the different retinal vascular plexuses. The preset parameters of the software were used to automatically segment the SVP and the deep vascular complex (DVC).
The accuracy of the automatic segmentation was verified visually by scrolling the 320 B-scans. The methodology for image averaging is shown in Fig 1. Briefly, all Jpeg formatted images of the SVP and DVC were extracted from the Optovue HD device and analysed using ImageJ software in its FIJI version. All the images were cropped in order to remove a square logo in the bottom left corner. As previously reported (Uji et al. [13] ), averaging the raw images provided poor results because of eye motion between the acquisitions causing translation and rotational differences between the frames. To compensate for this misalignment, an image registration was performed: first, a linear registration to align the 5 images, and then an elastic registration to correct for deformations due to the spherical conformation of the eyes.