dataesr/scientific-paragraphs-categorization huggingface dataset:
The MMA algorithm  [72, 73]  is based on the idea of using a shifted Lagrangian function to make a convex approximation and then solves a sequence of convex approximations. The MMA algorithm is used to solve the optimization problem, which allows determination of the distribution of two materials in the considered domain. One can Also, two values of the parameter t are considered, which means that the thickness of the ribs equals either 0. 2 or 0. 28. In all cases, the value of the rib length L was constant and resulted from the length of the side of a regular hexagon inscribed in the circle of radius equalling 1. On the basis of the length L and the angle α = 15°, the dimensions of the cell Lx and Ly are calculated. All these values are collected in Table  1. All numerical calculations were performed by means of FEM software (Comsol Multiphysics, Stockholm, Sweden).
The MMA algorithm is used to solve the optimization problem, which allows determination of the distribution of two materials in the considered domain. One can Also, two values of the parameter t are considered, which means that the thickness of the ribs equals either 0. 2 or 0. 28. In all cases, the value of the rib length L was constant and resulted from the length of the side of a regular hexagon inscribed in the circle of radius equalling 1. On the basis of the length L and the angle α = 15°, the dimensions of the cell Lx and Ly are calculated. All these values are collected in Table  1. All numerical calculations were performed by means of FEM software (Comsol Multiphysics, Stockholm, Sweden). The finite-element mesh consisted of over 29,000 triangle elements for the thickness of ribs equal to 0.
Acknowledgments: This work was supported by grants from the  Ministry of Science and Higher Education in Poland :  02/21/DS-PB/3493/2017 ,  02/21/DS-PB/3494/2017  and  02/21/DS-MK/3498/2017. The simulations were carried out at the  Institute of Applied Mechanics, Poznan University of Technology. Acknowledgments: This work was supported by grants from the  Ministry of Science and Higher Education in Poland :  02/21/DS-PB/3493/2017 ,  02/21/DS-PB/3494/2017  and  02/21/DS-MK/3498/2017. The simulations were carried out at the  Institute of Applied Mechanics, Poznan University of Technology.
Microscopic Investigation Scanning electron microscopy (SEM) micrographs of the films' surfaces were obtained with a Zeiss Merlin SEM (Carl Zeiss, Oberkochen, Germany). For investigation of cross-sections, the films were frozen in liquid nitrogen and fractured perpendicularly to their surface. Coating with carbon layer was used for preparation of the samples for SEM. Scanning probe microscope multimode 8 (Bruker, Santa Barbara, CA, USA) operating in PeakForce TUNA TM mode was used for atomic force microscopy (AFM) experiments. Scanning was done in PeakForce QNM mode with feedback adjusted automatically by ScanAsyst program protocol. Major PeakForce parameters were: amplitude 100 nm and frequency 2 kHz. ScanAsyst-Air probe (Bruker, Santa Barbara, CA, USA) with a tip radius of 5 nm and spring constant 0.
Prepared samples were also investigated with DSC (Figure  8 ). It was found that glass-transition temperature (T g ) was 203-205 • C for both samples. Peaks corresponding to melting of crystalline phase are clearly visible in the range 315-319 • C, which confirms the semi-crystalline nature of prepared films as it was observed by WAXD. The thermal stability of the prepared samples was evaluated by TGA. The TGA curves indicate that solvent has been successfully eliminated from polyimide film and also from composite film with ZrO 2 because there is no weight loss below 100 • C. Both TGA curves show one region of weight loss, which correspond to the decomposition of the polymer backbone. The step of weight was 500 • C for pristine polyimide and 480 • C for composite film with ZrO 2 , which agrees with data published in for R-BAPB  [30].
It was found that glass-transition temperature (Tg) was 203-205 °C for both samples. Peaks corresponding to melting of crystalline phase are clearly visible in the range 315-319 °C, which confirms the semi-crystalline nature of prepared films as it was observed by WAXD. The thermal stability of the prepared samples was evaluated by TGA. The TGA curves indicate that solvent has been successfully eliminated from polyimide film and also from composite film with ZrO2 because there is no weight loss below 100 °C. Both TGA curves show one region of weight loss, which correspond to the decomposition of the polymer backbone. The step of weight was 500 °C for pristine polyimide and 480 °C for composite film with ZrO2, which agrees with data published in for R-BAPB  [30]. This demonstrates a high thermal stability of the prepared samples.
Acknowledgments: This work was supported by the  Russian Science Foundation (RSF) , grant  16-13-10164 :  Maria Sokolova ,  Michael Smirnov , and  Alexander Toikka  acknowledge the  RSF  for support in the synthesis of membranes, studies of their structural characteristics and analysis of results. Alexander Bugrov  acknowledges  St. Petersburg State University  for the postdoctoral fellowship (grant  12. 50. 23. 2014 ). Valentin Svetlichnyi  and  Elena Popova  acknowledge  RFBR  ( 17-03-00733  a). The experimental work was facilitated by the equipment of the  Resource Center of X-ray Diffraction Studies, Nanotechnology Interdisciplinary Resource Center, and of Thermogravimetric and Calorimetric Resource Centre at St. Petersburg State University. Authors are grateful to  Elena N. Vlasova  from  Institute of Macromolecular Compounds RAS  for the study of samples obtained in this article by the FT-IR spectroscopy.
Results The methylome landscape of EBV+ Burkitt's lymphomas derived cell lines. To identify a potential impact of EBV on DNA methylation patterns in Burkitt Lymphoma (BL), we first profiled the DNA methylome of 10 EBV (+) and 9 EBV (-) BL-derived human cell lines. The EBV (-) BL cell lines derived from BL samples from individuals of Caucasian origin and display a very low number of EBV copies (from 0. 02 to 0 copies per cell) when analysed by Taqman PCR, while the EBV (+) BL were almost all derived from BL samples from individuals of African origin and displayed at least 1 copy of EBV genome per cell (Supplementary Table  1 ). DNA was bisulfite converted and interrogated for DNA methylation using Illumina HM450 bead arrays (as described in Methods). Data quality was ensured by verifying internal standards, filtering out low quality or cross-reactive probes, and using multi-dimensional scaling to rule out batch effects.
2D ). Hypomethylated regions also showed an increase in DNase hypersensitive site (DHS) (Fig. 2E ). On the contrary, hypermethylated sites were significantly more distant from TSS (Fig. 2B  and C ), and enriched in CpG island shelves (4 kilobases up and downstream from islands), with a trend to be localized in enhancer regions (Fig. 2D  and F ). Of note, many of the identified DMPs corresponded to the same gene symbols (Table  1 ), indicating that changes associated with EBV infection were spanning larger genomic regions. To further investigate regional differences in methylation we performed region-level analysis in the same dataset. With a DMR (differentially methylated region) definition of at least 2 differentially methylated sites and a gap of less than 1000 bp, we identified 966 DMRs (Table  2 ).
6E ). As, our data show that the EBV-mediated downregulation of ID3 occurs by methylation of the gene promoter, we next asked whether LMP1 also alters ID3 expression by triggering epigenetic changes on the ID3 promoter. Indeed, treating RPMI-LMP1 cells with the DNA demethylating agent, Aza, led to a significant rescue of ID3 levels (Fig. 6F ), but left unchanged the levels of TCF3 (Fig. 6G ), indicating that DNMTs could play a role in LMP1-mediated inhibition of ID3. We therefore performed ChIP-qPCR experiments in RPMI -pLXSN or RPMI -LMP1 cells to quantify the amount of DNMT1, 3A and 3B recruited onto ID3 regulatory promoter regions, in the proximity of the cg02978140. None of the three DNMTs bound to this region in RPMI pLXSN, but they were efficiently recruited to it in the presence of LMP1 (Fig.
Materials and Methods Cell culture. Peripheral B cells were purified from blood samples as previously described  45. The myeloma-derived RPMI-8226 cells (http://web. expasy. org/cellosaurus/CVCL_0014) and the Burkitt lymphomas cell lines (BL), including the BL EBV(-) cell line Louckes (http://web. expasy. org/cellosaurus/CVCL_8259), were obtained from the IARC biobank. The EBV genome copy number determined by Taqman PCR and the geographical origin of BL used in the present study are described in Supplementary Table  1. Primary and immortalized B cells were cultured in RPMI 1640 medium (GIBCO; Invitrogen life Technologies, Cergy-Pontoise, France) supplemented with 10% FBS, 100 U/ml penicillin G, 100 mg/ml streptomycin, 2 mM L-glutamine, and 1 mM sodium pyruvate (PAA, Pasching, Austria) or in advanced RPMI 1640 (LIFE TECHNOLOGIES; 12633012).
The analysis on the bead array was conducted following the recommended protocols for amplification, labelling, hybridization and scanning. Bioinformatics Analysis. Raw methylation data was imported and processed using R/Bioconductor packages  48, 49. Data quality was inspected using boxplots for the distribution of methylated and unmethylated signals, and inter-sample relationship using multidimensional scaling plots and unsupervised clustering. Probes were filtered for low quality (detection P value > 0. 05) and known cross-reactive probes  50. The remaining dataset was background subtracted, and normalized using intra-array beta-mixture quantile normalization  51. Methylation beta values were logarithmically transformed to M values before parametric statistical analyses, as recommended  52.
To define differentially methylated positions (DMPs) and differentially methylated regions (DMRs), we modelled the EBV status as a categorical variable in a linear regression using an empirical Bayesian approach  53. DMPs were selected based on a differential methylation (delta beta) of at least 40% when comparing the two EBV categories. DMRs were identified with the DMRcate package using the recommended proximity-based criteria  54. A DMR was defined by the presence of at least 2 differentially methylated CpG sites with a maximum gap of 1000 bp. Differentially methylated genes (DMPs and DMRs) were further analyzed to determine functional pathways and ontology enrichment using Enrichr  55. All methylation data have been deposited to the Gene Expression Omnibus repository (GEO accession number GSE92378).
Whole Genome Expression Analysis. Differential expression analysis was performed using Human HT-12 Expression BeadChips (Illumina) as previously described  45, 56  and 500 ng total RNA isolated with the TRIzol Reagent (Invitrogen) according to the manufacturer's instructions. Raw expression bead array data (AVG-Signal), with no normalization and no background subtraction was exported from Genome Studio (version 2011. 1, Illumina) into BRB-ArrayTools software (version 4. 3. 1, developed by Dr. Richard Simon and the BRB-ArrayTools Development Team. Data were normalized and annotated using the R/Bioconductor package "lumi"  48. Quality of the data was assessed by plotting the distribution of the intensity for all probes, and a correlation between technical replicates performed. Class comparison between groups of bead arrays was done computing a t-test separately for each gene using the normalized log-transformed beta values.
Acknowledgements We are grateful to all members of the  Infections and Cancer Biology Group  for their support. We would also like to thank  Dr Maimuna Mendy ,  Dr Elodie Caboux  and  Gertrude Tchoua  for giving us access to IARC Biobank archive BL cells and cell pellets. We are thankful to  Nicole Suty  for helping with the manuscript preparation. We finally thanks our funders:  La Ligue Contre le Cancer (LNCC) Rhone  ( GR-IARC-2014-04-07-03  to RA),  Oncostarter-(CLARA)  ( GR-IARC-2014-05-15-02  to RA),  IARC   Junior Award 2016  ( AFEES-2016  to RA) and  European Commission  ( FP7-HEALTH-2011-282562  to MT).
The use of secondary structure of ITS2 in microalgal taxonomy increased after Coleman et al. 21 and Muller et al. 26  suggested a link between the presence of compensatory base changes (CBCs) and species boundaries. The ITS2 secondary structure includes four helices. A double-sided base change of a nucleotide pair in a given helix retaining the secondary structure is considered a CBC, while a single-side change is called hemi-CBC (hCBC). In this paper, we analyze a wide set of phenotypic and genetic characters of members of prasinophyte clade VII, including ultrastructure, cell size, DNA content, pigment profiles, multigene phylogeny and ITS2 secondary structure. The data obtained lead us to describe two novel classes, the Picocystophyceae and the Chloropicophyceae, which contain two novel genera, Chloropicon and Chloroparvula, and eight species that are new to science.
ITS2 secondary structures. Forty-two ITS2 sequences (second internal transcribed spacer, separating the 5. 8S and 28S rRNA genes) were obtained from the strains listed in Table  1. The ITS2 boundaries (5. 8 and 28S rRNA flanking regions) were annotated using Hidden Markov Models (HMMs) and a Viridiplantae database  38  as implemented in the ITS2 database annotation tool with the default parameters (http://its2. bioapps. biozentrum. uni-wuerzburg. de/)  39. The partial B9 helix formed by the hybridization of 5. 8 and 28S rRNA ITS2 flanking regions was checked for structural motifs known to be required for the precise removal of ITS2 during ribosomal RNA processing  25. RNA secondary structure predictions were performed using the Mfold web interface  40  under the default options with the folding temperature fixed at 37 °C, resulting in multiple alternative folding patterns per sequence.
Phylogenetic analyses (ITS2 and concatenated 18S/Plastid 16S rRNA). Nuclear 18S rRNA and partial plastid 16S RNA sequences obtained from the strains listed in Table  1  as well GenBank sequences belonging to members of the core chlorophytes and streptophytes were concatenated using Geneious 10. 0. 5  46. Streptophytes sequences were used as outgroup. Accession numbers are provided on the phylogenetic trees. The concatenated sequences were aligned with MAFFT using the E-INS-i algorithm  47. For ITS2, only the sequences from Chloropicophyceae strains were aligned with MAFFT using the G-INS-i algorithm  47. For each sequence within the alignment, the preliminary secondary structure annotated in dot-bracket format was associated, generating a Vienna file which was imported to 4SALE  43, 44. The final alignment was edited on the basis of conserved secondary structures.
Phylogenetic reconstructions were performed with two different methods: maximum likelihood (ML) and Bayesian analyses. The substitution models TN93 + G + I and K2 + G were selected for concatenated 18S rRNA/plastid 16S rRNA and ITS2 sequence datasets respectively, based on Akaike information criterion (AIC) and the Bayesian information criterion (BIC) options implemented in MEGA 6. 06  48. ML analysis was performed in PhyML 3. 0  49  with SPR (Subtree Pruning and Regrafting) tree topology search operations and the approximate likelihood ratio test with the Shimodaira-Hasegawa-like procedure. Markov chain Monte Carlo iterations were conducted for 1,000,000 generations sampling every 100 generations with burning length 100,000 using MrBayes 3. 2. 2  50. MAFFT and MrBayes programs were run within Geneious 10.
0. 5  46. Clade nodes were considered as well supported when SH-like support values and Bayesian posterior probabilities were higher than 0. 7 and equal to 1. 0, respectively. Intra-and inter-clade sequence distances (p-distance) were calculated with combined nuclear and plastid datasets as well as for ITS2. The analysis was conducted using MEGA v. 6  48  and all positions containing gaps and missing data were removed. All alignments are available as Supplementary Material 2. 2 ) from the Moore Foundation Marine Microbiology Transcriptome Sequencing Program (MMETSP)  51  were selected to determine the phylogenetic placement of Chloropicophyceae based on a multigene alignment. Reads were downloaded from the MMETSP archive (http://data. imicrobe. us/project/view/104) to the ABiMS platform in Roscoff (http://abims.
sb-roscoff. fr). The quality of the reads was checked by FastQC v. 0. 52 (http://www. bioinformatics. babraham. ac. uk/ projects/fastqc/). Reads were separated into ribosomal and non-ribosomal sequences with RiboPicker v. 0. 4. 3  52  using as a reference the Small Subunit RNA database (SSR database) from the SILVA project (release 119)  53. Ribosomal and non-ribosomal sequences were assembled separately using the de novo reconstruction method of Trinity release r20140717 54 using default parameters. Contig abundance was estimated based on Fragments Per Kilobase Of Exon Per Million Fragments Mapped 55 using RSEM v. 1. 1. 17  56. We only retained non-ribosomal contigs for which FPKM ≥ 2000 and percent of isoform ≥ 1.
The most appropriate model of protein evolution was determined with ProtTest v. 3. 2  61  using the Akaike Information Criterion to be LG + I + G + F. Two different methods were used for phylogenetic inferences: Maximum Likelihood using PhyML 3. 0  49  and Bayesian using MrBayes v. 3. 2. 2  50, 62. 100 bootstrap replicates were set for ML and 500,000 generations for Bayesian analysis. Convergence was checked with Tracer (http://tree. bio. ed. ac. uk/software/tracer/) and all effective sample sizes (ESS) were in excess of 350.
However, the global pattern of genome size was species-specific  66. Another possibility would be that some strains have undergone diploidy as previously observed in macroalgae  67  although this does not seem to have been observed in microalgae. Despite these differences in genome size, concatenated 18S and 16S rRNA sequence divergence within clade A4 was very low (0. 1%, one substitution in 1579 analyzed positions), and ITS2 sequences were identical for all strains (see below). In contrast, B2 showed the highest intra-clade sequence divergence for both the combined dataset and ITS2 sequences (see below) which may correspond with the differences in estimated genome size.
In the present study five other clade A4 strains from a wider range of latitudes were analyzed. The data confirm that all strains of clade A4, whatever the latitude from which they were isolated, lacked loroxanthin (Table  2 ). Clearly the absence of loroxanthin is a phenotypic characteristic of clade A4, but it is also absent from most strains from lineage B, and therefore cannot be used as a biomarker to distinguish A4 from all other members of prasinophyte clade VII. Phylogenomic analysis of chloroplast sequences have suggested that prasinophyte clade VII lineage A is a sister group of the core Chlorophyta  12, 74, 75. The core Chlorophyta comprise a well-supported clade containing the classes Chlorophyceae, Ulvophyceae, Trebouxiophyceae, Chlorodendrophyceae and Pedinophyceae. The presence of astaxanthin and loroxanthin carotenoids in clade VII lineage A and B strains, as in core Chlorophyta, while it is absent in other prasinophytes is indicative of another common feature between this group of prasinophytes and core Chlorophyta.
A phylogenetic analysis combining partial plastid SSU rRNA gene sequences with a congruent data set of nuclear 18S rDNA sequences (Fig. 5 ) recovered the major diverging clades within prasinophyte clade VII lineages A and B with high support values for maximum likelihood (ML) and Bayesian analyses. The only exception was clade B2 which had no support from ML (0. 46) analysis (Fig. 5 ). Phylogenetic analysis based on ITS2 (internal transcribed spacer 2) sequences from 41 unique strains from lineages A and B also confirmed the major divergent clades described above (Supplementary Figure  3 ). However, both analyses (combined SSU rRNA and ITS2) failed to resolve the relationships between the different clades (low bootstrap and variable tree topologies). The uncorrected sequence distance (p-distance) within clades calculated with the combined 18S nuclear and 16S plastid datasets was below 0.
6 ). Within clades, only clade B2 had CBCs (and hCBCs) in helices II and III, between strain RCC696 on the one hand and the other two, RCC999 and NIES-2756, on the other (Table  3 ). In fact, sequence divergence within this clade was highest among the clades for both sequence datasets used (Supplementary Table  4 ) and the pigment composition of RCC696 was slightly different from that of NIES-2756 since it lacked loroxanthin (Table  2 ). Within the other clades of lineages A and B, the ITS2 sequences were nearly identical and neither CBCs nor hCBCs were detected (Table  2 , Supplementary Table  5 ). In general, several CBCs were detected between clades or solitary branches. There were two exceptions for which CBCs were not observed: between RCC996 and A1 and between A4 and A2 (Table  3 ), although hCBCs (7 and 6 respectively) were found in helices I, II and III (Supplementary Table  5 ).
These regions, corresponding to the apical part of helices I and II as well as the lateral helix IIIa are drawn for each clade/branch in the panels on the right side. a fact that was further confirmed here. The branch formed by RCC996 has not been classified within a specific clade  9  given the absence of similar complete 18S rRNA gene sequence from other cultures or environmental samples. In addition, A1 possesses a 500 bp long 18S rRNA intron around position 1,000 which is not detected in any other clade. While few sequences corresponding to that of RCC996 have been found in metabarcoding datasets  9  , clade A1 was relatively more important at the DCM (deep chlorophyll maximum) of some Pacific Tara Ocean stations fitting the fact that all A1 strains have been isolated from deep euphotic waters  9.
Another example of distinct molecular signatures congruent with ecological specificities was provided by contrasting clades A4 and A2. Clade A4 is the second most abundant clade after B1 and is mainly found in coastal waters (OSD dataset), probably indicating a habitat preference, while the abundance and distribution of A2 is very sporadic  9. Strains belonging to A4 differed from others by the absence of loroxanthin (Table  2 ). Thus, despite the absence of CBCs between clade A1 and RCC996 or between A2 and A4, each probably represents organisms with distinct biological and ecological properties. Nuclear multigene phylogeny confirms the monophyly of lineages A and B. A multigene phylogenetic analysis was performed using the transcriptome sequence database obtained in the frame of the MMETSP Marine Microbiology Initiative  51.
The numbers in brackets represent the CBC identification number (see Supplementary Table  5  for the list of all CBC and for their position on the ITS2 alignment). our concatenated dataset is similar to the divergence between well-established classes of the core Chlorophyta (Supplementary Table  4 ), justifying separation of these two lineages (at least) at the genus level. Müller et al. 26  and Caisová et al. 45, 79  showed that the absence of CBCs in ITS2 secondary structures is not an indicator that two organisms belong to the same species. This is particularly true for Ulvales and Chlorophyceae for which a lack of correlation between CBCs in ITS2 at the species level was reported  45, 79. However, the presence of at least one CBC is a good indicator that two organisms represent distinct species (93.