dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank the  Bioinformatics and Expression Analysis (BEA) core facility at Karolinska Institutet  for their assistance. We thank  Peter Espenshade  for kindly providing the Tf2-12-neoAI strain. This study was in part performed at the  Live Cell Imaging Unit, Department of Biosciences and Nutrition ,  Karolinska Institutet , Huddinge, Sweden, supported by grants from the  Knut and Alice Wallenberg Foundation , the  Swedish Research Council , the  Centre for Biosciences , and the  Jonasson donation  to the  School of Technology and Health, Kungliga Tekniska Högskolan, Huddinge, Sweden. Work in the KE laboratory  is supported by grants from the  Swedish Cancer Society  and the  Swedish Research Council  (VR). KE received a  Wenner-Gren  stipend for work as a visiting researcher at  Institut Pasteur, France.
1/AP1 binding sites were analyzed (Supplementary Figure  S1D ). This result indicated that TRIM33 might be recruited at nucleosome free macrophage-specific regions   [18] ). (Right) Distribution of genes according to their numbers of associated TRIM33 and PU. 1 peaks in 32D and RAW cells. D. Occurrence of the indicated transcription factor binding sites in the different TRIM33/PU. 1 peak subsets in 32D (green) and RAW (blue) cells compared to their frequency in random PU. 1-bound regions in BMDM (red). Transcription factor matrices were extracted from Homer database and analyzed with RSAT Matrix-scan, using a threshold p-value<1e-4. E. MNase profiles in BMDM (data sets from  [19] ) around the summit of TRIM33 peaks in 32D (blue) or RAW (green) cells and around the summit of PU. 1 peaks in BMDM (red).
For MDP and MOP analyses BM cells were labeled with APC-efluor780 anti-c-Kit, PE anti-CD115 and APC anti-CD135 antibodies (eBioscience). Peritoneal macrophages were labeled with PE anti-B220, FITC anti-F4-80, PECy7 anti-CD11b and APC anti CD11c antibodies (eBioscience). BMDM and dendritic cells from BM cultures were labeled with FITC anti-CD11c, PC7 anti-Ly6G, APC anti-CD11b, APC-Cy7 anti-F4-80 and PerCP5. 5 anti-CD64. Plasma levels of cytokines were quantified by flow cytometry (CBA Mouse inflammation kit, BD Biosciences). Data acquisition was performed on FACS LSR II (BD Biosciences). Data were analyzed with FlowJo software version 9. 5. Sorting cells were performed on FACS Aria II (BD Biosciences).
cDNA microarrays and analysis Total RNA was extracted with the RNeasy Micro kit (QIAGEN). Gene expression profiling was performed in biological duplicates on Mouse GE 8x60K Microarrays (Agilent) according to the manufacturer's instructions. Accession number (E-MTAB-1441, European Bioinformatic Institute (http://www. ebi. ac. uk/ arrayexpress/). The Bioconductor package LIMMA was used to assess statistical significance of differences in mRNA levels between Trim33 -/-and Control macrophages. Transcripts with at least two-fold change and p-value<0. 05 were retained as differentially regulated. Subsequent analyses were limited to probe sets matching a known transcript.
Chromatin immunoprecipitation and sequencing ChIP experiments were carried out with an anti-TRIM33 antibody (A301-059A, Bethyl) as previously described  [12]. For sequencing, 10ng of purified DNA from ChIP was adapter-ligated, PCR amplified and sequenced by Illumina Genome Analyzer IIx according to the manufacturer's instructions (Illumina). Accession number (GSE43654). The libraries were sequenced on the Illumina Genome Analyzer IIx as single-end 50 base reads following Illumina's instructions. Image analysis and base calling were performed using the Illumina Pipeline and sequence reads mapped to reference genome mm9/ NCBI37 using Bowtie v0. 12. 7. In order to keep just the reads mapping to a unique position in the genome, Bowtie was run with the option -m 1. The option -best -strata were also used to get the best mapping position with the minimum of mismatch.
In order to define the TRIM33 enriched genomic regions, peak calling was performed using MACS  [32]  with default parameters and using the corresponding IgG as control samples. Peaks were then annotated according to genomic features of Ensembl v67 using Homer  [18]  (http://homer. salk. edu/ homer/). For co-localization studies, the TRIM33 peak positions of 32D and RAW cells and the PU. 1 peaks in BMDM were intersected using BEDTools, requiring at least 1bp overlap. MEME-ChIP  [33]  (http://memesuite. org/tools/meme-chip) was used to perform de novo motif discovery in TRIM33 peaks. Sequences spanning from -100bp to +100bp relative to the 600 highest enriched ChIP-Seq peak centers were extracted and repeat masked. The MEME algorithm was then used to identify motifs with a maximum size of 15bp and known motifs were derived from JASPAR and uniprobe databases.
RSAT Matrix-Scan (http://rsat. ulb. ac. be/) was used to analyze TRIM33 and TRIM33/PU. 1 peaks for transcription factor binding sites. Transcription factor matrices were extracted from Homer database and the occurrence was analyzed using a threshold p-value < 1e-4. The enrichment of Gene Ontology terms was calculated using DAVID tools or GREAT. Comparisons between 32D and RAW ChIPseq datasets at selected regions were performed using seqMINER  [34]. Genomic coordinates were retrieved from Ensembl v67 and used as reference in the density array method. The collected data were subjected to k-means clustering using linear normalization. Data were represented as heat maps or average plots.
1-bound regions in BMDM (red). Transcription factor matrices were extracted from Homer database and analyzed with RSAT Matrix-scan, using a threshold p-value<1e-4. E. MNase profiles in BMDM (data sets from [19]) around the summit of TRIM33 peaks in 32D (blue) or RAW (green) cells and around the summit of PU. 1 peaks in BMDM (red). F. (Left) PU. 1 binding sites in macrophages were clustered according to their TRIM33 ChIP-seq profiles in 32D and RAW cells. (Right) Gene Ontology (GO) functional annotation analysis of the three clusters of TRIM33/PU. 1 target genes.
ACKNOWLEDGMENTS We are grateful to the staff of the iRCM animal facility and of cytometry platform for excellent support during mouse studies. FF and AP were supported by fellowships from  Dim Stem Pole, Ligue contre le Cancer , and  French National Research Agency (ANR). This project was supported by grants to  Paul-Henri Romeo  from  La Ligue contre le Cancer (équipe labelisée) ,  ANR  ( ANR-12-BSV1-0001-02 ),  Inca  ( PL BIO 013031 ),  Inserm  and  CEA/DRF.
Genetic findings. Family 1. We found the TIMP3 variation c. 572A > G (p. Y191C) in exon 5, previously described in a family with isolated SFD (initially p. Y168C)  2. This variation is considered to be probably damaging by PolyPhen 2 with a score = 1 (http://genetics. bwh. harvard. edu/pph2), damaging according to SIFT with a score = 0 (http://sift. jcvi. org), and to interfere most likely with the function of the protein by the align-GVDG program with a class C65 (http://agvgd. iarc. fr/agvgd_input. php), disease causing for mutation taster with a probability of 0. 99 (www. mutationtaster. org), and neutral for Provean (provean. jcvi. org). The mutation co-segregated with the disease in the family and is not reported in the ExAc database (http://exac. broadinstitute. org). Multiple amino-acid sequence alignment of TIMP3 orthologs showed the conservation of the leucine at position 191 in all eukaryotic sequences available.
Chest computed tomography Family Family 2. We found the TIMP3 variation c. 113C > G (p. S38C) in exon 1 which has been previously described in SFD  24. This variation is considered to be probably damaging by PolyPhen 2 with a score = 1 (http://genetics. bwh. harvard. edu/pph2), damaging according to SIFT with a score = 0 (http://sift. jcvi. org), and to interfere most likely with the function of the protein by the align-GVDG program with a class C65 (http://agvgd. iarc. fr/agvgd_input. php), disease causing for mutation taster with a probability of 0. 99 (www. mutationtaster. org), and deleterious for Provean (provean. jcvi. org). This variation is not present in ExAC. In addition, the mutation co-segregated with the disease in the family. This mutation has been reported previously in 5 SFD unrelated patients  24, 25.
Genetic analysis. Genomic DNA was extracted using a standard salting-out procedure. All exons of TIMP3 (refseq NG_009117. 1) were screened in all patients. The screening was performed on genomic DNA using primers designed to flank the splice junctions of each exon (sequences available upon request). After standard polymerase chain reaction (PCR) amplification, products were purified with ExoSAP-IT (GE Healthcare Life Sciences, USB Corporation) and direct sequencing was performed on an Applied Biosystems (ABI) 3130 xL genetic analyzer (Applied BioSystems, Foster City, CA, USA) using the BigDye Terminator Cycle Sequencing Ready Reaction kit V3. 1. Sample sequences were aligned to the wild-type sequence and analyzed with the Collection and Sequence Analysis software package (Applied Biosystems).
The pathogenicity of nucleotide changes was estimated by different predictive software including, Polyphen program -Harvard University, Boston, MA. http://genetics. bwh. harvard. edu/pph, SIFT (http://sift. jcvi. org), Align-GVDG program (http://agvgd. iarc. fr/agvgd_input. php), Mutation taster (www. mutationtaster. org), and Provean (provean. jcvi. org). The pathogenicity was also assessed considering multiple-amino-acid sequence alignment of TIMP3 orthologs and the protein structure identity according to Nextprot database (www. nextprot. org). Indeed, the variation had to segregate with the disease in the family. The identified variations were tracked in all genetic databases and in previous articles about Sorsby fundus dystophy.
Primers used for molecular cloning are listed in Supplementary Table  6. Agrobacterium tumefaciens GV3101 carrying the expression vector was used to transform Arabidopsis wild-type plants (Ws background) by dipping immature inflorescences in a bacterial suspension  37. Transgenic plants were selected on soil via Basta treatment (250 mg l À 1 ; Agro Evo). T2 seeds were used for subsequent analyses. Amplification of CYP98A region from lineage III species. To obtain CYP98A8 and CYP98A9 sequence data from species in Brassicaceae lineage III, we performed multiple rounds of high-efficiency thermal asymmetric interlaced PCR (hiTAIL-PCR)  38. Initial nested primer sets were designed to anneal to regions highly conserved in known Brassicaceae CYP98A8 and CYP98A9 sequences. Polymorphic sites were incorporated into primers, and thus the resulting primers were degenerate at several nucleotide positions.
Amplicons were sequenced and used to inform sequence-specific primer design to walk upstream and downstream along the chromosome using additional rounds of hiTAIL-pPCR  38. Primers are available in Supplementary Table  6. E. syriacum and C. tenella DNA samples were those used in Beilstein et al. 39. Nested amplification was performed in a two-step process according to the hiTAIL-PCR protocol  38. The process was repeated until the assembled reads reached flanking genes. The software CoGe  40  was used to compare assembled sequence reads for E. syriacum and C. tenella with published whole-genome sequences from Brassicaceae lineage I and II species. PCR products were separated on a 1% agarose gel with low EDTA before excision, filtration (Millapore Centrifugal Filter Units), and ethanol precipitation.
Purified PCR products were ligated into pGEM-T Easy vector (Promega) and transformed into TOP10 competent cells and plated on selective media for screening. Positive transformants were cultured overnight in liquid media, and plasmid DNA harvested using an alkaline lysis kit (Zymo Research). Cloned fragments were sequenced in both directions to achieve a minimum of 85% overlap. Overlapping sequence reads were assembled into a consensus sequence using the software Geneious v. 6. 6 (Biomatters). Recombinant CYP98 protein production in yeast. Intronless coding sequences of EsCYP98A8, AaCYP98A8/9 and ThCYP98A8/9 genes were PCR-amplified from genomic DNA using USER-compatible primers  41. Amplicons were subsequently introduced in the pYeDP60u2 vector  42  and verified by sequencing. For AtCYP98A8 and AtCYP98A9 pYeDP60 plasmids construction, the corresponding coding sequences were PCR-amplified from genomic DNA and introduced between the BamHI and KpnI sites and BamHI and EcoRI sites, respectively, as described previously  18.
MS scans in positive and negative mode were performed, and multiple reactions monitoring were developed for every detected peak. Compounds were identified by comparison of two orthogonal data (RT and MS/MS) relative to authentic compounds analysed under identical experimental conditions, or putatively annotated by comparison of MS/MS spectra with published data  45, 46. Vanillin assay. Mature dry seeds were incubated in a solution of 1% (w/v) vanillin (Fluka #350346) prepared in 6 N HCl at room temperature for 1 h. Vanillin turns red upon binding to flavan-3,4-diols (leucoanthocyanidins) and flavan-4-ols (catechins), which are present either as monomers or as terminal subunits of proanthocyanidins  31. Determination of gene expression divergence. pCYP98A8:uidA and pCYP98A9:uidA plants  18  were incubated in 90% acetone for 20 min on ice, rinsed with water, and transferred to a GUS solution containing 1 mM 5-bromo-4-chloro-3-indolyl-b-D-glucuronide (X-Gluc), 100 mM sodium phosphate (pH 7.
All reactions were performed in triplicate. The SAND gene expression was stable among flower samples and thus chosen as internal standard for normalization. Primers used for qRT-PCR detection were previously described  18  and their sequences are provided in Supplementary Table  6. Phylogenetic d N /d S analysis. Coding sequences were aligned with MUSCLE  49  and phylogenies were built using PhyML 50 using the generalized time-reversible (GTR) model with gamma distribution (four rate classes of sites with optimized alpha) via the Seaview software (http://pbil. univ-lyon1. fr/)  51. PAML (codeml) (http://abacus. gene. ucl. ac. uk/software/paml. html)  52 and Fitmodel  53  were applied to the coding-sequence alignments and phylogenetic trees. All the analyses were run both with a trimmed alignment (404 over 560 codons) where the most variable sites, mainly in the 5 0 and 3 0 regions of the coding sequences, were suppressed by GBlocks  54, 55  and with a longer alignment where all but the gap-containing sites were conserved (457 over 560 codons).
As a result, the selected AtCYP98A8 and AtCYP98A9 models had a QMEAN score equal to 0. 701 and 0. 689, respectively, which are good scores when compared to the QMEAN scores of individual PDB templates. Docking experiments. The protein structures generated by Modeller were first stripped of all hydrogen atoms, and then atom charges and hydrogen atoms were added to the protein with the UCSF Chimera package (www. cgl. ucsf. edu/chimera)  62 sing AMBER ff99SB parameters. The first parameters applied for the heme (defined as Fe III protoporphyrin IX) were obtained from Oda et al. 63  , and in the docking experiments with S-Naringenin (Nar) the heme cofactor was defined as the highly reactive intermediate compound I (Fe IV ¼ O) þ by using the parameters (geometry and atom charges) of an AMBER-compatible heme model developed by Shahrokh et al.
The receptor was kept rigid. The docking box, in which grid maps were computed using program AutoGrid  65  , included the active site with the iron-protoporphyrin group on one edge, and the whole distal moiety of the enzyme, including access channels and protein surface, to allow a large sampling of potential poses. The grid built by AutoGrid included 100, 70 and 86 points in x, y and z directions, with a grid spacing of 0. 37Å to allow a good compromise between resolution of the explored volume and the size of the binding area. For each Nar conformer, 500 independent runs were performed using the Lamarckian genetic algorithm  66. The default settings were used for all other parameters. The poses were assigned a score calculated by Autodock that can be considered as an estimated free energy of ligand binding (indicative of binding affinity), then clustered as a function of the closeness of their positions and conformations with root mean square deviation set at 2.
Acknowledgements We are grateful to  Clint Chapple  ( Purdue university, USA ) for providing the pCC0996 vector. Z. L. is grateful to the  China Scholarship Council  and the  Region Alsace  for co-funding a PhD scholarship. D. W. -R. and H. R. acknowledge the support of the  Agence Nationale pour la Recherche  to the PHENOWALL  ANR-10-BLAN-1528  project, and of the  Freiburg Institute for Advanced Studies (FRIAS)  and the  University of Strasbourg Institute for Advanced Study (USIAS)  to the  METABEVO  project. F. A. acknowledges  Laura Dhers  ( PhD student, UniversiteParis Descartes ) for help in model structures set-up and the staff of the computing facility of the  Commissariat al'Energie Atomique (CEA/DSV/GIPSI, Saclay)  for help and access to the national cluster Gabriel. A portion of this work was supported by a grant ( MCB 1409251 ) from the  National Science Foundation  of the United States to M.
Patient II-3 and his mother were then included in a next generation sequencing project for X-LID patients in our institute using SOLiD 5500 sequencer (Life technologies Grand Island,USA). DNA (5 µg for each patient) was enriched by micro droplet PCR procedure (Raindance technology, Billerica, Massachusetts, USA) to target 11575 exons. Sorting and calling of SNP/InDel were performed using SAMTOOL and GATK softwares (Bioinformatic Programs, USA). Novelty was assessed by filtering the variants against a set of polymorphisms that are available in public databases such as dbSNP (http:// www. ncbi. nlm. nih. gov/projects/SNP/), 1000 genomes (http://browser. 1000genomes. org/in-dex. html), Exome Variant Server (http://evs. gs. washington. edu/EVS/), and ExaC (http://exac. broadinstitute. org/). Only nonsynonymous variants or changes affecting splice sites were analyzed.
All sequence variants were prioritized by scoring phylogenetic conservation and functional impact (SIFT and Polyphen-2) and analyzed by Mutation Taster program (Charite-University Berlin, Germany, Europe). Candidate variants were selected and confirmed by Sanger sequencing  11  , using the 3500XL Genetic analyzer  12  and the Big Dye cycle sequencing Kit of Applied Biosystem technology (Thermo-Fisher scientific, USA). To sequence exon 31 of ATRX gene, forward (GGCTGGTGTTACATGTTTTGC) and revese (GCTGAAACCAACCCATAAAGA) primers were designed by Primer3 program (Cambridge, Massachusetts, USA) an online tool to design and analyze primers for PCR, and then were procured from Eurogentec (Belgium, Europe) in Belgium. X-chromosome inactivation study was carried out in the mother  10  (Fig. 1 ).
Results & Discussion Karyotypes of three patients (I-1, I-2 and II-4) were 46, XY. The high resolution karyotype and the CGH revealed no chromosome aberrations. Inactivation affected 60 and 40 per cent of X-chromosomes. Sequencing of X-exome from patient II-3 and his mother identified a single nucleotide substitution in exon 31 of the ATRX gene (Genbank accession number NG_008838) resulting in a substitution of an adenine (A) by a cytosine (c. 6740A>C), and led to the substitution of a conserved histidine to a proline (p. His2247Pro). This mutation was not detected in any of the public databases (such as Exome Variant Server, 1000 genomes, dbSNP135) and in >200 X-exomes of index patients from other XLID familes. This mutation was confirmed by Sanger sequencing in the three affected males as well as in the mother and her two daughters.
Aircraft observations Aerosol sampling on the ATR-42 was performed using the AVIRAD system. AVIRAD is an iso-axial and iso-kinetic inlet which samples air at a volumetric flow of ∼ 350 L min -1. The 50 % passing efficiency of the inlet is 12 µm diameter. Various lines depart from AVIRAD to connect to different instruments for the measurement of the aerosol physicochemical and optical properties. Additionally, several sensors for the measurements of the atmospheric composition were installed on the ATR-42 aircraft as basic equipment. A brief description of the different in situ measurements considered in this study from the AVIRAD system and the ATR-42 equipment and their data analysis is reported in the following. The aerosol scattering coefficient (σ s ) at 450, 550, and 700 nm was measured by a three-wavelength integrating nephelometer (TSI Inc.
the ratio of the ozone to carbon monoxide variations compared to their baseline values. A background value of ∼ 70 ppbv in the boundary layer and ∼ 60 ppbv in the free troposphere was used for CO, while the background was set at ∼ 30 ppbv for O 3 at all levels (Di  Biagio et al. , 2015). O 3 / CO data were used together with dN UFP /dN Acc to retrieve information on the age of the sampled air masses, as discussed in Di  Biagio et al. (2015). In order to compare SLRs measurements obtained at different altitudes, the data analysed here were reported to standard temperature and pressure (STP) using T = 293. 15 K and P = 1013. 25 hPa. In this case, the scattering and absorption coefficients were scaled to STP conditions and the particle concentrations (in number or volume) were given as particles per standard cm -3 (scm -3 ).
Optical calculations were performed using Mie theory for spherical particles. The Mie_single. pro IDL routine available at http://eodg. atm. ox. ac. uk/MIE/mie_single. html was used. In the calculations the real part of the refractive index was varied in the range 1. 30-1. 80 at steps of 0. 01, while the imaginary part in the range 0. 001-0. 1 at steps of 0. 001, for a total of 5100 inversions for each SLR data set. The uncertainty on the real and imaginary parts of the refractive index was estimated with a sensitivity study. To this purpose, the values of n and k were also obtained by using as input the observed σ s , σ abs , and dN d log D g plus or minus 1σ standard deviation on their measurement. The deviations of the values of n and k retrieved in the sensitivity study with respect to those obtained in the first inversions were assumed to correspond to the 1σ standard deviation uncertainty.
Figure8. Spectral real (n, left panel) and imaginary (k, right panel) parts of the complex refractive index obtained by optical closure for the eight selected case studies. For the sake of clarity, uncertainties on n and k are not reported in the plot. The values of the single scattering albedo measured at 370 and 950 nm for the different cases are reported in the legend. The spectral real and imaginary parts of the complex refractive index as obtained from the Optical Properties of Aerosols and Clouds (OPAC, Hess et al. , 1998)  database for insoluble, water soluble, soot and sea salt components are also reported in the plot. These components are used in OPAC to model continental polluted, continental rural, urban, and maritime polluted aerosols.
Acknowledgements. All measurement presented here are from the  Chemistry-Aerosol Mediterranean Experiment  project (ChArMEx, http://charmex. lsce. ipsl. fr),which is the atmospheric component of the  French multidisciplinary program MISTRALS (Mediterranean Integrated Studies aT Regional And Local Scales ). ChArMEx-France was principally funded by  INSU, ADEME ,  ANR ,  CNES ,  CTC  ( Corsica region ),  EU/FEDER ,  Météo-France , and  CEA. TRAQA was funded by  ADEME/PRIMEQUAL  and  MIS-TRALS/ChArMEx programmes and Observatoire Midi-Pyrénées. Claudia Di Biagio  thanks the  Centre National des Etudes Spatiales (CNES)  for financial support. The authors wish to thank the technicians, pilots and ground crew of  SAFIRE (Service des Avions Francais Instruments pour la Recherche en Environnement ) for facilitating the instrument integration and conducting flying operations.