dataesr/scientific-paragraphs-categorization huggingface dataset:
, 1995). Most registries used DAS28-ESR; when not available, we used the DAS28-CRP instead. All patients had either complete data for the DAS28-ESR or complete data for the DAS28-CRP. Almost all registries had some patients with missing DAS28-ESR data. The Italian registry, GISEA, was the only registry with only DAS28-CRP data. In addition to the DAS28, we extracted demographic variables, BMI, smoking status, comorbidities, seropositivity according to rheumatoid factor or anti-citrullinated protein antibodies (ACPAs), disease duration, and disability as measured by the health assessment questionnaire (HAQ). We also extracted information about treatment, including number of past biologics treatment, conventional DMARD (cDMARD) and glucocorticosteroid therapy. We further computed ABA drug retention, which integrates both drug effectiveness and tolerance, ABA drug retention until stopping for ineffectiveness, reason for ABA discontinuation, EULAR good or moderate response rate at 6 months, one year, and two years (van Riel, 2014) corrected for drug discontinuation (Lundex)  (Kristensen et al.
We then examined the association of these groups with demographic-, disease-, and treatment-related covariates, as well as treatment effectiveness. We analyzed patients and disease characteristics at treatment initiation using standard descriptive statistics and Fisher exact test for categorical variables or Wilcoxon rank sum test for continuous variables. We ran a sensitivity analysis using probabilityweighted regression with weights based on posterior probability of classification in each trajectory group. Data are presented as means (SD) or medians (interquartile ranges) depending on their distribution. ABA drug retention was analyzed by the Kaplan Meier method. Given the inherent differences between registries  (Finckh et al. , 2015) , we tested for effect modification by registry using an interaction term between types of trajectories and national registry using a Cox proportional hazard model.
The severity of the phenotype in ADH varies genetically with the type of mutation and the gene affected  ( 8, 9 ). LDLR is the gene most frequently associated with ADH and is also the best characterized. It is responsible for the disease called familial hypercholesterolemia (FH)  (9) (10) (11). With the exception of a few founder populations, the spectrum of LDLR causing FH mutations is large. To date, more than 1,600 variants have been identifi ed [Leiden Open Variation Database (LOVD) of ADH, http://www. ucl. ac. uk/ldlr/; and Human Gene Mutation Database, http://www. hgmd. cf. ac. uk/ac/]. France is among the most heterogeneous in the world: recent studies have identifi ed almost 400 mutations in more than 1,000 affected subjects  ( 9, 12 ). In contrast, only a few mutations implicated in ADH were identifi ed in the APOB gene, causing the familial defective apoB-100  ( 13, 14 ).
Global molecular analysis of ADH in France In this cohort of 229 patients, 105 (46%), 77 (34%), and 47 (20%) were diagnosed with defi nite, probable, and possible ADH, respectively. A likely pathogenic variant or a VUS was found in the four studied genes in 85 patients (81%) with a defi nite score, in 36 (47%) with a probable score, and in 9 (19%) with a possible score. LDL-C levels, fi rst-degree antecedent of hypercholesterolemia, and personal or familial history of CVD for all 229 patients are given in the supplementary data (supplementary Table  2 ). The relative contribution of the four examined genes to ADH in the cohort is shown in supplementary Figure  1. All the identifi ed variants with in silico analysis results, frequency data, and references are presented in the supplementary data (supplementary Table  3 ).
Molecular analysis Genomic DNA was extracted from peripheral blood leukocytes by using a phenol/chloroform extraction. Genotyping for the LDLR , a fragment of exon 26 of APOB , PCSK9 , and APOE was carried out using primers and conditions as described in the supplementary data (supplementary Table  1 ). Sequencing analysis of PCR products was performed by the Sanger method using ABI 3500xL DX sequencer and the Big Dye Terminator v. 3. 1 cycle sequencing kit (Applied Biosystems). The MLPA was carried out to detect rearrangements within the LDLR in accordance with the manufacturer's protocol (kit P062; MRC-Holland, The Netherlands). In all cases, the presence of a mutation was confi rmed by an independent PCR amplifi cation followed by sequencing or by a second MLPA analysis. The sequence variants of this study were designated according to the Human Genome Variation Society guidelines (http://www.
Bioinformatic tools and molecular modeling The programs SIFT  ( 30 )  and PolyPhen2 ( 31 ) were used to predict possible impact of genetic variations on the structure and function of altered proteins. For splicing predictions, we used four algorithms to computationally score 5 ′ and 3 ′ splice sites. The four algorithms were based on different concepts [Neural Network Splice Prediction (NNSP), MaxEntScan (MES), Splice Site Finder Like (SSFL), and Human Splicing Finder (HSF)] included in the ALAMUT (Interactive Biosoftware v2. 4. 0), and the default parameter settings were used. The prediction of changes in thermal protein stability for each observed APOE variant was obtained from the CUPSAT web server  ( 32 ). The functional/structural consequences of the APOE amino acid changes were estimated using the NMR structure of the full-length isoform E3 [pdb id 2L7B  ( 33 ) ].
Accordingly, the p. Leu46Pro mutation was predicted to be destabilizing by the CUPSAT program, with a large change in free folding energy of 1. 4 kcal/mol. Indeed, very recently the variant Leu46Pro of apoE isoform E4 was experimentally found to be thermodynamically destabilized, more prone to proteolysis, and affected in its lipid binding properties  ( 40 ). Gly145 is located within a loop region connecting helices H3 and H4; this residue being solvent-accessible, the CUPSAT program predicts a stabilizing mutation for the variant p. (Gly145Asp). Contrariwise, Arg163 and Leu167 are in the middle of the ␣ -helix H4, precisely in the putative LDLR binding site (region 158-168). Therefore, p. (Arg163Cys) and p. (Leu167del) mutants are thought to impair LDLR binding properties of the apoE protein.
Even the homozygous form Cys163 appears to retain usual properties toward the VLDL and IDL remnants in plasma, considering the normal TG level observed in patient #1. From our data, it appears that the homozygous form C163 in APOE is less severe than a homozygous FH form and looks like the APOB homozygous form, at least with respect to the LDL-C levels  ( 46 ). Interestingly, the statin treatment was associated with good outcome in patient #1, reducing the LDL-C level from 4. 15 to 2. 70 g/l. Interestingly, we did not notice any notable CVD history for the four families with APOE changes. This observation has to be confi rmed by a precise outcome as our data suggest that the APOE modifi cations in ADH could lead to less atherosclerosis than LDLR or PCSK9 changes. In conclusion, changes in LDLR remain the main cause of ADH accounting for 89% of the mutated ADH patients in this study.
Real and virtual P flow calculations We determined the value of 'virtual' and 'real' P flows for the EU27, including its oversea territories 5  for 1995 and 2009. These years were selected to cover the period during which the EU set up policies to limit domestic water eutrophication risks, and because they corresponded to the first and last years for which we had comprehensive data availability (e. g. , about detailed imports, yields, and fertilisation rate; see below). Estimates of both flows were focused on mineral P fertiliser use and did not account for P supplements used in animal feed. The virtual P flow corresponded to the amount of mineral P fertiliser that was used in source countries to grow agricultural products for export to the EU (Matsubae et al 2011,  Schaffartzik et al 2015).
The data on yields were extracted using FAOSTAT production module which provides annual data on crop yields for each FAO country and for each of the considered commodities from 1961 to 2013 (http:// faostat3. fao. org/download/Q/QC/E, accessed 16 September 2015). Ferti i,j represents the amount of mineral P fertiliser that was applied on crop i in the country j (in kg of P per ha of cropland). The data on fertiliser use were extracted using reports from the Fertilizer Industry Association (IFA), the International Fertilizer Development Center (IFDC) and the FAO  (FAO et al 1994 , FAO et al 1996 , FAO et al 1999 , FAO 2006 , IFA 2009 , IFA 2013). These reports provide expert-based data on the amount of mineral P used as fertiliser for major crops and major agricultural countries. As some data were sometimes missing for some crops, some countries or some years, we used 5 year windows, centred on the year 1995 and 2009.
This helped to correct for possible inter-annual variability in fertiliser use and to avoid missing data for some specific years. Additional details about P fertilisation rates are available in SI. The full dataset of imported commodities, crop yields and fertilisation rates in source countries is available in table  S2. The real P flow corresponded to the amount of mineral P fertiliser that was used on the EU's domestic agricultural area in 1995 and 2009, including that used to support domestic crop and grass production, which was both consumed domestically and exported. Since our study aimed to estimate only the amount of P needed to support EU food and feed consumption, we removed the amount of mineral fertiliser needed to produce exported agricultural products. To do so, we used an equation similar to (equation (  1 ) with Q ij , yield ij and ferti ij representing the amount of agricultural products exported out of the EU, the average yield of the exported commodities at the EU scale and the average crop fertilisation rate at the EU scale, respectively.
The corresponding data were extracted from FAOSTAT for Q ij and yield ij and from IFA, FAO and IFDC reports for ferti ij. Animal products represented a significant fraction of the total P exported through trade from the EU (18% and 14% of total P exported through trade in 1995 and 2009, respectively). We thus accounted for the P needed to produce these animal products in our P footprint approach and provide detailed calculations in SI.
This uncertainty is difficult to estimate but it may be limited in this study by the fact that our dataset integrated possible changes in fertilisation rates through time. As such, we avoided using outdated data on farming practices which is often a severe limitation of virtual resource flow calculations  (Yang and Suh 2015). There is also uncertainty about P fertiliser application rates to specific crops when they are used in rotation. Farmers generally make their decisions about fertilisation over the duration of a whole crop rotation sequence by accounting for carry-over effects of applied fertilisers on past crops  (Haileslassie et al 2007). Our annual crop fertilisation averages cannot explicitly account for such nuances (and how these numbers may be under-or over-estimates). This uncertainty is reduced however for source regions that export all the crop products in a particular rotation to the EU.
In other words considering specific trade partners is key to assessing the full impact of virtual P flows. The disconnect between agricultural production and associated resource use and the consumption activities that drive such resource use practices has been facilitated by international trade and makes coordinated interventions to increase sustainability difficult  (Hertwich and Peters 2009). As such the fact that many countries are increasingly involved in the global food/feed trade  (Fader et al 2013 , Puma et al 2015)  calls for the development of robust and flexible indicators and databases that could help quantify virtual resource flows among countries and potential positive and negative effects on local and global resource use. For instance, using such indicators in our study helped to identify a limited set of commodities and countries that could be targeted for the EU to reduce its overall P footprint: prioritising trade relations with Brazil and Argentina, and/or the five crops (soybeans, palm kernel, copra, coffee beans and cottonseeds) that represent the majority of the virtual P flow.
Acknowledgments We thank  Peder Engstrom  and  Nathan Mueller  ( Univ. Minnesota ) for providing some data on P fertilisation rate for coffee, cocoa, tea and pea. We also thank  Bruno Ringeval ,  Sylvain Pellerin  and  Tamara Ben-Ari , as well as two anonymous reviewers for their comments on an earlier version of this manuscript. This work was funded by grants from  Bordeaux Sciences Agro  ( Univ. Bordeaux ) and the  McGill School of Environment during TN's sabbatical at McGill , as well as by an  NSERC   Discovery Grant  to EMB.
e. , the first half of 8th century AD). Finally, palaeogenomic analyses conducted on the human remains provide arguments in favor of a North African ancestry of the three individuals, at least considering the paternal lineages. Given all of these data, we propose that the skeletons from the Nimes burials belonged to Berbers integrated into the Umayyad army during the Arab expansion in North Africa. Our discovery not only discusses the first anthropological and genetic data concerning the Muslim occupation of the Visigothic territory of Septimania but also highlights the complexity of the relationship between the two communities during this period.
If written sources indicate that the "Saracens" were able to stay in Septimania for several decades, at this point, we have been ignoring all data regarding the nature of this occupation. The discovery in 2006 of three Muslim burials in Nimes (Languedoc-Roussillon, France) immediately appeared as a unique opportunity to document the "Saracen" settlement in the South of France. A multidisciplinary study was then developed combining (i) archaeological analyses to characterize the site funerary practices, to determine the burials dating, and to discuss the burials' integration in the Nimes funerary context, (ii) anthropological analyses to test the potential attribution of the individuals to Arab army soldiers (through sex and age individuals' characterization, and through the search of potential osteological evidence of combat) and (iii) palaeogenomic analyses to provide biological arguments concerning individuals' origins.
The significant presence of this haplogroup outside North Africa-i. e. , in extant populations of Iberia, Italy and Sicily (S4 Fig)-relates directly to the long-term Arab rule in these regions  [46]. If the paternal lineage E-M81 and the maternal lineage L1c3 characterized implies with a high degree of probability a North African origin for all Nimes individuals, we have to note that the large distribution of mtDNA lineages H1 and K (both in North Africa and Europe) do not permit to drive any clear conclusion concerning individuals' maternal ancestry. Indeed, the determination of these maternal lineages on Nimes burials may be both the result of a direct North African maternal origin and the result of admixture between migrating Muslims and local European women. If the low discriminatory power of mtDNA does not permit us to decide between both hypotheses, genome-wide data may permit to precise individuals' ancestries in the next future.
Nevertheless, if admixture between Muslims and European women is well established for later al-Andalus periods (genetically established for sites in Andalusia dating to the 12 th -13 th centuries;  [11] ), such admixture had not been raised so far for the very first Muslim groups arriving in Europe. If admixture with local women was confirmed concerning Nimes individuals, these data would constitute the most ancient evidence of admixture in the al-Andalus context. Mutations are transitions unless specified. Transversions are indicated by an A, C, G, T after the nucleotide position, and mutations back to the CRS nucleotide are indicated by a "!". Note that the positions that have 4-fold and more coverage are indicated in bold and the positions that have less than 4-fold coverage are noted in brackets.
Conclusion Using a multidisciplinary approach that combines history, archeology, anthropology and palaeogenomics, we discuss the first early medieval Muslim graves discovered in an area north of the Pyrenees. Although a Muslim presence in Septimania was already known through textual evidence, the complete analysis of the graves provides new data concerning the first groups of Muslims that arrived in France. Notably, the analyses confirm the Berber origin of some of the first Muslim troops spreading through Europe and also indicate the co-existence of communities in Nimes practicing Christian and Muslim funerary customs without any clear partition of their respective funerary spaces. These results clearly highlight the complexity of the relationship between communities during this period, far from the cliché depiction still found in some history books.
Acknowledgments We are grateful to the  French National Institute of Preventive Archeology (INRAP)  and the municipality of Nimes. We thank  Valérie Bel  (INRAP) and  Henri Duday (CNRS)  for their support and comments. We thank  Odile Maufras  ( INRAP ) for his assistance related to the early medieval occupation at Nimes,  Gauthier Devilder  ( CNRS ) for the infography,  Aurélien Ginolhac  ( Centre for GeoGenetics Natural History Museum of Denmark University of Copenhagen ) for helpful discussions concerning bioinformatic analyses, and  Priscilla Bayle  ( University of Bordeaux ) for very helpful comments on the first version of this manuscript.
This study benefitted from excavation grant support from the  city of Nîmes, France  (INRAP;  FB11045601 ). The paleogenomic analyses were made possible by funding from the  CNRS  ( Centre National de la Recherche Scientifique; PEPS APEGE ) and from the  Research National Agency  as a program of prospects investments  ANR-10-LABX-52  ( CAP  project; dir. MFD;  University of Bordeaux, LaScArBx-ANR ;  2012-2014 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
, 2012). Datasets for each of the viewpoints were generated from wild-type as well as MiEκ and 3'Eκ enhancer deficient pre-B cells (Table  S1 ). In wild-type cells we detected a high frequency of contact between MiEκ, 3'Eκ and Edκ. We found that deletion of either the MiEκ or the 3'Eκ interferes with interactions between each enhancer and the others. Their absence also disrupts interactions between the two other partner enhancers in the hub: in MiEκ -/-cells the contact frequency between 3'Eκ and Edκ was significantly reduced, which is especially apparent from the 4C signal of the 3'Ek bait. Likewise, the contact frequency between MiEκ and Edκ is significantly reduced in 3'Eκ -/- cells (Figure  1D ). To determine whether the changes in contact have a functional effect we performed RNA-seq to examine the impact of enhancer deletions on transcription.
ncRNA scan RNA-seq reads from DN and pre-B samples were mapped to the mm10 genome using TopHat2 (-N 1 -no discordant --no-mixed --library-type fr-firststrand -G (RefSeq GTF file provided). Transcripts from chromosome 6 were assembled using Cufflinks version 2. 2. 0. Transcript assemblies from the same cell type were merged using Cuffmerge. Merged transcripts were annotated with Cuffcompare using RefSeq GTF file. Following the lncRScan  (Sun et al. , 2012; Trimarchi et al. , 2014 ) pipeline, we extracted lncRNAs with class code 'u','x','i' or 's'. Multi-exonic transcripts with more than 200 nucleotides as well as with less than 300 nucleotides putative Open Reading Frame were selected. Mono-exonic transcripts overlapping antigen receptor loci enhancers were manually added back to the final non-coding transcriptome of pre-B cells.
Confocal microscopy and analysis DNA FISH with immunofluorescence was imaged by confocal microscopy on a Leica SP5 AOBS system (Acousto-Optical Beam Splitter). Optical sections separated by 0. 3 µm were collected and only cells with signals from both alleles (typically over 95%) were analyzed using Image J software (NIH). For γH2AX colocalization analysis alleles were defined as colocalized with the protein if the DNA probe signals and immunofluorescence foci directly overlapped (at least two pixels of colocalization).
Acknowledgments We would like to thank members of the  Skok lab  for helpful discussions, especially  Pedro Rocha  and  Lili Blumenberg  for input in the revision of the manuscript. C. P. was supported by an  NCC  fellowship; V. S. is supported by  NYSTEM  institutional training grant (contract # C026880 ); J. A. S. is a  Leukemia & Lymphoma Society  ( LLS) scholar. J. A. S. and Y. K. are supported by  NIH  grant  R01 GM086852 , J. A. S. and R. B. are supported by  NIH  grant  R01 GM112192. We would also like to thank  NYU CHIBI , the NYUMC sorting facility and NYUMC genome technology center for their contributions to this work.
Conflict of interest The authors declare that they have no competing financial interests. TGTGGATTGATTAAGCCATG-3′, DpnII primer 5′-TGAGCATTTCTTTCTCCTAGTGG-3′) and REIR (NIaIII 5'-CACCCAGAGCTCCTTCCATG-3′, DpnII 5′-CAAGTCTTGGAGCCTTCCTG-3′), respectively. The Illumina-specified adapters for Illumina sequencing together with multiplexing indexes were included at the 5' end of each primer. Our 4C libraries were sequenced on the Illumina Hi-Seq 2000 using single-read 100-cycle runs. The number of reads obtained for each dataset is listed in Table  S1. Sequence reads from 4C-Seq were mapped to a reduced genome derived from mm10 containing unique sequences adjacent to restriction enzyme sites. Reads were mapped using Bowtie2  (Dryden et al. , 2014; Langmead and Salzberg, 2012 ) (-N=0 and -5 was used to trim the barcode and primer sequences).
The cDNA levels of chaperone genes were then analyzed by quantitative real-time PCR (RT-qPCR) using a LightCycler 480 Instrument II with LightCycler 480 SYBR Green I Master reaction mixes according to the instructions of the manufacturer (Roche Diagnostics). RT-qPCR was performed with an initial denaturation at 95 °C for 5 min, followed by 45 cycles of 10 s at 95 °C, 10 s at 60 °C, and 10 s at 72 °C. Each sample was analyzed in duplicate using 1:15 and 1:50 dilutions of the cDNAs and the gene-specific primers listed in Table  1. The primer pairs (Table  1 ) were designed following the rules of highest possible sensitivity and efficiency with the Primer3 2. 3. 4 plugin of the Geneious v9. 0. 5 software (Biomatters, Auckland, New Zealand). Relative expression levels of the target genes were normalized to the internal reference gene ihfB for the β-subunit of the integration host factor using the comparative 2 -∆∆Ct method  [25].
Acknowledgements Protein production has been partially performed by the  ICTS  " NANBIOSIS ", more specifically by the  Protein Production Platform of CIBER in Bioengineering, Biomaterials & Nanomedicine (CIBER-BBN)/IBB , at the  UAB  (http://www. nanbiosis. es/unit/u1-protein-production-platform-ppp/). We are indebted to MINECO BIO2013-41019-P,  AGAUR  ( 2014SGR-132 ) and  CIBER de Bioingeniería, Biomateriales y Nanomedicina  (project  NANOPROTHER ) to AV, Plan Estatal de I+D+I 2013-2016 del  Instituto de Salud Carlos III (FEDER co-funding)   FIS PI12/00327  to EV, Marató  TV3 416/C/2013-2030  to RM for funding our research. We thank the  CIBER-BBN Nanotoxicology Unit  for fluorescent in vivo follow-up using the IVIS equipment. The authors thank  Manuel Hein  and  Dörte Grella  ( Research Center Borstel ) and also Fran Cortes the  Cell Culture and Citometry Units of the Servei de Cultius Cel•lulars, Producció d' Anticossos i Citometria (SCAC) ,  Servei de Proteómica  and to the  Servei de Microscòpia , for technical assistance, and the  Soft Materials Service  ( ICMAB-CSIC/CIBER-BBN ).