dataesr/scientific-paragraphs-categorization huggingface dataset:
Annex A-1. T-cell epitopes known in celiac disease Several listings/databases of the known T-cell stimulatory sequences identified in gluten, hordeins, secalins and avenins are available including the https://propepper. net database and the http://www. allergenonline. org/ database. Furthermore, an overview of the best characterised epitopes along with a unified nomenclature is presented in  Sollid et al. (2012). Table  A. 1 lists the epitopes described in the latter manuscript. This compilation lists both the HLA-DQ2-and HLA-DQ8-restricted epitopes and includes the known immunodominant epitopes present in the a-and x-gliadins as well as the less commonly recognised epitopes in the c-gliadins and the LMW-and HMW-glutenins. The list contains a convenient overview of the most important and well defined epitopes.
It is, nevertheless, important to note that due to the extreme variability of the gluten and gluten-like proteins in barley and rye, (single) amino acid variants of these epitopes do exist, some of which may also exhibit T-cell stimulatory activity. Also, it cannot be fully excluded that additional gluten epitopes may be identified in the future. However, this is unlikely because large numbers of patients have already been extensively tested for gluten reactivity, on the basis of gluten peptide libraries  (Tye-Din et al. , 2010). Thus, any protein containing one or more sequences that display high sequence identity to the epitope sequences present in this list will likely have the capacity to trigger gluten-specific T cells. The development of a comprehensive database that is publicly available, curated regularly and appropriately built and designed for risk assessment purposes is an important aspect to be further investigated.
Annex A-3. Considerations for HLA-DQ peptide modelling Recent studies have determined the T-cell receptor repertoire used by CD4+ T cells specific for immunodominant gluten epitopes and crystal structures of such T-cell receptors bound to the HLA-DQgluten complexes were determined. As a consequence, detailed knowledge is available indicating which amino acids in the gluten peptides are responsible for the high-affinity binding to HLA-DQ and which amino acids mediate the specific interaction with the T-cell receptor. Several publications describing the binding of CD peptides to HLA-DQ molecules are available. The coordinates of all these structures are available through public databases  (Broughton et al. , 2012; Henderson et al. , 2007; Kim et al. , 2004; Petersen et al. , 2014; Petersen et al.
, 2015 Petersen et al. , , 2016;; Rossjohn and Koning, 2016). As an example, the x-ray coordinates of HLA-DQ8 bound to a gliadin peptide were deposited in the Protein Data Bank (www. rcsb. org) with the accession number 2NNA while the coordinates and structure factors for the HLA-DQ2-gliadin complexes have been deposited in the Protein Data Bank under the following accession codes: S2 TCR-DQ2. 5-glia-a1a, 4OZI; S16 TCR-HLA-DQ2a2, 4OZH; D2 TCR-HLA-DQ2a2, 4OZG; JR5. 1 TCR-HLA-DQ2a2, 4OZF. This extensive information allows modelling studies in which the gluten peptide can be replaced by any peptide sequence of choice  (Moustakis et al. , 2000; Wiesner et al. , 2008; van Heemst et al. , 2015). It can be anticipated that, if the selected peptide is likely to bind to HLA-DQ in a way that it resembles the known structure of gluten peptides bound to HLA-DQ, it might have the capacity to stimulate gluten-specific T cells  (Figure A.
, 1978b ). Yet another study measured chymotrypsin activity in duodenal aspirates of healthy individuals and found on average 120. 5 international units/ml of chymotrypsin but no clear indication is given as to the substrate used  (Gaia et al. , 1984). There is also data on the analysis of pancreatic tissue from human fetal, newborn and adult origin which suggest that adult pancreas contains 100 mU/mg protein trypsin while chymotrypsin was around 6 mU/mg protein; however, the methods and reporting units are not clearly described and enzymatic assays may lack specificity  (Track et al. , 1975). Analysis of intestinal contents in a fed state suggested that trypsin and chymotrypsin levels vary greatly between 50 and 850 lg/mL  (Track et al. , 1975). While enzyme activities were measured no indication is given as to how the mass of enzyme in the intestinal contents was calculated in this study.
B. 4. 1. 2. Digestion conditions Digestion conditions should be selected based on the range of conditions found in vivo and which encompass the needs of special groups and those receiving medication, such as antacids. The current document provides a set of conditions to reflect the different situations experienced in vivo. Different concentrations for proteolytic enzymes and/or biosurfactants have also been described in in vitro digestion models  (Dupont et al. , 2010; Mandalari et al. , 2009b; Minekus et al. , 2014 , Thomas et al. , 2004)  and summarised in Annexes B-3. 2 and B-3. 3. An elaboration of the current classical pepsin resistance test would build on both in vivo data and current in vitro test methodology thus maintaining a link to previous test results and building on best practice.
Traditionally, protein digestibility has been measured using SDS-PAGE. However, while providing valuable data especially for intact proteins and large resistant fragments, this technique is essentially qualitative in nature, can provide inconsistent results between laboratories and is not an appropriate technique to carry out reliable quantification of peptide fragments. Tandem mass spectrometry, even with caveats with regard to peptide ionisation efficiency, is a more effective tool to carry out a comprehensive peptide mapping of digesta and identify stable digestion fragments ≥ 9 amino acids in length. Since at present no single methodology can readily characterise the digestion of both proteins and peptides effectively, a combination of the best available methodology, such as SDS-PAGE and mass spectrometry, should be used.
Annex C-2. Possible approach for selection of soybean allergens to be analysed The OECD list of 'potential allergens'  (Table 20 of OECD, 2012)  which is based on allergens listed in the WHO/IUIS database (2011 www. allergen. org) and a review (L'Hocine and Boyne 2007), was taken as a basis, and further complemented with other allergen databases including the updated WHO/IUIS, the FARRP allergen database of the University of Nebraska-Lincoln (www. allergenonline. org) and Allergome (http://allergome. org/). Sequence information was additionally reviewed using the NCBI and Uniprot databases. Other allergen databases, listed in the EFSA 2010 scientific opinion (EFSA GMO Panel, 2010), were also considered, but could not be screened in detail because they did not provide additional information or were no longer available.
Using these sources, data on individual 'potential allergens' and on the allergic individuals tested were retrieved. Furthermore, information was collected connecting clinical reactivity to total soy preparations with data on specific allergens, as well as possible clinical reactions to single purified allergens (either isolated from the plant or produced as recombinant allergens). To date, clinical data for soy allergy were obtained by double-blind placebo-controlled food challenge (DBPCFC) using whole soybean protein extract or soy flour  (Ballmer-Weber et al. , 2007) , while only limited clinical research studies, mostly restricted to component resolved diagnostics  (Tuano and Davis, 2015) , are available for single proteins. The available information retrieved on the soybean 'potential allergens' are listed in Table  C.
1 (available in Supporting Information; please see also  Selb et al. , 2017). It is challenging to unequivocally connect clinical data obtained on soy extracts by DBPCFC with reactivity to single proteins. In this particular example, taking the information collected for Table  C. 1 as starting point and following the strategy proposed above, defined criteria were applied for a possible selection of relevant allergens. WHO/IUIS defines criteria to include a protein in the allergen list. These are: (i) a minimum of five sera from allergic individuals (allergic to the allergen source in question) have to contain IgE which binds to the protein in question, or (ii) at least 5% of the allergic individuals' sera tested react with the allergen in question by IgE binding. It is noteworthy that WHO/IUIS database was the main contributor for listing allergens in the OECD document on soybean.
WHO/IUIS is also mentioned as a key reference for listing allergens in the EFSA NDA Panel opinion on food allergens (See section 8 of EFSA NDA Panel opinion 2014). WHO/IUIS committee meetings deciding the inclusion of new allergen in the list are held in the frame of EAACI and AAAAI international allergy meetings. Notably, because an application must be filed to include a protein into the WHO/IUIS database, not all proteins clearly fulfilling the requirements are included in the current database. In our example approach following the current WHO/IUIS criteria, the following allergens listed in Table  C. 1 are also part of the WHO/IUIS database and should be measured accordingly: Gly m 1, Gly m 2, Gly m 3, Gly m 4, Gly m 5, Gly m 6, Gly m 7 and Gly m 8. Out of these, Gly m 2 can currently not be measured since the sequence is unknown.
General Experimental Methods Commercially available reagents were purchased from commercial suppliers and used as received unless otherwise specified. Solvents were obtained from same commercial sources and used without further purification unless otherwise specified. Et 3 N, CH 2 Cl 2 , and Et 2 O were distilled respectively on sodium, CaH 2 , and sodium/benzophenon. Toluene was stored over 4 Å molecular sieve under Ar. Copper(I) chloride has been prepared according to a reported procedure  [28]  and stored in a Schlenk tube under Ar. Glassware was oven-dried prior to use. 1 H NMR spectra (were recorded on a Bruker (Karlsruhe, Germany) 300 MHz and on a 400 MHz spectrometer in CDCl 3 , CD 2 Cl 2 or (CD 3 ) 2 SO and data are reported as follows: chemical shift in ppm from tetramethylsilane with the solvent as an internal indicator (CDCl 3 7.
26 ppm, CD 2 Cl 2 5. 32 ppm, and (CD 3 ) 2 SO 2. 50 ppm), multiplicity (s = singlet, d = doublet, t = triplet, q = quartet, quint = quintet, m = multiplet, or overlap of non-equivalent resonances), integration. 13 C NMR spectra were recorded either on a 75. 4 MHz or on a 101 MHz in CDCl 3 , CD 2 Cl 2 , or (CD 3 ) 2 SO and data are reported as follows: chemical shift in ppm from tetramethylsilane with the solvent as an internal indicator (CDCl 3 77. 16 ppm, CD 2 Cl 2 53. 84 ppm, and (CD 3 ) 2 SO 39. 52 ppm). Absorption measurement has been performed on a Jasco V-670 (JASCO International Co. Ltd. , Tokyo, Japan) and luminescence measurement on a Jasco FP-8300 Fluorometer (JASCO International Co. Ltd. , Tokyo, Japan).
X-ray Crystal Structure Determination A single crystal of [(L 1 )-Au-Cl] (1c) was selected, mounted, and transferred into a cold nitrogen gas stream. Intensity data was collected with a Bruker Kappa-APEX2 system (Bruker AXS, Karlsruhe, Germany) using fine-focus sealed-tube radiation. Unit-cell parameters determination, data collection strategy, integration, and absorption correction were carried out with the Bruker APEX2 suite of programs (v2014. 11-0, Bruker AXS, Karlsruhe, Germany). The structure was solved with SHELXT-2014  [29]  and refined anisotropically by full-matrix least-squares methods with SHELXL-2014  [29]  using the WinGX suite  [30]. Relevant data was deposited at the Cambridge Crystallographic Data Center with number CCDC 1558193 and can be obtained free of charge via www. ccdc.
By examining microarray expression data for BLM-depleted or non-specific shRNA-treated isogenic control fibroblasts available under accession no. GSE54502  22  , we also found that Tau was significantly upregulated in BLM-depleted cells relative to control cells (Fold-change = 1. 45, P = 7. 63×10 -4 ; Moderated t-test; Supplementary Fig. 2a, b ), supporting our findings. The overexpression of Tau in BS cells was confirmed by reverse transcription quantitative PCR (RT-qPCR) and western blotting (WB) (Fig. 2a-c ). We used Tau-5 monoclonal antibody, which detects all Tau proteins, regardless of their phosphorylation state (Fig. 2b ). As we planned to investigate the nucleolar distribution of Tau in subsequent experiments and the Tau-5 antibody is not suitable for Tau nucleolar immunostaining, we also tested the only Tau antibody for which nucleolar staining has been reported  23  , the Tau-1 antibody (Fig.
Two days after the second round of transfection, cells were collected for western blotting (n), or were plated, in a serial dilution series, in 12-well plates. Seven days later, colonies were fixed and stained with crystal violet. Non-targeting siRNA was used as a control, with the values obtained set to 1 (o). For qPCR, the mean value for 3 independent experiments is represented as a fold-change. B2M, β-actin, and TBP were used as housekeeping genes for qPCR normalization. For western blots, β-actin was used as a loading control. Each data bar is the mean of at least three independent experiments performed in triplicate. Error bars represent ± SEM. The significance of differences was assessed in two-tailed paired Student's t-tests. ***P < 0. 0005, **P < 0. 005, *P < 0. 05, NS not significant depletion (Fig.
DNA was quantified by qPCR with primer pairs covering the rDNA repeat. Their approximate positions relative to the transcription start site (TSS) are indicated on the x axis. Data are the means from three independent experiments. n, o Endogenous pre-rRNA (45 S) levels were monitored by qPCR. B2M, β-actin, and TBP were used as housekeeping genes for normalization. The significance of differences was assessed in two-tailed paired Student's t-tests. p, q ChIP with Tau-1 (p), UBTF (q), and IgG (p, q) antibodies. Results are obtained as described in (m). r, s Measurements of pools of NMPs and NTPs. Values of peak surface areas ratios between the endogenous nucleotide and its internal standard are shown. The data are the means of 9 independent measurements corresponding to three independent experiments performed in triplicate.
The PCR product was purified with a Qiagen kit, subjected to quality control and sequenced on the Hiseq Illumina platform. Overall, 678 million sequences aligned with the ENSEMBL v70 transcripts by Bowtie were analyzed by DESeq to identify shRNAs specifically depleted during the growth of the BLM-deficient cells. We rejected shRNAs that were highly toxic to the BLMcomplemented cells (decreasing their viability by more than 50%). Hits were selected on the basis of their relative abundance, which was significantly lower 20 days after infection than before transfection in BLM-deficient cells (at least 10-fold) but not in BLM-complemented cells. Transcriptomic analysis. The analysis was performed on BS-Ctrl (BLM) and BS-BLM cells  7. For each cell line, three independent total RNA samples were extracted using the RNeasy system (Qiagen).
Fragmented biotinylated antisense RNA was generated and hybridized to Affymetrix Human Genome U133 Plus 2. 0 Arrays. After hybridization, arrays were scanned following guidelines from Affymetrix (http://www. affymetrix. com). These arrays contain ∼54,000 probesets, representing ∼47,000 transcripts. Data were input into R and normalized with the robust multiarray average expression measure  67. Differential expression was then assessed with a linear model and the Bioconductor limma package  68. Differentially expressed genes were identified on the basis of a |fold change| ≥ 1. 5 and P < 0. 05. Transfection with siRNA and colony formation assay. Cells were transfected with a pool of four siRNAs specific for MAPT, UBTF, CDA or BLM (ON-TAR-GETplus SMART-pool, Dharmacon) or negative control siRNAs (ON-TARGETplus siCONTROL Non Targeting Pool, Dharmacon), in the presence of DharmaFECT 1 (Dharmacon).
Bands were visualized by chemiluminescence (Clarity Western ECL Substrate, Bio-Rad) with a ChemiDoc XRS+Molecular Imager and Image Lab software. Uncropped immunoblots are presented in Supplementary Fig. 5. The following antibodies were used for detection: mouse anti-Tau-5 (#ab80579, Abcam, dilution 1:1000), mouse anti-Tau-1 (clone PC1C6, #MAB3420, Millipore, dilution 1:1000), rabbit anti-CDA (#ab56053, Abcam, dilution 1:500), rabbit anti-BLM (#ab2179, Abcam, dilution 1:5000), rabbit anti-UBTF (#sc-9131, H-300, Santa Cruz, dilution 1:500), rabbit anti-γH2AX (S139) (#2577, Cell Signaling, dilution 1:500), mouse anti-GAPDH (#G8795, Sigma-Aldrich, dilution 1:10,000), rabbit anti-β-actin (#A2066, Sigma-Aldrich, dilution 1:10,000), horseradish peroxidase (HRP)-conjugated goat anti-rabbit IgG (#sc-2054, Cruz, dilution 1:5000), and HRP-conjugated goat anti-mouse IgG (#sc-2055, Santa Cruz, dilution 1:5000).
The cross-linking reaction was reversed by overnight incubation of the eluents with 0. 2 M NaCl at 65 °C, and the DNA was then treated with 1 μg of each RNase A and proteinase K, and recovered with a PCR purification kit (Qiagen). Approximately 5% of the bound DNA fraction was used for quantitative PCR. All primers used in qPCR analyses are detailed in Supplementary Table  6. Data were normalized against non-specific genomic DNA and relative to IgG. Cell viability assay. Cells were plated at a density of 2×10 3 per well in 96-well microplates, in triplicate. After 24 h, cells were left untreated or treated with various doses of each drug. After 72 h, cell viability was assessed with 3-(4,5-dimethyl-2thiazolyl)-2,5 diphenyl-2H-tetrazolium bromide (MTT; Life Technologies). Nucleotide determinations.
Differences in ultrafine anaphase bridge frequencies were assessed in two-tailed unpaired t-tests. Pearson correlation analysis was used to assess the association between CDA and MAPT transcript levels. P-values for nucleotide pool measurements were obtained in Mann-Whitney tests, with values of P < 0. 05 considered significant. Data availability. Raw and normalized sequencing (synthetic lethality screen) and transcriptomic data are available from the Institut Curie microarray dataset repository (http://microarrays. curie. fr/; Direct links: http://microarrays. curie. fr/ publications/ UMR3348/shRNA-based-bloom-syndrome-cells/ and http:// microarrays. curie. fr/publications /UMR3348/pyrimidine-bloom-syndrome/). MAPT and CDA expression levels were extracted from a collection of 34 human breast tumor cell lines (mostly from ATCC) established at the Translational Research Department of Institut Curie  45  , from the Gene Expression Omnibus (GEO) dataset no.
Acknowledgements We thank  David Gentien ,  Caroline Hégo ,  Philippe Huppé ,  Pierre Gestraud , and  Philippe La Rosa  for helping us with transcriptomic data analysis and online data deposition. We thank the  PICT-IBISA imaging facility  staff for assistance. We thank  Dr. Amy Virbasius  for helping to produce the pooled shRNA library. We thank the  TCGA network  for making available the high-throughput data. We thank  Hamza Mameri  for stimulating discussions. This work was supported by the  Institut Curie (Translational Cancer Research  grant and PICSysBio),  CNRS ,  Ligue Nationale Contre le Cancer (Comité de l'Essonne) , the  Agence Nationale de la Recherche  and the  Institut National du Cancer. E. B. S. was supported by grants from  Institut Curie and Ligue Nationale Contre le Cancer.
1. Although population responses to environmental variability have been extensively studied for many organisms, few studies have considered early-life stages owing to the inherent difficulties in tracking the fate of young individuals. However, young individuals are expected to be more sensitive to environmental stochasticity owing to their inexperience and lower competitive abilities. Thus, they are keys to understand demographic responses of an age-structured population to environmental variability. 2. In this study, we used capture-recapture modelling, based on a 49 year-long individualbased longitudinal monitoring dataset, to investigate climatic and population density effects on immature demographic parameters in a long-lived seabird, the wandering albatross. 3. We provide evidence that climate and population size affected both survival and recruitment age of young individuals although in different ways according to the trait.
Although there is an increasing need to predict the responses of populations to climate change for conservation purposes, investigating relationships between demographic processes and environmental conditions remains challenging for at least four reasons. First, such studies require long-term datasets which are difficult to run and maintain  (Clutton-Brock & Sheldon 2010). Second, studies focusing on young individuals raise additional challenges since survival of early-life stages is typically low  (Newton 1989 ) and accompanied by a high dispersal probability  (Clobert et al. 2001). Estimating early-life survival under such constraints requires both large sample sizes and large scale monitoring over extended periods. Third, studying the relationships between population dynamics and environmental variation is often difficult owing to the simultaneous effects of different ecological factors  (Gaillard et al.
In mid-April, June and August, nests were checked and the chick status recorded (alive/dead). During all visits, non-breeding individuals (mainly immatures) were searched for and their identity determined (from ring number) when possible. From mid-September to mid-October fledglings were ringed. Chicks that died on the colony between ringing and fledgling were noted during the first checks of the following breeding cycle and were excluded from our dataset (0Á3% of all individuals). Sex assignment was carried out as described in Appendix S1 (Supporting Information).
2012) , and indirectly, affecting primary productivity through large-scale impact on ocean mixed layer depth (Sall ee, Speer & Rintoul 2010). SAM data were selected from the online database of the British Antarctic Survey (http:// www. nerc-bas. ac. uk/icd/gjma/sam. html). At a regional scale, SSTA may determine the development and productivity of the whole trophic web, and hence may be used as a proxy of oceanographic conditions. SSTA have been related to demographic parameters for many seabird species in the Southern Ocean and elsewhere, probably through indirect mechanisms such as the After fledging, all birds remain at least 2 years continuously at sea (i. e. juvenile stage). Pre-recruitment state becomes observable from 3 years old when birds start to return to the colony and are now considered as immature.
From 6 years old, birds can pass into the breeding group of the population though recruitment represented by dashed arrows. Then mature birds irrespectively of age can transit between mature states: successful breeder (SB), failed breeder (FB), recruited non-breeder (NB), post successful breeder (PSB) and post-failed breeder (PFB). abundance of food resources  (Sandvik et al. 2005; Barbraud et al. 2012). SSTA data were obtained from the IRI Data Library http:/ iridl. ldeo. columbia. eduSOURCES/. NOAA/. NCEP/. EMC/. CMB/. GLOBAL/. Reyn_SmithOIv2/. monthly/. ssta/ First, we assessed the impact of selected covariates on prerecruitment survival considering their annual averages the previous year. We included the natal climatic conditions for juvenile survival since this parameter is expected to be affected by climatic conditions both during chick stage and after fledging.