dataesr/scientific-paragraphs-categorization huggingface dataset:
eu) [11]  is more comprehensive and gathers food composition data on all known polyphenols, either aglycones, glycosides or esters depending on how they are found in foods. Moreover, a new module of the Phenol-Explorer database contains data on the effects of cooking and food processing on polyphenol contents  [12]. These retention factors permit to take into account the effects of food cooking and processing measurements when calculating polyphenol intake and to improve the reliability of such measurements  [13]. Several descriptive papers on intakes of flavonoids and other polyphenols have been published using either the USDA databases  [14] [15] [16] , the Phenol-Explorer database  [17] [18] [19]  or custom databases  [20]. The purpose of the present work is to describe intake of all currently known dietary polyphenols in several European countries using the more comprehensive Phenol-Explorer database and especially applying polyphenol-specific retention factors.
Data used in the present work were derived from the EPIC calibration study, in which a 24-h dietary recall (24-HDR) was administered. The cohort comprises an 8 % (n = 36,994) random sample stratified by age, sex, and center, and weighted for expected cancer cases in each stratum of the whole EPIC cohort  [23]. After exclusion of 941 subjects who were aged younger than 35 years or older than 74 years because of low participation in these age categories, and 16 individuals due to incomplete dietary information, 36,037 participants were included in the present analysis. Approval for the study was obtained from ethical review boards of the International Agency for Research on Cancer (IARC) and from all local participating institutions. All participants provided written informed consent.
Dietary and lifestyle information Dietary assessment was performed with a single 24-HDR using specialized software (EPIC-Soft)  [24] , and administered in a face-to-face interview, except in Norway, where it was obtained by telephone interview  [25]. Data on age, as well as on body weight and height, were self-reported by the participants during the 24-HDR interview. Data on other lifestyle factors, including educational level, physical activity, and smoking history, were collected at baseline through standardized questionnaires  [23, 26]. The mean time interval between completion of the baseline questionnaire measures and the 24-HDR interview varied by country, and ranged from the same day to 3 years later  [23].
Food composition database on polyphenols The Phenol-Explorer database provides data on 502 polyphenol compounds in 452 plant-based foods collected from 638 scientific peer-reviewed articles  [11]. All animal foods that contain none or only traces of plant polyphenols were excluded. Phenol-Explorer contains data on four main polyphenol classes: flavonoids, phenolic acids, stilbenes, and lignans, as well as on a number of miscellaneous minor polyphenols that include tyrosols, alkylphenols (mainly alkylresorcinols), and alkylmethoxyphenols among others, described in the Phenol-Explorer database and in this manuscript as ''other polyphenols''  [11]. Total polyphenol content was calculated as the sum of the contents of individual compounds expressed in mg/100 g food fresh weight. The data used in the present study were mainly acquired by chromatography without previous hydrolysis of the food extracts except for a few polyphenols bound to the food matrix.
Lignans in all foods, ellagic acid in walnuts, and hydroxycinnamic acids in cereals, legumes, and olives were quantified by chromatography after previous basic or acid hydrolysis. Proanthocyanidin dimers were measured as individual compounds by chromatography without prior hydrolysis, whereas other proanthocyanidin oligomers (trimers, 4-6 and 7-10 oligomers) and proanthocyanidin polymers were measured as mixtures by normal-phase HPLC. Overall data on 463 individual polyphenols were used. Some missing polyphenol content values for orange fruit and breakfast cereals were extrapolated from orange juice and wheat flour, respectively. The polyphenol content of different types of coffee, ''American'' or filtered diluted coffee and espresso, reported in the 24-HDR, was estimated by multiplying the polyphenol contents of ''normal'' filtered coffee from the Phenol-Explorer database by 0.
4 and 2, respectively  [27, 28]. When the type of herbal tea was unspecified in the 24-HDRs, the polyphenolic composition of a mix of herbal tea was applied on a country-bycountry basis. The effect of food cooking and processing was accounted for by applying polyphenol-specific retention factors from Phenol-Explorer  [12]  to 24-HDR foods wherever relevant. Phenol-Explorer contains data on 1253 aggregated retention factors, including data on 161 polyphenols and 35 processes, such as domestic cooking, storage, and industrial processing.
Discussion In the current study, dietary intake of total polyphenols, polyphenol classes, and individual polyphenols was estimated across 10 European countries, using a standardized 24-HDR and the Phenol-Explorer database, allowing easy comparisons between groups of individuals and countries. Main food sources were also identified, and the influence of some socio-demographic characteristics was assessed. Most previous descriptive studies on polyphenols used the USDA food composition data to document intake of approximately 50 polyphenol aglycones  [14-16, 20, 29-31]. In the current study, intakes of 437 polyphenols, either glycosides, esters or aglycones are described. This study follows one of our earlier studies in which intakes of 337 polyphenols in the French SUpplementation en VItamines et Mineraux AntioXydants (SU.
VI. MAX) cohort were reported  [17]. In addition to the large number of polyphenols and diversity of countries considered, the present study is also the first one to take into account the effects of cooking and processing on polyphenol contents in foods by applying retention factors recently collected in the Phenol-Explorer database  [12]. In our previous studies in EPIC, a common retention factor for each cooking method (boiled, fried, and microwaved) was eventually applied irrespective of the polyphenol compound and food considered  [15, 31]. This simple approach could only lead to a crude estimation of the effects of cooking on polyphenol intake. Even after applying retention factors, mean polyphenol intakes in our French EPIC centers (1166-1449 mg/day) were slightly   [17] , indicating that the use of retention factors does not seem to have high impact on the estimated total polyphenol intake.
This can be explained by the fact that these retention factors mainly concern vegetables and legumes  [12]  which were not major contributors to polyphenol intake in the present or previous studies  [14, 15, 17, 20]. It is still important to highlight that polyphenol losses due to cooking and food processing can have a great impact on the intake of some individual polyphenols mainly present in vegetables, such as quercetin 3,4 0 -Odiglucoside that is only present in onions  [1]. Using a single 24-HDR for each of the 36,037 subjects across 10 European countries in EPIC, 437 different individual polyphenols have been documented. Intakes of 347, 337, and 290 polyphenols have been reported utilizing Food Frequency Questionnaires and the Phenol-Explorer database in the Polish arm of the HAPIEE (Health, Alcohol and Psychosocial factors In Eastern Europe) study  [19] , in the SU.
Another example is delphinidin 3-Orutinoside (anthocyanidin subclass) only found in blackcurrants; its intake varied from 7. 0 mg/day (rank 31) in men from non-MED countries to 0. 04 mg/day (rank 245) in men from MED countries. This illustrates the need for further detailed analyses of polyphenols in foods not commonly consumed in Western countries and poorly described in the Phenol-Explorer or USDA databases, to document their intake across different geographical areas of the world. Our results show a wide range of total polyphenol intake and a south-to-north geographical gradient. Mean intake was as much as three times higher in men from Aarhus-Denmark (1786 mg/day) than in women from Greece (584 mg/day). When stratified by regions, total polyphenol   intake in the non-MED countries was higher than that in the MED countries.
Isoflavonoid intake is very low in European  [17, 20, 36]  and other Western populations  [14, 16]  in comparison with Asian populations  [37] , but the intake in the UK healthconscious group was quite large, due to the high consumption of soya products in this mainly vegetarian cohort   [36]  and the use of flour fortified with soya protein in the United Kingdom  [38]. Lignans are minor contributors to total polyphenol intake as reported earlier (\0. 7 %)  [17, 18, 20]. We estimated the intake of 29 lignans, including those usually assessed in other cohort studies, such as lariciresinol, matairesinol, pinoresinol, and secoisolariciresinol  [36, 39]. One of the three most widely consumed lignans was sesamolin, a lignan not considered in previous studies on polyphenol intake. This highlights the importance of using the most comprehensive databases when evaluating the relationships between lignan/polyphenol intake and health outcomes.
Intakes of other polyphenols were almost negligible (\0. 7 % of total polyphenol). The present study shows a number of strengths, in particular the large number of EPIC participants, the use of the Phenol-Explorer database as the most comprehensive food MED Mediterranean a Means and standard error (s. e. ) were computed using general linear models adjusted for sex, age, and center and weighted by season and weekday of recall composition database for polyphenols, the uniform application of retention factors to take into account the effects of cooking and food processing on polyphenol contents in foods, and the use of a standardized 24-HDR in all participants, allowing to easily compare results across countries. However, our study has some limitations. Our results cannot be totally generalizable, since not all the EPIC cohorts are population-based  [21, 22].
Acknowledgments This study was supported by the  Institut National du Cancer, Paris  ( INCa  Grants  2011-105 ), and the  Wereld Kanker Onderzoek Fonds  ( WCRF NL 2012/604 ). The EPIC study was supported by the  European Commission :  Public Health  and Consumer Protection Directorate 1993-2004, Research Directorate-General 2005; the  French National Cancer Institute (L'Institut National du Cancer; INCA)  (Grant Number  2009-139 ); Ligue contre le Cancer; the  Institut Gustave Roussy ; the  Mutuelle Generale de l'Education Nationale ; the  Institut National de la Santeet de la Recherche Medicale (INSERM) ; the  German Cancer Aid ; the  German Cancer Research Center (DKFZ) ; the  German Federal Ministry of Education and Research ; the  Danish Cancer Society ; The  Danish Council for Strategic Research; Health Research Fund (FIS)  of the  Spanish Ministry of Health  (RTICC ( DR06/0020/0091 ); the participating regional governments from  Asturias, Andalucı ´a, Murcia, Navarra  and  Vasco Country  and the  Catalan Institute of Oncology of Spain; Cancer Research UK; Medical Research Council, UK ; the  Stroke Association, UK ;  British Heart Foundation ;  Department of Health, UK ;  Food Standards Agency, UK ; the  Wellcome Trust, UK ; the  Hellenic Health Foundation (Greece) ;  Italian Association for Research on Cancer ;  Compagnia San Paolo, Italy ;  Dutch Ministry of Public Health, Welfare and Sports ;  Dutch Ministry of Health ; Dutch Prevention Funds;  LK Research Funds; Dutch ZON (Zorg Onderzoek Nederland) ;  World Cancer Research Fund (WCRF) ;  Statistics Netherlands  (the  Netherlands) ;  Swedish Cancer Society; Swedish Scientific Council; Regional Government of Skane, The County Council of Va ¨sterbotten, Sweden ;  Nordforsk-Centre of Excellence programme ; some authors are partners of ECNIS, a network of excellence of the 6th Framework Program of the  European Commission.
1b ). Next, we screened an independent T-ALL cohort, comprising of 1,084 patients and identified two additional T-ALL patient samples with an identical t(2;14)(q22;q32) translocation. Taken together, we identified a novel and rare, but recurrent translocation involving ZEB2 and BCL11B in human T-ALL. ZEB2 levels are elevated in human immature/ETP-ALL. Microarray-based genome-wide expression studies have shown that T-ALL encompasses distinct molecular groups with defined gene expression signatures. Several key genes, such as LYL1, MEF2C and HHEX, show elevated levels of gene expression in the immature/ETP-ALL subclass  [3] [4] [5] [6]  as compared with other T-ALL subtypes. Gene expression profiling data were available for one of the four t(2;14)(q22;q32) cases (TL88)  4  , and showed an immature/ETP-ALL gene signature.
For IHC details see Supplementary Table  4. Flow cytometry. Cells were analysed by LSRII (BD Biosciences) and FACSDiva or FlowJo software (BD Biosciences). Cell debris and cell aggregates were gated out, dead cells were discarded using Propidium Iodide or the fixable Viability Dye eFluro506 (eBioscience). Antibodies used for flow cytometry are listed in Supplementary Table  5. Intracellular stainings were done using BD Cytofix/ Cytoperm kit (BD Bioscience) according to the manufacturer guidelines. Cell culture. Primary mouse thymic lymphoma cell lines were generated according to the previously published protocols  46. In short, thymus tumours were dissected under aseptic conditions and plated in RPMI medium supplemented with 10% heat-inactivated fetal bovine serum (Sigma), penicillin (100 U ml À 1 )-streptomycin (100 mg ml À 1 ), 2 mM L-glutamine (Gibco), 0.
qRT-PCRs were performed using the LightCycler 480 SYBR Green I Master (Roche), monitored on a LichtCycler 480 system (Roche) and analysed using qBase software from Biogazelle. Gene expression was standardized against housekeeping genes b-actin, glyceraldehyde-3-phosphate dehydrogenase (Gapdh), RPL13 and TBP. All primers used are listed in Supplementary Table  6. In the qRT-PCR analysis of human T-ALL patients, results of two mature T-ALL and one immature T-ALL cases were excluded because of high variability within the housekeeper genes or between technical replicates, most probably due to low RNA quality. Gene expression profiling. For human T-ALL patients, expression data of previously published gene expression profiling arrays of two independent cohorts of T-ALL patients (one paediatric and one adult cohort) was used.
The first cohort consisted of bone marrow lymphoblast samples from 64 paediatric T-ALL patients (15 immature, 25 TAL/LMO, 17 TLX1/TLX3 and 7 HOXA), which were collected with informed consent according to the declaration of Helsinki from Saint-Louis Hospital (Paris, France). Transcriptome profiling was performed on GeneChip Human Genome U133 2. 0 Plus arrays (Affymetrix) according to the standardized procedures at the IGBMC (www. igbmc. fr, Strasbourg, France) and microarray data files are available from ArrayExpress under accession no. E-MTAB-604 (ref. 16). The second cohort consisted of 57 cryopreserved lymphoblast samples, which were provided by the Eastern Cooperative Oncology Group. All samples were collected in clinical trials E2993 and C10403. Gene expression profiling was performed using the HumanHT-12 v4 Expression BeadChip (Illumina) and microarray data files are available from the Gene Expression Omnibus accession nr GSE33469 (ref.
17). Expression data of the mi-R141/200c cluster were obtained via a quantitative PCR-based microRNA profilering study on 15 immature and 25 mature primary T-ALLs  48. From the mouse leukaemia, RNA was isolated using the miRNeasy mini kit with DNA digestion on-column (Qiagen). RNA concentration was measured on the NanoDrop 1000 Spectrophotometer followed by RNA quality assessment by use of the Experion Automated Electrophoresis System according to the manufacturer's instructions (Bio-Rad). Next, RNA samples were profiled for gene expression analysis on SurePrint G3 Mouse 8 Â 60 K Microarrays according to the manufacturer's instructions (Agilent Technologies). Normalization of gene expression data was done by quantile normalization using R. Differential gene expression analysis was performed using fold change analysis and P-value calculation based on unpaired t-test.
Microarray data files are available from the Gene Expression Omnibus accession number GSE62653. Gene set enrichment analysis was executed against annotated gene set of a 500-probe set enriched in human immature/ETP-ALL. Gene profiling was originally performed on three P53/R26 þ / þ vs three P53/R26-Zeb2 tg/tg thymic tumours, however, one of the control P53/R26 þ / þ had spontaneously high levels of Zeb2 that occurred and was therefore excluded from the control group. In all aspects, the phenotype of this one control mouse tumour (decreased tumour latency, cKit expression, high Lyl1, Mef2c, Hhex and Il7r expression) resembled the phenotype of the Zeb2overexpressing tumours, indicating that similarly high levels of Zeb2 can be spontaneously observed in human and mouse immature T-cell lymphoblastic leukaemias (Supplementary Fig.
Acknowledgements This work was supported by the  Fund for Scientific Research-Flanders  (FWO-V;  G056813N  to JJH and  3G002711  to T. T. ) as well as the  Belgian Federation for the Study Against Cancer (BFAC)  and the  European Hematology Association  (EHA;  2009/26 ) and the  Australian NHMRC  grant  1047995. The work is part of the DevRepair ( P7/07 )  IAP-VII network. P. V. V. and T. T. are the recipients of an Odysseus type II grant. S. G. , T. T. , P. V. V. and P. R. are postdoctoral fellows and J. V. derM. is a PhD student supported by the  FWO-V. K. C. -B. is financially supported by The  Children Cancer Free Foundation (Stichting Kinderen Kankervrij ;  KIKA2008-029 ). L. H. and K. D. are funded by  PhD grants of the Agency for Innovation by Science and Technology (IWT). D. H. was supported by a visiting professorship awarded by the  Royal Dutch Academy of Arts and Sciences to work at Erasmus MC, Rotterdam.
Materials and methods A process of debate was carried out in two phases in a group of pulmonologists who are specialists in asthma or COPD. The participating physicians were selected based on their participation in the Spanish working groups and in the Spanish guidelines of asthma or COPD. In the first phase, the participants were sent a structured questionnaire developed by two coordinators of the study (MM and VP), which was composed of 22 items on the profile of the specialists and their opinion on different aspects of ACOS: epidemiology, diagnosis, and treatment. The data obtained in the questionnaire were analyzed by means of descriptive statistics (percentages and mean values) before undergoing the second phase in order to have, a priori, some orientation as to the opinion of the participants in the debate.
Contextual data collected concurrently with molecular samples are critical to the use of metagenomics in the fields of marine biodiversity, bioinformatics and biotechnology. We present here Marine Microbial Biodiversity, Bioinformatics and Biotechnology (M2B3) standards for "Reporting" and "Serving" data. The M2B3 Reporting Standard (1) describes minimal mandatory and recommended contextual information for a marine microbial sample obtained in the epipelagic zone, (2) includes meaningful information for researchers in the oceanographic, biodiversity and molecular disciplines, and (3) can easily be adopted by any marine laboratory with minimum sampling resources. The M2B3 Service Standard defines a software interface through which these data can be discovered and explored in data repositories.
Second, the M2B3 Service Standard defines and describes a software interface through which hosts of marine data, such as the public data repositories, can present their marine data holdings. The resulting standards were used by marine sampling stations and cruises participating in the Micro B3 sampling campaign, Ocean Sampling Day (OSD)  [5] , a simultaneous world-scale sample and contextual data collection to investigate dynamics and functions of marine microbial diversity. We believe that our work will also be of value to other marine surveys in the future.
M2B3 Reporting standard compliance It is worth noting that if all mandatory descriptors from the M2B3 Reporting Standard are reported by a sampling station or a cruise, then a data management centre is frequently able to infer additional descriptors available from the public record. In one example, relating to OSD, the Micro B3 Information System (Micro B3 IS)  [10]  and the OSD coordinators are able to infer additional descriptors available from public data archives, such as the Data Publisher for Earth and Environmental Science (PANGAEA) for environmental data  [11, 12]  and the European Nucleotide Archive (ENA) for molecular data  [13, 14]. The additional information can be added post hoc for all samples acquired within the OSD campaign since the campaign has standardised and published sampling protocols and a Registry of OSD stations and cruises  [15].
Free text Inorganic carbon removed by acidification We define the M2B3 Service Standard as a standardised set of informatics methods through which marine data can be discovered in data resources. The six interoperability descriptors are presented by a compliant data resource using a programmatic service interface that follows Open Geospatial Consortium (OGC) standards, the Web Map Service (WMS), Web Feature Service (WFS) and/or the OpenSearch protocol. To date, the European Nucleotide Archive, European Ocean Biogeographic Information System (EurOBIS)  [19, 20] , Micro B3 Information System, PANGAEA and SeaDataNet  [21]  have committed to supporting the M2B3 Service Standard for OSD data.
Acknowledgements We gratefully acknowledge contribution and comments from participants of the Micro B3 Use Case Workshop [22], Micro B3 Best Practice Workshop [23] and  Micro B3 General Assembly. This project has received funding from the  European Union 's  Seventh Framework Programme  for research, technological development and demonstration (Joint Call OCEAN. 2011-2: Marine microbial diversitynew insights into marine ecosystems functioning and its biotechnological potential)  under grant agreement no  287589.
The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are available through the International Pseudomonas Consortium Database (http://ipcd. ibis. ulaval. ca/). Here, we present our strategy and the results that emerged from the analysis of the first 389 genomes. With as yet unmatched resolution, our results confirm that P. aeruginosa strains can be divided into three major groups that are further divided into subgroups, some not previously reported in the literature. We also provide the first snapshot of P. aeruginosa strain diversity with respect to antibiotic resistance.
The International P. aeruginosa Consortium (IPC) The science of genomics applied to opportunistic infections via whole bacterial genome sequencing promises to transform the practice of clinical microbiology. With rapidly falling costs and turnaround times, microbial genome sequencing and analysis are becoming a viable strategy to understand CF lung infections as well as other human and animal infections. The objective of the International P. aeruginosa Consortium (IPC) is to sequence a minimum of 1000 P. aeruginosa genomes, link the data to the Pseudomonas Genome Database (www. pseudomonas. com, Winsor et al. , 2011) , integrate the information with the Canadian CF registry and develop a user-friendly pipeline to study these genomes. Genomics data will support molecular epidemiology for the surveillance of outbreaks and has the potential for future genotypic antimicrobial susceptibility testing as well as the identification of novel therapeutic targets and prognostic markers.