dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors would like to thank  Reiner Tretter  ( Senior Manager Biostatistics, Fresenius Kabi, Germany ) and  Dr. Dirk Dormann  (Vice President Medical Affairs I. V. Fluids ,  Fresenius Kabi, Germany ) for supporting the preparation of this manuscript. The authors would like to thank all PHOENICS investigators for their contribution to the conduct of the study:  Prof. Dr. Klimscha , Vienna, Austria;  Dr. Kahn, Brussels ,  Belgium ;  Dr. Ongenae Gent ,  Belgium ;  Dr. Stessel Hasselt ,  Belgium ;  Dr. Baronica , Zagreb, Croatia;  Dr. Persec , Zagreb, Croatia;  Dr. Vymazal ,  Prague, Czech Republic ;  Dr. Tyll ,  Prague, Czech Republic ;  Dr. Novacek ,  Kolin, Czech Republic ;  Prof. Cholley , Paris, France;  Dr. Mertes , Strasbourg, France;  Dr. Boselli ,  Bourgoin Jallieu , France;  Dr.
Data sources We performed two-sample MR using individual-level data from 130 957 European-ancestry women (69 838 with invasive breast cancers; 6667 with in situ breast cancers; 54 452 controls) from 76 Breast Cancer Association Consortium (BCAC) studies (table 1, online supplemental table S1)(outcome dataset). ] [11]  Instruments were single-nucleotide polymorphisms (SNPs) associated in the UK Biobank GWAS with overall physical activity (all movement), vigorous physical activity, or sedentary time (online supplemental table S2).
Outcomes We estimated breast cancer risk overall, by menopausal status, and by case-groups defined by molecular/morphological subtype, stage, or grade at diagnosis. We used BCAC clinical data to assign case-groups according to hypotheses arising from the literature. We defined separate case/control groups for invasive pre/peri-menopausal (n=23 999 cases; 17 686 controls) and postmenopausal (n=45 839 cases; 36 766 controls) breast cancers. We used age at diagnosis/interview (</≥50 years) to assign missing menopausal status (27%). We examined subtypes separately by hormone-receptor (HR) status (ER±n=46 528/11 246; PR±n=34 891/16,432) and HER2 status (±n=6945/33 214), and jointly including HER2-enriched (ER-/PR-/HER2+; n=1974) and triple-negative (ER-/PR-/HER2-; n=4964) cancers. We examined invasive ductal/lobular cancers (n=42 223/8,795), ductal carcinoma in situ (n=3510), and risk by stage (stage 1, n=17 583; stage 2, n=15 992; stages 3/4, n=4553) and grade (well/moderately differentiated, n=34 647; poorly/ undifferentiated, n=16 432).
SNP-exposure (UK Biobank) and SNP-outcome (BCAC) associations We extracted or derived estimates of association (beta coefficients, standard errors (SEs)) between SNPs and exposures from the UK Biobank GWAS publications, 9 10 standardised to refer to the trait-increasing allele. Where required,  10  we converted estimates to per-SD changes in activity/sedentary time using UK Biobank activity data. We determined genotypes in BCAC using the OncoArray, an Illumina custom array, and imputed using IMPUTE2. 15 We harmonised UK Biobank and BCAC data so SNP-exposure and SNP-outcome estimates related to the same allele, using allele frequency information to resolve strand-ambiguous SNPs where.
Original research possible (ie, unless allele frequencies were 45%-55%). For each SNP, we derived trait-specific effect-allele dosages (range 0-2) by summing alleles predicting more activity (activity instruments) or sedentary time (sitting instrument). We assessed the association between each SNP and each outcome from individual-level BCAC data by fitting logistic regression models, adjusted for age at diagnosis (cases) or interview (controls), country, and 10 principal components of genetic population structure (accounting for genetic substructure within Europeans), obtaining beta coefficients and SEs for use in the MR analysis. Table  1  summarises the BCAC studies and participants.
9. We checked whether SNPs are associated with other relevant traits (possible confounders, adiposity, cancer risk) or gene expression using the National Human Genome Research Institute-European Bioinformatics Institute-(NHGRI-EBI) GWAS Catalogue  23  and PhenoScanner. 24 25 ata preparation and analyses were performed using R software (R Foundation for Statistical Computing, Vienna), including the 'Mendelian Randomization'  18  and 'MR-PRESSO' packages. 22 Statistical power was calculated using the mRnd Mendelian randomisation power calculation online tool. 26 Further details are in online supplemental methods (Online Resource).
Original research cancer risk, and less power for other exposure/outcome combinations; online supplemental table  S13 ), there were no larger datasets available to increase power. The UK Biobank studies are the only GWAS of accelerometer-assessed movement, which substantially decreases measurement error compared with selfreport. Measurement error in assessing genotype is typically very low (often estimated as less than 1%  29 30  ). The UK Biobank GWAS which identified our instruments used wrist-worn accelerometers, which may not capture ambulation as well as hip-worn accelerometers  31  ; while this may have slightly affected precision, no superior data are available. Gene-exposure associations were estimated from a population (UK Biobank) including men, but no strong evidence of sexual dimorphism was reported in UK Biobank, 9 so we assume that SNP-exposure estimates adequately reflect associations in women.
Fomento de la Investigación Clínica Independiente ,  Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and Grant FEDERInnterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the  Dietmar-Hopp Foundation , the  Helmholtz Society  and the  German Cancer Research Center (DKFZ). CBCS is funded by the  Canadian Cancer Society  (grant #  313404 ) and the  Canadian Institutes of Health Research. CCGP is supported by funding from the  University of Crete. The CECILE study was supported by  Fondation de France ,  Institut National du Cancer (INCa) ,  Ligue Nationale contre le Cancer ,  Agence Nationale de Sécurité Sanitaire, de l'Alimentation, de l'Environnement et du Travail (ANSES) ,  Agence Nationale de la Recherche (ANR). The CGPS was supported by the  Chief Physician Johan Boserup and Lise Boserup Fund , the  Danish Medical Research Council , and  Herlev and Gentofte Hospital.
The opinions, findings, and conclusions expressed herein are those of the author(s) and do not necessarily reflect the official views of the  State of California, Department of Public Health , the  National Cancer Institute , the  National Institutes of Health , the  Centers for Disease Control and Prevention  or their Contractors and Subcontractors, or the  Regents of the University of California , or any of its programs. The University of Westminster curates the DietCompLyf database funded by  Against Breast Cancer Registered Charity  No. 1121258  and the  NCRN. The coordination of EPIC is financially supported by the  European Commission (DG-SANCO)  and the  International Agency for Research on Cancer. The national cohorts are supported by:  Ligue Contre le Cancer ,  Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale ,  Institut National de la Santé et de la Recherche Médicale (INSERM) (France) ;  German Cancer Aid ,  German Cancer Research Center (DKFZ) ,  Federal Ministry of Education and Research (BMBF) (Germany) ; the  Hellenic Health Foundation , the  Stavros Niarchos Foundation (Greece) ;  Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy) ;  Dutch Ministry of Public Health, Welfare and Sports (VWS) ,  Netherlands Cancer Registry (NKR) ,  LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland) ,  World Cancer Research Fund (WCRF) ,  Statistics Netherlands  (The Netherlands);  Health Research Fund (FIS) ,  PI13/00061  to Granada,  PI13/01162  to  EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC  ( RD06/0020 ) (Spain);  Cancer Research UK  ( 14136  to  EPIC-Norfolk ;  C570/A16491  and  C8221/A19170  to  EPIC-Oxford ),  Medical Research Council  ( 1000143  to  EPIC-Norfolk ,  MR/M012190/1  to  EPIC-Oxford) (United Kingdom ).
The ESTHER study was supported by a grant from the  Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the  German Cancer Aid (Deutsche Krebshilfe ). FHRISK and PROCAS are funded from  NIHR  grant  PGfAR   0707-10031. DGE, AH and WGN are supported by the  NIHR Manchester Biomedical Research Centre  ( IS-BRC1215-20007 ). The  GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer)  is supported by the  German Cancer Aid  (grant no  110837  and  70114178 , coordinator:  Rita K. Schmutzler ,  Cologne ) and the  Federal Ministry of Education and Research, Germany  (grant no  01GY1901 ). This work was also funded by the  European Regional Development Fund and Free State of Saxony, Germany (LIFE -Leipzig Research Centre for Civilization Diseases , project numbers  713-241202 ,  713-241202 ,  14505/2470 ,  14575/2470 ).
Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between  Stockholm County Council and Karolinska Institutet , the  Swedish Cancer Society , The Gustav V Jubilee foundation and Bert von Kantzows foundation. The KARMA study was supported by  Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (VTR) of  Kuopio University Hospital  grants,  Cancer Fund of North Savo , the  Finnish Cancer Organizations , and by the strategic funding of the  University of Eastern Finland. LMBC is supported by the 'Stichting tegen Kanker'. DL is supported by the  FWO. The MABCS study is funded by the  Research Centre for Genetic Engineering and Biotechnology "Georgi D.
Efremov", MASA. The MARIE study was supported by the  Deutsche Krebshilfe e. V. [ 70-2892-BR I, 106332 ,  108253 ,  108419 ,  110826 ,  110828 ], the  Hamburg Cancer Society , the  German Cancer Research Center (DKFZ)  and the  Federal Ministry of Education and Research (BMBF) Germany  [ 01KH0402 ]. MBCSG is supported by grants from the  Italian Association for Cancer Research (AIRC). The MCBCS was supported by the  NIH  grants  R35CA253187 ,  R01CA192393 ,  R01CA116167 ,  R01CA176785  a  NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer  [ P50CA116201 ], and the  Breast Cancer Research Foundation. The Melbourne Collaborative Cohort Study (MCCS) cohort recruitment was funded by  VicHealth  and  Cancer Council Victoria. The MCCS was further augmented by  Australian National Health and Medical Research Council  grants  209057 , 396414 and 1074383 and by infrastructure provided by  Cancer Council Victoria.
Cases and their vital status were ascertained through the  Victorian Cancer Registry  and the  Australian Institute of Health and Welfare , including the  National Death Index  and the Australian Cancer Database. The MEC was supported by  NIH  grants  CA63464 ,  CA54281 ,  CA098758 ,  CA132839  and  CA164973. The MISS study is supported by funding from  ERC -2011-294576 Advanced grant,  Swedish Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foundation ,  Gunnar Nilsson. The MMHS study was supported by  NIH  grants  CA97396 ,  CA128931 ,  CA116201 ,  CA140286  and  CA177150. MSKCC is supported by grants from the  Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer Genetics Initiative. The work of MTLGEBCS was supported by the  Quebec Breast Cancer Foundation , the  Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" program  -grant #  CRN-87521  and the  Ministry of Economic Development, Innovation and Export Trade  -grant #  PSR-SIIRI-701.
The content of this manuscript does not necessarily reflect the views or policies of the  National Cancer Institute  or any of the collaborating centers in the  Breast Cancer Family Registry (BCFR) , nor does mention of trade names, commercial products, or organizations imply endorsement by the  USA Government  or the BCFR. The  Carolina Breast Cancer Study (NCBCS)  was funded by  Komen Foundation , the  National Cancer Institute  ( P50 CA058223 ,  U54 CA156733 ,  U01 CA179715 ), and the  North Carolina University Cancer Research Fund. The NHS was supported by  NIH  grants  P01 CA87969 ,  UM1 CA186107 , and  U19 CA148065. The NHS2 was supported by  NIH  grants  UM1 CA176726  and  U19 CA148065. The ORIGO study was supported by the  Dutch Cancer Society  ( RUL 1997-1505 ) and the  Biobanking and Biomolecular Resources Research Infrastructure  ( BBMRI-NL CP16 ).
The PBCS was funded by  Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. Genotyping for PLCO was supported by the  Intramural Research Program  of the  National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. The PLCO is supported by the  Intramural Research Program of the Division of Cancer Epidemiology and Genetics  and supported by contracts from the  Division of Cancer Prevention, National Cancer Institute, National Institutes of Health. The POSH study is funded by  Cancer Research UK  (grants  C1275/A11699 ,  C1275/C22524 ,  C1275/A19187 ,  C1275/A15956  and  Breast Cancer Campaign   2010PR62 ,  2013PR044. The RBCS was funded by the  Dutch Cancer Society  ( DDHK 2004-3124 ,  DDHK 2009-4318 ). The SBCS was supported by  Sheffield Experimental Cancer Medicine Centre and Breast Cancer Now Tissue Bank.
SEARCH is funded by  Cancer Research UK  [ C490/A10124 ,  C490/A16561 ] and supported by the  UK National Institute for Health Research Biomedical Research Centre  at the  University of Cambridge. The  University of Cambridge  has received salary support for PDPP from the  NHS in the East of England through the Clinical Academic Reserve. The Sister Study (SISTER) is supported by the  Intramural Research Program  of the  NIH, National Institute of Environmental Health Sciences  ( Z01-ES044005  and  Z01-ES049033 ). The  Two Sister Study  ( 2SISTER ) was supported by the  Intramural Research Program  of the  NIH, National Institute of Environmental Health Sciences  ( Z01-ES044005  and  Z01-ES102245 ), and, also by a grant from  Susan G. Komen for the Cure , grant  FAS0703856. SKKDKFZS is supported by the  DKFZ.
The SMC is funded by the  Swedish Cancer Foundation  and the  Swedish Research Council  ( VR 2017-00644 ) grant for the  Swedish Infrastructure for Medical Populationbased Life-course Environmental Research (SIMPLER). The SZBCS was supported by Grant  PBZ_KBN_122/P05/2004  and the program of the  Minister of Science and Higher Education  under the name " Regional Initiative of Excellence " in 2019-2022 project number  002/RID/2018/19  amount of financing  12 000 000 PLN. The TNBCC was supported by: a  Specialized Program of Research Excellence (SPORE) in Breast Cancer  ( CA116201 ), a grant from the  Breast Cancer Research Foundation , a generous gift from the  David F. and Margaret T. Grohne Family Foundation. UBCS was supported by funding from  National Cancer Institute (NCI)  grant  R01 CA163353  (to N.
J. Camp) and the  Women's Cancer Center at the Huntsman Cancer Institute (HCI). Data collection for UBCS was supported by the  Utah Population Database (UPDB)  and  Utah Cancer Registry (UCR). The UPDB is supported by  HCI  (including the  Huntsman Cancer Foundation ),  University of Utah program in Personalized Health and Center for Clinical and Translational Science , and  NCI  grant  P30 CA42014. The UCR is funded by the  NCI's SEER Program , Contract No. HHSN261201800016I , the  US Center for Disease Control and Prevention's National Program of Cancer Registries , Cooperative Agreement No. NU58DP0063200 , the  University of Utah  and  Huntsman Cancer Foundation. The UCIBCS component of this research was supported by the  NIH  [ CA58860 ,  CA92044 ] and the  Lon V Smith Foundation  [LVS39420].
The UKBGS is funded by  Breast Cancer Now  and the  Institute of Cancer Research (ICR), London. ICR  acknowledges  NHS  funding to the  NIHR Biomedical Research Centre. The UKOPS study was funded by  The Eve Appeal (The Oak Foundation ) and supported by the  National Institute for Health Research University College London Hospitals Biomedical Research Centre. The  USRT Study  was funded by  Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. RMM is a  National Institute for Health Research Senior Investigator  ( NIHR202411 ). RMM is supported by a  Cancer Research UK  ( C18281/A19169 ) programme grant (the  Integrative Cancer Epidemiology Programme). RMM is also supported by the  NIHR Bristol Biomedical Research Centre  which is funded by the  NIHR  and is a partnership between  University Hospitals Bristol and Weston NHS Foundation Trust  and the  University of Bristol.
RMM is affiliated with the  Medical Research Council Integrative Epidemiology Unit at the University of Bristol  which is supported by the  Medical Research Council  ( MC_UU_00011/1 ,  MC_UU_00011/3 ,  MC_UU_00011/6 , and  MC_UU_00011/4 ) and the  University of Bristol. Department of Health and Social Care  disclaimer: The views expressed are those of the authors and not necessarily those of the  NHS , the  NIHR  or the  Department of Health and Social Care. DGE, AH and WGN are supported by the  NIHR Manchester Biomedical Research Centre  ( IS-BRC-1215-20007 ). BML is funded by the  Victorian Cancer Agency  ( MCRF-18005 ).
CLOuD9 The CLOud9 design was adapted from the original study  (71)  with the following modifications. The HEK-CLOuD9 cell line was generated to stably express Staphylococcus pyogenes (SP) and S. aureus nuclease (SA) deficient Cas9, respectively fused to the dimerizable PYL1 and ABI1 domains, but devoid of their guide RNA (gRNA) scaffold sequence. The U6 promoters and gRNA scaffold sequences were deleted from both parental plasmids EF1a-dCas9-PYL1-P2A-Hygro and dCas9-ABI-P2A-Puro lentiviral cloning vectors (System Biosciences SBI, obtained from Dr Kevin C. Wang, Stanford University School of Medicine). The resulting lentiviral constructs were used to infect parental HEK293 cells (ATCC) at a MOI of 1. 5, followed by puromycin and hygromycin selection for a week. Genomic integration was confirmed by PCR and protein expression of dCas9 was validated by Western-blotting using HA/Flag antibodies (data not shown).
U6 promoters and gRNA scaffold sequences specific for SA and SP dCas9 were respectively subcloned from the original dCas9-ABI-P2A-Puro plasmid and from the PX459 plasmid (Addgene #62988) into pBluescript SK (-), between KpnI and EcoRI sites. This allowed to clone gRNA sequences into pBSK-SA (BsmBI site) and pBSK-SP (BbsI site). Sequences of gR-NAs were the following: FBLN1 promoter (AGAGACC-CGGGAAGTCACCG) and polyadenylation site (CAGT-GAAATGCTCACCTCCG), and EYA3 promoter (CC-GAAAACAGTGTGCACGAA) and exon 7 (TAAACCA-CACTCCTAAGCTG). Expression of gRNAs was confirmed by RT-PCR using primers located into gRNA sequence and gRNA scaffold (data not shown). HEK-CLOuD9 cells were transfected with 1 g of each gRNA-containing plasmid using jetPRIME (PolyPlus Transfection), 1 mM Abscisic Acid (Merck Sigma-Aldrich) or DMSO was added to the cells 4 h after transfection.
Digestion was carried out by the successive addition of 3 × 20 l of Fast-Digest SacI (for the PRMT2 gene) or PstI (for the NCS1 gene) enzyme (ThermoFisher), during a 24 h-long incubation at 37 • C under mixing at 900 rpm. The overall efficiency of digestion was verified on a small aliquot by agarose gel electrophoresis. Digestion at specific restriction sites was also verified by qPCR using primers flanking the restriction site. This control showed that the digestion was homoge-neous across the regions of interest and in all experimental conditions (data not shown). Nuclei were then centrifuged at 2000 rpm for 10 min, washed once with 1× ligation buffer (ThermoFisher #B69) and resuspended in the same buffer. Ligation was performed overnight at 16 • C under mixing at 750 rpm in the presence of 1 mM ATP and 250 U of T4 DNA Ligase (Thermofisher), and continued for another 4 h following the addition of 175 U ligase and 1 mM ATP.
We selected only primer couples that gave a linear amplification during the PCR reaction, a Ct value within a similar range, and whose melting curve did not reveal any non-specific product. PCR products were also analysed by agarose gel electrophoresis to verify their size and purity. Primers were next validated on 80 ng of 3C samples to determine the exponential amplification range and to define the number of cycles to use for quantitative analyses (36 cycles for NCS1, 34 cycles for PRMT2). Amplified 3C products were analysed by 2% agarose gel electrophoresis and quantified in a GelDoc XR+ imager (Bio-Rad) using the Image Lab software. The amount of each 3C product was normalized to the loading control corresponding to a PCR product amplified between two restrictions sites (GAPDH for 3C-PstI, DDX17 for 3C-SacI).
For each terminal exon from the Fas-terDB database (19 415 genes), we designed a 5 kb region downstream of the exon. When another gene was present within this window, the size was adjusted to fit with the intergenic distance. The region was then divided in successive 50 nt segments, in which the read coverage was computed using SAMTools  (75). A segment was considered positive only when the average coverage was >2. The size of the read-through region was calculated by iterative extension of the segments, until it was interrupted by two consecutive negative segments. An average coverage and standard deviation was then computed. We performed the same coverage analysis on the last 500 nt of the exon (or the entire size of the terminal exon for smaller exons), which were also divided in 50-nt boxes starting from the 3 end of the gene.
Analysis of CTCF ChIP-seq data To analyse the relative proximity of DDX5/DDX17 exons to CTCF binding sites, we first generated a BED file containing a merged list of CTCF peaks retrieved from several ENCODE datasets (Supplementary Table  S5 ). We next calculated the genomic distance (negative or positive for upstream and downstream peaks, respectively) between each exon from the FasterDB database  (78)  and the center of the closest CTCF peak. The exon boundary that minimizes the distance to the nearest CTCF peak was chosen for this computation. We performed a logistic regression analysis to test if the different exons regulated by DDX5/DDX17 are closer to CTCF peaks than control exons. This analysis was carried out on: (i) the first (n = 740) and last exons (n = 744) of genes presenting a 3 end processing defect upon DDX5/DDX17 depletion, or all other genes (n = 16 040/16 046 for first/last exons, respectively); (ii) internal exons regulated by DDX5/DDX17 or by SRSF1, which were split in two groups depending on their stronger skipping or inclusion induced by depletion of those factors (1751 activated and 160 repressed exons for DDX5/DDX17, 1115 activated and 561 repressed exons for SRSF1) or all other exons not regulated by these factors (n = 179 618); (iii) the first (n = 1819) and last (n = 1821) exons of genes containing a DDX5/DDX17-dependent internal exon or other internal exons (n = 14 969/14 969 for first/last exons, respectively).